The department is composed of three teams on (1) Individual Dynamics, (2) Population Dynamics and (3) Biodiversity Dynamics.
-
Stephanie Kramer-Schadt is the department head and leader of the Population Dynamics team. Conny Landgraf is the assistant of the department head; she can assist with administrative duties (e.g. contracts, travel sheets, etc.). Moritz Wenzler and Jan Axtner are responsible for data management, data storage and the working group’s R code collection. As each department member has a specific area of expertise, we created an expert list (see 1.3) if you need help on specific topics. PhD students and scientists are obliged to update this expert list with their own skills and responsibilities as well.
+
Stephanie Kramer-Schadt is the department head and leader of the Population Dynamics team. Conny Landgraf is the assistant of the department head; she can assist with administrative duties (e.g. contracts, travel sheets, etc.). Moritz Wenzler-Meya and Jan Axtner are responsible for data management, data storage and the working group’s R code collection. As each department member has a specific area of expertise, we created an expert list (see 1.3) if you need help on specific topics. PhD students and scientists are obliged to update this expert list with their own skills and responsibilities as well.
For information on the Department, check our webpage or subscribe to our Twitter account (@EcoDynIZW) for news about papers, helpful R-code, courses or scientific positions.
Teams of the Department of Ecological Dynamics:
@@ -2838,7 +2837,7 @@
Organizing Workflows
Project workflow
Contact the Data Managers (Jan Axtner or Moritz Wenzler-Meya) of the respective teams to organize your project ID, get server access and how to arrange your workspace best. To setup a project folder, we ask you to follow the setup:
Make an outline of the structure separately in your electronic lab-book (see 3.3.1), to indicate what to find in each folder and keep it updated.
Please hand over the raw data to the data manager before starting your project analysis, to avoid accidental data losses.
Store the raw data, e.g. data from field work, in the folder named data-raw. Use a folder named output to store data created from the raw data (e.g. after data cleaning or editing). This should also be the place where the master table is located, i.e. the data set of all subsequent analyses. If needed you can have a temporary subfolder in the “output” folder for everyday work and analysis trials. Empty the temporary folder regularly. Plots and figures should be stored in the plots folder. Scripts should be stored in the R folder. Documents like manuscripts, proposals, etc. should be stored in the docs folder. Save important, computational or labour intensive interim results or final results. Use appropriate subfolders such as interim-results_<date> or final-results_<date>.
@@ -2851,85 +2850,11 @@
Electronic lab-book
At the start of each new project, create an electronic lab-book to document your workflow and decisions therein. It is of major importance that you keep this lab-book updated. For the ease of use we recommend simple .doc files (MS Word, Libre Office etc.) to keep record of our work. Write down important thoughts, things you have tried, also failed experiments. Try to use clear and comprehensible notes. Although this generates some additional effort you will realize soon that it will help you and others to track your work and make it reproducible. We highly recommend to use GitHub as version control of your project. You have to connect your GitHub account to the EcoDynIZW organization on GitHub to share code with colleagues. Please create repositories as part of this organization. It is mandatory to hand over the electronic lab-book to the institute as part of the ‘Safeguarding and Storing of Primary Data’ regulation of the German Research Council DFG after finishing your project.
To document scripting we recommend to use R Markdown (.rmd) files if possible. Between your code chunks you should annotate the script with everything that is necessary to understand and follow the code. Additionally, if you push new code to GitHub for version control, you have to comment on your committed code as well. It may be necessary to have an additional word document.
Write the author, name and date in a header (you can use the d6 package templates for this as well).
-
Keep code in scripts as concise as possible.
-
Use in-line comments to explain your code that others can follow your code.
-
If possible, use dynamic paths (i.e. see R-package here).
-
Always set variables/ parameters at the top of your script; do not set values somewhere inside the code as this is error prone, because these values tend to be forgotten to get changed when updating a script. The same applies to loading packages. Please also make sure to only load packages that are really needed and remove those that you are not using for the final analysis.
-
Save the output of a script as .rds file to smoothly load it in the next script. Additionally, save the output in a file format usable beyond R, e.g. use .csv or .txt if you want to save tabular data or GeoTiff if you want to save a raster map.
-
Use separate scripts to create figures of publishable quality (700 dpi) from the results. Use a vector graphics format like pdf.
-
For simulation studies: Include all scripts, e.g. additional model code, batch files with simulated parameters, simulated landscapes and simulation results, and files used for the analyses.
If you are using RStudio, make sure to set the following under Tools > Global Options > General > Basic:
-
-
untick “Restore .RData into workspace at startup”
-
set “Save workspace to .RData on exit:” to “Never”
-
untick “Always save history (even when not saving .RData)” (recommended)
-
-
-
-
-A screenshot of the RStudio general settings
-
-
-
We recommend using R-Studio projects and R Markdown documents when scripting in R. If you use another “integrated development environment” (IDE) make sure you can provide versioned plain R scripts using a relative path to the used data files.
-
Implement version control by using GitHub. If you install packages or use scripts and code chunks from GitHub provided by others, be aware to acknowledge the code developer prior to publication of scripts.
-
Do not save the R history or the R environment. Always start a fresh and an empty R session to avoid artifacts by using objects of functions that were not defined in your script. More details here: https://www.tidyverse.org/blog/2017/12/workflow-vs-script/.
-
If possible use log files to document messages and errors.
-
-
Python
-
In general we recommend using Jupyter notebooks.
-[under construction]
-
Netlogo
-
[under construction]
-
QGIS
-
In general we recommend doing GIS analyses in R. If you have to use QGIS use Python as scripting language. However, the RQGIS package provides a great opportunity to script complete workflows in QGIS by using R. Moreover, you can include R scripts in the QGIS toolbox.
If you are working with spatial data please have the following in mind:
-
-
Always check the projection (cartographic reference system (CRS)) of your data. Depending on what you want to do it could be necessary to change the CRS system, i.e. from an angular unit (like GPS data) to a projected unit in meters. BUT sometimes you cannot easily change it or it will drastically change your data.
-
If you want to save you spatial data, please save it as Geopackage (.gpkg) or raster data GeoTiff (.tif). Please give a clear name, document the filename in your lab book and add the EPSG code of your CRS to the file name. Always use utf-8 as file encoding.
-
If you are not sure how to handle your spatial data please contact Moritz Wenzler, the GIS manager, for help.
-
-
For detailed information about Spatial data go to Appendix B).
Important: backup your work! Make copies of raw data/files and scripts and save it in another location if you work on private computers. PhD students should work on the M-drive or the U-drive, never directly on the C-drive of the computer.
-
Manuscript Submissions/Revisions
-
When you are submitting a manuscript create a copy of the related subproject folder and add a suffix submission_1_<JournalAbbreviation>. This copy shall be stored and never changed—we recommend to zip this folder! When conducting a revisions or resubmission, copy the folder to submission_2_<JournalAbbreviation> and revise the paper.
-
Please find additional information on ‘how to write a scientific paper’, how to avoid statistical pitfalls or how to organize workflows here.
-
GitHub repository
-
The final step after your paper gets published is to make the GitHub repository public (or create a repository if you haven’t before). The repository should contain clean code and data that runs properly. If you are using R, please make sure to use a R-Project with the given folder structure (see appendix A).
-
The title of the repository should contain the last name of the first author, the year, and the abbreviation of the journal (e.g. Smith_2023_Science). Please add the title of the paper as the description (in quotation marks). Please provide the reference of the paper, including the DOI as a hyperlink, and the abstract in the README file. Add further notes on the files contained and the scripts if needed. Please use this template:
-
# Smith et al. (2023) *Science*
-
-> **Richard Smith**, Don Joe Radchuk & **Jane Head** (2023): Study title.
-*Science* 1-2. DOI: [doi-goes-here](https://doi.org/doi-goes-here)
-
-Abstract text.
-
-## Scripts
-
-... more notes if needed
-
-
Add the title in quotation marks as the description and the DOI as link to the repository about (right upper corner). For examples see study repositories on our GitHub).
-
Finally, make sure to turn the visibility to public and transfer the ownership to the EcoDynIZW GitHub organization. If you have need help or have questions please ask the data manager for help.
A new project can be started by installing the d6 R-package. Running new_project() with a unique and descriptive name for your project (see below) will create a full scaffolding structure for all your future analysis steps. If you like, you can also specify a path and the project will be created there.
Please create repositories on the EcoDynIZW account and not on your private
account!
Important: backup your work! Make copies of raw data/files and scripts and save it in another location if you work on private computers. PhD students should work on the M-drive or the U-drive, never directly on the C-drive of the computer.
+
Manuscript Submissions/Revisions
+
When you are submitting a manuscript create a copy of the related subproject folder and add a suffix submission_1_<JournalAbbreviation>. This copy shall be stored and never changed—we recommend to zip this folder! When conducting a revisions or resubmission, copy the folder to submission_2_<JournalAbbreviation> and revise the paper.
+
Please find additional information on ‘how to write a scientific paper’, how to avoid statistical pitfalls or how to organize workflows here.
+
GitHub repository
+
The final step after your paper gets published is to make the GitHub repository public (or create a repository if you haven’t before). The repository should contain clean code and data that runs properly. If you are using R, please make sure to use a R-Project with the given folder structure (see appendix A).
+
The title of the repository should contain the last name of the first author, the year, and the abbreviation of the journal (e.g. Smith_2023_Science). Please add the title of the paper as the description (in quotation marks). Please provide the reference of the paper, including the DOI as a hyperlink, and the abstract in the README file. Add further notes on the files contained and the scripts if needed. Please use this template:
+
# Smith et al. (2023) *Science*
+
+> **Richard Smith**, Don Joe Radchuk & **Jane Head** (2023): Study title.
+*Science* 1-2. DOI: [doi-goes-here](https://doi.org/doi-goes-here)
+
+Abstract text.
+
+## Scripts
+
+... more notes if needed
+
+
Add the title in quotation marks as the description and the DOI as link to the repository about (right upper corner). For examples see study repositories on our GitHub).
+
Finally, make sure to turn the visibility to public and transfer the ownership to the EcoDynIZW GitHub organization. If you have need help or have questions please ask the data manager for help.
Write the author, name and date in a header (you can use the d6 package templates for this as well).
+
Keep code in scripts as concise as possible.
+
Use in-line comments to explain your code that others can follow your code.
+
If possible, use dynamic paths (i.e. see R-package here).
+
Always set variables/ parameters at the top of your script; do not set values somewhere inside the code as this is error prone, because these values tend to be forgotten to get changed when updating a script. The same applies to loading packages. Please also make sure to only load packages that are really needed and remove those that you are not using for the final analysis.
+
Save the output of a script as .rds file to smoothly load it in the next script. Additionally, save the output in a file format usable beyond R, e.g. use .csv or .txt if you want to save tabular data or GeoTiff if you want to save a raster map.
+
Use separate scripts to create figures of publishable quality (700 dpi) from the results. Use a vector graphics format like pdf.
+
For simulation studies: Include all scripts, e.g. additional model code, batch files with simulated parameters, simulated landscapes and simulation results, and files used for the analyses.
If you are using RStudio, make sure to set the following under Tools > Global Options > General > Basic:
+
+
untick “Restore .RData into workspace at startup”
+
set “Save workspace to .RData on exit:” to “Never”
+
untick “Always save history (even when not saving .RData)” (recommended)
+
+
+
+
+A screenshot of the RStudio general settings
+
+
+
We recommend using R-Studio projects and R Markdown documents when scripting in R. If you use another “integrated development environment” (IDE) make sure you can provide versioned plain R scripts using a relative path to the used data files.
+
Implement version control by using GitHub. If you install packages or use scripts and code chunks from GitHub provided by others, be aware to acknowledge the code developer prior to publication of scripts.
+
Do not save the R history or the R environment. Always start a fresh and an empty R session to avoid artifacts by using objects of functions that were not defined in your script. More details here: https://www.tidyverse.org/blog/2017/12/workflow-vs-script/.
+
If possible use log files to document messages and errors.
+
+
Python
+
In general we recommend using Jupyter notebooks.
+[under construction]
+
Netlogo
+
[under construction]
+
QGIS
+
In general we recommend doing GIS analyses in R. If you have to use QGIS use Python as scripting language. However, the RQGIS package provides a great opportunity to script complete workflows in QGIS by using R. Moreover, you can include R scripts in the QGIS toolbox.
If you are working with spatial data please have the following in mind:
+
Always check the projection (cartographic reference system (CRS)) of your data. Depending on what you want to do it could be necessary to change the CRS system, i.e. from an angular unit (like GPS data) to a projected unit in meters. BUT sometimes you cannot easily change it or it will drastically change your data.
+
If you want to save you spatial data, please save it as Geopackage (.gpkg) or raster data GeoTiff (.tif). Please give a clear name, document the filename in your lab book and add the EPSG code of your CRS to the file name. Always use utf-8 as file encoding.
+
If you are not sure how to handle your spatial data please contact Moritz Wenzler-Meya, the GIS manager, for help.
When using spatial data give clear names for maps ≤ 13 characters without special characters or spaces.
Write down the cartographic reference system (CRS) at the end of the file name, e.g. filename_4326.
Always use utf-8 encoding, NEVER use the system setting. If you have to use different character encoding settings, then name the used encoding in the filename.
@@ -3007,7 +3000,7 @@
Appendix B) Detailed Spatial Data Information
Always include the Coordinate Reference System as EPSG code (e.g. 4326 for log/lat WGS84 Coordinates) at the end of a file name, e.g. my_env_variable_4326.gpkg.
Please save all your geo data into geopackage files (.gpkg) format to save and process your data. In general, if you export data from R please save it as an R Studio file (.rds). It will be saved without any losses.
Store all point/line/polygon data as WGS84 (EPSG 4326).
-
If you do not understand this paragraph, contact the geodata-manager (Moritz Wenzler) before doing anything involving geodata.
+
If you do not understand this paragraph, contact the geodata-manager (Moritz Wenzler-Meya) before doing anything involving geodata.
Leibniz Institute for Zoo and Wildlife Research
diff --git a/docs/msc-bsc-theses-2018.html b/docs/msc-bsc-theses-2018.html
index 9880f817..aa3023df 100644
--- a/docs/msc-bsc-theses-2018.html
+++ b/docs/msc-bsc-theses-2018.html
@@ -2644,7 +2644,7 @@
color: var(--hover-color, white);
}
-
+
diff --git a/docs/search.json b/docs/search.json
index 996adbdc..366e4025 100644
--- a/docs/search.json
+++ b/docs/search.json
@@ -6,14 +6,14 @@
"description": "",
"author": [],
"contents": "\r\n\r\n\r\n\r\nWe are scientists of the Department of Ecological Dynamics at the Leibniz Institute for Zoo and Wildlife Research, Berlin, Germany. Our research is focused on understanding ecological dynamics in space and time, at different levels of organisation, from individuals to communities, and across gradients of human altered environments. We investigate how fitness consequences of processes acting at the individual level, such as social behaviour or movements, competition, predator-prey or host-pathogen interactions, shape population and community dynamics, also at evolutionary scales.\r\n\r\nHow to contact us?\r\nEmail: assist6[at]izw-berlin.de\r\nAddress:\r\nLeibniz Institute for Zoo and Wildlife Research\r\nDepartment of Ecological Dynamics\r\nAlfred-Kowalke-Str. 17\r\nD-10315 Berlin, Germany\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n",
- "last_modified": "2023-10-09T17:11:20+02:00"
+ "last_modified": "2023-10-10T10:26:13+02:00"
},
{
"path": "coding.html",
"title": "Coding",
"author": [],
"contents": "\r\n\r\n\r\n\r\n",
- "last_modified": "2023-10-09T17:11:21+02:00"
+ "last_modified": "2023-10-10T10:26:14+02:00"
},
{
"path": "doctoral-theses.html",
@@ -21,22 +21,22 @@
"description": "",
"author": [],
"contents": "\r\n\r\nSuccessfully Defended Theses\r\n\r\nMorgane Gicquel: Early-life conditions and their long-term consequences in spotted hyenas (Crocuta Crocuta). 07.02.2023. Department of Biology, Chemistry and Pharmacy Freie Universität Berlin. Benhaiem S, East ML, Hofer H.\r\nTobias Kürschner: Disease transmission and persistence in dynamic landscapes. 23.09.2022. Institut für Biochemie und Biologie der Universität Potsdam. Kramer-Schadt S, Grimm V, Berger U.\r\nThanh Van Nguyen: Unravelling the mysteries of the Annamites: First insights in ecology, distribution, and genetic diversity of Annamite mammals. 24.06.2022. Mathematisch-Naturwissenschaftliche Fakultät\r\nInstitut für Biochemie und Biologie der Universität Potsdam. Fickel J, Wilting A.\r\nJoseph Premier: Research for Eurasian lynx conservation. Inclusion of genetic processes in an individual-based spatially explicit population model and updating the ecological and demographic basis to support evidence-based conservation management of Eurasian lynx. 25.05.2022. Faculty of Environment and Natural Resources, Albert-Ludwigs-Universität, Freiburg im Breisgau. Heurich M, Kramer-Schadt S.\r\nCarolin Scholz: The ecology of red foxes (Vulpes vulpes) in anthropogenic landscapes. 28.01.2021. Department of Biology, Chemistry and Pharmacy Freie Universität Berlin. Hofer H, Kramer-Schadt S.\r\nAndrew Tilker: Assessing defaunation in the central Annamites ecoregion of Vietnam and Laos. 19.11.2020. Biologie Freie Universität Berlin. Hofer H, Wilting A.\r\nSusana Carolina Martins Ferreira: Intrinsic and extrinsic determinants of parasite infection in spotted hyenas in the Serengeti National Park. 23.09.2019. Veterinärmedizin Freie Universität Berlin. Hofer H, East ML.\r\nJohn Mathai: Distribution and conservation of small carnivores focussing on the Bornean endemic Hose’s civet. 17.04.2019. Biologie Freie Universität Berlin. Hofer H, Wilting A.\r\nPhilipp Cédric Scherer: Infections on the move: Individual host movement drives disease persistence in spatially structured landscapes. 25.03.2019. Institut für Biochemie und Biologie der Universität Potsdam. Kramer-Schadt S, Jeltsch F.\r\n\r\n\r\n\r\n",
- "last_modified": "2023-10-09T17:11:22+02:00"
+ "last_modified": "2023-10-10T10:26:15+02:00"
},
{
"path": "geodata.html",
"title": "Geodata",
"author": [],
"contents": "\r\n\r\n\r\n\r\n",
- "last_modified": "2023-10-09T17:11:24+02:00"
+ "last_modified": "2023-10-10T10:26:16+02:00"
},
{
"path": "guidelines.html",
"title": "Department Guidelines",
"description": "The guidelines for studies in the Department of Ecological Dynamics are meant to ease your start in the department and to secure high quality standards for the analysis of your data.",
"author": [],
- "contents": "\r\nThe TL;DR Version\r\n\r\nGeneral Information\r\nImportant lab information (server access, responsibilities,…) can be found on our cloud in the folder Lab_Orga.\r\nFollow our rules how to call project folders: animal_species_where_what_who.\r\nCreate the project folder structure with our d6 package: d6::new_project().\r\nFor consistent style, we ask you to use our corporate d6 theme: d6::theme_d6().\r\nAt the end of a project, transfer your repository to our EcoDynIZW GitHub account.\r\nAsk Moritz Wenzler (wenzler[at]izw-berlin.de) for help of needed.\r\nInformation for Students (BSc | MSc | PhD)\r\nSupervisory Meetings\r\nPlan regular meetings at least 3 months ahead (2 weeks for non-regular meetings).\r\nPrepare for the meeting! Think about open questions, difficulties encountered, and the timeline for upcoming tasks.\r\nWrite the minutes of the meeting and send it to your supervisor(s).\r\nThesis writing\r\nStart writing your thesis early enough.\r\nAttend writing courses.\r\nRegularly send your chapter drafts to your supervisor(s) to get feedback. Allow for sufficient time to read and respond (1-3 weeks).\r\nSend the final version of your manuscript/thesis to all supervisors/colleagues at least 4 weeks before the submission date. Keep in mind that you have to revise it afterwards!\r\nTable of Content\r\nGeneral Information\r\nConducting BSc/MSc/PhD Projects\r\nOrganizing Workflows\r\nScripting\r\nSpatial Data\r\nData Backup\r\nManuscript Submissions/Revisions\r\nGitHub repository\r\nAppendices\r\nFolder Structure for Project Folders\r\nDetailed Spatial Data Information\r\nWhat Nature Says…\r\n\r\n\r\n\r\n\r\n\r\n\r\nGeneral Information\r\nThe department is composed of three teams on (1) Individual Dynamics, (2) Population Dynamics and (3) Biodiversity Dynamics.\r\nStephanie Kramer-Schadt is the department head and leader of the Population Dynamics team. Conny Landgraf is the assistant of the department head; she can assist with administrative duties (e.g. contracts, travel sheets, etc.). Moritz Wenzler and Jan Axtner are responsible for data management, data storage and the working group’s R code collection. As each department member has a specific area of expertise, we created an expert list (see 1.3) if you need help on specific topics. PhD students and scientists are obliged to update this expert list with their own skills and responsibilities as well.\r\nFor information on the Department, check our webpage or subscribe to our Twitter account (@EcoDynIZW) for news about papers, helpful R-code, courses or scientific positions.\r\nTeams of the Department of Ecological Dynamics:\r\nIndividual Dynamics – PI: Sarah Benhaiem & Sonja Metzger (field coordination)\r\nPopulation Dynamics – PI: Stephanie Kramer-Schadt & Viktoriia Radchuk\r\nBiodiversity Dynamics – PI: Andreas Wilting & Rahel Sollmann\r\nAdministrative support\r\nConny Landgraf\r\nTel: -466\r\nEmail: assist6[at]izw-berlin.de or landgraf[at]izw-berlin.de\r\nData Managers\r\nDr. Jan Axtner\r\nTel: -342\r\nEmail: axtner[at]izw-berlin.de\r\nMoritz Wenzler-Meya\r\nTel: -342\r\nEmail: wenzler[at]izw-berlin.de\r\nIn-house experts / scientists / responsibilities\r\nWho does what in the department? Tasks and expertise as well as meeting dates and protocols can be found in the IZW Wolke.\r\n↑ Jump back to top.\r\nConducting BSc/MSc/PhD Projects\r\nFor PhD students: please read the IZW PhD guidelines (\\\\izw-daten-8\\Alle\\GUEST\\Doktorand(inn)en\\IZW-PhD-rules) carefully and follow the instructions (e.g. when you have to give an introduction talk). For any question about these guidelines, contact the PhD coordinators Gábor Czirják (czirjak[at]izw-berlin.de) and Sarah Benhaiem (benhaiem[at]izw-berlin.de).\r\nMeetings\r\nRegular meetings with your supervisor often help to avoid a waste of time (see also Appendix C). It is in the responsibility of the student to organize and schedule regular meeting with his/ her supervisor or the team.\r\nYou can either arrange a fixed date with your supervisor (e.g. first Monday of every month) or schedule them on demand. Please find an agreement with your supervisor how to handle this best. Please keep in mind that any non-regular meeting should be planned at least two weeks ahead.\r\nUse the IZW outlook calendar to schedule meetings with supervisors and colleagues (if you have an IZW Email address). That is: create the entry in the calendar and ‘invite’ the others, so that the date/ location appears in each calendar, with sufficient notice time for the automated reminder (i.e. 1 day/ 1 hr).\r\nPrepare the meetings: Think carefully about your problems/questions and write your agenda (what you want to discuss) before the meeting, make suggestions for your solution(s) and ask the supervisors/collaborators to comment on your solution(s).\r\nWrite the minutes of the meeting and save it in the project folder (we give instructions about this project folder below 3.1.). Minimum information needed: (1) date of meeting, (2) name of participants, (3) questions or problems discussed, (4) main solutions suggested and (5) aims or results to prepare for the next meeting. Write down agreements of the responsibilities of all collaborators.\r\nPresent your project progress regularly in the department meetings, also to get feedback and discuss problems you ran into.\r\nThesis writing\r\nStart writing the thesis early enough. Write simple and concise sentences based on what is known in the literature. Join a ‘pub club’ (i.e. retreats for writing), e.g. Team 2 has regular meetings on jointly discussing drafts of each other. Please also read the instructions (Under construction) for how to write good scientific papers.\r\nArrange with your supervisor how and in what form you report progress. Getting regular feedback for chapters or even just paragraphs might keep you from running into dead ends. When asking for revisions plan in sufficient time for the reviewers to read and respond (1-3 weeks, depending on the amount of text).\r\nFor PhD students: A first complete manuscript draft should be ready after ~ 1 year after starting time.\r\nSend the final version of your manuscript/thesis to all supervisors/colleagues at least 4 weeks before the submission date and keep in mind that you might have to revise it.\r\n↑ Jump back to top.\r\nOrganizing Workflows\r\nTo store data and results, the IZW follows the DFG-guidelines for good scientific practice. In our department, we often use “scripting” (written code of different programming languages) to process and analyze data, and make results reproducible. Work is structured and organized in projects and each project will get a project ID from the data administrators of the department. We consider a project to be a self-contained topic, e.g. analyses for a manuscript, thesis chapter, etc. For each project a separate folder is created and all relevant scripts, results, the lab-book, documents, literature, minutes of meetings etc. related to this project are to be kept in that main folder. For documents (not for scripts!) use your surname, type of document, project name and in the end the date (YYYYMMDD) as version numbers for file names (kramer_manuscript_lynxibm_20201231.docx) and do not use names like doc_final.docx, doc_finalfinal.docx, doc_lastversion.docx etc. It should contain all information needed to repeat the study and conduct follow-up studies. Whenever possible use the standardized project/folder structure shown in section 3.1. Each project or subproject should have a concise but meaningfully electronic lab-book (see section X.Z) that allows to follow the workflow and the decisions made in it.\r\nProject workflow\r\nContact the Data Managers (Jan Axtner or Moritz Wenzler-Meya) of the respective teams to organize your project ID, get server access and how to arrange your workspace best. To setup a project folder, we ask you to follow the setup:\r\nUse the standardized project folder structure! (see Appendix A, cf. d6 R package and GitHub)\r\nMake an outline of the structure separately in your electronic lab-book (see 3.3.1), to indicate what to find in each folder and keep it updated.\r\nPlease hand over the raw data to the data manager before starting your project analysis, to avoid accidental data losses.\r\nStore the raw data, e.g. data from field work, in the folder named data-raw. Use a folder named output to store data created from the raw data (e.g. after data cleaning or editing). This should also be the place where the master table is located, i.e. the data set of all subsequent analyses. If needed you can have a temporary subfolder in the “output” folder for everyday work and analysis trials. Empty the temporary folder regularly. Plots and figures should be stored in the plots folder. Scripts should be stored in the R folder. Documents like manuscripts, proposals, etc. should be stored in the docs folder. Save important, computational or labour intensive interim results or final results. Use appropriate subfolders such as interim-results_ or final-results_.\r\nReproducibility\r\nTo ensure reproducibility and for your own sake always try to script your work! If possible use R, Python, SQL, etc. for analyses and avoid manual / mouse commands (e.g. ‘clicking’ in ArcGIS, QGIS etc.). If you cannot use scripts, use tools such as the model-builder in ArcGIS or QGIS and save the drag & drop model builder scripts.\r\nDocumentation\r\nProject documentation is not a final task, but an ongoing process starting from day one. DFG guidelines for Safeguarding and Storing of Primary Data states ‘Primary data as the basis for publications shall be securely stored for ten years in a durable form in the institution of their origin.’ Hence, at the end of a research project, you have to hand over a single well-documented folder per project (usually a paper on the respective subject, or the BSc thesis) along with all original data. The project folder should contain all project related documents and data (e.g. simulation model codes, simulation results, scripts for statistical analysis, scripts for tables and figures, manuscripts, important work documents, applications, permits, reports, etc.) as well as a the final version of a thesis or paper. Unfinished work (data from conducted experiments that were not analyzed or published) should contain the above documents as far as possible, including a very detailed method description. For the ease of documentation effort please follow the section (3.3.1).\r\nElectronic lab-book\r\nAt the start of each new project, create an electronic lab-book to document your workflow and decisions therein. It is of major importance that you keep this lab-book updated. For the ease of use we recommend simple .doc files (MS Word, Libre Office etc.) to keep record of our work. Write down important thoughts, things you have tried, also failed experiments. Try to use clear and comprehensible notes. Although this generates some additional effort you will realize soon that it will help you and others to track your work and make it reproducible. We highly recommend to use GitHub as version control of your project. You have to connect your GitHub account to the EcoDynIZW organization on GitHub to share code with colleagues. Please create repositories as part of this organization. It is mandatory to hand over the electronic lab-book to the institute as part of the ‘Safeguarding and Storing of Primary Data’ regulation of the German Research Council DFG after finishing your project.\r\nTo document scripting we recommend to use R Markdown (.rmd) files if possible. Between your code chunks you should annotate the script with everything that is necessary to understand and follow the code. Additionally, if you push new code to GitHub for version control, you have to comment on your committed code as well. It may be necessary to have an additional word document.\r\n↑ Jump back to top.\r\nScripting\r\nGeneral recommendations\r\nWrite the author, name and date in a header (you can use the d6 package templates for this as well).\r\nKeep code in scripts as concise as possible.\r\nUse in-line comments to explain your code that others can follow your code.\r\nIf possible, use dynamic paths (i.e. see R-package here).\r\nAlways set variables/ parameters at the top of your script; do not set values somewhere inside the code as this is error prone, because these values tend to be forgotten to get changed when updating a script. The same applies to loading packages. Please also make sure to only load packages that are really needed and remove those that you are not using for the final analysis.\r\nSave the output of a script as .rds file to smoothly load it in the next script. Additionally, save the output in a file format usable beyond R, e.g. use .csv or .txt if you want to save tabular data or GeoTiff if you want to save a raster map.\r\nUse separate scripts to create figures of publishable quality (700 dpi) from the results. Use a vector graphics format like pdf.\r\nFor simulation studies: Include all scripts, e.g. additional model code, batch files with simulated parameters, simulated landscapes and simulation results, and files used for the analyses.\r\nR\r\nStick to the Rstudio style guide to ensure readability of code.\r\nIf you are using RStudio, make sure to set the following under Tools > Global Options > General > Basic:\r\nuntick “Restore .RData into workspace at startup”\r\nset “Save workspace to .RData on exit:” to “Never”\r\nuntick “Always save history (even when not saving .RData)” (recommended)\r\n\r\nA screenshot of the RStudio general settingsWe recommend using R-Studio projects and R Markdown documents when scripting in R. If you use another “integrated development environment” (IDE) make sure you can provide versioned plain R scripts using a relative path to the used data files.\r\nImplement version control by using GitHub. If you install packages or use scripts and code chunks from GitHub provided by others, be aware to acknowledge the code developer prior to publication of scripts.\r\nDo not save the R history or the R environment. Always start a fresh and an empty R session to avoid artifacts by using objects of functions that were not defined in your script. More details here: https://www.tidyverse.org/blog/2017/12/workflow-vs-script/.\r\nIf possible use log files to document messages and errors.\r\nPython\r\nIn general we recommend using Jupyter notebooks.\r\n[under construction]\r\nNetlogo\r\n[under construction]\r\nQGIS\r\nIn general we recommend doing GIS analyses in R. If you have to use QGIS use Python as scripting language. However, the RQGIS package provides a great opportunity to script complete workflows in QGIS by using R. Moreover, you can include R scripts in the QGIS toolbox.\r\n[under construction]\r\n↑ Jump back to top.\r\nSpatial Data\r\nIf you are working with spatial data please have the following in mind:\r\nAlways check the projection (cartographic reference system (CRS)) of your data. Depending on what you want to do it could be necessary to change the CRS system, i.e. from an angular unit (like GPS data) to a projected unit in meters. BUT sometimes you cannot easily change it or it will drastically change your data.\r\nIf you want to save you spatial data, please save it as Geopackage (.gpkg) or raster data GeoTiff (.tif). Please give a clear name, document the filename in your lab book and add the EPSG code of your CRS to the file name. Always use utf-8 as file encoding.\r\nIf you are not sure how to handle your spatial data please contact Moritz Wenzler, the GIS manager, for help.\r\nFor detailed information about Spatial data go to Appendix B).\r\n↑ Jump back to top.\r\nData Backup\r\nImportant: backup your work! Make copies of raw data/files and scripts and save it in another location if you work on private computers. PhD students should work on the M-drive or the U-drive, never directly on the C-drive of the computer.\r\nManuscript Submissions/Revisions\r\nWhen you are submitting a manuscript create a copy of the related subproject folder and add a suffix submission_1_. This copy shall be stored and never changed—we recommend to zip this folder! When conducting a revisions or resubmission, copy the folder to submission_2_ and revise the paper.\r\nPlease find additional information on ‘how to write a scientific paper’, how to avoid statistical pitfalls or how to organize workflows here.\r\nGitHub repository\r\nThe final step after your paper gets published is to make the GitHub repository public (or create a repository if you haven’t before). The repository should contain clean code and data that runs properly. If you are using R, please make sure to use a R-Project with the given folder structure (see appendix A).\r\nThe title of the repository should contain the last name of the first author, the year, and the abbreviation of the journal (e.g. Smith_2023_Science). Please add the title of the paper as the description (in quotation marks). Please provide the reference of the paper, including the DOI as a hyperlink, and the abstract in the README file. Add further notes on the files contained and the scripts if needed. Please use this template:\r\n# Smith et al. (2023) *Science*\r\n\r\n> **Richard Smith**, Don Joe Radchuk & **Jane Head** (2023): Study title. \r\n*Science* 1-2. DOI: [doi-goes-here](https://doi.org/doi-goes-here)\r\n\r\nAbstract text.\r\n\r\n## Scripts\r\n\r\n... more notes if needed\r\n\r\nAdd the title in quotation marks as the description and the DOI as link to the repository about (right upper corner). For examples see study repositories on our GitHub).\r\nFinally, make sure to turn the visibility to public and transfer the ownership to the EcoDynIZW GitHub organization. If you have need help or have questions please ask the data manager for help.\r\n↑ Jump back to top.\r\nAppendices\r\nAppendix A) Folder Structure for Project Folders\r\nA new project can be started by installing the d6 R-package. Running new_project() with a unique and descriptive name for your project (see below) will create a full scaffolding structure for all your future analysis steps. If you like, you can also specify a path and the project will be created there.\r\nPlease create repositories on the EcoDynIZW account and not on your private\r\naccount!\r\nRoot project folder\r\nName it like:\r\nspecies|topic_country|simu_method|approach_surname_firstletterofgivenname\r\ne.g. unicornus_wl_sdm_smith_j (unicornus project in wonderland, species distribution model from John Smith) or stability_simu_rpackage_smith_j\r\nEverything should be written in small letters.\r\nAvoid spaces or hyphen in the path to the file.\r\nSpecies name should be in latin and please use your surname and the first letter of your given name at the end.\r\nCountry should be the international abbreviation.\r\nThe root project folder should hold:\r\nR_Project_file: your main file for your R project (if used) — do not confuse this with R-scripts!\r\nWe highly recommend to use R, but if it is necessary to use another programming language and/or program please use the same structure as described in the following:\r\n\r\ndata-raw: A folder that contains the complete raw data set (e.g. telemetry data, experiment results, electrophoresis images, vegetation survey plots, species lists, etc.).\r\nDo not use MS Excel files use .csv or .txt files to store/ save data.\r\nMetadata belonging to the raw data should be provided in a separate file but it should be given the same name with an additional suffix as the raw data file, e.g. area1_specieslist.txt or area1_specieslist_metadata.txt\r\n\r\ndocs: A folder that contains anything related with project administration e.g. applications, permits, grants, timeline, research proposal, the electronic lab-book.\r\noutput: A folder that contains processed raw data\r\nResults of data preparation and wrangling\r\nResults of spatial data processing and spatial analysis, e.g. rasterizing, extracting, calculating on the basic layer and the resulting map used for analyses.\r\nFinal results from analyses\r\n\r\nplots: A folder that contains all produced images for the data exploration, presentations, and publications.\r\nR: A folder that contains all scripts that are used within the project.\r\nIf you need additional subfolders add them. Please use also second-level subfolders inside the subfolders to keep a clear and tidy structure.\r\nThe main folder structure created in the root directory should look like this:\r\n.\r\n└── my_project\r\n ├── data-raw\r\n ├── docs\r\n ├── output\r\n ├── plots\r\n └── R\r\nThe full scaffolding structure including all subdirectories and\r\nadditional files looks like this:\r\n. \r\n└── my_project\r\n ├── .Rproj.user — Rproject files\r\n ├── data-raw — raw data (tabular data in root folder)\r\n │ └── geo-raw — raw spatial data\r\n ├── docs — documents\r\n │ ├── admin — adminstrative docs, e.g. permits \r\n │ ├── literature — literature used for parameterization + ms\r\n │ ├── manuscript — manuscript drafts (main + supplement)\r\n │ ├── presentations — talks and poster presentations\r\n │ └── reports — rendered reports\r\n ├── output — everything that is computed (except plots)\r\n │ ├── data-proc — processed tabular data\r\n │ └── geo-proc — processed spatial data\r\n ├── plots — plot output\r\n ├── R — scripts\r\n │ ├── 00_start.R — first script to run\r\n │ └── XX_submit.R — final script to run\r\n ├── .gitignore — contains which files to ignore for version control\r\n ├── .Rbuildignore — contains which files to ignore for package builds\r\n ├── DESCRIPTION — contains project details and package dependencies\r\n ├── NAMESPACE — contains context for R objects\r\n └── project.Rproj — Rproject file: use to start your project\r\n↑ Jump back to top.\r\nAppendix B) Detailed Spatial Data Information\r\nWhen using spatial data give clear names for maps ≤ 13 characters without special characters or spaces.\r\nWrite down the cartographic reference system (CRS) at the end of the file name, e.g. filename_4326.\r\nAlways use utf-8 encoding, NEVER use the system setting. If you have to use different character encoding settings, then name the used encoding in the filename.\r\nSave the data as geopackage (.gpkg, recommended but cannot be used via ArcGis) or shapefile. Geopackages should be the first choice as the format is much quicker in every task (loading, saving, changing and computing), less limited and OGC-Standard (Open Geospatial Consortium). Be aware, that shapefiles have many limitations e.g. max 7 characters for column names. Further information is listed in Appendix B.\r\nCrosscheck your scripts and results. If you have calculated data/processed maps, make a plot and check for consistency. E.g. there should be no data outliers, terrestrial species should not occur in the sea etc. If results are valid, mark it as a milestone in your project documentation.\r\nBe aware: if you want to change the coordinate reference system (CRS) you have to transform / project the data. Never just specify a new one, because this doesn’t change the CRS!\r\nAlways include the Coordinate Reference System as EPSG code (e.g. 4326 for log/lat WGS84 Coordinates) at the end of a file name, e.g. my_env_variable_4326.gpkg.\r\nPlease save all your geo data into geopackage files (.gpkg) format to save and process your data. In general, if you export data from R please save it as an R Studio file (.rds). It will be saved without any losses.\r\nStore all point/line/polygon data as WGS84 (EPSG 4326).\r\nIf you do not understand this paragraph, contact the geodata-manager (Moritz Wenzler) before doing anything involving geodata.\r\n↑ Jump back to top.\r\nAppendix C) What Nature Says…\r\nNature 561, 277 (2018)\r\nWhy you need an agenda for meetings with your principal investigator\r\nA list of talking points can help with navigating potentially difficult topics and sticky negotiations.\r\nAs PhD students, we often find ourselves discussing our interactions with our principal investigators (PIs) and swapping advice for improving our mentoring meetings. We have found three practices to be consistently helpful:\r\nasking our PIs about all aspects of their job;\r\npreparing an agenda for each meeting;\r\nnegotiating new experiments without explicitly saying ‘no’.\r\nRead the full text: https://doi.org/10.1038/d41586-018-06619-3\r\n↑ Jump back to top.\r\n\r\n\r\n\r\n",
- "last_modified": "2023-10-09T17:11:25+02:00"
+ "contents": "\r\nThe TL;DR Version\r\n\r\nGeneral Information\r\nImportant lab information (server access, responsibilities,…) can be found on our cloud in the folder Lab_Orga.\r\nFollow our rules how to call project folders: animal_species_where_what_who.\r\nCreate the project folder structure with our d6 package: d6::new_project().\r\nFor consistent style, we ask you to use our corporate d6 theme: d6::theme_d6().\r\nAt the end of a project, transfer your repository to our EcoDynIZW GitHub account.\r\nAsk Moritz Wenzler-Meya (wenzler[at]izw-berlin.de) for help if needed.\r\nInformation for Students (BSc | MSc | PhD)\r\nSupervisory Meetings\r\nPlan regular meetings at least 3 months ahead (2 weeks for non-regular meetings).\r\nPrepare for the meeting! Think about open questions, difficulties encountered, and the timeline for upcoming tasks.\r\nWrite the minutes of the meeting and send it to your supervisor(s).\r\nThesis writing\r\nStart writing your thesis early enough.\r\nAttend writing courses.\r\nRegularly send your chapter drafts to your supervisor(s) to get feedback. Allow for sufficient time to read and respond (1-3 weeks).\r\nSend the final version of your manuscript/thesis to all supervisors/colleagues at least 4 weeks before the submission date. Keep in mind that you have to revise it afterwards!\r\nTable of Content\r\nGeneral Information\r\nConducting BSc/MSc/PhD Projects\r\nOrganizing Workflows\r\nProject Folders\r\nData Backup\r\nManuscript Submissions/Revisions\r\nGitHub repository\r\nAppendices\r\nScripting\r\nSpatial Data Information\r\nWhat Nature Says…\r\n\r\n\r\n\r\n\r\n\r\n\r\nGeneral Information\r\nThe department is composed of three teams on (1) Individual Dynamics, (2) Population Dynamics and (3) Biodiversity Dynamics.\r\nStephanie Kramer-Schadt is the department head and leader of the Population Dynamics team. Conny Landgraf is the assistant of the department head; she can assist with administrative duties (e.g. contracts, travel sheets, etc.). Moritz Wenzler-Meya and Jan Axtner are responsible for data management, data storage and the working group’s R code collection. As each department member has a specific area of expertise, we created an expert list (see 1.3) if you need help on specific topics. PhD students and scientists are obliged to update this expert list with their own skills and responsibilities as well.\r\nFor information on the Department, check our webpage or subscribe to our Twitter account (@EcoDynIZW) for news about papers, helpful R-code, courses or scientific positions.\r\nTeams of the Department of Ecological Dynamics:\r\nIndividual Dynamics – PI: Sarah Benhaiem & Sonja Metzger (field coordination)\r\nPopulation Dynamics – PI: Stephanie Kramer-Schadt & Viktoriia Radchuk\r\nBiodiversity Dynamics – PI: Andreas Wilting & Rahel Sollmann\r\nAdministrative support\r\nConny Landgraf\r\nTel: -466\r\nEmail: assist6[at]izw-berlin.de or landgraf[at]izw-berlin.de\r\nData Managers\r\nDr. Jan Axtner\r\nTel: -342\r\nEmail: axtner[at]izw-berlin.de\r\nMoritz Wenzler-Meya\r\nTel: -342\r\nEmail: wenzler[at]izw-berlin.de\r\nIn-house experts / scientists / responsibilities\r\nWho does what in the department? Tasks and expertise as well as meeting dates and protocols can be found in the IZW Wolke.\r\n↑ Jump back to top.\r\nConducting BSc/MSc/PhD Projects\r\nFor PhD students: please read the IZW PhD guidelines (\\\\izw-daten-8\\Alle\\GUEST\\Doktorand(inn)en\\IZW-PhD-rules) carefully and follow the instructions (e.g. when you have to give an introduction talk). For any question about these guidelines, contact the PhD coordinators Gábor Czirják (czirjak[at]izw-berlin.de) and Sarah Benhaiem (benhaiem[at]izw-berlin.de).\r\nMeetings\r\nRegular meetings with your supervisor often help to avoid a waste of time (see also Appendix C). It is in the responsibility of the student to organize and schedule regular meeting with his/ her supervisor or the team.\r\nYou can either arrange a fixed date with your supervisor (e.g. first Monday of every month) or schedule them on demand. Please find an agreement with your supervisor how to handle this best. Please keep in mind that any non-regular meeting should be planned at least two weeks ahead.\r\nUse the IZW outlook calendar to schedule meetings with supervisors and colleagues (if you have an IZW Email address). That is: create the entry in the calendar and ‘invite’ the others, so that the date/ location appears in each calendar, with sufficient notice time for the automated reminder (i.e. 1 day/ 1 hr).\r\nPrepare the meetings: Think carefully about your problems/questions and write your agenda (what you want to discuss) before the meeting, make suggestions for your solution(s) and ask the supervisors/collaborators to comment on your solution(s).\r\nWrite the minutes of the meeting and save it in the project folder (we give instructions about this project folder below 3.1.). Minimum information needed: (1) date of meeting, (2) name of participants, (3) questions or problems discussed, (4) main solutions suggested and (5) aims or results to prepare for the next meeting. Write down agreements of the responsibilities of all collaborators.\r\nPresent your project progress regularly in the department meetings, also to get feedback and discuss problems you ran into.\r\nThesis writing\r\nStart writing the thesis early enough. Write simple and concise sentences based on what is known in the literature. Join a ‘pub club’ (i.e. retreats for writing), e.g. Team 2 has regular meetings on jointly discussing drafts of each other. Please also read the instructions (Under construction) for how to write good scientific papers.\r\nArrange with your supervisor how and in what form you report progress. Getting regular feedback for chapters or even just paragraphs might keep you from running into dead ends. When asking for revisions plan in sufficient time for the reviewers to read and respond (1-3 weeks, depending on the amount of text).\r\nFor PhD students: A first complete manuscript draft should be ready after ~ 1 year after starting time.\r\nSend the final version of your manuscript/thesis to all supervisors/colleagues at least 4 weeks before the submission date and keep in mind that you might have to revise it.\r\n↑ Jump back to top.\r\nOrganizing Workflows\r\nTo store data and results, the IZW follows the DFG-guidelines for good scientific practice. In our department, we often use “scripting” (written code of different programming languages) to process and analyze data, and make results reproducible. Work is structured and organized in projects and each project will get a project ID from the data administrators of the department. We consider a project to be a self-contained topic, e.g. analyses for a manuscript, thesis chapter, etc. For each project a separate folder is created and all relevant scripts, results, the lab-book, documents, literature, minutes of meetings etc. related to this project are to be kept in that main folder. For documents (not for scripts!) use your surname, type of document, project name and in the end the date (YYYYMMDD) as version numbers for file names (kramer_manuscript_lynxibm_20201231.docx) and do not use names like doc_final.docx, doc_finalfinal.docx, doc_lastversion.docx etc. It should contain all information needed to repeat the study and conduct follow-up studies. Whenever possible use the standardized project/folder structure shown in section 3.1. Each project or subproject should have a concise but meaningfully electronic lab-book (see section X.Z) that allows to follow the workflow and the decisions made in it.\r\nProject workflow\r\nContact the Data Managers (Jan Axtner or Moritz Wenzler-Meya) of the respective teams to organize your project ID, get server access and how to arrange your workspace best. To setup a project folder, we ask you to follow the setup:\r\nUse the standardized project folder structure! (see Project Folder Structure, d6 R package and GitHub)\r\nMake an outline of the structure separately in your electronic lab-book (see 3.3.1), to indicate what to find in each folder and keep it updated.\r\nPlease hand over the raw data to the data manager before starting your project analysis, to avoid accidental data losses.\r\nStore the raw data, e.g. data from field work, in the folder named data-raw. Use a folder named output to store data created from the raw data (e.g. after data cleaning or editing). This should also be the place where the master table is located, i.e. the data set of all subsequent analyses. If needed you can have a temporary subfolder in the “output” folder for everyday work and analysis trials. Empty the temporary folder regularly. Plots and figures should be stored in the plots folder. Scripts should be stored in the R folder. Documents like manuscripts, proposals, etc. should be stored in the docs folder. Save important, computational or labour intensive interim results or final results. Use appropriate subfolders such as interim-results_ or final-results_.\r\nReproducibility\r\nTo ensure reproducibility and for your own sake always try to script your work! If possible use R, Python, SQL, etc. for analyses and avoid manual / mouse commands (e.g. ‘clicking’ in ArcGIS, QGIS etc.). If you cannot use scripts, use tools such as the model-builder in ArcGIS or QGIS and save the drag & drop model builder scripts.\r\nDocumentation\r\nProject documentation is not a final task, but an ongoing process starting from day one. DFG guidelines for Safeguarding and Storing of Primary Data states ‘Primary data as the basis for publications shall be securely stored for ten years in a durable form in the institution of their origin.’ Hence, at the end of a research project, you have to hand over a single well-documented folder per project (usually a paper on the respective subject, or the BSc thesis) along with all original data. The project folder should contain all project related documents and data (e.g. simulation model codes, simulation results, scripts for statistical analysis, scripts for tables and figures, manuscripts, important work documents, applications, permits, reports, etc.) as well as a the final version of a thesis or paper. Unfinished work (data from conducted experiments that were not analyzed or published) should contain the above documents as far as possible, including a very detailed method description. For the ease of documentation effort please follow the section (3.3.1).\r\nElectronic lab-book\r\nAt the start of each new project, create an electronic lab-book to document your workflow and decisions therein. It is of major importance that you keep this lab-book updated. For the ease of use we recommend simple .doc files (MS Word, Libre Office etc.) to keep record of our work. Write down important thoughts, things you have tried, also failed experiments. Try to use clear and comprehensible notes. Although this generates some additional effort you will realize soon that it will help you and others to track your work and make it reproducible. We highly recommend to use GitHub as version control of your project. You have to connect your GitHub account to the EcoDynIZW organization on GitHub to share code with colleagues. Please create repositories as part of this organization. It is mandatory to hand over the electronic lab-book to the institute as part of the ‘Safeguarding and Storing of Primary Data’ regulation of the German Research Council DFG after finishing your project.\r\nTo document scripting we recommend to use R Markdown (.rmd) files if possible. Between your code chunks you should annotate the script with everything that is necessary to understand and follow the code. Additionally, if you push new code to GitHub for version control, you have to comment on your committed code as well. It may be necessary to have an additional word document.\r\n↑ Jump back to top.\r\nProject Folder Structure\r\nA new project can be started by installing the d6 R-package. Running new_project() with a unique and descriptive name for your project (see below) will create a full scaffolding structure for all your future analysis steps. If you like, you can also specify a path and the project will be created there.\r\nPlease create repositories on the EcoDynIZW account and not on your private\r\naccount!\r\nRoot project folder\r\nName it like:\r\nspecies|topic_country|simu_method|approach_surname_firstletterofgivenname\r\ne.g. unicornus_wl_sdm_smith_j (unicornus project in wonderland, species distribution model from John Smith) or stability_simu_rpackage_smith_j\r\nEverything should be written in small letters.\r\nAvoid spaces or hyphen in the path to the file.\r\nSpecies name should be in latin and please use your surname and the first letter of your given name at the end.\r\nCountry should be the international abbreviation.\r\nThe root project folder should hold:\r\nR_Project_file: your main file for your R project (if used) — do not confuse this with R-scripts!\r\nWe highly recommend to use R, but if it is necessary to use another programming language and/or program please use the same structure as described in the following:\r\n\r\ndata-raw: A folder that contains the complete raw data set (e.g. telemetry data, experiment results, electrophoresis images, vegetation survey plots, species lists, etc.).\r\nDo not use MS Excel files use .csv or .txt files to store/ save data.\r\nMetadata belonging to the raw data should be provided in a separate file but it should be given the same name with an additional suffix as the raw data file, e.g. area1_specieslist.txt or area1_specieslist_metadata.txt\r\n\r\ndocs: A folder that contains anything related with project administration e.g. applications, permits, grants, timeline, research proposal, the electronic lab-book.\r\noutput: A folder that contains processed raw data\r\nResults of data preparation and wrangling\r\nResults of spatial data processing and spatial analysis, e.g. rasterizing, extracting, calculating on the basic layer and the resulting map used for analyses.\r\nFinal results from analyses\r\n\r\nplots: A folder that contains all produced images for the data exploration, presentations, and publications.\r\nR: A folder that contains all scripts that are used within the project.\r\nIf you need additional subfolders add them. Please use also second-level subfolders inside the subfolders to keep a clear and tidy structure.\r\nThe main folder structure created in the root directory should look like this:\r\n.\r\n└── my_project\r\n ├── data-raw\r\n ├── docs\r\n ├── output\r\n ├── plots\r\n └── R\r\nThe full scaffolding structure including all subdirectories and\r\nadditional files looks like this:\r\n. \r\n└── my_project\r\n ├── .Rproj.user — Rproject files\r\n ├── data-raw — raw data (tabular data in root folder)\r\n │ └── geo-raw — raw spatial data\r\n ├── docs — documents\r\n │ ├── admin — adminstrative docs, e.g. permits \r\n │ ├── literature — literature used for parameterization + ms\r\n │ ├── manuscript — manuscript drafts (main + supplement)\r\n │ ├── presentations — talks and poster presentations\r\n │ └── reports — rendered reports\r\n ├── output — everything that is computed (except plots)\r\n │ ├── data-proc — processed tabular data\r\n │ └── geo-proc — processed spatial data\r\n ├── plots — plot output\r\n ├── R — scripts\r\n │ ├── 00_start.R — first script to run\r\n │ └── XX_submit.R — final script to run\r\n ├── .gitignore — contains which files to ignore for version control\r\n ├── .Rbuildignore — contains which files to ignore for package builds\r\n ├── DESCRIPTION — contains project details and package dependencies\r\n ├── NAMESPACE — contains context for R objects\r\n └── project.Rproj — Rproject file: use to start your project\r\n↑ Jump back to top.\r\nData Backup\r\nImportant: backup your work! Make copies of raw data/files and scripts and save it in another location if you work on private computers. PhD students should work on the M-drive or the U-drive, never directly on the C-drive of the computer.\r\nManuscript Submissions/Revisions\r\nWhen you are submitting a manuscript create a copy of the related subproject folder and add a suffix submission_1_. This copy shall be stored and never changed—we recommend to zip this folder! When conducting a revisions or resubmission, copy the folder to submission_2_ and revise the paper.\r\nPlease find additional information on ‘how to write a scientific paper’, how to avoid statistical pitfalls or how to organize workflows here.\r\nGitHub repository\r\nThe final step after your paper gets published is to make the GitHub repository public (or create a repository if you haven’t before). The repository should contain clean code and data that runs properly. If you are using R, please make sure to use a R-Project with the given folder structure (see appendix A).\r\nThe title of the repository should contain the last name of the first author, the year, and the abbreviation of the journal (e.g. Smith_2023_Science). Please add the title of the paper as the description (in quotation marks). Please provide the reference of the paper, including the DOI as a hyperlink, and the abstract in the README file. Add further notes on the files contained and the scripts if needed. Please use this template:\r\n# Smith et al. (2023) *Science*\r\n\r\n> **Richard Smith**, Don Joe Radchuk & **Jane Head** (2023): Study title. \r\n*Science* 1-2. DOI: [doi-goes-here](https://doi.org/doi-goes-here)\r\n\r\nAbstract text.\r\n\r\n## Scripts\r\n\r\n... more notes if needed\r\n\r\nAdd the title in quotation marks as the description and the DOI as link to the repository about (right upper corner). For examples see study repositories on our GitHub).\r\nFinally, make sure to turn the visibility to public and transfer the ownership to the EcoDynIZW GitHub organization. If you have need help or have questions please ask the data manager for help.\r\n↑ Jump back to top.\r\nAppendices\r\nAppendix A) Scripting\r\nGeneral recommendations\r\nWrite the author, name and date in a header (you can use the d6 package templates for this as well).\r\nKeep code in scripts as concise as possible.\r\nUse in-line comments to explain your code that others can follow your code.\r\nIf possible, use dynamic paths (i.e. see R-package here).\r\nAlways set variables/ parameters at the top of your script; do not set values somewhere inside the code as this is error prone, because these values tend to be forgotten to get changed when updating a script. The same applies to loading packages. Please also make sure to only load packages that are really needed and remove those that you are not using for the final analysis.\r\nSave the output of a script as .rds file to smoothly load it in the next script. Additionally, save the output in a file format usable beyond R, e.g. use .csv or .txt if you want to save tabular data or GeoTiff if you want to save a raster map.\r\nUse separate scripts to create figures of publishable quality (700 dpi) from the results. Use a vector graphics format like pdf.\r\nFor simulation studies: Include all scripts, e.g. additional model code, batch files with simulated parameters, simulated landscapes and simulation results, and files used for the analyses.\r\nR\r\nStick to the Rstudio style guide to ensure readability of code.\r\nIf you are using RStudio, make sure to set the following under Tools > Global Options > General > Basic:\r\nuntick “Restore .RData into workspace at startup”\r\nset “Save workspace to .RData on exit:” to “Never”\r\nuntick “Always save history (even when not saving .RData)” (recommended)\r\n\r\nA screenshot of the RStudio general settingsWe recommend using R-Studio projects and R Markdown documents when scripting in R. If you use another “integrated development environment” (IDE) make sure you can provide versioned plain R scripts using a relative path to the used data files.\r\nImplement version control by using GitHub. If you install packages or use scripts and code chunks from GitHub provided by others, be aware to acknowledge the code developer prior to publication of scripts.\r\nDo not save the R history or the R environment. Always start a fresh and an empty R session to avoid artifacts by using objects of functions that were not defined in your script. More details here: https://www.tidyverse.org/blog/2017/12/workflow-vs-script/.\r\nIf possible use log files to document messages and errors.\r\nPython\r\nIn general we recommend using Jupyter notebooks.\r\n[under construction]\r\nNetlogo\r\n[under construction]\r\nQGIS\r\nIn general we recommend doing GIS analyses in R. If you have to use QGIS use Python as scripting language. However, the RQGIS package provides a great opportunity to script complete workflows in QGIS by using R. Moreover, you can include R scripts in the QGIS toolbox.\r\n[under construction]\r\n↑ Jump back to top.\r\nAppendix B) Spatial Data\r\nIf you are working with spatial data please have the following in mind:\r\nAlways check the projection (cartographic reference system (CRS)) of your data. Depending on what you want to do it could be necessary to change the CRS system, i.e. from an angular unit (like GPS data) to a projected unit in meters. BUT sometimes you cannot easily change it or it will drastically change your data.\r\nIf you want to save you spatial data, please save it as Geopackage (.gpkg) or raster data GeoTiff (.tif). Please give a clear name, document the filename in your lab book and add the EPSG code of your CRS to the file name. Always use utf-8 as file encoding.\r\nIf you are not sure how to handle your spatial data please contact Moritz Wenzler-Meya, the GIS manager, for help.\r\nWhen using spatial data give clear names for maps ≤ 13 characters without special characters or spaces.\r\nWrite down the cartographic reference system (CRS) at the end of the file name, e.g. filename_4326.\r\nAlways use utf-8 encoding, NEVER use the system setting. If you have to use different character encoding settings, then name the used encoding in the filename.\r\nSave the data as geopackage (.gpkg, recommended but cannot be used via ArcGis) or shapefile. Geopackages should be the first choice as the format is much quicker in every task (loading, saving, changing and computing), less limited and OGC-Standard (Open Geospatial Consortium). Be aware, that shapefiles have many limitations e.g. max 7 characters for column names. Further information is listed in Appendix B.\r\nCrosscheck your scripts and results. If you have calculated data/processed maps, make a plot and check for consistency. E.g. there should be no data outliers, terrestrial species should not occur in the sea etc. If results are valid, mark it as a milestone in your project documentation.\r\nBe aware: if you want to change the coordinate reference system (CRS) you have to transform / project the data. Never just specify a new one, because this doesn’t change the CRS!\r\nAlways include the Coordinate Reference System as EPSG code (e.g. 4326 for log/lat WGS84 Coordinates) at the end of a file name, e.g. my_env_variable_4326.gpkg.\r\nPlease save all your geo data into geopackage files (.gpkg) format to save and process your data. In general, if you export data from R please save it as an R Studio file (.rds). It will be saved without any losses.\r\nStore all point/line/polygon data as WGS84 (EPSG 4326).\r\nIf you do not understand this paragraph, contact the geodata-manager (Moritz Wenzler-Meya) before doing anything involving geodata.\r\n↑ Jump back to top.\r\nAppendix C) What Nature Says…\r\nNature 561, 277 (2018)\r\nWhy you need an agenda for meetings with your principal investigator\r\nA list of talking points can help with navigating potentially difficult topics and sticky negotiations.\r\nAs PhD students, we often find ourselves discussing our interactions with our principal investigators (PIs) and swapping advice for improving our mentoring meetings. We have found three practices to be consistently helpful:\r\nasking our PIs about all aspects of their job;\r\npreparing an agenda for each meeting;\r\nnegotiating new experiments without explicitly saying ‘no’.\r\nRead the full text: https://doi.org/10.1038/d41586-018-06619-3\r\n↑ Jump back to top.\r\n\r\n\r\n\r\n",
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"path": "impressum.html",
@@ -44,7 +44,7 @@
"description": "",
"author": [],
"contents": "\r\nAngaben gemäß § 5 TMG\r\nStephanie Kramer-Schadt\r\nBerlin\r\nKontakt\r\nE-Mail: kramer[at]izw-berlin.de\r\nVerantwortlich für den Inhalt nach § 55 Abs. 2 RStV\r\nStephanie Kramer-Schadt\r\nBerlin\r\nEU-Streitschlichtung\r\nDie Europäische Kommission stellt eine Plattform zur Online-Streitbeilegung (OS) bereit: https://ec.europa.eu/consumers/odr. Unsere E-Mail-Adresse finden Sie oben im Impressum.\r\nVerbraucherstreitbeilegung/Universalschlichtungsstelle\r\nWir sind nicht bereit oder verpflichtet, an Streitbeilegungsverfahren vor einer Verbraucherschlichtungsstelle teilzunehmen.\r\nHaftung für Inhalte\r\nAls Diensteanbieter sind wir gemäß § 7 Abs.1 TMG für eigene Inhalte auf diesen Seiten nach den allgemeinen Gesetzen verantwortlich. Nach §§ 8 bis 10 TMG sind wir als Diensteanbieter jedoch nicht verpflichtet, übermittelte oder gespeicherte fremde Informationen zu überwachen oder nach Umständen zu forschen, die auf eine rechtswidrige Tätigkeit hinweisen.\r\nVerpflichtungen zur Entfernung oder Sperrung der Nutzung von Informationen nach den allgemeinen Gesetzen bleiben hiervon unberührt. Eine diesbezügliche Haftung ist jedoch erst ab dem Zeitpunkt der Kenntnis einer konkreten Rechtsverletzung möglich. Bei Bekanntwerden von entsprechenden Rechtsverletzungen werden wir diese Inhalte umgehend entfernen.\r\nHaftung für Links\r\nUnser Angebot enthält Links zu externen Websites Dritter, auf deren Inhalte wir keinen Einfluss haben. Deshalb können wir für diese fremden Inhalte auch keine Gewähr übernehmen. Für die Inhalte der verlinkten Seiten ist stets der jeweilige Anbieter oder Betreiber der Seiten verantwortlich. Die verlinkten Seiten wurden zum Zeitpunkt der Verlinkung auf mögliche Rechtsverstöße überprüft. Rechtswidrige Inhalte waren zum Zeitpunkt der Verlinkung nicht erkennbar.\r\nEine permanente inhaltliche Kontrolle der verlinkten Seiten ist jedoch ohne konkrete Anhaltspunkte einer Rechtsverletzung nicht zumutbar. Bei Bekanntwerden von Rechtsverletzungen werden wir derartige Links umgehend entfernen.\r\nUrheberrecht\r\nDie durch die Seitenbetreiber erstellten Inhalte und Werke auf diesen Seiten unterliegen dem deutschen Urheberrecht. Die Vervielfältigung, Bearbeitung, Verbreitung und jede Art der Verwertung außerhalb der Grenzen des Urheberrechtes bedürfen der schriftlichen Zustimmung des jeweiligen Autors bzw. Erstellers. Downloads und Kopien dieser Seite sind nur für den privaten, nicht kommerziellen Gebrauch gestattet.\r\nSoweit die Inhalte auf dieser Seite nicht vom Betreiber erstellt wurden, werden die Urheberrechte Dritter beachtet. Insbesondere werden Inhalte Dritter als solche gekennzeichnet. Sollten Sie trotzdem auf eine Urheberrechtsverletzung aufmerksam werden, bitten wir um einen entsprechenden Hinweis. Bei Bekanntwerden von Rechtsverletzungen werden wir derartige Inhalte umgehend entfernen.\r\nQuelle: eRecht24\r\n\r\n\r\n\r\n",
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{
"path": "index.html",
@@ -52,7 +52,7 @@
"description": "Department 6 at Leibniz Institute for Zoo and Wildlife Research (IZW)",
"author": [],
"contents": "\r\nWelcome to D6!\r\nWe are scientists of the Department of Ecological Dynamics at the Leibniz Institute for Zoo and Wildlife Research in Berlin, Germany. Our research is focused on understanding ecological dynamics in space and time, at different levels of organisation, from individuals to communities, and across gradients of human altered environments.\r\nWe investigate how fitness consequences of processes acting at the individual level, such as social behaviour or movements, competition, predator-prey or host-pathogen interactions, shape population and community dynamics, also at evolutionary scales. To ensure transparency and reproducibility, we follow the FAIR principles and provide code and data of published papers in our GitHub repositories.\r\n→ Follow us on Twitter and GitHub.\r\n\r\nOur Vision\r\n\r\nOur ultimate goal is to predict the future viability of wildlife populations, species, and communities faced with accelerating environmental change in the anthropocene and to improve landscape scale planning for conservation.\r\n\r\n\r\n\r\nOur Mission\r\n\r\nWe advance theory and concepts in ecology and evolution as well as the use of computational toolkits by developing and using a wide range of modern field and lab techniques and dynamic and simulation modeling.\r\n\r\n\r\n\r\nOur Teams\r\n\r\nWe are organized in three teams spanning all levels from individuals to populations to communities. Check out the three team pages for an overview of our current projects, group activities, and our latest publications!\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\nContact\r\nDepartment Lead: Prof. Dr. S. Kramer-Schadt\r\nDeputy Lead: Dr. Andreas Wilting\r\nCoordination: Dr. Conny Landgrafassist6[at]izw-berlin.de\r\n\r\n\r\n\r\nAddress\r\nLeibniz Institute for Zoo and Wildlife Research\r\nDepartment of Ecological Dynamics\r\nAlfred-Kowalke-Str. 17\r\nD-10315 Berlin, Germany\r\n\r\n\r\n\r\n",
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"path": "msc-bsc-theses-2018.html",
@@ -60,7 +60,7 @@
"description": "",
"author": [],
"contents": "\r\n2018\r\nLife-history consequences of snare injuries in female spotted hyenas: A long term study in the Serengeti National Park, Tanzania. Sara Kaidatzi. 02.05.2018. Diploma thesis. Biologie. Freie Universität Berlin. Benhaiem S, East ML, Hofer H.\r\nUsage of landscape metrics to predict spatial distribution of mammals in urban areas. Jessica Thimian. 04.08.2018. BSc. Biologie. Freie Universität Berlin. Supervision: Gras P, Kramer-Schadt S, Hofer H.\r\nMonthly home ranges and habitat preferences of raccoons (Procyon lotor) in the Uckermark, Germany – a estimation method comparison. Pedro Mello Rose. 2018. BSc. Biologie. Freie Universität Berlin. Supervision: Scholz C, Hofer H.\r\nAn occupancy analysis of the ocelot (Leopardus pardalis) and its potential preys in Eastern Panama. Angelica Maria Moreno Sosa. 09.10.2018. MSc. Universität Bremen. Supervision: Abrams J, Kramer-Schadt S, Marko Rohlfs (U Bremen).\r\n\r\n\r\n\r\n",
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},
{
"path": "msc-bsc-theses-2019.html",
@@ -68,7 +68,7 @@
"description": "",
"author": [],
"contents": "\r\n2019\r\nDemography and population viability of the Northern Bald Ibis (Geronticus eremita), a reintroduced bird species. Sinah Drenske. 04.02.2019. Bsc. Ökologie und Umweltplanung. Technische Universität Berlin. Supervision: Kramer-Schadt S, Radchuk V, Kowarik I (TUB).\r\nWolfmanagement in Deutschland – Vergleich der Wolfmanagementpläne der Bundesländer. Patrick Enders. 26.09.2019. Bsc. Landschaftsarchitektur und Landschaftsplanung. TU Berlin. Supervision: Heiland S (TUB), Kramer-Schadt S.\r\nInwiefern beeinflussen anthropogene Faktoren die Streifgebietsgrößen sowie täglichen Distanzen von Wildschweinen (Sus scrofa)? Elena Wernitz. 08.08.2019. Bsc. Ökologie und Umweltplanung. TUB. Supervision: Stillfried M, Kramer-Schadt S.\r\nPredicting community structure in a changing world – a new dynamic agent-based model to simulate multi-species home range behavior. Marie-Sophie Rohwäder. 26.02.2019. Msc. Ökologie, Evolution und Naturschutz. Universität Potsdam. Supervision: Kramer-Schadt S, Jeltsch F (UP).\r\nAssessing patterns of livestock attacks caused by wolf (Canis lupus) using sightings and habitat predictions. Moritz Wenzler. 26.11.2019. Msc. Global Change Geography. Humboldt-Universität zu Berlin. Kramer-Schadt S, Planillo A, Kümmerle T (HU).\r\n\r\n\r\n\r\n",
- "last_modified": "2023-10-09T17:11:30+02:00"
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{
"path": "msc-bsc-theses-2020.html",
@@ -76,7 +76,7 @@
"description": "",
"author": [],
"contents": "\r\n2020\r\nA population viability and connectivity analysis for the alpine lynx (Lynx lynx) population. Eva Sanchez Arribas. 19.11.2020. MSc. Uppsala University, Sweden. Supervision: Kramer-Schadt S, Planillo A, Molinari-Jobin A (KORA).\r\nInfluence of roost site availability on activity of forest-dwelling bats above coniferous forests. Franziska Röpke. 15.10.2020. BSc. Ökologie und Umweltplanung. TU Berlin. Supervision: Volker Kelm (K&S Umweltgutachten), Kramer-Schadt S.\r\nSpatial, temporal and interindividual determinants of wildlife-vehicle collision mortality in spotted hyenas in the Serengeti National Park between 1989 and 2020. Marwan Naciri. 25.06.2020. Msc. Master Biosciences École Normale Supérieure (ENS) Lyon, Frankreich. Supervision: Benhaiem S, Gicquel M, Planillo A, East M, Hofer H.\r\nUsing social network analysis on a population of reintroduced Northern Bald Ibis (Geronticus eremita) to understand decisions of migratory association. Sinah Drenske. 03.08.2020. Msc. Ökologie und Umweltplanung. Technische Universität Berlin. Supervision: Kramer-Schadt S, Radchuk V, Benhaiem S, Landgraf C. → Prize for best Master thesis!\r\n\r\n\r\n\r\n",
- "last_modified": "2023-10-09T17:11:31+02:00"
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"path": "msc-bsc-theses-2021.html",
@@ -84,7 +84,7 @@
"description": "",
"author": [],
"contents": "\r\n2021\r\nModelling Eurasian red squirrel (Sciurus vulgaris) occurrence along urban gradients in Berlin. Marius Grabow. 29.09.2021. MSc. TU Berlin. Ecology and Environmental Planning. Supervision: Louvrier J (IZW), Kramer-Schadt S. → Prize for best Master thesis!\r\nAccuracy of a new high throughput wildlife movement tracking system in comparison with GPS tracking. Johannes Marold. 16.09.2021. BSc. TU Berlin. Ecology and Environmental Planning. Supervision: Radchuk V (IZW), Kramer-Schadt S.\r\nDensity and life-history of the Sunda clouded leopard Neofelis diardi in the Deramakot Forest Complex, Sabah, Malaysia. Katharina Kasper. 30.08.2021. MSc. Goethe-Universität Frankfurt am Main. Supervision: Thomas Müller (SBiK-F), Andreas Wilting (IZW).\r\nEvaluating the habitat suitability of tiger in Bardia National Park and Buffer Zone areas, Nepal. Kamal Ghimire. 18.08.2021. MSc. TU Dresden. Tropical Forestry. Supervision: Berger U (TUD), Kramer-Schadt S.\r\nSmall-Scale Habitat Selection of the European Wildcat Felis silvestris silvestris in the Bernese Seeland, Switzerland. Johanna Bellack. 26.06.2021. BSc. TU Berlin. Ecology and Environmental Planning. Supervision: Maronde L (KORA), Kramer-Schadt S.\r\nEffect of artificial light at night (ALAN) on behaviour of the European hedgehog (Erinaceus europaeus Linnaeus, 1758) in the urban area of Berlin. Briseida Lozano Granados. 15.05.2021. MSc. TU Berlin. Urban Ecology. Supervision: Berger A, Kramer-Schadt S.\r\nWhat contribution can non-standardized Citizen Science data make in biodiversity monitoring? Lena Fiechter. 21.01.2021. MSc. TU Berlin. Ecology and Environmental Planning. Supervision: Planillo A, Kramer-Schadt S, Heucke-Voigt S (MfN).\r\nA habitat suitability model for Grey Crowned Cranes (Balearica regulorum) in Rwanda based on sightings. Ann-Marie Attenberger. 04.01.2021. MSc. TU Berlin. Ecology and Environmental Planning. Supervision: Olivier Nsengimana (RWCA), Kramer-Schadt S, vd Lippe M (TUB).\r\n\r\n\r\n\r\n",
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{
"path": "msc-bsc-theses-2022.html",
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"description": "",
"author": [],
"contents": "\r\n2022\r\n\r\nPilot study for the use of tick surveys and blood meal analysis to monitor wildlife populations and disease risk in the Southern Black Forest. Sarah Evelyn Hollis. 18.11.2022. MSc. Albert-Ludwigs-Universität Freiburg , Faculty of Environmental and Natural Sciences. Supervision: Prof. Dr. Gernot Segelbacher (ALUF), S Kramer-Schadt.\r\nRetracing the wolf colonization of Germany using an individual-based model. Paul Ritter. 19.10.2022. BSc. Rheinische Friedrich-Wilhelms-Universität Bonn, Geographisches Institut. Supervision: Prof. Dr. Jürgen Löffler (UB), S Kramer-Schadt, Cedric Scherer, Aimara Planillo (all IZW).\r\nControlled habitat degradation as a mitigation measure for interventions in habitats of Lacerta agilis. Magdalena Sophia Engl. 16.10.2022. MSc. TU Berlin. Urban Ecosystem Sciences. Supervision: S Kramer-Schadt, PD Dr. M.-O. Rödel (MfN).\r\nEinfluss von Witterungsbedingungen auf den Nachweis von Zauneidechsen (Lacerta agilis) in Berlin und Brandenburg. Maximilian Schwenke 18.07.2022. BSc. TU Berlin. Ecology and Environmental Planning. Supervision: S Kramer-Schadt, M von der Lippe (TUB).\r\nEvaluating the effects of blackberry (Rubus niveus) abundance on land bird diversity on Santiago Island, Galapagos. Mateo Reyes. 23.05.2022. BSc. TU Berlin. Ecology and Environmental Planning. Supervision: S Kramer-Schadt, M von der Lippe (TUB).\r\nZur Verbreitung des Rotfuchses (Vulpes vulpes) in deutschen Nationalparken auf Grundlage von Kamerafallendaten. Clara Heinrich. 20.05.2022. BSc. TU Berlin. Ecology and Environmental Planning. Supervision: S Kramer-Schadt, C Fiderer (ALUF).\r\nWildtiere in deutschen Großstädten: ein Vergleich zwischen Medienpräsenz und Wahrnehmung von Stadtbewohnern. Henry Karsch. 15.05.2022. MSc. FU Berlin. Fachbereich Biologie/Chemie/Pharmazie. Supervision: J Jeschke (FU), T Straka (TUB), S Kramer-Schadt\r\nSocial status driven epigenetic differences in female spotted hyenas in the Serengeti National Park. Nick Mewes. 14.06.2022. MSc. Universität Potsdam. Ecology, Evolution and Conservation. Supervision: A Weyrich, S Benhaiem\r\nBirds in the city: understanding direct and indirect effects of human disturbance and vegetation structure on functional diversity in Berlin. Estelle Solem. 06.04.2022. BSc. Humboldt Universität zu Berlin. Geographie. Supervision: T Kümmerle (HU), A Planillo, S Kramer-Schadt\r\nDifferential DNA methylation between dominant and subordinate spotted hyena twins. Lena Ruf. 05.04.2022. MSc. University of Potsdam. Ecology, Evolution and Conservation. Supervision: A Weyrich, S Benhaiem, J Fickel (UP)\r\nUrban planning for animals and humans: An empirical investigation of planning approaches and their perception by Berlin citizens. Lisa Jäger. 23.02.2022. MSc. TU Berlin. Ecology and Environmental Planning. Supervision: T Straka (TUB), S Kramer-Schadt\r\nEinfluss einer Unterrichtseinheit über Wildbienen auf die Einstellungen, die Emotionen und das Wissen von Schülern. Sarah Festl. 25.02.2022. BSc. TU Berlin. Ecology and Environmental Planning. Supervision: T Straka (TUB), S Kramer-Schadt\r\nSpatial use and population development of the Eurasian otter Lutra lutra in Sielmanns Naturlandschaft Groß Schauen and the state of Brandenburg. Yvonne Rychlak. 02.02.2022. MSc. Ecology, Evolution and Nature Conservation. University of Potsdam. Supervision: N Blaum (UP), S Kramer-Schadt.\r\n\r\n\r\n\r\n",
- "last_modified": "2023-10-09T17:11:34+02:00"
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},
{
"path": "msc-bsc-theses-202x-dummy.html",
@@ -100,7 +100,7 @@
"description": "",
"author": [],
"contents": "\r\n20xx\r\n\r\n\r\n\r\n",
- "last_modified": "2023-10-09T17:11:35+02:00"
+ "last_modified": "2023-10-10T10:26:25+02:00"
},
{
"path": "msc-bsc-theses-amphibian_radchuk.html",
@@ -108,7 +108,7 @@
"description": "",
"author": [],
"contents": "\r\n(contact radchuk[at]izw-berlin.de)\r\nDue to their dam-building activity, beavers affect other species in diverse ways, ranging from positive to negative effects. Although effects of beaver activity on several taxa were studied, our understanding of their effects on amphibian assemblages is still incomplete. Especially little is understood how effects of beaver activity on amphibians may be moderated by the gradient of anthropogenic disturbance (represented by human population density). However, such knowledge is important in our human-dominated world. In this study we will sample amphibian diversity (both compositional and functional) along the gradient of human population density, in ponds with and without beavers. The study will take place in North Rhine-Westfalia, in Eifel region, where beaver presence is monitored along the gradient of human population density over several decades.\r\nProfile: interest in community and functional ecology, previous field work experience is an advantage, driver’s license, basic knowledge of R\r\nSupervisors: Viktoriia Radchuk radchuk@izw-berlin.de, Lutz Dalbeck, Stephanie Kramer-Schadt\r\n\r\n\r\n\r\n",
- "last_modified": "2023-10-09T17:11:36+02:00"
+ "last_modified": "2023-10-10T10:26:26+02:00"
},
{
"path": "msc-bsc-theses-bacteria_starlings_swallows_grabow.html",
@@ -116,7 +116,7 @@
"description": "",
"author": [],
"contents": "\r\nM.Sc. Marius Grabow/ Dr. Conny Landgraf\r\n(contact grabow[at]izw-berlin.de or landgraf[at]izw-berlin.de)\r\nGeneral background\r\nParasites are ubiquitous, shaping host traits and behaviours such as movement. While parasite dynamics and host movements are often studied at large scales, e.g. migratory behaviour, our knowledge of the implications at fine scales, e.g. local movements during breeding, remains scarce. We hypothesize that parasites are proximate drivers of individual movement decisions, altering the way hosts allocate their energy, and ultimately influencing foraging, competition and fitness.\r\nThe overarching project aims to understand how fitness consequences of parasites are reflected by individual movement decisions and the surrounding environment. By accounting for a broad range of parasites, high resolution animal movement data and individual trait measures of passerines (swallows and starlings) we follow an integrative approach to model effects of host–parasite interactions in agricultural landscapes.\r\nFeather degrading bacteria (FDB)\r\nFDB are a group of bacteria with the ability to to degrade β-keratin, the principal building block of feathers, imposing substantial selection pressures on host plumage. These bacterial species colonize the plumage of most wild birds with ground-foraging and water birds having a higher prevalence. Although there is no experimental evidence about a direct link between FDB and changes in feather condition in free-living birds, we hypothesize that reduced feather quality associated with higher FDB load might affect flight performance and thus, movement behaviours in temperate breeding birds. To investigate this we collected feather samples from different passerine species including common starling (Sturnus vulgaris), barn swallow (Hirundo rustica) and house martin (Delichon urbica) at their breeding colonies, which will used to quantify the FDB loads. Additionally, for each bird we have information on individual bird condition (body measures and infection status), breeding behaviour and reproductive success as well as movement data which can be analysed using GLM/ GLMM (optional depending on candidate).\r\nJob description\r\nThe successful applicant will perform classic bacteriological analysis to quantify the total and feather-degrading bacterial loads on feather samples collected from each bird. This involves work under sterile conditions, from handling the samples, extract both free-living and attached microorganisms, dilute the obtained bacterial solutions, prepare bacteriological growth media, weigh the quantity of feather used, to count the visible colony-forming units on each plate. If the candidate is motivated statistical analyses (GLM/ GLMM) can be performed after lab work.\r\nProfile:\r\nEnrolled student (Bachelor / Master) in Biology, Ecology, Veterinary Medicine, etc.\r\nPrevious general/ basic laboratory experience (e.g. pipetting, dilution) and skills in bacteriology (work under sterile conditions, preparing growth media) is advantageous\r\nHigh motivation & sense of responsibility to work in an academic environment\r\nGood knowledge of English\r\nDate/ duration: starting time November 2022 (but flexible), minimum duration 3 month (internship), preferably longer (e.g. Master thesis)\r\nApplications and working environment:\r\nThe position preferably starts on 14. November 2022 and will last for at least 3 months. The place of employment is the IZW Berlin. Enquiries or questions should be directed to Dr. Conny Landgraf / M.Sc. Marius Grabow.\r\nPlease upload complete application documents including a letter of motivation, CV, proof of university enrolment and contact details (email address and telephone). Submit your application as soon as possible but no later than 21st October, 2022 via the Leibniz-IZW’s online-job-market.\r\nInterviews will take place 7.-11. November 2022.\r\nWe are looking forward to your application!\r\n\r\n\r\n\r\n",
- "last_modified": "2023-10-09T17:11:37+02:00"
+ "last_modified": "2023-10-10T10:26:26+02:00"
},
{
"path": "msc-bsc-theses-flying-insect_kramer.html",
@@ -124,7 +124,7 @@
"description": "",
"author": [],
"contents": "\r\n(contact wiebke.ullmann[at]uni-potsdam.de or kramer[at]izw-berlin.de)\r\nShort Abstract:\r\nDie reduzierte Abundanz und Diversität von Insekten bedeutet eine Verringerung der Nahrungsverfügbarkeit für insektivore Räuber. Dadurch steigt die Konkurrenz zwischen Arten welche sich von ähnlichen Insekten ernähren. Dies kann zum Konkurrenzausschlussprinzip und somit zum Verlust von Biodiversität führen. Um die Auswirkungen des Insektensterbens auf das Konkurrenzverhalten insektivorer Tierarten zu bestimmen, wollen wir Rauch- und Mehlschwalben in insektenarmen Agrarlandschaften besendern und die Bewegungen der Tiere mit der lokalen Abundanz und Diversität der Insekten in Zusammenhang bringen. Da die fliegenden Insektivoren jedoch in unterschiedlichen Flughöhen ihre Beute jagen, müssen die Insekten in unterschiedlichen Luftschichten gefangen werden. Dazu wollen wir eine Drohne mit einem Insektenfangnetz ausstatten. Die insektenfangende Drohne soll dann in unterschiedlichen Luftschichten mit dem Netz fliegen und Insekten fangen. Mit dieser Methode wollen wir die Insektendiversität und –abundanz in den unterschiedlichen Luftschichten quantifizieren und diese mit den Flugpfaden der Schwalben korrelieren. Gleichzeitig soll ein Vergleich verschiedener Insektenfangmethoden unternommen werden: Befinden sich die gleichen Insekten im Netz der Drohne wie in der Malaisefalle?\r\n\r\nFreilanduntersuchungen und Laborarbeit:\r\n- Erstellen einer Arbeitsroutine zum Abfliegen verschiedener Luftschichten mit Drohnen und Insektenfangnetzen\r\n- Durchführung des Insektenfangs an verschiedenen Orten im Untersuchungsgebiet\r\n- Hilfe bei der Ausstattung der Drohne mit dem Fangnetz\r\n- Insektenbestimmung und Quantifizierung, der mit den Drohnen und den Malaisefallen gefangenen Insekten (möglichst bis zur Familie)\r\nUntersuchungsgebiet/Zeitraum:\r\nDie Masterarbeit beginnt im März 2023 mit den Vorbereitungen (Annerkennung als Vertiefungsmodul möglich). Im Mai 2023 und Juni/Juli 2023 werden für jeweils ca. eine Woche täglich Insektenfänge durchgeführt. Das Untersuchungsgebiet befindet sich in der Nordwestuckermark (ca. 15km westlich von Prenzlau). In der ZALF-Forschungsstation in Dedelow stehen Zimmer als Unterkunftsmöglichkeit bereit.\r\nVoraussetzungen\r\nFührerschein Klasse B, selbständige Arbeit im Feld und im Team mit Masterstudenten, HiWis und Praktikanten, Drohnenführerschein von Vorteil\r\nKontakt:\r\nWiebke Ullmann\r\nUniversität Potsdam, Vegetationsökolgie & Naturschutz\r\nAm Mühlenberg 3, 14476 PotsdamUllmann\r\nTel.: 01715453029\r\nProf. Dr. Stephanie Kramer-Schadt\r\nLeibniz-Institute für Zoo- und Wild-tierforschung\r\nAlfred-Kowalke-Str. 17, 10315 Berlin\r\nKramer-Schadt\r\n\r\n\r\n\r\n",
- "last_modified": "2023-10-09T17:11:38+02:00"
+ "last_modified": "2023-10-10T10:26:27+02:00"
},
{
"path": "msc-bsc-theses-offers.html",
@@ -132,7 +132,7 @@
"description": "",
"author": [],
"contents": "\r\nFeather analysis of swallows and starlings\r\nGeneral background\r\nParasites are ubiquitous, shaping host traits and behaviours such as movement. While parasite dynamics and host movements are often studied at large scales, e.g. migratory behaviour, our knowledge of the implications at fine scales, e.g. local movements during breeding, remains scarce. We hypothesize that parasites are proximate drivers of individual movement decisions, altering the way hosts allocate their energy, and ultimately influencing foraging, competition and fitness.\r\nThe overarching project aims to understand how fitness consequences of parasites are reflected by individual movement decisions and the surrounding environment. By accounting for a broad range of parasites, high resolution animal movement data and individual trait measures of passerines (swallows and starlings) we follow an integrative approach to model effects of host–parasite interactions in agricultural landscapes.\r\n → read more\r\nAssessing resource-mediated movement strategies of breeding starlings\r\nContact: grabow[at]izw-berlin.de\r\nReproduction and survival are key elements in the life-history of individuals and have significant impact on fitness of populations. Among other species, the Common Starling (Sturnus vulgaris) is declining in Europe mainly due to agricultural intensification and associated loss of biodiversity, which is decreased habitat quality in the face of foraging quality (Heldbjerg et al., 2017). During breeding season of birds, foraging movements of parents play a substantial role regarding reproduction success and survival of nestlings.\r\n → read more\r\nEffects of beavers on amphibian communities along the anthropogenic gradient\r\nContact: radchuk[at]izw-berlin.de\r\nDue to their dam-building activity, beavers affect other species in diverse ways, ranging from positive to negative effects. Although effects of beaver activity on several taxa were studied, our understanding of their effects on amphibian assemblages is still incomplete. Especially little is understood how effects of beaver activity on amphibians may be moderated by the gradient of anthropogenic disturbance (represented by human population density).\r\n → read more\r\nQuantifying demographic resilience across animals\r\nContact: radchuk[at]izw-berlin.de\r\nAssessing demographic resilience is crucial to assist the conservation of populations and species. A recently proposed method to quantify demographic resilience is based on using average population matrices over time to calculate a single demographic resilience metric. This neglects the fact that the resilience of a population may change over time and is driven by population responses to disturbances, which may also change over time.\r\n → read more\r\nThe chicken or the egg: Population cycles of rodents\r\nContact: radchuk[at]izw-berlin.de\r\nAlthough population cycles received much research interest, we still poorly understand how the demographic structure of the population, i.e. sex ratio and age structure, are changing along the cycle. This is partly because in rodents, which became models for studying population cycles, the field data are typically collected at the coarse yearly resolution.\r\n → read more\r\nDoes prey abundance and diversity drive offspring numbers and flight pathes of hirundines foraging in highly industrialized agricultural landscapes?\r\nContact: wiebke.ullmann[at]uni-potsdam.de or kramer[at]izw-berlin.de\r\nDie reduzierte Abundanz und Diversität von Insekten bedeutet eine Verringerung der Nahrungsverfügbarkeit für insektivore Räuber. Dadurch steigt die Konkurrenz zwischen Arten welche sich von ähnlichen Insekten ernähren. Dies kann zum Konkurrenzausschlussprinzip und somit zum Verlust von Biodiversität führen. Um die Auswirkungen des Insektensterbens auf das Konkurrenzverhalten insektivorer Tierarten zu bestimmen, wollen wir Rauch- und Mehlschwalben in insektenarmen Agrarlandschaften besendern und die Bewegungen der Tiere sowie deren Reproduktionserfolg mit der lokalen Abundanz und Diversität der Insekten in Zusammenhang bringen. Dazu werden die Schwalben mit hochauflösenden Telemetriesendern ausgestattet und Insekten mit Malaisefallen im Untersuchungsgebiet gefangen. Um den Reproduktionserfolg verzeichnen zu können, müssen die Nester der besenderten Schwalben identifiziert werden. Die Nestidentifikation wird während des Schwalbenfangs mit Sichtbeobachtungen durchgeführt und später mit der Telemetrietechnick überprüft bzw. vervollständigt. Der Nachwuchs soll mit Kameraauf-zeichnungen und/oder mit einer Endoskopkamera gezählt werden. Die Insekten aus den Malaisefallen sollen möglichst bis zur Familie bestimmt werden und in Größenklassen unterteilt und gewogen werden.\r\n → read more\r\nLinking flying-insect abundance in various air layers and in several habitats with vertical and horizontal hirundine flight patterns in agricultural landscapes?\r\nContact: wiebke.ullmann[at]uni-potsdam.de or kramer[at]izw-berlin.de\r\nDie reduzierte Abundanz und Diversität von Insekten bedeutet eine Verringerung der Nahrungsverfügbarkeit für insektivore Räuber. Dadurch steigt die Konkurrenz zwischen Arten welche sich von ähnlichen Insekten ernähren. Dies kann zum Konkurrenzausschlussprinzip und somit zum Verlust von Biodiversität führen. Um die Auswirkungen des Insektensterbens auf das Konkurrenzverhalten insektivorer Tierarten zu bestimmen, wollen wir Rauch- und Mehlschwalben in insektenarmen Agrarlandschaften besendern und die Bewegungen der Tiere mit der lokalen Abundanz und Diversität der Insekten in Zusammenhang bringen. Da die fliegenden Insektivoren jedoch in unterschiedlichen Flughöhen ihre Beute jagen, müssen die Insekten in unterschiedlichen Luftschichten gefangen werden. Dazu wollen wir eine Drohne mit einem Insektenfangnetz ausstatten. Die insektenfangende Drohne soll dann in unterschiedlichen Luftschichten mit dem Netz fliegen und Insekten fangen. Mit dieser Methode wollen wir die Insektendiversität und –abundanz in den unterschiedlichen Luftschichten quantifizieren und diese mit den Flugpfaden der Schwalben korrelieren. Gleichzeitig soll ein Vergleich verschiedener Insektenfangmethoden unternommen werden: Befinden sich die gleichen Insekten im Netz der Drohne wie in der Malaisefalle?\r\n → read more\r\nDoes prey abundance and diversity drive offspring numbers, flight pathes and competition patterns of hirundines foraging in highly industrialized agricultural landscapes?\r\nContact: wiebke.ullmann[at]uni-potsdam.de or kramer[at]izw-berlin.de\r\nDie reduzierte Abundanz und Diversität von Insekten bedeutet eine Verringerung der Nahrungsverfügbarkeit für insektivore Räuber. Dadurch steigt die Konkurrenz zwischen Arten welche sich von ähnlichen Insekten ernähren. Dies kann zum Konkurrenzausschlussprinzip und somit zum Verlust von Biodiversität führen. Um die Auswirkungen des Insektensterbens auf das Konkurrenzverhalten insektivorer Tierarten zu bestimmen, wollen wir Rauch- und Mehlschwalben in insektenarmen Agrarlandschaften besendern und die Bewegungen der Tiere sowie deren Reproduktionserfolg mit der lokalen Abundanz und Diversität der Insekten in Zusammenhang bringen. Dazu werden die Schwalben mit hochauflösenden Telemetriesendern ausgestattet und Insekten mit Malaisefallen im Untersuchungsgebiet gefangen. Um den Reproduktionserfolg verzeichnen zu können, müssen die Nester der besenderten Schwalben identifiziert werden. Die Nestidentifikation wird während des Schwalbenfangs mit Sichtbeobachtungen durchgeführt und später mit der Telemetrietechnick überprüft bzw. vervollständigt. Der Nachwuchs soll mit Kameraauf-zeichnungen und/oder mit einer Endoskopkamera gezählt werden. Die Insekten aus den Malaisefallen sollen möglichst bis zur Familie bestimmt werden und in Größenklassen unterteilt und gewogen werden.\r\n → read more\r\n\r\n\r\n\r\n",
- "last_modified": "2023-10-09T17:11:39+02:00"
+ "last_modified": "2023-10-10T10:26:28+02:00"
},
{
"path": "msc-bsc-theses-prey_abundance_diversity_kramer.html",
@@ -140,7 +140,7 @@
"description": "",
"author": [],
"contents": "\r\n(contact wiebke.ullmann[at]uni-potsdam.de or kramer[at]izw-berlin.de)\r\nShort Abstract:\r\nDie reduzierte Abundanz und Diversität von Insekten bedeutet eine Verringerung der Nahrungsverfügbarkeit für insektivore Räuber. Dadurch steigt die Konkurrenz zwischen Arten welche sich von ähnlichen Insekten ernähren. Dies kann zum Konkurrenzausschlussprinzip und somit zum Verlust von Biodiversität führen. Um die Auswirkungen des Insektensterbens auf das Konkurrenzverhalten insektivorer Tierarten zu bestimmen, wollen wir Rauch- und Mehlschwalben in insektenarmen Agrarlandschaften besendern und die Bewegungen der Tiere sowie deren Reproduktionserfolg mit der lokalen Abundanz und Diversität der Insekten in Zusammenhang bringen. Dazu werden die Schwalben mit hochauf-lösenden Telemetriesendern ausgestattet und Insekten mit Malaisefallen und Drohnen im Untersuchungsgebiet gefangen.\r\nIn den Gebieten in denen die Insektivoren nach Nahrung suchen werden 18 Malaisefallen aufgestellt und gleichzeitig unterschiedliche Luftschichten mit insektenfangenden Drohnen abgeflogen. So soll die Nahrungsverfügbarkeit im Unterschungsgebiete überprüft werden. Für die Mitarbeit im Drohnenprojekt, der Betreuung der Insektenfallen vor Ort und eventuell der Bestimmung der Insekten im Labor benötigen wir Hilfe und vergeben Praktikanten-Stellen.\r\n\r\nFreilanduntersuchungen und eventuelle Laborarbeit:\r\n- Hilfe bei der Durchführung des Insektenfangs mit Drohnen und Malaisefallen im Untersuchungsgebiet\r\n- Eventuell Insektenbestimmung und Quantifizierung, der mit den Drohnen und den Malaisefallen gefangenen Insekten (möglichst bis zur Familie)\r\nUntersuchungsgebiet/Zeitraum:\r\nDas Feldarbeit findet statt vom 30.04. bis zum 12.05.2023 und vom 24.06. bis 06.07.2023. Wenn ein längeres Praktikum erwünscht wird, kann bei der Insektenbestimmung im Labor geholfen werden. Die Laborarbeit findet zwischen dem 12.05. und dem 24.06.2023 statt. Das Untersuchungsgebiet befindet sich in der Nordwestuckermark (ca. 15km westlich von Prenzlau). In der ZALF-Forschungsstation in Dedelow stehen Zimmer als Unterkunfts-möglichkeit bereit. Die Insektenbestimmungen können zuhause oder an der Uni Potsdam im Labor durchgeführt werden.\r\nVoraussetzungen\r\nFührerschein Klasse B (wenn möglich, eigenes Auto), selbständige Arbeit im Feld und im Team mit Masterstudenten, HiWis und Praktikanten\r\nKontakt:\r\nWiebke Ullmann\r\nUniversität Potsdam, Vegetationsökolgie & Naturschutz\r\nAm Mühlenberg 3, 14476 PotsdamUllmann\r\nTel.: 01715453029\r\nProf. Dr. Stephanie Kramer-Schadt\r\nLeibniz-Institute für Zoo- und Wild-tierforschung\r\nAlfred-Kowalke-Str. 17, 10315 Berlin\r\nKramer-Schadt\r\n\r\n\r\n\r\n",
- "last_modified": "2023-10-09T17:11:40+02:00"
+ "last_modified": "2023-10-10T10:26:29+02:00"
},
{
"path": "msc-bsc-theses-prey_abundance_kramer.html",
@@ -148,7 +148,7 @@
"description": "",
"author": [],
"contents": "\r\n(contact wiebke.ullmann[at]uni-potsdam.de or kramer[at]izw-berlin.de)\r\nShort Abstract:\r\nDie reduzierte Abundanz und Diversität von Insekten bedeutet eine Verringerung der Nahrungsverfügbarkeit für insektivore Räuber. Dadurch steigt die Konkurrenz zwischen Arten welche sich von ähnlichen Insekten ernähren. Dies kann zum Konkurrenzausschlussprinzip und somit zum Verlust von Biodiversität führen. Um die Auswirkungen des Insektensterbens auf das Konkurrenzverhalten insektivorer Tierarten zu bestimmen, wollen wir Rauch- und Mehlschwalben in insektenarmen Agrarlandschaften besendern und die Bewegungen der Tiere sowie deren Reproduktionserfolg mit der lokalen Abundanz und Diversität der Insekten in Zusammenhang bringen. Dazu werden die Schwalben mit hochauf-lösenden Telemetriesendern ausgestattet und Insekten mit Malaisefallen im Untersuchungsgebiet gefangen. Um den Reproduktionserfolg verzeichnen zu können, müssen die Nester der besenderten Schwalben identifiziert werden. Die Nestidentifikation wird während des Schwalbenfangs mit Sichtbeobachtungen durchgeführt und später mit der Telemetrietechnick überprüft bzw. vervollständigt. Der Nachwuchs soll mit Kameraauf-zeichnungen und/oder mit einer Endoskopkamera gezählt werden. Die Insekten aus den Malaisefallen sollen möglichst bis zur Familie bestimmt werden und in Größenklassen unterteilt und gewogen werden.\r\n\r\nFreilanduntersuchungen und Laborarbeit:\r\n- Erstellen einer Arbeitsroutine zur Nestidentifikation und zum Zählen des Nachwuches\r\n- Nestidentifikation und Zählen des Nachwuchses der besenderten Tiere\r\n- Mitbetreuung der Malaisefallen im Untersuchungsgebiet\r\n- Insektenbestimmung und Quantifizierung, der mit Malaisefallen gefangenen Insekten (möglichst bis zur Familie)\r\nUntersuchungsgebiet/Zeitraum:\r\nDie Masterarbeit beginnt im März 2023 mit den Vorbereitungen (Annerkennung als Vertiefungsmodul möglich). Im Mai 2023 und Juni/Juli 2023 findet die Feldarbeit statt (ca. 10-14 Tage im Mai und dann noch mal 10-14 Tage ab ca. Ende Juni). Das Untersuchungsgebiet befindet sich in der Nordwestuckermark (ca. 15km westlich von Prenzlau). In der ZALF-Forschungsstation in Dedelow stehen Zimmer als Unterkunftsmöglichkeit bereit.\r\nVoraussetzungen\r\nFührerschein Klasse B, selbständige Arbeit im Feld und im Team mit weiteren Masterstudenten, HiWis und Praktikanten\r\nKontakt:\r\nWiebke Ullmann\r\nUniversität Potsdam, Vegetationsökolgie & Naturschutz\r\nAm Mühlenberg 3, 14476 PotsdamUllmann\r\nTel.: 01715453029\r\nProf. Dr. Stephanie Kramer-Schadt\r\nLeibniz-Institute für Zoo- und Wild-tierforschung\r\nAlfred-Kowalke-Str. 17, 10315 Berlin\r\nKramer-Schadt\r\n\r\n\r\n\r\n",
- "last_modified": "2023-10-09T17:11:42+02:00"
+ "last_modified": "2023-10-10T10:26:30+02:00"
},
{
"path": "msc-bsc-theses-resilience_radchuk.html",
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"description": "",
"author": [],
"contents": "\r\n(contact radchuk[at]izw-berlin.de)\r\nAssessing demographic resilience is crucial to assist the conservation of populations and species. A recently proposed method to quantify demographic resilience is based on using average population matrices over time to calculate a single demographic resilience metric. This neglects the fact that the resilience of a population may change over time and is driven by population responses to disturbances, which may also change over time. We will use the COMADRE database to assess demographic resilience of many animal species by considering time explicitly and compare this measure to a single demographic resilience metric calculated over the whole period. The results will be of high importance for revealing the factors affecting demographic resilience and, in turn, for designing appropriate management measures.\r\nProfile: interest in population ecology, basic knowledge of R\r\nSupervisors: Viktoriia Radchuk radchuk@izw-berlin.de, Stephanie Kramer-Schadt, Oliver Höner, Sarah Benhaiem\r\n\r\n\r\n\r\n",
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},
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"path": "msc-bsc-theses-rodents_radchuk.html",
@@ -164,7 +164,7 @@
"description": "",
"author": [],
"contents": "\r\n(contact radchuk[at]izw-berlin.de)\r\nAlthough population cycles received much research interest, we still poorly understand how the demographic structure of the population, i.e. sex ratio and age structure, are changing along the cycle. This is partly because in rodents, which became models for studying population cycles, the field data are typically collected at the coarse yearly resolution. Another question that remains unanswered is whether the dynamics of demographic structure contributes to the emergence of population cycles, or, the other way around, demographic structure is changing because of the population cycling. To address these research gaps we are using a previously developed agent-based model that depicts the mechanisms of predator-prey population dynamics at fine weekly temporal resolution. This model allows obtaining both population abundance and demographic data (sex, age, reproductive state) at a weekly resolution. We will analyse these data with the advanced methods in time series analyses to answer our research questions.\r\nProfile: interest in population ecology, good command of R\r\nSupervisors: Viktoriia Radchuk radchuk@izw-berlin.de, Stephanie Kramer-Schadt\r\n\r\n\r\n\r\n",
- "last_modified": "2023-10-09T17:11:44+02:00"
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},
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"path": "msc-bsc-theses-starlings_grabow.html",
@@ -172,7 +172,7 @@
"description": "",
"author": [],
"contents": "\r\n(contact grabow[at]izw-berlin.de)\r\nShort Abstract:\r\nReproduction and survival are key elements in the life-history of individuals and have significant impact on fitness of populations. Among other species, the Common Starling (Sturnus vulgaris) is declining in Europe mainly due to agricultural intensification and associated loss of biodiversity, which is decreased habitat quality in the face of foraging quality (Heldbjerg et al., 2017). During breeding season of birds, foraging movements of parents play a substantial role regarding reproduction success and survival of nestlings.\r\nHowever, the impacts of foraging in lower quality habitat might be mitigated by increased effort in parental care, for example by increased foraging movements (Tremblay et al., 2005) or altered patterns of bi-parental care (Cockburn, 2006). Theoretical frameworks, such as Life-history theory, predict individuals to allocate resources in favour of single traits, while neglecting others (Stearns, 1992). These trade-offs allow individuals to cope with extensive changes of resource availability, e.g. increased paternal care allows to persist in lower quality habitat without decreasing reproduction rates.\r\nIn this Master thesis, we will capture adult Starlings in two habitat types of different foraging quality and equip them with VHF-tags of the ATLAS system to derive high resolution information about their movements during nestling period. By applying statistical methods, such as Step-Selection Functions (Fortin et al., 2005), we will estimate spatiotemporal resource selection of animals moving through the landscape (Thurfjell et al., 2014). Simultaneous control of deployed nest boxes gives us supporting information about reproduction success so that we can characterize and assess foraging decisions in the different habitat types and their feedback to reproduction.\r\nProfile:\r\nOwn research focus and interests are a real enrichment, we are happy to hear your ideas (e.g. assessing habitat quality based on invertebrate abundance or grazing type)\r\nInterest in scientific work (reviewing literature, conducting field work, statistical experiments and publishing results)\r\nProfound knowledge of spatial R and interest in working with high resolution movement data; candidates should feel comfortable in applying advanced statistical methods in coding environments\r\nHigh flexibility for the field work season (April-July) in Uckermark (around 2h car ride from Berlin). Field work days will cover 1-3 full days of work each week in agreement to other participants of the project, are physically demanding and (sometimes) require overnight stays at our field work station. Accommodation and travel costs will be covered\r\nCockburn, A. (2006). Prevalence of different modes of parental care in birds. Proceedings of the Royal Society B: Biological Sciences, 273(1592), 1375–1383. https://doi.org/10.1098/rspb.2005.3458\r\nFortin, D., Beyer, H. L., Boyce, M. S., Smith, D. W., Duchesne, T., & Mao, J. S. (2005). Wolves influence elk movements: Behavior shapes a trophic cascade in Yellowstone National Park. Ecology, 86(5), 1320–1330. https://doi.org/10.1890/04-0953\r\nHeldbjerg, H., Fox, A. D., Thellesen, P. V., Dalby, L., & Sunde, P. (2017). Common Starlings (Sturnus vulgaris) increasingly select for grazed areas with increasing distance-to-nest. PLoS ONE, 12(8), 1–17. https://doi.org/10.1371/journal.pone.0182504\r\nRoselli, M. A., Cady, S. M., Lao, S., Noden, B. H., & Loss, S. R. (2020). Variation in Tick Load among Bird Body Parts: Implications for Studying the Role of Birds in the Ecology and Epidemiology of Tick-Borne Diseases. Journal of Medical Entomology, 57(3), 845–851. https://doi.org/10.1093/jme/tjz228\r\nStearns, S. C. (1992). The evolution of life histories. Oxford University Press. https://doi.org/10.1046/j.1420-9101.1993.6020304.x\r\nThurfjell, H., Ciuti, S., & Boyce, M. S. (2014). Applications of step-selection functions in ecology and conservation. Movement Ecology, 2(1), 1–12. https://doi.org/10.1186/2051-3933-2-4\r\nTremblay, I., Thomas, D., Blondel, J., Perret, P., & Lambrechts, M. M. (2005). The effect of habitat quality on foraging patterns, provisioning rate and nestling growth in Corsican Blue Tits Parus caeruleus. Ibis, 147(1), 17–24. https://doi.org/10.1111/j.1474-919x.2004.00312\r\n\r\n\r\n\r\n",
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},
{
"path": "msc-bsc-theses.html",
@@ -180,7 +180,7 @@
"description": "",
"author": [],
"contents": "\r\n\r\nWe are looking for motivated students interested in questions about wildlife dynamics and distributions under global change, animal behavioral ecology or advancing theory in ecology and evolution. Students should have a strong background in (or the will to learn) R, statistics and modelling. Please contact us for possible thesis subjects and state your skills and interests (e.g., CV, certificates,…) along with the name of one or two references.\r\nHere you’ll find a list of offers for Bachelor and Master theses.\r\nFor TU Berlin students: Please consider the Reader for the steps necessary to conduct a thesis. Successful attendance of our courses ‘biodiversity dynamics I + II’ , where we teach spatial R, distribution modelling and occupancy modelling, is of advantage.\r\n\r\nBelow, you will find an overview over currently running theses as well as a list of completed theses for your information.\r\nFor older Bachelor and Master theses please check here:2022 2021 2020 2019 2018\r\n\r\nCompleted Theses in 2023\r\n\r\nWildtiere in der Stadt: Die komplexe beziehung von Urbanisierung, menschlicher Wahrnehmung und Sozialökonomie. Titus M. Mußhoff, 30.08.2023 MSc.\r\nUniversität Freiburg. Fakultät für Umwelt und Natürliche Ressourcen. Supervision: Prof. Ilse Storch (ALUF) & S Kramer-Schadt (TUB/ IZW).\r\nFood or parasite? Classification of fecal DNA based on taxonomic profiling of interaction data. Milena Luke, 11.07.2023 BSc. Humboldt-Universität zu Berlin. Lebenswissenschaftliche Fakultät Institut für Biologie. Supervision: Prof. E. Heitlinger (HU) & S Kramer-Schadt (TUB/ IZW).\r\nThe effect of natural haemosporidian infections on host fitness and movement patterns in passerines. Sirkka Mang. 24.04.2023 MSc. Universität Koblenz Landau, Fachbereich 3 Mathematik/ Naturwissenschaften. Supervision: S Kramer-Schadt (TUB/ IZW), Conny Landgraf (IZW).\r\nChanging climates, shifting phenologies. Analysing long-term data of juvenile bat occurrences for signals of climate change impacts in Bavaria, Germany. Alec Paul Christoph. 05.02.2023 MSc. Urban Ecosystem Studies, TU Berlin. Supervison: S Kramer-Schadt (IZW&TUB) & Tanja Straka (TUB).\r\nAre acoustic measurements at wind masts an effective additional method to evaluate the mortality risk for bats at wind turbines before their construction? Corinna Seidel. 17.01.2023 MSc. Urban Ecosystem Studies, TU Berlin. Supervison: S Kramer-Schadt (IZW&TUB) & Volker Kelm (Umweltgutachten K&S).\r\n\r\n\r\n\r\n",
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{
"path": "publications.html",
@@ -188,7 +188,7 @@
"description": "",
"author": [],
"contents": "\r\nFind all our publication as PDFs also at ResearchGate.\r\nFor older publications please check here:2022 | 2021 | 2020 | 2019 | 2018\r\n\r\n2023\r\n\r\nPeer-Reviewed Publications\r\n\r\nBonenfant C, Rutschmann A, Burton J, Boyles R, García F, Tilker A, Schütz E (2023): Cast away on Mindoro island: lack of space limits population growth of the endangered tamaraw. ANIM CONSERV. doi:10.1111/acv.12842\r\nBrodie JF, Mohd-Azlan J, Chen C, …, Nguyen A, …, et al. (2023): Landscape-scale benefits of protected areas for tropical biodiversity. NATURE, 620, 807–812. doi:10.1038/s41586-023-06410-z\r\nCaro T, Rashid RS, Zeltman J, Gierse L-M and Sollmann R (2023): Meta- and subpopulation estimation with disparate data: coconut crabs in the Western Indian Ocean. ANIM CONSERV.\r\ndoi:10.1111/acv.12896\r\nChakravarty R, Radchuk V, Managave S, Voigt CC (2023): Increasing species richness along elevational gradients is associated with niche packing in bat assemblages. J ANIM ECOL, 92, 863– 874. doi:10.1111/1365-2656.13897\r\nDanabalan R, Planillo A, Butschkau S, Deeg S, Pierre G, Thion C, Calvignac-Spencer S, Kramer-Schadt S, Mazzoni C (2023): Comparison of mosquito and fly derived DNA as a tool for sampling vertebrate biodiversity in suburban forests in Berlin, Germany. ENVIRON DNA, 00, 1-12. doi:10.1002/edn3.398\r\nDrenske S, Radchuk V, Scherer C, Esterer C, Kowarik I, Fritz J, Kramer-Schadt S (2023): On the road to self-sustainability: Reintroduced migratory European northern bald ibises Geronticus eremita still need management interventions for population viability. ORYX, 1-12. doi:10.1017/S0030605322000540\r\nHermanns K, Marklewitz M, Zirkel F, Kopp A, Kramer-Schadt S, Junglen S (2023): Mosquito community composition shapes virus prevalence patterns along anthropogenic disturbance gradients.\r\nELIFE, 12:e66550. doi:10.7554/eLife.66550\r\nLi J, Seeber P, Axtner J, et al. (2023): Monitoring terrestrial wildlife by combining hybridization capture and metabarcoding data from waterhole environmental DNA. BIOL CONSERV 284, 110168. doi:10.1016/j.biocon.2023.110168\r\nLokatis S, Jeschke JM, Bernard-Verdier M, Buchholz S, Grossart H-P, Havemann F, Hölker F, Itescu Y, Kowarik I, Kramer-Schadt S, Mietchen D, Musseau CL, Planillo A, Schittko C, Straka TM and Heger T (2023): Hypotheses in urban ecology: building a common knowledge base. BIOL REV. doi:10.1111/brv.12964\r\nMilles A, Banitz T, Bielcik M, Frank K, Gallagher CA, Jeltsch F, Jepsen JU, Oro D, Radchuk V, Grimm V (2023): Local buffer mechanisms for population persistence. TRENDS ECOL EVOL. doi:10.1016/j.tree.2023.06.006\r\nMugerwa B, Niedballa J, Planillo A, Sheil D, Kramer-Schadt S, Wilting A (2023): Global disparity of camera trap research allocation and defaunation risk of terrestrial mammals. REMOTE SENS ECOL CONS. doi:10.1002/rse2.360\r\nNaciri M, Planillo A, Gicquel M, East ML, Hofer H, Metzger S, Benhaiem S (2023): Three decades of wildlife-vehicle collisions in a protected area: main roads and long-distance commuting trips to migratory prey increase spotted hyena roadkills in the Serengeti. BIOL CONSERV, 279, 109950. doi:10.1016/j.biocon.2023.109950\r\nNguyen AT, Tilker A, Le Khac Q, Le M (2023): New records of the Annamite striped rabbit in Ngoc Linh, Quang Nam and Kon Tum provinces, Vietnam. MAMMALIA. doi:10.1515/mammalia-2023-0005\r\nOeser J, Heurich M, Kramer-Schadt S et al. (2023): Prerequisites for coexistence: human pressure and refuge habitat availability shape continental-scale habitat use patterns of a large carnivore. LANDSC ECOL. doi:10.1007/s10980-023-01645-7\r\nPlanillo A, Viñuela J, Malo JE, García JT, Acebes P, Santamaría AE, Domínguez JC, Olea PP (2023): Addressing phase of population cycle and spatial scale is key to understand vole abundance in crop field margins: Implications for managing a cyclic pest species. AGRIC ECOSYST ENVIRON, 345, 108306. doi:10.1016/j.agee.2022.108306\r\nPalmero S, Premier J, Kramer-Schadt S, Monterroso P and Heurich M (2023): Sampling variables and their thresholds for the precise estimation of wild felid population density with camera traps and spatial capture–recapture methods. MAM REV. doi:10.1111/mam.12320\r\nReusch R, Paul AA, Fritze M, Kramer-Schadt S, Voigt C (2023): Wind energy production in forests conflicts with tree-roosting bats. CURR BIOL, 33(4). doi:10.1016/j.cub.2022.12.050\r\nRevilla-Martín N, Giralt D, Sanz-Pérez A, Bota G, Sardà-Palomera F (2023): Disentangling the effects of management, field characteristics of fallows, and surrounding landscape to promote steppe bird conservation. AGRIC ECOSYST ENVIRON 357, 108657. doi:10.1016/j.agee.2023.108657\r\nRocha DG and Sollmann R (2023): Habitat use patterns suggest that climate-driven vegetation changes will negatively impact mammal communities in the Amazon. ANIM CONSERV. doi:10.1111/acv.12853\r\nRostro-García S, Kamler JF, Sollmann R, Balme G, Augustine BC, Kéry M, Crouthers R, Gray TNE, Groenenberg M, Prum S, Macdonald DW (2023): Population dynamics of the last leopard population of eastern Indochina in the context of improved law enforcement. BIOL CONSERV, 283. doi:10.1016/j.biocon.2023.110080\r\nRusman M, Sikhounmeuang S, Phommachak A, Pathoummavan S, Ngonephetsy K, Valao M, Yoganand K, Tilker A (2023): A recent record of the Annamite striped rabbit Nesolagus timminsi in a local market in southern Lao P.D.R. MAMMALIA. doi:10.1515/mammalia-2023-0038\r\nSchmitz OJ, Sylvén M, Atwood TB, Bakker ES, Berzaghi F, Brodie JF, Cromsigt JPGM, Davies AB, Leroux SJ, Schepers FJ, Smith FA, stark S, Svenning J-C, Tilker A, Ylänne H (2023): Trophic rewilding can expand natural climate solutions. NAT CLIM CHANG, 13, 324–333. doi:10.1038/s41558-023-01631-6\r\nSemper-Pascual A, Sheil D, Beaudrot L, … , Mugerwa B, et al. (2023): Occurrence dynamics of mammals in protected tropical forests respond to human presence and activities. NAT ECOL EVOL. doi:10.1038/s41559-023-02060-6\r\nSvendsen NA, Radchuk V, Morel-Journel T, Thuillier V, Schtickzelle N (2023): Complexity vs linearity: relations between functional traits in a heterotrophic protist. BMC ECOL EVOL, 23, 1. doi:10.1186/s12862-022-02102-w\r\nTilker A, Sinovas P (2023): Reading the signs: Camera-trapping provides new insights on scent marking in the large-antlered muntjac (Muntiacus vuquangensis). ECOL EVOL, 13, e9692. doi:10.1002/ece3.9692\r\nUllmann W, Fischer C, Kramer-Schadt S et al. (2023): The secret life of wild animals revealed by accelerometer data: how landscape diversity and seasonality influence the behavioural types of European hares. LANDSC ECOL. doi:10.1007/s10980-023-01765-0\r\nvan Moorsel SJ, Thébault E, Radchuk V, Narwani A, Montoya JM, Dakos V, Holmes M, De Laender F, Pennekamp F (2023): Predicting effects of multiple interacting global change drivers across trophic levels. GLOB CHANG BIOL, 29, 1223– 1238. doi:10.1111/gcb.16548\r\nZelnik YR, Clark AT, Radchuk V, Hodapp D and Dominguez-Garcia V (2023): Editorial: Stability across spatial and temporal scales. FRONT ECOL EEVOL 11, 1201269. doi:10.3389/fevo.2023.1201269\r\n\r\n\r\n\r\n",
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},
{
"path": "pubs-2018.html",
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"description": "",
"author": [],
"contents": "\r\n2023 | 2022 | 2021 | 2020 | 2019\r\n\r\nPeer-Reviewed Publications\r\n\r\nAbrams JF, Hohn S, Rixen T & Merico A (2018). Sundaland peat carbon dynamics and its contribution to the Holocene atmospheric CO2 concentration. Global Biogeochemical Cycles 32:704-719. DOI: 10.1002/2017GB005763.\r\nAsad S, Siku J, Shabrani A, Wilting A & Rödel MO (2018). Naja sumatrana (Sumatran spitting cobra) diet. Herpetological Review 49:134-135.\r\nAsad S, Siku J, Guharajan R, Wilting A & Rödel MO (2018). Alcalus baluensis (Dwarf Mountain Frog); Predation. Herpetological Review 49:727.\r\nAsad S, Siku J, Loader C, Gordon M, Siku J, Wilting A & Rödel MO (2018). Rhacophorus nigropalmatus (Wallace’s Flying Frog) and Polypedates leucomystax (Four-lined Treefrog); Interspecific amplexus. Herpetological Review 49:728-729.\r\nBenhaiem S, Marescot L, Hofer H, East ML, Lebreton J-D, Kramer-Schadt S & Gimenez O (2018). Robustness of eco-epidemiological capture-recapture parameter estimates to variation in infection state uncertainty. Frontiers in Veterinary Science 5:197. DOI: 10.3389/fvets.2018.00197.\r\nBenhaiem S, Marescot L, East ML, Kramer-Schadt S, Gimenez O, Lebreton JD & Hofer H (2018). Slow recovery from a disease epidemic in the spotted hyena, a keystone social carnivore. Communications Biology 1:201. DOI: 10.1038/s42003-018-0197-1.\r\nBrozovic R, Abrams JF, Mohamed A, Wong ST, Niedballa J, Bhagwat T, Sollmann R, Mannan S, Kissing J & Wilting A (2018). Effects of forest degradation on the moonrat Echinosorex gymnura in Sabah, Malaysian Borneo. Mammalan Biology 93:135-143. DOI: 10.1016/j.mambio.2018.10.003.\r\nBudiharta S, Meijaard E, Gaveau DLA, Struebig MJ, Wilting A, Kramer-Schadt S, Niedballa J, Raes N, Maron M & Wilson KA (2018). Restoration to offset the impacts of developments at a landscape scale reveals opportunities, challenges and tough choices. Global Environmental Change 52:152-161. DOI: 10.1016/j.gloenvcha.2018.07.008.\r\nCostantini D, Seeber PA, Soilemetzidou SE, Azab W, Bohner J, Buuveibaatar B, Czirják GA, East ML, Greunz EM, Kaczensky P, Lamglait B, Melzheimer J, Uiseb K, Ortega A, Osterrieder N, Sandgreen DM, Simon M, Walzer C & Greenwood AD (2018). Physiological costs of infection: herpesvirus replication is linked to blood oxidative stress in equids. Global Environmental Change 8:10347. DOI: 10.1016/j.gloenvcha.2018.07.008.\r\nEgli L, Weise H, Radchuk V, Seppelt R, Grimm V (2018). Exploring resilience with agent-based models: State of the art, knowledge gaps and recommendations for coping with multidimensionality. Ecological Complexity 40. DOI: 10.1016/j.ecocom.2018.06.008.\r\nFrigerio D, Pipek P, Kimmig S, Winter S, Melzheimer J, Diblikova L, Wachter B & Richter A (2018). Citizen science and wildlife biology: synergies and challenges. Ethology 124:365-377. DOI: 10.1111/eth.12746.\r\nFlemming D, Cress U, Kimmig S, Brandt M, Kimmerle J (2018). Emotionalization in Science Communication: The Impact of Narratives and Visual Representations on Knowledge Gain and Risk Perception. FRONT COMM 3(3), 1-9. DOI: 10.3389/fcomm.2018.00003.\r\nFranz M, Kramer‐Schadt S, Greenwood AD & Courtiol A (2018). Sickness‐induced lethargy can increase host contact rates and pathogen spread in water‐limited landscapes. Funcitonal Ecology 32:2194–2204. DOI: 10.1111/1365-2435.13149.\r\nGras P, Knuth S, Börner K, Marescot L, Benhaiem S, Aue A, Wittstatt U, Kleinschmit B & Kramer-Schadt S (2018). Landscape structures affect risk of canine distemper in urban wildlife. Frontiers in Ecology and Evolution 6:136. DOI: 10.3389/fevo.2018.00136.\r\nHeim O, Lenski J, Schulz J, Jung K, Kramer-Schadt S, Eccard JA & Voigt CC (2018). The relevance of vegetation structure and smaller water bodies for bats foraging above farmland. Basic and Applied Ecology 27:9-19. DOI: 10.1016/j.baae.2017.12.001.\r\nHernández MC, Navarro-Castilla A, Planillo A, Sánchez-González B & Barja I (2018). The landscape of fear: why some free-ranging rodents choose repeated live-trapping over predation risk and how it is associated with the physiological stress response. Behavioural Processes 157:125–132. DOI: 10.1016/j.beproc.2018.09.007.\r\nHeurich M, Schultze-Naumburg J, Piacenza N, Magg N, Cerveny J, Engleder T, Herdtfelder M, Sladova M & Kramer-Schadt S (2018). Illegal hunting as a major driver of the source-sink dynamics of a reintroduced lynx population in Central Europe. Biological Conservation 224:355-365. DOI: 10.1016/j.biocon.2018.05.011.\r\nJerosch S, Kramer-Schadt S, Götz M & Roth M (2018). The importance of small-scale structures in an agriculturally dominated landscape for the European wildcat (Felis silvestris silvestris) in central Europe and implications for its conservation. Journal for Nature Conservation 41:88-96. DOI: 10.1016/j.jnc.2017.11.008.\r\nKarakoc C, Radchuk V, Hauke H & Chatzinotas A (2018). Interactions between predation and disturbances shape prey communities. Scientific Reports:2968. DOI: 10.1038/s41598-018-21219-x.\r\nKuemmerle T, Levers C, Bleyhl B, Olech W, Perzanowski K, Reusch C & Kramer-Schadt S (2018). One size does not fit all: European bison habitat selection across herds and spatial scales. Landscape Ecology 33:1559-1572. DOI: 10.1007/s10980-018-0684-2.\r\nLehnert LS, Kramer-Schadt S, Teige T, Hoffmeister U, Popa-Lisseanu A, Bontadina F, Ciechanowski M, Dechmann DKN, Kravchenko K, Presetnik P, Starrach M, Straube M, Zöphel U & Voigt CC (2018). Variability and repeatability of noctule bat migration in Central Europe: evidence for partial and differential migration. Proc R Soc B 285:-20182174. DOI: 10.1098/rspb.2018.2174.\r\nMarescot L, Benhaiem S, Gimenez O, Hofer H, Lebreton JD, Olarte-Castillo XA, Kramer-Schadt S & East ML (2018). Social status mediates the fitness costs of infection with canine distemper virus in a social carnivore. Functional Ecology 32:1237-1250. DOI: 10.1111/1365-2435.13059.\r\nMartins RF, Schmidt A, Lenz D, Wilting A, Fickel J (2018). Human- mediated introduction of introgressed deer across Wallace’s line: Historical biogeography of Rusa unicolor and R. timorensis. Ecology and Evolution 8:1465-1479. DOI: 10.1111/2041-210X.13076.\r\nSchnell IB, Bohmann K, Sebastian E, Schultze SE, Richter SR, Murray DC, Sinding MHS, Bass D, Cadle JE, Campbell MJ, Dolch R, Edwards DP, Gray TNE, Hansen T, Hoa ANQ, Lehmkuhl Noer C, Heise-Pavlov S, Pedersen AFS, Ramamonjisoa JC, Siddall ME, Tilker A, Traeholt C, Wilkinson N, Paul Woodcock P, Yu DW, Bertelsen MF, Bunce M & Gilbert MTP (2018). Debugging diversity – a pan-continental exploration of the potential of terrestrial blood-feeding leeches as a vertebrate monitoring tool. Molecular Ecology Resources 2018:1-17. DOI: 10.1111/1755-0998.12912.\r\nSciaini M, Fritsch M, Scherer C & Simpkins CE (2018). NLMR and landscapetools: An integrated environment for simulating and modifying neutral landscape models in R. Methods in Ecology and Evolution 9:2240-2248. DOI: 10.1111/2041‐210X.13076.\r\nSeeber PA, Franz M, Dehnhard M, Ganswindt A, Greenwood AD & East ML (2018). Plains zebra (Equus quagga) adrenocortical activity increases during times of large aggregations in the Serengeti ecosystem. Hormones and Behavior 102:1-9. DOI: 10.1016/j.yhbeh.2018.04.005. Data DOI: 10.17632/zpt32w3k39.1.\r\nTeckentrup L, Grimm V, Kramer-Schadt S & Jeltsch F (2018). Community consequences of foraging under fear. Ecological Modelling 383:80-90. DOI: 10.1016/j.ecolmodel.2018.05.015.\r\nTilker A, Nguyen A, Abrams JF, Bhagwat T, Le M, Nguyen TV, Nguyen AT, Niedballa J, Solllmann R & Wilting A (2020). A little-known endemic caught in the South-east Asian extinction crisis: the Annamite striped rabbit Nesolagus timminsi. Oryx 54:178-187. DOI: 10.1017/S0030605318000534.\r\nUllmann W, Fischer C, Pirhofer-Walzl K, Kramer-Schadt S & Blaum N (2018). Spatiotemporal variability in resources affects herbivore home range formation in structurally contrasting and unpredictable agricultural landscapes. Landscape Ecology volume 33:1505-1517. DOI: 10.1007/s10980-018-0676-2.\r\nWietzkea A, Westphal C, Gras P, Kraft M, Pfohl K, Karlovsky P, Pawelzik E, Tscharntke T & Smit I (2018). Insect pollination as a key factor for strawberry physiology and marketable fruit quality. Agriculture, Ecosystems & Environment 258:197-204. DOI: 10.1016/j.agee.2018.01.036.\r\nWong ST, Belant JL, Sollmann R, Mohamed A, Niedballa J, Mathai J, Meijaard E, Street GM, Kissing J, Mannan S & Wilting A (2018). Habitat associations of the Sunda stink-badger Mydaus javanensis in three forest reserves in Sabah, Malaysian Borneo. Mammalian Biology 88:75-80. DOI: 10.1016/j.mambio.2017.11.010.\r\n\r\nBook Chapters & Reports\r\n\r\nEast ML (2018). Reproductive behavior in the Hyaenidae. In: Encyclopedia of Animal Behavior (2nd ed.). Choe JC (ed), Vol. 4, pp. 539–546, Elsevier, Academic Press. ISBN: 9780128132517. DOI: 10.1016/B978-0-12-809633-8.90127-4.\r\n\r\n\r\n\r\n",
- "last_modified": "2023-10-09T17:11:48+02:00"
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},
{
"path": "pubs-2019.html",
@@ -204,7 +204,7 @@
"description": "",
"author": [],
"contents": "\r\n2023 | 2022 | 2021 | 2020 | 2018\r\n\r\nPeer-Reviewed Publications\r\n\r\nAbrams JF, Vashishtha A, Wong ST, Nguyen A, Mohamed A, Wieser S, Kuijper A, Wilting A & Mukhopadhyay A (2019). Habitat-Net: segmentation of habitat images using deep learning. Ecological Informatics 51:121-128. DOI: 10.1016/j.ecoinf.2019.01.009.\r\nAbrams JF, Hörig LA, Brozovic R, Axtner J, Crampton-Platt A, Mohamed A, Wong ST, Sollmann R, Yu DW & Wilting A (2019). Shifting up a gear with iDNA: from mammal detection events to standardised surveys. Journal of Applied Ecology 56:1637-1648. DOI: 10.1111/1365-2664.13411.\r\nAxtner J, Crampton-Platt A, Hörig LA, Mohamed A, Xu CCY, Yu DW & Wilting A (2019). An efficient and robust laboratory workflow and tetrapod database for larger scale environmental DNA studies. GigaScience 8:giz025. DOI: 10.1093/gigascience/giz029.\r\nDalleau M, Kramer‐Schadt S, Gangat Y, Bourjea J, Lajoie G & Grimm V (2019). Modeling the emergence of migratory corridors and foraging hot spots of green sea turtle. Ecology and Evolution 9;10317-10342. DOI: 10.1002/ece3.5552.\r\nFerreira SCM, Torelli F, Klein S, Fyumagwa R, Karesh WB, Hofer H, Seeber F & East ML (2019). Evidence of high exposure to Toxoplasma gondii in free-ranging and captive African carnivores. International Journal for Parasitology: Parasites and Wildlife 8:111-117. DOI: 10.1016/j.ijppaw.2018.12.007.\r\nFerreira SCM, Hofer H, Madeira de Carvalho L & East ML (2019). Parasite infections in a social carnivore: evidence of their fitness consequences and factors modulating infection load. Ecology and Evolution 9:8783-8799. DOI: 10.1002/ece3.5431.\r\nFischer M, Di Stefano J, Gras P, Kramer‐Schadt S, Sutherland DR, Coulson G & Stillfried M (2019). Circadian rhythms enable efficient resource selection in a human‐modified landscape. Ecology and Evolution 9:7509-7527. DOI: 10.1002/ece3.5283.\r\nKanagaraj R, Araujo MB, Barman R, Davidar P, De R, Digal DK, Gopi GV, Johnsingh AJT, Kakati K, Kramer‐Schadt S, Lamichhane BR, (…), Goyal SP (2019):.Predicting range shifts of Asian elephants under global change. Diversity and Distributions 25:822-838. DOI: 10.1111/ddi.12898.\r\nKhwaja H, Buchan C, Wearn OR, Bahaa-el-din L, Bantlin D, Bernard H, Bitariho R, Bohm T, Borah J, Brodie J, Chutipong W, du Preez B, Ebang-Mbele A, Edwards S, Fairet E, Frechette JL, Garside A, Gibson L, Giordano A, Veeraswami Gopi G, Granados A, Gubbi S, Harich F, Haurez B, Havmøller RW, Helmy O, Isbell LA, Jenks K, Kalle R, Kamjing A, Khamcha D, Kiebou-Opepa C, Kinnaird M, Kruger C, Laudisoit A, Lynam A, Macdonald SE, Mathai J, Metsio Sienne J, Meier A, Mills D, Mohd-AzlanJ, Nakashima Y, Nash HC, Ngoprasert D, Nguyen A, O’Brien T, Olson D, Orbell C, Poulsen J, Ramesh T, Reeder D, Reyna R, Rich LN, Rode-Margono J, Rovero F, Sheil D, Shirley MH, Stratford K, Sukumal N, Suwanrat S, Tantipisanuh N, Tilker A, Van Berkel T, Van der Weyde LK, Varney M, Weise F, Wiesel I, Wilting A, Wong ST, Waterman C, Challender DWS (2019). Pangolins in global camera trap data: Implications for ecological monitoring.\r\nGlobal Ecology and Conservation 20:e00769. DOI: 10.1016/j.gecco.2019.e00769.\r\nMaas B, Heath S, Grass I, Cassano C, Classen A, Faria D, Gras P, Williams-Guillén K, Johnson M, Karp D, Linden V, Martínez Salinas MA, Schmack J, Kross S (2019): Experimental field exclosure of birds and bats in agricultural systems – methodological insights, potential improvements, and cost-benefit trade-offs. Basic and Applied Ecology 351-12. DOI: 10.1016/j.baae.2018.12.002.\r\nMathai J, Niedballa J, Radchuk V, Sollmann R, Heckmann I, Brodie J, Struebig M, Hearn AJ, Ross J, Macdonald DW, Hin J & Wilting A (2019). Identifying refuges for Borneo’s elusive Hose’s civet. Global Ecology and Conservation 17:e00531. DOI: 10.1016/j.gecco.2019.e00531.\r\nNiedballa J, Wilting A, Sollmann R, Hofer H & Courtiol A (2019). Assessing analytical methods for detecting spatiotemporal interactions between species from camera trapping data. Remote Sensing in Ecology and Conservation 5:272-285. DOI: 10.1002/rse2.107.\r\nNguyen A, Tran VB, Huang MD, Nguyen TAM, Nguyen DT, Tran VT, Long B, Meijaard E, Holland J, Wilting A & Tilker A (2019). Camera-trap evidence that the silver-backed chevrotain Tragulus versicolor remains in the wild in Vietnam. Nature Ecology & Evolution 3:1650–1654. DOI: 10.1038/s41559-019-1027-7.\r\nPrinz C, Stillfried M, Neubert LK & Denner J (2019). Detection of PCV3 in German wild boars. Virology Journal 16:25. DOI: 10.1186/s12985-019-1133-9.\r\nRadchuk V, Reed T, Teplitsky C, van de Pol M, Charmantier A, Hassall C, Adamík P, Adriaensen F, Ahola, Markus, Arcese P, Avilés JM, Balbontin J, Blanckenhorn W, Borras A, Burthe S, Clobert J, Dehnhard N, de Lope F, Dhondt AA, Dingemanse NJ, Doi H, Eeva T, Fickel J, Filella I, Fossøy F, Goodenough AE, Hall SJG, Hansson B, Harris M, Hasselquist D, Hickler T, Joshi J, Kharouba H, Martínez JG, Mihoub J-B, Mills JA, Molina-Morales M, Moksnes A, Ozgul A, Parejo D, Pilard P, Poisbleau M, Rousset F, Rödel MO, Scott D, Senar JC, Stefanescu C, Stokke BG, Tamotsu K, Tarka M, Tarwater C, Thonicke K, Thorley J, Wilting A, Tryjanowski P, Merilä J, Sheldon B, Møller AP, Matthysen E, Janzen F, Dobson S, Visser ME, Beissinger SR, Courtiol A & Kramer-Schadt S (2019). Adaptive responses of animals to climate change: not universal, likely insufficient. Nature Communications 10:3109. DOI: 10.1038/s41467-019-10924-4.\r\nRadchuk V, Kramer-Schadt S & Grimm V (2019). Transferability of mechanistic ecological models is about emergence. Trends in Ecology & Evolution 34:487-488. DOI: 10.1016/j.tree.2019.01.010.\r\nRadchuk V, Kramer-Schadt S, Fickel J & Wilting A (2019). Distributions of mammals in Southeast Asia: the role of the legacy of climate and species body mass. Journal of Biogeography 46:2350-2362. DOI: 10.1111/jbi.13675. Data DOI: 10.5061/dryad.qp44619.\r\nRadchuk V, De Laender F, Sarmento Cabral J, Boulangeat I, Crawford M, Bohn F, De Raedt J, Scherer C, Svenning JC, Thonicke K, Schurr FM, Grimm V & Kramer‐Schadt S (2019). The dimensionality of stability depends on disturbance type. Ecology Letters 22:674-684. DOI: 10.1111/ele.13226.\r\nRenner IW, Louvrier J & Gimenez O (2019). Combining multiple data sources in species distribution models while accounting for spatial dependence and overfitting with combined penalized likelihood maximization. Methods in Ecology and Evolution 10:2118-2128. DOI: 10.1111/2041-210X.13297\r\nRunting RK, Ruslandi G, Bronson W, Struebig MJ, Satar M, Meijaard E, Burivalova Z, Cheyne SM, Deere NJ, Game ET, Putz FE, Wells JA, Wilting A, Ancrenaz M, Ellis P, Khan FA, Leavitt SM, Marshall AJ, Possingham HP, Watson JEM & Venter OPY (2019). Larger gains from improved management over sparing–sharing for tropical forests. NAT SUSTAIN 2:53-61. DOI: 10.1038/s41893-018-0203-0.\r\nScherer C, Radchuk V, Staubach C, Müller S, Blaum N, Thulke HH & Kramer-Schadt S (2019). Seasonal host life-history processes fuel disease dynamics at different spatial scales. Journal of Animal Ecology 88:1812-1824. DOI: 10.1111/1365-2656.13070.\r\nSeeber PA, Franz M, Greenwood AD & East ML (2019). Life history stage and extrinsic factors affect behavioural time allocation in plains zebras (Equus quagga) in the Serengeti ecosystem. Behavioral Ecology and Sociobiology 73:126. DOI: 10.1007/s00265-019-2738-0.\r\nSeeber PA, McEwen GK, Löber U, Förster DW, East ML, Melzheimer J & Greenwood AD (2019). Terrestrial mammal surveillance using hybridization capture of environmental DNA from African waterholes. Molecular Ecology Resources 19:1486-1496. DOI: 10.1111/1755-0998.13069.\r\nStraka T, Wolff M, Gras P, Buchholz S & Voigt CC (2019). Tree cover mediates the effect of artificial light on urban bats. Frontiers in Ecology and Evolution, DOI: 10.3389/fevo.2019.00091.\r\nTeckentrup L, Kramer-Schadt S & Jeltsch F (2019). The risk of ignoring fear: Underestimating the effects of habitat loss and fragmentation on biodiversity. Landscape Ecology 34:2851–2868. DOI: 10.1007/s10980-019-00922-8.\r\nTilker A, Abrams JF, Mohamed A, Nguyen A, Wong ST, Sollmann R, Niedballa J, Bhagwat T, Gray TNE, Rawson BM, Guegan F, Kissing J, Wegmann M & Wilting A (2019). Habitat degradation and indiscriminate hunting differentially impact faunal communities in the Southeast Asian tropical biodiversity hotspot. Communications Biology 2:396. DOI: 10.1038/s42003-019-0640-y.\r\nWong ST, Belant JL, Sollmann R, Mohamed A, Niedballa J, Mathai J, Street GM & Wilting A (2019). Influence of body mass, sociality, and movement behavior on improved detection probabilities when using a second camera trap.\r\nGlobal Ecology and Conservation 20:e00791. DOI: 10.1016/j.gecco.2019.e00791.\r\n\r\nBook Chapters & Reports\r\n\r\nAbrams RW & Abrams JF (2019). Why should we care so much about old world tropical rainforests? In: Reference Module in Earth Systems and Environmental Sciences. Scott A. Elias (ed), Elsevier, ISBN 9780124095489. DOI: 10.1016/B978-0-12-409548-9.11969-4\r\nCourtiol A, Rousset F, Rohwäder MS, Soto DX, Lehnert LS, Voigt CC, Hobson KA, Wassenaar LI & Kramer-Schadt S (2019). Isoscape computation and inference of spatial origins with mixed models using the R package IsoriX. In: Tracking Animals with stable isotopes. Hobson KA & Wassenaar L (eds), pp. 207-236, Elsevier Academic Press, Cambridge, USA.\r\n\r\n\r\n\r\n",
- "last_modified": "2023-10-09T17:11:50+02:00"
+ "last_modified": "2023-10-10T10:26:36+02:00"
},
{
"path": "pubs-2020.html",
@@ -212,7 +212,7 @@
"description": "",
"author": [],
"contents": "\r\n2023 | 2022 | 2021 | 2019 | 2018\r\n\r\nPeer-Reviewed Publications\r\n\r\nAsad S, Abrams JF, Guharajan R, Sikui J, Wilting A & Rödel MO (2020). Stream amphibian detectability and habitat associations in a reduced impact logging concession in Malaysian Borneo. Journal of Herpetology 54:385-392. DOI: 10.1670/19-136.\r\nAsad S, Wilting A & Rödel MO (2020): Possible spatial separation at macro-habitat scales between two congeneric Psammodynastes species, including observations of fishing behaviour in Psammodynastes pictus. Salamandra 56:411-415. ISSN 0036-3375.\r\nBarnett G, Westbury MV, Sandoval-Velasco M, Vieira FG, Jeon S, Zazula G, Martin MD, Ho SYW, Mather N, Gopalakrishnan S, Ramos-Madrigal J, de Manuel M, Zepeda-Mendoza ML, Antunes A, Baez AC, De Cahsan B, Larson G, O’Brien SJ, Eizirik E, Johnson WE, Koepfli KP, Wilting A, Fickel J, Dalén L, Lorenzen ED, Marques-Bonet T, Hansen AJ, Zhang G, Bhak J, Yamaguchi N & Gilbert MTP (2020). Genomic adaptations and evolutionary history of the extinct scimitar-toothed cat, Homotherium latidens. Current Biology 30:5018-5025.E5. DOI: 10.1016/j.cub.2020.09.051.\r\nBerger A, Barthel LMF, Rast W, Hofer H & Gras P (2020). Urban hedgehog behavioural responses to temporary habitat disturbance versus permanent fragmentation. Animals 10:2109. DOI: 10.3390/ani10112109.\r\nChero G, Pradel R, Derville S, Bonneville C, Gimenez O & Garrigue C (2020). Reproductive capacity of an endangered and recovering population of humpback whales in the Southern Hemisphere. Marine Ecology Progress Series 643:219-227. DOI: 10.3354/meps13329.\r\nGicquel M, Sand H, Månsson J, Wallgren M & Wikenros C (2020): Does recolonization of wolves affect moose browsing damage on young Scots pine? Forest Ecology and Management 473:118298. DOI: 10.1016/j.foreco.2020.118298.\r\nGuerrero TP, Fickel J, Benhaiem S & Weyrich A (2020). Epigenomics and gene regulation in mammalian social systems. Current Zoology 66:307–319. DOI: 10.1093/cz/zoaa005.\r\nGrimm V, Railsback SF, Vincenot CE, Berger U, Gallagher C, DeAngelis DL, Edmonds B, Ge J, Giske J, Groeneveld J, Johnston ASA, Milles A, Nabe-Nielsen J, Polhill JG, Radchuk V, Rohwäder M-S, Stillman RA, Thiele JC, and D Ayllón (2020). The ODD protocol for describing agent-based and other simulation models: a second update to improve clarity, replication, and structural realism. JASSS 23:7. DOI: 10.18564/jasss.4259.\r\nHagen R & Suchant R (2020). Evidence of a spatial auto-correlation in the browsing level of four major European tree species. Ecology and Evolution 10:8517-8527. DOI: 10.1002/ece3.6577.\r\nHeger T, Aguilar-Trigueros AG, Bartram I, Braga RR, Dietl GP, Enders M, Gibson DJ, Gomez Aparicio L, Gras P, Jax K, Lokatis S, Lortie CJ, Mupepele AC, Schindler S, Starrfelt J, Synodinos AD & Jeschke JM (2020). The hierarchy-of-hypotheses approach: a synthesis method for enhancing theory development in ecology and evolution. BioScience 71:337–349. DOI: 10.1093/biosci/biaa130.\r\nHohn S, Acevedos-Trejos E, Abrams JF, Fulgencio de Moura J, Spranz R & Merico A (2020). The long term legacy of plastic mass production.\r\nScience of The Total Environment 746:141115. DOI: 10.1016/j.scitotenv.2020.141115.\r\nHorn J, Becher MA, Johst K, Kennedy P, Osborne JL, Radchuk V & Grimm V (2021). Honeybee colony performance affected by crop diversity and farmland structure: a modelling framework. Ecological Applications 31:e02216. DOI: 10.1002/eap.2216.\r\nKimmig SE, Beninde J, Brandt, M, Schleimer A, Kramer-Schadt S, Hofer H, Boerner K, Schulze C, Wittstatt U, Heddergott M, Halczok T, Staubach C & Frantz A (2020). Beyond the landscape: resistance modelling infers physical and behavioural gene flow barriers to a mobile carnivore across a metropolitan area. Molecular Ecology 29:466-484. DOI: 10.1111/mec.15345.\r\nKimmig SE, Flemming D, Kimmerle J, Cress U & Brandt M (2020). Elucidating the socio-demographics of wildlife tolerance using the example of the red fox (Vulpes vulpes) in Germany. Conservation Science and Practice 2:e212. DOi: 10.1111/csp2.212.\r\nKoenig H, Kiffner C, Kramer-Schadt S, Fuerst C, Keuling O & Ford A (2020). Human-wildlife coexistence in a changing world. Conservation Biology 34:786-794. DOI: 10.1111/cobi.13513.\r\nKrüger L, Stillfried M, Prinz C, Schröder V, Neubert LK & Denner J (2020). Copy number and prevalence of porcine endogenous retroviruses (PERVs) in German wild boars. Viruses 12:419. DOI: 10.3390/v12040419.\r\nKunde MN, Martins RF, Premier J, Fickel J & Förster D (2020). Population and landscape genetic analysis of the Malayan sun bear Helarctos malayanus. Conservation Genetics 21:23–135. DOI: 10.1007/s10592-019-01233-w.\r\nLigmann-Zielinska A, Siebers PO, Maglioccia N, Parker D, Grimm V, Jing Du E, Cenek M, Radchuk V, Arbab NN, Li S, Berger U, Paudel R, Robinson DT, Jankowski P, An L & Ye X (2020). One size does not fit all: a roadmap of purpose-driven mixed-method pathways for sensitivity analysis of agent-based models. JASSS 23:6. DOI: 10.18564/jasss.4201.\r\nMeijaard E, Abrams J, Juffe-Bignoli D, Voigt M & Sheil D (2020). Coconut Oil, Conservation and the Conscientious Consumer. Current Biology 30:2419-2650. DOI: 10.1016/j.cub.2020.05.059.\r\nMeijaard E, Brooks TM, Carlson KM, Slade EM, Garcia-Ulloa J, Gaveau DLA, Lee JSH, Santika T, Juffe-Bignoli D, Struebig MJ, Wich SA, Ancrenaz M, Koh LP, Zamira N, Abrams JF, Prins HHT, Sendashonga CN, Murdiyarso D, Furumo PR, Macfarlane N, Hoffmann R, Persio M, Descaks A, Szantoi Z & Sheil D (2020). The environmental impacts of palm oil in context. Nature Plants 6:1418-1426. DOI: 10.1038/s41477-020-00813-w.\r\nNguyen AT, Nguyen TV, Timmins R, Mcgowan P, Van Hoang T & Le MD (2020) Efficacy of camera traps in detecting primates in Hue Saola Nature Reserve. Primates 61:697–705. DOI: 10.1007/s10329-020-00823-4.\r\nPecoraro C, Zudaire I, Galiberti G, Romeo M, Murua H, Fruciano C, Scherer C, Tinti F, Diaha NC, Bodin N & Chassot E (2020). When size matters: the gonads of larger female yellowfin tuna (Thunnus albacares) have different fatty acid profiles compared to smaller individuals. Fisheries Research 232:105726. DOI: 10.1016/j.fishres.2020.105726\r\nPietzsch B, Fiedler S, Mertens KG, Richter M, Scherer C, Widyastuti K, Wimmler MC, Zakharova L & Berger U (2020). Metamodels for evaluating, valibrating and applying agent-based models: a review. JASSS 23:9. DOI: 10.18564/jasss.4274.\r\nPremier J, Fickel J, Heurich M & Kramer-Schadt S (2020). The boon and bane of boldness: movement syndrome as saviour and sink for population genetic diversity. Movement Ecology 8:16. DOI: 10.1186/s40462-020-00204-y.\r\nRast W, Kimmig SE, Giese L & Berger A (2020). Machine learning goes wild: Using data from captive individuals to infer wildlife behaviours. PLoS ONE 15:e0227317. DOI: 10.1371/journal.pone.0227317.\r\nScherer C, Radchuk V, Franz M, Thulke H, Lange M, Grimm V & Kramer–Schadt S (2020). Moving infections: individual movement decisions drive disease persistence in spatially structured landscapes. OIKOS 129:651-667. DOI: 10.1111/oik.07002.\r\nSchlägel UE, Grimm V, Blaum N, Colangeli P, Dammhahn M, Eccard J, Hausmann SL, Herde A, Hofer H, Joshi J, Kramer-Schadt S, Litwin M, Lozada Gobilard SD, Müller MEH, Müller T, Nathan R, Petermann JS, Pirhofer-Walzl K, Radchuk V, Rillig MC, Roeleke M, Schäfer M, Scherer C, Schiro G, Scholz C, Teckentrup L, Tiedemann R, Ullmann W, Voigt C, Weithoff G & Jeltsch F (2020). Movement-mediated community assembly and coexistence. Biological Reviews 94:1073-1096. DOI: 10.1111/brv.12600.\r\nSeeber AP, Morrison T, Ortega A, East ML, Greenwood AD & Czirják GA (2020). Immune differences in captive and free-ranging zebras (Equus zebra and E. quagga). Mammalian Biology 100:155–164. DOI: 10.1007/s42991-020-00006-0.\r\nScholz C, Firozpoor J, Kramer‐Schadt S, Gras P, Schulze C, Kimmig SE, Voigt CC & Ortmann S (2020). Individual dietary specialization in a generalistic predator: a stable isotope analysis of urban and rural red foxes. Ecolofy and Evolution 10:8855-8870. DOI: 10.1002/ece3.6584.\r\nTilker A, Abrams JF, Nguyen A, Hörig L, Axtner J, Louvrier J, Rawson BM, Nguyen HAQ, Guegan F, Nguyen TV, Le M, Sollmann R & Wilting A (2020). Identifying conservation priorities in a defaunated tropical biodiversity hotspot. Diversity and Distributions 26:426-440. DOI: 10.1111/ddi.13029.\r\nTilker A, Nguyen A, Abrams JF, Bhagwat T, Le M, Nguyen TV, Nguyen AT, Niedballa J, Sollmann R & Wilting A (2020). A little-known endemic caught in the South-east Asian extinction crisis: the Annamite striped rabbit Nesolagus timminsi. Oryx 54:178-187. DOI: 10.1017/S0030605318000534.\r\nTilker A, Nguyen A, Timmins RJ & Gray TNE (2020). No longer Data Deficient: recategorizing the Annamite striped rabbit Nesolagus timminsi as Endangered. ORYX 54:151-151. DOI: 10.1017/S0030605319001078.\r\nUllmann W, Fischer C, Kramer-Schadt S, Pirhofer-Walzl K, Glemnitz M & Blaum N (2020). How do agricultural practices affect the movement behaviour of European brown hares (Lepus europaeus)? Agriculture, Ecosystems & Environment 292:106819. DOI: 10.1016/j.agee.2020.106819.\r\nVoigt CC, Scholl JM, Bauer J, Teige T, Yovel Y, Kramer-Schadt S & Gras P (2020). Movement responses of common noctule bats to the illuminated urban landscape. Landscape Ecology 35:189–201. DOI: 10.1007/s10980-019-00942-4.\r\nWeise H, Auge H, Baessler C, Bärlund I, Bennett EM, Berger U, Bohn F, Bonn A, Borchardt D, Brand F, Chatzinotas A, Corstanje R, Laender FD, Dietrich P, Dunker S, Durka W, Fazey I, Groeneveld J, Guilbaud CSE, Harms H, Harpole S, Harris J, Jax K, Jeltsch F, Johst K, Joshi J, Klotz S, Kühn I, Kuhlicke C, Müller B, Radchuk V, Reuter H, Rinke K, Schmitt–Jansen M, Seppelt R, Singer A, Standish RJ, Thulke HH, Tietjen B, Weitere M, Wirth C, Wolf C & Grimm V (2020). Resilience trinity: safeguarding ecosystem functioning and services across three different time horizons and decision contexts. OIKOS 129:445-456. DOI: 10.1111/oik.07213.\r\n\r\nPreprints\r\n\r\nAbrams JF, Sollmann R, Mitchell SL, Struebig MJ & Wilting A (2020). Capturing biodiversity complexities while accounting for imperfect detection: the application of occupancy-based diversity profiles. bioRxiv DOI: 10.1101/2020.09.07.285510 → see Abrams et al. (2021) Ecography.\r\nAlfano N, Dayaram A, Axtner J, Tsangaras K, Kampmann ML, Mohamed A, Wong ST, Gilbert MTP, Wilting A & Greenwood AD (2020). Non-invasive surveys of mammalian viruses using environmental DNA. bioRxiv. DOI: 10.1101/2020.03.26.009993 → see Alfano et al. (2021) Methods in Ecology and Evolution.\r\nMarescot L, Franz M, Benhaiem S, Hofer H, East ML & Kramer-Schadt S (2020). Keeping the kids at home can limit the persistence of contagious pathogens in social animals. bioRXiv. DOI: 10.1101/2020.04.11.036806 → see Marescot, Franz, Benhaiem et al. (2021) Journal of Animal Ecology.\r\n\r\nBook Chapters & Reports\r\n\r\nHagen R, Kühl N, Kröschel M & Suchant R (2020). Verbiss an Tanne und Eiche in Baden-Württemberg: Ein Vergleich zwischen nadelbaum- und laubbaumdominierten Waldbeständen. Allgemeine Forst- und Jagdzeitung, Heft 7-8 der AFJZ Band 190.\r\nKramer-Schadt S, Wenzler M, Gras P & Knauer F (2020). Habitatmodellierung und Abschätzung der potenziellen Anzahl von Wolfsterritorien in Deutschland. BfN Skripten 556:7-30. DOI: 10.19217/skr556.\r\n\r\n\r\n\r\n",
- "last_modified": "2023-10-09T17:11:51+02:00"
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{
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"description": "",
"author": [],
"contents": "\r\n2023 | 2022 | 2020 | 2019 | 2018\r\n\r\nPeer-Reviewed Publications\r\n\r\nAbrams JF, Sollmann R, Mitchel SL, Struebig MJ, Wilting A (2021). Occupancy-based diversity profiles: capturing biodiversity complexities while accounting for imperfect detection. ECOGRAPHY 44(7), 975-986. DOI: 10.1111/ecog.05577\r\nAlfano N, Dayaram A, Axtner J, Tsangaras K, Kampmann ML, Mohamed A, Wong ST, Gilbert MTP, Wilting A & Greenwood AD (2021). Non-invasive surveys of mammalian viruses using environmental DNA. Methods in Ecology and Evolution. DOI: 10.1111/2041-210X.13661\r\nAsad S, Abrams JF, Guharajan R, Lagan P, Kissing J, Sikui J, Wilting A, Rödel MO (2021). Amphibian responses to conventional and reduced impact logging. FOR ECOL MANAG 484, 118949. DOI: 10.1016/J.foreco.2021.118949\r\nAyllón D, Augusiak J, Baveco H, Berger U, Charles S, Martin R, Focks A, Galic N, Gallagher C, Liu C, van Loon EE, Nabe-Nielsen J, Piou C, Polhill JG, Preuss TG, Radchuk V, Schmolke A, Stadnicka-Michalak J, Thorbek P, Railsback SF & Grimm V (2021). Keeping modelling notebooks with TRACE: good for you and good for environmental research and management support. Environmental Modelling & Software 136:104932. DOI: 10.1016/j.envsoft.2020.104932\r\nBastianelli ML, Premier J, Herrmann M, Anile S, Monterroso P, Kuemmerle T, …, & Heurich M (2021). Survival and cause-specific mortality of European wildcat (Felis silvestris) across Europe. Biological Conservation 261:109239. DOI: j.biocon.2021.109239\r\nBueno de Mesquita CP, Nichols LM, Gebert MJ, Vanderburgh C, Bocksberger G, Lester JD, Kalan AK, Dieguez P, McCarthy MS, Agbor A, Álvarez Varona P, Ayimisin AE, Bessone M, Chancellor R, Cohen H, Coupland C, Deschner T, Egbe VE, Goedmakers A, Granjon A-C, Grueter CC, Head J, R. Hernandez-Aguilar A, Jeffery KJ, Jones S, Kadam P, Kaiser M, Lapuente J, Larson B, Marrocoli S, Morgan D, Mugerwa B, Mulindahabi F, Neil E, Niyigaba P, Pacheco L, Piel AK, Robbins MM, Rundus A, Sanz CM, Sciaky L, Sheil D, Sommer V, Stewart FA, Ton E, van Schijndel J, Vergnes V, Wessling EG, Wittig RM, Yuh YG, Yurkiw K, Zuberbühler K, Gogarten JF, Heintz-Buschart A, Muellner-Riehl AN, Boesch C, Kühl HS, Fierer N, Arandjelovic M, Dunn RR. 2021. Structure of Chimpanzee Gut Microbiomes across Tropical Africa. MSYSTEMS 6(3), e01269-20. DOI: 10.1128/mSystems.01269-20\r\nBruckermann T, Greving H, Schumann A, Stillfried M, Börner K, Kimmig SE, Hagen R, Brandt M, Harms U. (2021). To know about science is to love it? Unraveling cause–effect relationships between knowledge and attitudes toward science in citizen science on urban wildlife ecology. Journal of Research in Science Teaching 58, 1179-1202. DOI: 10.1002/tea.21697\r\nChakravarty, R., Mohan, R., Voigt, C.C. , Krishnan, A., Radchuk, V. (2021). Functional diversity of Himalayan bat communities declines at high elevation without the loss of phylogenetic diversity. Sci Rep 11, 22556. DOI: 10.1038/s41598-021-01939-3\r\nClark AT, Arnoldi J‐F, Zelnik YR, Barabas G, Hodapp D, Karakoç C, König S, Radchuk V, Donohue I, Huth A, Jacquet C, de Mazancourt C, Mentges A, Nothaaß D, Shoemaker LG, Taubert F, Wiegand T, Wang S, Chase JM, Loreau M, Harpole S (2021). General statistical scaling laws for stability in ecological systems. ECOL LETT. DOI: 10.1111/ele.13760\r\nDayaram AS, Seeber P, Courtiol A, Soilemetzidou S, Tsangaras K, Franz M, McEwen G, Azab W, Kaczensky P, Melzheimer J, East ML, Ganbaatar O, Walzer C, Osterrieder N, Greenwood AD (2021). Seasonal host and ecological drivers may promote restricted water as a viral vector. SCI TOTAL ENVIRON 773, 145446. DOI: 10.1016/j.scitotenv.2021.145446\r\nFerreira SCM, Veiga MM, Hofer H, East ML, Czirják GÁ (2021). Noninvasively measured immune responses reflect current parasite infections in a wild carnivore and are linked to longevity. ECOL EVOL, early view 11(12), 7685-7699. DOI: 10.1002/ece3.7602\r\nFischer L, Möller Palau-Ribes F, Kipper S, Weiss M, Landgraf C, Lierz M (accepted). Absence of Mycoplasma spp. in nightingales (Luscinia megarhynchos) and blue (Cyanistes caeruleus) and great tits (Parus major) in Germany and its potential implication for evolutionary studies in birds. EUR J WILDL RES 68, 2. DOI: 10.1007/s10344-021-01554-7\r\nFischer M, Sutherland D, Coulson G, Stillfried M, Kramer-Schadt S, di Stefano J (2021). Spatial and temporal responses of swamp wallabies to roads in a human-modified landscape. WILDL BIOL 2021(2), wlb.00691. DOI: 10.2981/wlb.00691\r\nGray TNE, Belecks M, O’Kelly HJ, Rao M, Roberts O, Tilker A, Signs M, Yoganand K (2021). Understanding and solving the South-East Asian snaring crisis. THE ECOLOGICAL CITIZEN 4(2), 129-141. https://www.ecologicalcitizen.net\r\nGuharajan R, Mohamed A, Wong ST, Niedballa J, Petrus A, Jubili J, Lietz R, Clements GR, Wong WM, Kissing J, Lagan P, Wilting A (2021). Sustainable forest management is vital for the persistence of sun bear Helarctos malayanus populations in Sabah, Malaysian Borneo. FOR ECOL MANAG 493, 119270. DOI: 10.1016/j.foreco.2021.119270\r\nHagen R, Ortmann S, Elliger A & Arnold J (2021). Advanced roe deer (Capreolus capreolus) parturition date in response to climate change. Ecosphere 12(11), e03819. DOI: 10.1002/ecs2.3819\r\nKrause T, Tilker A (2021). Defaunation jeopardizes the SDG’s – How the loss of forest fauna undermines the achievements of the SDG’s. AMBIO. DOI: 10.1007/s13280-021-01547-5\r\nKrücken J, Czirják GÁ, Ramünke S, Maria Serocki, Heinrich SK, Melzheimer J, Costa MC, Hofer H, Aschenborn OHK, Barker NA, Capodanno S, Madeira de Carvalho L, von Samson-Himmelstjerna G, East ML & Wachter B (2021). Genetic diversity of vector-borne pathogens in spotted and brown hyenas from Namibia and Tanzania relates to ecological conditions rather than host taxonomy. PARASITES VECTORS 14, 328. DOI: 10.1186/s13071-021-04835-x\r\nKürschner T, Scherer C, Radchuk V, Blaum N, Kramer-Schadt S. (2021) Movement can mediate temporal mismatches between resource availability and biological events in host-pathogen interactions. ECOL EVOL 11(10), 5728-41. DOI: 10.1002/ece3.7478\r\nLouvrier J; Planillo A; Stillfried M; Hagen R; Boerner K; Kimmig S; Ortmann S; Schumann A; Brandt M; Kramer-Schadt S (2021). Spatiotemporal interactions of a novel mesocarnivore community in an urban environment before and during SARS-CoV-2 lockdown. J ANIM ECOL, 00, 1– 14. DOI: 10.1111/1365-2656.13635\r\nMalishev M and Kramer-Schadt S (2021). Movement, Models, and Metabolism: Individual-based energy budget models as next-generation extensions for predicting animal movement outcomes across scales. ECOL MODELL 441, 109413. DOI: 10.1016/j.ecolmodel.2020.109413\r\nMarescot L, Franz M, Benhaiem S, Hofer H, Scherer C, East ML & Kramer-Schadt S (2021). Keeping the kids at home can limit the persistence of contagious pathogens in social animals. Journal of Animal Ecology. DOI: 10.1111/1365-2656.13555.\r\nMohamed A, Sollmann R, Wong ST, Niedballa J, Abrams JF, Kissing J, Wilting A (2021): Counting Sunda clouded leopards with confidence: incorporating individual heterogeneity in density estimates. ORYX 55(1), 56-65. DOI: 10.1017/S0030605318001503\r\nNguyen A, Tilker A, Le D, Le HV, Le SV, Luu TH, Tran BV, Wilting A (2021). New records and southern range extension of the Annamite striped rabbit Nesolagus timminsi in Vietnam. MAMMALIA, online first. DOI: 10.1515/mammalia-2020-0189\r\nNguyen AT, Tilker A, Nguyen TV & Le M (2021). Camera-trap records of muntjac in the lowlands of Hue Saola Nature Reserve, central Vietnam. DSG Newsletter 32.\r\nNguyen TV, Tilker A, Nguyen A, Hörig L, Axtner J, Schmidt A, Le M, Nguyen AHQ, Rawson BM, Wilting A, Fickel J (2021). Using terrestrial leeches to assess the genetic diversity of an elusive species: the Annamite striped rabbit Nesolagus timminsi. ENVIRONMENTAL DNA 3, 780-791. DOI: 10.1002/edn3.182\r\nOlarte-Castillo XA, Dos Remédios JF, Heeger F, Hofer H, Karl S, Greenwood AD, East ML (2021). The virus-host interface: Molecular interactions of Alphacoronavirus-1 variants from wild and domestic hosts with mammalian aminopeptidase N. MOL ECOL. 2021;30(11):2607-2625. DOI: 10.1111/mec.15910\r\nPlanillo A, Kramer-Schadt S, Buchholz S, Gras P, von der Lippe M, Radchuk V. (2021) Arthropod abundance modulates bird community responses to urbanization. DIV DISTRIB 27(1), 34-49. DOI: 10.1111/ddi.13169\r\nPlanillo A, Fiechter L, Sturm U, Heucke-Voigt S, Kramer-Schadt S (2021) Citizen science data for urban planning: Comparing different sampling schemes for modelling urban bird distribution. LAND URB PLAN 211. DOI: 10.1016/j.landurbplan.2021.104098\r\nPremier J, Gahbauer M, Leibl F, Heurich M (2021). In-situ feeding as a new management tool to conserve orphaned Eurasian lynx (Lynx lynx). ECOL EVOL, accepted. DOI: 10.1002/ece3.7261\r\nPretzlaff I, Radchuk V, Turner JM, Dausmann KH (2021) Flexibility in thermal physiology and behaviour allows body mass maintenance in hibernating hazel dormice. J ZOOL, 314(1), 1-11. DOI: 10.1111/jzo.12862\r\nTran DV, Viet DP, Tien TV, Nguyen A, Van CP & Tilker A (2021). New records of the forest musk deer Moschus berezovskii in Viet Nam revealed by camera-traps. ORYX 55(4) , 494-495. DOI: 10.1017/S0030605321000569\r\nWikenros C, Gicquel M, Zimmermann B, FlagstaO, Akesson M (2021). Age at first reproduction in wolves: different patterns of density dependence for females and males. PRoc R SOC B 288, 2021020. DOI: 10.1098/rspb.2021.0207\r\nWilting A, Nguyen TV, Axtner J, Nguyen A, Schmidt A, Le M, Nguyen AHQ, Rawson BM, Tilker A, Fickel J (2021). Creating genetic reference datasets: Indirect sampling of target species using terrestrial leeches as sample “collectors”. ENVIRONMENTAL DNA, 4(2), 311-325. DOI: 10.1002/edn3.256\r\n\r\nPreprints\r\n\r\nDrenske S, Radchuk V, Scherer C, Esterer C, Kowarik I, Fritz J & Kramer-Schadt S (2021). Halfway to self-sustainability: reintroduced migratory European Northern Bald Ibises (Geronticus eremita) still need management interventions for population viability. bioRxiv. DOI: 10.1101/2021.04.03.438331\r\nHermanns K, Marklewitz M, Zirkel F, Kopp K, Kramer-Schadt S & Junglen S (2021). Mosquito community composition shapes virus prevalence patterns along anthropogenic disturbance gradients. bioRXiv. DOI: 10.1101/2021.02.04.429754\r\n\r\nBook Chapters & Reports\r\n\r\nHeurich M, Premier J, Schultze-Naumburg J, Herdtfelder M, Oeser J & Kramer-Schadt S (2021). Erforschung der Populations- und Bewegungsökologie des Luchses als Grundlage eines Metapopulationsmanagements der kontinentaleuropäischen Luchspopulationen (Lynx lynx). Natur und Landschaft 96 (1). DOI: 10.17433/1.2021.50153867.1118\r\nRadchuk V, Kramer-Schadt S, Berger U, Scherer C, Backmann P & Grimm V (2021). Individual-based models. In: Demographic Methods across the Tree of Life, Salguero-Gomez R & Gamelon M (eds.), Oxford University Press https://global.oup.com/academic/product/demographic-methods-across-the-tree-of-life-9780198838609?cc=de&lang=en&.\r\n\r\n\r\n\r\n",
- "last_modified": "2023-10-09T17:11:52+02:00"
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},
{
"path": "pubs-2022.html",
@@ -228,7 +228,7 @@
"description": "",
"author": [],
"contents": "\r\nFind all our publication as PDFs also at ResearchGate.\r\nFor older publications please check here:2023 | 2021 | 2020 | 2019 | 2018\r\n\r\n2022\r\n\r\nPeer-Reviewed Publications\r\n\r\nAlexiou I, Abrams JF, Coudrat CNZ, Nanthavong C, Nguyen A, Niedballa J, Wilting A , Tilker A (2022): Camera-trapping reveals new insights in the ecology of three sympatric muntjacs in an overhunted biodiversity hotspot. MAMM BIOL, 102, 489–500. doi:10.1007/s42991-022-00248-0\r\nAntunes AC, Montanarin A, Gräbin DM, …, Sollmann R, …, Ribeiro MC (2022): AMAZONIA CAMTRAP: A dataset of mammal, bird, and reptile species recorded with camera traps in the Amazon forest. ECOLOGY, 103(9), e3738. doi:10.1002/ecy.3738\r\nAppleton MR, Courtiol A, Emerton L, …, Tilker A, et al. (2022): Protected area personnel and ranger numbers are insufficient to deliver global expectations. NAT SUSTAIN, 5, 1100–1110. doi:10.1038/s41893-022-00970-0\r\nAsad S, Vitalis V, Guharajan R, Abrams JF, Lagan P, Kissing J, Sikui J, Wilting A, Rödel MO (2022): Variable species but similar amphibian community responses across habitats following reduced impact logging. GLOB ECOL CONSERV, 35, e02061. doi:10.1016/j.gecco.2022.e02061\r\nBolas EC, Sollmann R, Crooks KR, Boydston EE, Shaskey L, Boser CL, Dillon A, Van Vuren DH (2022): Role of microhabitat and temporal activity in facilitating coexistence of endemic carnivores on the California Channel Islands. J MAMMAL, 103, 18-28. doi:10.1093/jmammal/gyab125\r\nBenhaiem S, Kaidatzi S, Hofer H, East ML (2022): Long-term reproductive costs of snare injuries in a keystone terrestrial by-catch species. ANIM CONSERV. doi:10.1111/acv.12798\r\nBitariho R, Akampurira E, Mugerwa B (2022): Long-term funding of community projects has contributed to mitigation of illegal activities within a premier African protected area, Bwindi impenetrable National Park, Uganda. CONSERV SCI PRACT, e12761. doi:10.1111/csp2.12761\r\nBrieger F, Kämmerle JL, Hagen R, Suchant R (2022): Behavioural reactions to oncoming vehicles as a crucial aspect of wildlife-vehicle collision risk in three common wildlife species. ACCID ANAL PREV, 168. doi:10.1016/j.aap.2021.106564\r\nCalderon Quinonez AP, Louvrier J, Planillo AP, [….], Kramer-Schadt S (2022): Occupancy models reveal potential of conservation prioritization for Central American jaguars. ANIM CONSERV, doi:10.1111/acv.12772\r\nCardador L, Tella JL, Louvrier J, Anadón JD, Abellán P, Carrete M (2022): Climate matching, anthropogenic factors, and dispersal contribute differentially to the colonisation and extinction of local populations during dynamic avian invasions. DIVERS DISTRIB, 28, 1908– 1921. doi:10.1111/ddi.13591\r\nCulhane K, Sollmann R, White AM, Tarbill GL, Cooper SD, Young HS (2022): Small mammal responses to fire severity mediated by vegetation characteristics and species traits. ECOL EVOL, 12(5), e8918. doi:10.1002/ece3.8918\r\nEast ML, Thierer D, Benhaiem S, Metzger S, Hofer H (2022): Infanticide by adult females causes sexual conflict in a female-dominated social mammal. FRONT ECOL EVOL 10. doi:10.3389/fevo.2022.860854\r\nFesta F, AncillottoL, Santini L, Pacifici M, Rocha R, Toshkova N, Amorim F, Benítez-5 López A, Domer A, Hamidović D, Kramer-Schadt S, Mathews F, Radchuk V, Rebelo H, Ruczynski I, Solem E, Tsoar A, Russo D, Razgour O (2022): Bat responses to climate change: a systematic review. BIOL REV. doi:10.1111/brv.12893\r\nFigueiredo L, Scherer C, Cabral JS (2022): Computational notebooks to facilitate writing and improve reproducibility of (ecological) research. PLOS COMPUT BIOL, 18, e1010356. doi:10.1371/journal.pcbi.1010356\r\nFogarty FA, Yen JDL, Fleishman E, Sollmann R, Ke A (2022): Multiple-region, N-mixture community models to assess associations of riparian area, fragmentation, and species richness. ECOL APPL, e2698. doi:10.1002/eap.2698\r\nGicquel M, East ML, Hofer H, Benhaiem S (2022): Early-life adversity predicts performance and fitness in a wild social carnivore. J ANIM ECOL, 00, 1– 13. doi:10.1111/1365-2656.13785\r\nGicquel M, East ML, Hofer H, Cubaynes S, Benhaiem S (2022): Climate change does not decouple interactions between a central place foraging predator and its migratory prey. ECOSPHERE, 13, e4012. doi:10.1002/ecs2.4012\r\nGorczynski D, Hsieh C, Ahumad J, Akampurira E, Andrianarisoa MH, Espinosa S, Johnson S, Kayijamahe C, Lima MGM, Mugerwa B, Rovero F, Salvador J, Santos F, Sheil D, Uzabah, E, Beaudrot L (2022): Human density modulates spatial associations among tropical forest terrestrial mammal species. GLOB CHANG BIOL, 28, 7205–7216. doi:10.1111/gcb.16434\r\nGrabow M, Louvrier JLP, Planillo A, Kiefer S, Drenske S, Börner K, Stillfried M, Hagen R, Kimmig S, Straka TM, Kramer-Schadt S (2022): Data-integration of opportunistic species observations into hierarchical modeling frameworks improves spatial predictions for urban red squirrels. FRONT ECOL EVOL, 10, 881247. doi:10.3389/fevo.2022.881247\r\nGuharajan R, Abrams JF, Abram NK, Lim HY, Gopalasamy RC, Deere NJ, Struebig MJ, Goossens B, Gardner PC, Brodie JF, Granados A, Teoh SW, Hearn AJ, Ross J, Macdonald DW, Mohamed A, Wong ST, Hastie AYL, Wong W-M, Kretschmar P, Wong ST, Koh SPH, Wilting A (2022): Determinants of sun bear Helarctos malayanus habitat use in Sabah, Malaysian Borneo and its predicted distribution under future forest degradation and loss. BIODIVERS CONSERV. doi:10.1007/s10531-022-02503-9\r\nGünther T, Kramer-Schadt S, Fuhrmann M, Belik V (2022): Environmental factors associated with the prevalence of ESBL/AmpC-producing Escherichia coli in wild boar (Sus scrofa).\r\nFRONT VET SCI, 9, 980554. doi:10.3389/fvets.2022.980554\r\nHagen R, Ortmann S, Elliger A, & Arnold J (2022): Evidence for a male-biased sex ratio in the offspring of a large herbivore: The role of environmental conditions in the sex ratio variation. ECOL EVOL, 12, e8938. doi:10.1002/ece3.8938\r\nHering R, Hauptfleisch M, Jago M, Smith T, Kramer-Schadt S, Stiegler J, Blaum N (2022): Don’t stop me now: Managed fence gaps could allow migratory ungulates to track dynamic resources and reduce fence related energy loss. FRONT ECOL EVOL, 10, 907079. doi:10.3389/fevo.2022.907079\r\nHering R, Hauptfleisch M, Kramer-Schadt S, Stiegler J, Blaum N (2022): Effects of fences and fence gaps on the movement behavior of three southern African antelope species. FRONT CONSERV SCI, 3, 959423. doi:10.3389/fcosc.2022.959423\r\nKalyahe MM, Hofer H, East ML (2022): Do anthropogenic sources of food increase livestock predation in the area surrounding Ruaha National Park? ENVIRON CONSERV 49, 105-113. doi:10.1017/S037689292200008X\r\nKappeler PM, Benhaiem S, Fichtel C, Fromhage L, Höner OP, Jennions MD, Kaiser S, Krüger O, Schneider JM, Tuni C, van Schaik J, Goymann W (2022): Sex roles and sex ratios in animals. BIOL REV. doi:10.1111/brv.12915\r\nKitchener A, Hoffmann M, Yamaguchi N, Breitenmoser-Würsten C, Wilting A (2022): A system for designating taxonomic certainty in mammals and other taxa. MAMM BIOL, 102, 251-261. doi:10.1007/s42991-021-00205-3\r\nKitchener AC, Simo FT, Mugerwa B, Sanderson JG (2022): Evidence that Temminck described Felis aurata in 1825, not 1827. ARCH NAT HIST, 49, 78-85. doi:10.3366/anh.2022.0759\r\nKe A, Sollmann R, Frishkoff L, Karp DS (2022): A hierarchical N-mixture model to estimate behavioral variation and a case study of Neotropical birds. ECOL APPL, e2632. doi:[doi:10.1002/eap.2632](https://doi.org/10.1002/eap.2632)\r\nMcLaughlin JP, Schroeder J, White AM, Culhane K, Mirts HE, Tarbill GL, Sire L, Page M, Baker E, Moritz M, Brashares J, Young HS, Sollmann R (2022): Food webs for three burn severities after wildfire in the Eldorado National Forest, California. NAT SCI DATA, 9, 384. doi:10.1038/s41597-022-01220-w\r\nMirts HE, McLaughlin JP, Weller TJ, White AM, Young HS, Sollmann R (2022): Bats in the megafire: assessing species‘ site use in a postfire landscape in the Sierra Nevada. J MAMMAL, 103(1), 111-123. doi:10.1093/jmammal/gyab129\r\nMoreno-Sosa AM, Yacelga M, Craighead K, Kramer-Schadt S, Abrams JF (2022): Can prey occupancy act as a surrogate for mesopredator occupancy? A case study of ocelot (Leopardus pardalis). MAMM BIOL, 102, 163-175, doi:10.1007/s42991-022-00232-8\r\nNguyen TV, Wilting A, Niedballa J, Nguyen A, Rawson BM, Nguyen AQH, Cao TT, Wearn OR, Dao AC, Tilker A (2022): Getting the big picture: Landscape-scale occupancy patterns of two Annamite endemics among multiple protected areas. CONS SCI PRACT, e620. doi:10.1111/csp2.620\r\nNiedballa J, Axtner J, Döbert TF, Tilker A, Nguyen A, Wong ST, Fiderer C, Heurich M, & Wilting A (2022): imageseg: An R package for deep learning-based image segmentation. METHODS ECOL EVO, 13, 2363– 2371, doi:10.1111/2041-210X.13984\r\nReusch C, Lozar M, Kramer-Schadt S, Voigt CC (2022): Coastal onshore wind turbines lead to habitat loss for bats in Northern Germany. J ENV MANAGE 310. doi:10.1016/j.jenvman.2022.114715\r\nRipari L & Premier J, …, Kramer-Schadt S, Heurich M (2022): Human disturbance is the most limiting factor driving habitat selection of a large carnivore throughout Continental Europe. BIOL CONS, 266, 109446. doi:10.1016/j.biocon.2021.109446\r\nSemper-Pascual A, Bischof R, Milleret C, Beaudrot L, Vallejo-Vargas AF, Ahumada JA, Bitariho R, Jansen PA, Moreira Lima MG, Mugerwa B, Rovero F, Santos F, Sheil D (2022): Occupancy winners in tropical protected forests: a pantropical analysis. PROC R SOC B, 289. doi:10.1098/rspb.2022.0457\r\nStiegler J, Lins A, Dammhahn M, Kramer-Schadt S, Ortmann S, Blaum N (2022): Personality drives activity and space use in a mammalian herbivore. MOV ECOL, 10, 33. doi:10.1016/j.biocon.2021.109446\r\nSynodinos AD, Karnatak R, Aguilar-Trigueros CA, Gras P, Heger T, Ionescu D, Maaß S, Musseau CL, Onandia G, Planillo A, Weiss L, Wollrab S, Ryo M (2022): The rate of environmental change as an important driver across scales in ecology. OIKOS e09616. doi:10.1111/oik.09616\r\nVallejo-Vargas AF, Sheil D, Semper-Pascual A, … Mugerwa B, … et al. (2022): Consistent diel activity patterns of forest mammals among tropical regions. NAT COMMUN, 13, 7102. doi:10.1038/s41467-022-34825-1\r\nVlaschenko A, Kravchenko K, Yatsiuk Y, Hukov V, Kramer-Schadt S, Radchuk V (2022): Bat assemblages are shaped by land cover types and forest age: A case study from eastern Ukraine. FORESTS, 13, 1732. doi:10.3390/f13101732\r\nVoigt CC, Scherer C, Runkel V (2022). Modelling the power of acoustic monitoring to predict bat fatalities at wind turbines. CONSERV SCI PRACT, 4, e12841. doi:10.1111/csp2.12841\r\nWong S, Guharajan R, Petrus A, Jubili J, Lietz R, Abrams J, Hon J, Alen L, Ting N, Wong G, Tchin L, Bijack N, Kramer-Schadt S, Wilting A, Sollmann R (2022): How do terrestrial wildlife communities respond to small-scale Acacia plantations embedded in harvested tropical forest? ECOL EVOL, 12, e9337. doi:10.1002/ece3.9337\r\n\r\nPreprints\r\n\r\nMugerwa B, Niedballa J, Planillo A, Sheil D, Kramer-Schadt S, Wilting A (2022): Global disparity of research allocation and the Aichi biodiversity conservation targets. BIORXIV, 2022.04.07.486958, doi:10.1101/2022.04.07.486958\r\n\r\nBook Chapters & Reports\r\n\r\nGimenez O, Louvrier J, Lauret V, Santostasi N (2022): Studying Species Demography and Distribution in Natural Conditions: Hidden Markov Models. In Statistical Approaches for Hidden Variables in Ecology (eds N. Peyrard and O. Gimenez). https://doi.org/10.1002/9781119902799.ch3\r\nPapaïx J, Soubeyrand S, Bonnefon O, Walker E, Louvrier J, Klein E, Roques L (2022): Inferring Mechanistic Models in Spatial Ecology Using a Mechanistic-Statistical Approach. In Statistical Approaches for Hidden Variables in Ecology (eds N. Peyrard and O. Gimenez). https://doi.org/10.1002/9781119902799.ch4\r\nThonicke K, Rahner E, Arneth A, Bartkowski B, Bonn A, Döhler C, Finger R, Freitag J, Grosch R, Grossart H.-P, Grützmacher K, Hartman Scholz A, Häuser C, Hickler T, Hölker F, Jähnig S C, Jeschke J, Kasen R, Kastner T, Kramer-Schadt S, Krug C, Lakner S, Loft L, Matzdorf B, Meakins F, De Meester L, Monaghan M T, Müller D, Overmann J, Quaas M, Radchuk V, Reyer C, Roos C, Scholz I, Schroer S, Sioen G B, Sommer S, Sommerwerk N, Tockner K, Turk Z, Warner B, Wätzold F, Wende W, Veenstra, van der Voort H (2022): 10 Must-Knows aus der Biodiversitätsforschung 2022 | 10 Must knows from biodiversity science 2022. Leibniz-Forschungsnetzwerk Biodiversität, Potsdam, Deutschland. doi:10.5281/zenodo.6257476 | zenodo.org/record/6257527\r\n\r\n\r\n\r\n",
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{
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"description": "",
"author": [],
"contents": "\r\n\r\nPeer-Reviewed Publications\r\n\r\n\r\nPreprints\r\n\r\n\r\nBook Chapters & Reports\r\n\r\n\r\n\r\n\r\n",
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"description": "",
"author": [],
"contents": "\r\n\r\n\r\nAxtner et al. 2019\r\n\r\n\r\nAn efficient and robust laboratory workflow and tetrapod database for larger scale environmental DNA studies. GIGASCIENCE, 8:giz029.\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\nBenhaiem et al. 2018\r\n\r\n\r\nSlow recovery from a disease epidemic in the spotted hyena, a keystone social carnivore. COMMUN BIOL, 1:201.\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\nCalderon et al. 2022\r\n\r\n\r\nOccupancy models reveal potential of conservation prioritization for Central American jaguars. ANIM CONSERV.\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\nCaro et al. 2023\r\n\r\n\r\nMeta- and subpopulation estimation with disparate data: coconut crabs in the Western Indian Ocean. ANIM CONSERV.\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\nDalleau et al. 2019\r\n\r\n\r\nModeling the emergence of migratory corridors and foraging hot spots of the green sea turtle. ECOL EVOL, 9:10317–1034.\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\nDanabalan et al. 2023\r\n\r\n\r\nComparison of mosquito and fly derived DNA as a tool for sampling vertebrate biodiversity in suburban forests in Berlin, Germany. ENVIRON DNA.\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\nDrenske et al. 2023\r\n\r\n\r\nOn the road to self-sustainability: reintroduced migratory European northern bald ibises Geronticus eremita still need management interventions for population viability. ORYX, 1-12.\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\nGrabow et al. 2022\r\n\r\n\r\nData-integration of opportunistic species observations into hierarchical modeling frameworks improves spatial predictions for urban red squirrels. FRONT ECOL EVOL, 10:881247.\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\nKürschner et al. 2021\r\n\r\n\r\nMovement can mediate temporal mismatches between resource availability and biological events in host–pathogen interactions. ECOL EVOL, 11:5728–5741.\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\nLouvrier et al. 2021\r\n\r\n\r\nSpatiotemporal interactions of a novel mesocarnivore community in an urban environment before and during SARS-CoV-2 lockdown. J ANIM ECOL, 91:367–380.\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\nMarescot et al. 2020\r\n\r\n\r\n‘Keeping the kids at home’ can limit the persistence of contagious pathogens in social animals. J ANIM ECOL, 90:2523–2535.\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\nNguyen et al. 2021\r\n\r\n\r\nGetting the big picture: Landscape-scale occupancy patterns of two Annamite endemics among multiple protected areas. CONS SCI PRACT, 4:e620.\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\nPlanillo et al. 2021\r\n\r\n\r\nArthropod abundance modulates bird community responses to urbanization. DIV DIST, 27:34-49.\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\nPlanillo et al. 2021\r\n\r\n\r\nCitizen science data for urban planning: Comparing different sampling schemes for modelling urban bird distribution. LAND URB PLAN, 211:104098.\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\nRadchuk et al. 2016\r\n\r\n\r\nFrom individuals to population cycles: the role of extrinsic and intrinsic factors in rodent populations. ECOLOGY, 97:720-732.\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\nRadchuk et al. 2019\r\n\r\n\r\nAdaptive responses of animals to climate change are most likely insufficient. NAT COM, 10:3109.\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\nRocha & Sollmann 2023\r\n\r\n\r\nHabitat use patterns suggest that climate-driven vegetation changes will negatively impact mammal communities in the Amazon. ANIM CONSERV.\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\nScherer et al. 2020\r\n\r\n\r\nMoving infections: individual movement decisions drive disease persistence in spatially structured landscapes. OIKOS, 129:651–667.\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\nVoigt et al. 2022\r\n\r\n\r\nModelling the power of acoustic monitoring to predict bat fatalities at wind turbines. CONSER SCI PRACT, 4:e12841.\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n",
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"description": "",
"author": [],
"contents": "\r\nCourse biodiversity dynamics\r\nWelcome to the course collection we have developed at our Department. Below you will find the compilation of our courses. These are hosted within one repository, so that data can be shared between the single course blocks The course has a strong focus on ecological data analysis and modelling, especially spatio-temporal data of animals. It covers the whole pipeline from observation and sampling → data analysis → model prediction → conservation concept.\r\nCourse pipelineThe single course blocks follow a logical order. The first two introductory courses give an overview over handling data in R. These two course blocks are mandatory for all other courses; we then introduce statistical analyses for various types of data, e.g. from spatial distribution models for single species via biodiversity analyses of community counts, towards analyses of population trends. To do the courses, please follow the code step by step in the respective html-files of each course (see below).\r\n\r\nEach year, we teach a block course (in March) held in English, which comprises 6 ECTS (approx. 180 hrs, of which 60 hrs are preparation, 60 hrs are in presence, and 60 hrs are for preparing a project which will be graded). We will lecture the steps in data analysis, and you will prepare a little spatial conservation concept with data we provide; you are welcome to bring your own data. Drop us a line if you are interested in joining ( assist6[at]izw-berlin.de ).\r\n\r\nCourse announcements\r\n20.02.2023: 9 - 15 hrs CET: Introduction to spatial R via zoom; exercises on your own\r\n\r\n20.-24.03.2023: block course biodiversity dynamics (at IZW; hybrid possibility)\r\n\r\nPrior steps\r\nProgram installation\r\nRStudio Desktop (https://posit.co/download/rstudio-desktop/) \r\ncurrent R-version (https://cran.r-project.org/bin/windows/base/) \r\nRTools (https://cran.r-project.org/bin/windows/Rtools/) or you are using the {installr} package by following the examples (https://search.r-project.org/CRAN/refmans/installr/html/install.Rtools.html) \r\nIf you are not familiar with R and RStudio, open RStudio and follow the steps shown here of how to write scripts in R: Intro to RStudio\r\n\r\nIf you are familiar with scripting in R in RStudio, here is Cedric’s tip of the day of a cool feature in RStudio: use the rainbow parentheses option. For this, go to Tools → Global Options → Code →Display: tick rainbow parentheses. It helps you visually with closing brackets correctly for function calls and loops.\r\nChange decimal separator\r\n…from comma to point in your computer settings if you are working from a German PC, e.g. in Windows → Settings → Time and Region → Region → Advanced Settings → decimal separator: change here to point.\r\nDownload course\r\nSimply copy our course github repository directly here. This will download the whole folder structure with some basic data. However, we still recommend that you make a copy of the R-scripts so that you can write your own comments and code into the scripts. \r\nWe chose the following folder structure for our courses:\r\n\r\n└── d6_teaching_collection # root folder \r\n ├── data # data folder\r\n │ └── data_borneo # e.g., the Borneo data\r\n │ ├── geo_raster_current_asc # geo data, raster ascii format, as in data_borneo\r\n │ └── animal_data # animal observation data in borneo\r\n ├── output # storage for files created during course\r\n ├── R # store here all your scripts, i.e.\r\n │ ├── script_course1.R # r-files or rmd-files with codes\r\n │ └── script_course2.R\r\n ├── R_exercises # Exercises \r\n └── d6_teaching_collection.Rproj # the R-project\r\n\r\n\r\nOptional - use own course folder setup\r\nOptional - use own course folder setup\r\nOnly do this if you haven’t done the prior step of downloading the whole course and want to set up your own course folder structure or download only a part of the course. In order to ease access to data and script-functionality, we recommend that you use a similar folder structure as we do (see above). You will find the github repository here: https://github.com/EcoDynIZW/d6_teaching_collection.\r\nIf you are familiar with R and want to do the steps ‘by hand’, create a main (root) folder named d6_teaching_collection, then create the subfolders (data, output, R) relative to this root-folder (= d6_teaching_collection). Create an R-project within this folder (e.g. d6_teaching_collection.Rproj. For this, open RStudio → File → New Project → Existing directory: and then link it with the root folder).\r\n\r\nUsers familiar with R and RMarkdown could directly implement our d6 workflow package to make project setups easier and to handle code and projects in a reproducible way. If you chose this option, please read the ReadMe that appears on the github website and install the d6 package (with the options github= FALSE). This has the advantage that you have automatically created a root directory and an R-project. You can then load the data (e.g. data_borneo, provided in zip-files, see below) directly under the root directory. In the d6-package there are already start-rmd-scripts (= RMarkdown-scripts with yaml header → open and execute with the symbol knitR), which make the start easier. But you can also create your own R-scripts, e.g. a new script for each course unit, which you put into the folder R.\r\n\r\nFor both options, a) and b), you would need to download the data separately (link to zip.file below)\r\n\r\nFollow the courses\r\n…when you have downloaded the course folder repository (see above). In the respective course R folder, you will find html-files and rmd-files. Open the html-file in a browser by double-clicking. Open RStudio in parallel by double-clicking on the d6_teaching_collection.Rproj-file. Under Files (lower right window pane) , you can open the R-scripts.\r\n\r\nThen, either create your own R-script and follow the steps in the html-file (you can copy-paste the commands from the html-file), or save a copy of the rmd-file under your own name and run the code chunks step by step in the RStudio console. But you should always have the html-file opened in parallel to RStudio. Each course comes with exercises as a learning control.\r\nCourses 1 and 2: Basic concepts in R & Spatial R\r\n\r\nThese courses contain the minimum knowledge for handling, manipulating and visualizing various data types in R (Course1: vectors, data.frames, lists; Course2: spatial data like raster and vector files). The second course builds on the concepts introduced in course 1. It is therefore recommended to start with Course 1.\r\n\r\nYou can run Course 1 without downloading any additional data. Please note that course 1 is not meant as a beginners course - a lot of great in-depth courses are available online (see links provided in Course 1). Course 1 is rather a ‘refresher’ of the basic R concepts that are needed for all subsequent courses. In a nutshell, it goes through the base R cheatsheet. It is recommended to have the cheatsheet downloaded and to make your own notes into a copy of our script. You will find the course material for Course 1 in the repository under ./R/Course1_R_Intro.\r\n\r\nFor Course 2, you need to have the repository downloaded for access to the spatial data. Please open the .html file in ./R/Course2_R_Spatial.\r\n\r\nCourses 3_a and 3_b Species distribution models\r\n\r\nIn these courses, you will learn how to establish a functional relationship between the (relative) occurrence probability of species and (environmental) variables. This functional relationship – or species distribution/ occupancy model – can be extrapolated to other similar areas and used as an assessment of the availability of potentially suitable habitat for the respective species.\r\npresence only / MaxEnt\r\nPlease download MaxEnt here: https://biodiversityinformatics.amnh.org/open_source/maxent/\r\nFor MaxEnt you may still need to install a Java version. If you double-click the file maxent.jar, an interface should appear.\r\n\r\nDownload course data: For conducting course 3, we will provide you with additional data. Drag and drop the folders “data_borneo” and “data_berlin” from the provided zip files into the main folder (here: d6_teaching_collection).\r\n\r\nLink to data_borneo and data_berlin will be provided.\r\nPlease open the .html file in ./R/Course3_a_presence_only_sdm.\r\nrepeated presence absence / occupancy models\r\nPlease open the .html file in ./R/Course3_b_presence_absence_occupancy.\r\n\r\nCourse 4 Movement analysis\r\n\r\nThis course is an overview over the first steps for analysing relocation (telemetry) data. Using our collared red fox (Vulpes vulpes) ‘Q von Stralau’ as an example of movement data with fixes every 4 minutes, we will show how to clean your data and make first analyses of the tracks (step length, turning angles) and home range analyses.\r\nPlease open the .html file in ./R/Course4_telemetry_movement.\r\n\r\nCourse 5 Biodiversity metrics\r\n\r\nIn this part of the course we are going to explore more in detail how we measure and compare biodiversity among different sites. We will focus mainly of alpha diversity, which refers to the diversity at a specific site; this is the group of metrics we use to compare diversity among sites. We will explore the classic and current alpha diversity indices for both presence/absence data and abundance data. Then, we will learn which conditions the diversity samples need to meet to be comparable and how to analyse the effects of environmental variables in the diversity metric values. Finally, we will apply all this to statistically analyse urban Berlin bird diversity and create a spatial “map of diversity” for the city.\r\nPlease open the .html file in ./R/Course5_biodiversity_abundance_metrics.\r\n\r\nCourse 6 Population analyses\r\n\r\nPlease open the .html file in ./R/Course6_demography_population_models.\r\n\r\n\r\n\r\n\r\n",
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{
"path": "team-biodiversity.html",
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"description": "Lead: Dr. Andreas Wilting & Dr. Rahel Sollmann<\/b> \n Assistance: Dr. Jan Axtner<\/b>",
"author": [],
"contents": "\r\n\r\n\r\n\r\n\r\n\r\nGlobally mammalian biodiversity is declining at an alarming rate as a result of widespread habitat loss and degradation, and unsustainable hunting. We study how these anthropogenic drivers impact the distribution and abundance of ground dwelling mammals. In our field projects we use camera-traps and environmental DNA (eDNA) and invertebrate-derived DNA (iDNA) metabarcoding to assess species occurrences and we employ statistical models that investigate how anthropogenic drivers affect species distribution. We develop standardized methods and strategies for rigorous biodiversity assessments in order to provide robust scientific baseline data that allow monitoring species-specific and community-wide trends over time. In our work we regularly collaborate closely with local stakeholders and decision makers in order to integrate our data and results directly into wildlife and conservation management policy.\r\n\r\n\r\nDr. Andreas Wilting, Deputy Department and Team Lead — ecologist and evolutionary biologist with strong interest in species conservation, interested in methods and tools to study species distributions and to use these biodiversity data to target conservation efforts.\r\nDr. Rahel Sollmann, Team Lead — ecologist and quantitative biologist has specialised in the analysis of camera trap data with Bayesian methods for wildlife conservation.\r\nDr. Jan Axtner, Data Management — data manager, ecologist and evolutionary geneticist, finds ways how to produce, store and handle large amounts of data of modern high-throughput biodiversity assessments.\r\n\r\n\r\n\r\n\r\nRunning Projects\r\n\r\nField Projects\r\n\r\nMalaysia; Borneo\r\n\r\nPeople involved: Roshan Guharajan, Jürgen Niedballa, Seth T Wong\r\nLocal partners: Sabah Forestry Department, Ta Ann Holdings Berhad, WWF Malaysia (Sarawak)\r\nIn Malaysian Borneo we study how different anthropogenic drivers affect the occurrence and abundance of ground-dwelling mammal and bird communities. Since 2008, we have monitored mammalian communities over time in forest sites in various stages of recovering from severe logging impacts and under different forest management strategies. We compare the impacts of these strategies (i.e. mixed land-uses with industrial tree plantation and natural forest management, conventionally selective logging and reduced impact logging) at different spatial and temporal scales.\r\nFinancial support: Federal Ministry of Education and Research (BMBF), Panthera, Point Defiance Zoo and Aquarium, Point Defiance Zoo Society, Mohamed bin Zayed Species Conservation Fund, International Association for Bear Research and Management\r\n\r\nKey Publications:\r\n\r\nGuharajan et al. (2021) FOR ECOL MANAG\r\n\r\n\r\nMathai et al. (2019) GLOB ECOL EVOL\r\n\r\n\r\nBrozovic et al. (2018) MAMMALIAN BIOLOGY\r\n\r\n\r\nWong et al. (2018) MAMMALIAN BIOLOGY\r\n\r\n\r\nMathai et al. (2017) MAMMALIAN BIOLOGY\r\n\r\n\r\nSollmann et al. (2017) DIVERS DISTRIB\r\n\r\n\r\n\r\nViet Nam, Laos; Annamite region\r\n\r\nPeople involved: Andrew Tilker, An The Troung Nguyen, Thanh Van Nguyen, Jürgen Niedballa\r\nLocal partners Viet Nam: WWF Vietnam, Save Vietnam’s Wildlife, Fauna & Flora International, Re:wild, Southern Institute of Ecology SIE, Central Institute for Natural Resources and Environmental Studies, GreenViet\r\nLocal partners Laos: WWF Laos, Association Anoulak\r\nWe want to learn more about the ecology of the little known Annamite endemics and understand what anthropogenic predictors drive the current distribution of these threatened species. In addition to habitat loss, unsustainable hunting is emerging as an increasingly important threat to tropical wildlife biodiversity. Due to pervasive hunting even many protected areas face massive species losses today. This widespread defaunation has been particularly severe in Indochina, where ‘industrial’ snaring has decimated wildlife populations drastically and driven many species to local extinction. Since 2014 we have implemented systematic camera-trapping and iDNA surveys across protected and non-protected areas within the Annamite ecoregion. Using modern species distribution models we aim to identify and predict areas of particular conservation concern in order to support better conservation efforts by our partners.\r\nFinancial support: Federal Ministry of Education and Research (BMBF), Point Defiance Zoo & Aquaria, National Geographic, Ocean Park Conservation Foundation, Manfred-Hermsen-Stiftung, Mohamed bin Zayed Species Conservation Fund, Eva Mayr-Stihl Stiftung\r\n\r\nKey Publications:\r\n\r\nTilker et al. (2020) DIVERS DISTRIB\r\n\r\n\r\nNguyen et al. (2019) NAT ECOL EVOL\r\n\r\n\r\nTilker et al. (2019) COMMS BIOL\r\n\r\n\r\nTilker et al. (2017) SCIENCE\r\n\r\n\r\n\r\nConcepts & Methodology\r\n\r\nHierarchical statistical modeling for wildlife research.\r\n\r\n\r\nPeople involved: Ana Sanz, Jürgen Niedballa\r\nCollaborators: Prof. Dr. Beth Gardner and many others, depending on specific projects\r\nWildlife survey data are fraught with challenges: often sparse, spatially and/or temporally limited or biased due to logistic constraints, and imperfectly reflecting ecological states and processes due to imperfect detection (i.e., failing to observe species or individuals even though they are present). Hierarchical statistical modeling has emerged as the prime tool to deal with these challenges, by describing separate sub-models for the underlying ecological and the detection process. We employ such models throughout our research projects. But we also modify existing and develop new hierarchical models, and make these more accessible to end users, to improve our ability to study, monitor, and ultimately, protect wildlife. Modeling approaches we work with range from occupancy models for species occurrence to N-mixture, distance sampling and other count-based models for species abundance and population dynamics, to traditional and spatial capture-recapture models for abundance, density and demographics.\r\n\r\nKey Publications:\r\n\r\nKe et al. (2022) ECOL APPL\r\n\r\n\r\nSollmann et al. (2021) ECOL APPL\r\n\r\n\r\nGardner et al. (2018) ECOL EVOL\r\n\r\n\r\nSollmann et al. (2016) MEE\r\n\r\n\r\nRoyle et al. (2014) Spatial Capture Recapture. Academic Press, Waltham, MA.\r\n\r\n\r\n\r\nDeveloping standardized and reliable survey tools to monitor mammals in tropical rainforests.\r\n\r\n\r\nPeople involved: Jan Axtner, Roshan Guharajan, Thanh Van Nguyen, Jürgen Niedballa, Rahel Sollmann, Badru Mugerwa, Andrew Tilker, Seth T Wong, Andreas Wilting\r\nCollaborators: Prof. Dr. Douglas Yu (University of East Anglia, Norwich, UK & Kunming University, Kunming, China), Dr. Jesse F Abrams (University of Exeter, Exeter, UK)\r\nStudying biodiversity on a larger scale is essential to support political and conservation decisions. However, combining and integrating different biodiversity datasets into larger scale analyses is often challenging and associated with a loss of data accuracy and detail. We improve, develop and establish standardized methods and protocols to study and monitor biodiversity. Hereby we focus mainly on high-throughput methods that are applicable in tropical rainforests.\r\nScreenForBio user guide\r\n\r\nKey Publications:\r\n\r\nAbrams et al. (2021) ECOGRAPHY\r\n\r\n\r\nNguyen et al. (2021) ENVIRONMENTAL DNA\r\n\r\n\r\nWong et al. (2019) GLOBAL ECOL AND EVOL\r\n\r\n\r\nAbrams et al. (2019) J APPL ECOL\r\n\r\n\r\nAxtner et al. (2019) GIGASCIENSE\r\n\r\n\r\nNiedballa et al. (2019) REMOTE SENS ECOL CONSERV\r\n\r\n\r\nAbrams et al. (2019) ECOL INFORM\r\n\r\n\r\nBush et al. (2017) NAT ECOL EVOL\r\n\r\n\r\nMohd Salleh et al. (2017) GIGASCIENSE\r\n\r\n\r\nNiedballa et al. (2016) METHODS ECOL EVOL\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n",
- "last_modified": "2023-10-09T17:11:59+02:00"
+ "last_modified": "2023-10-10T10:26:43+02:00"
},
{
"path": "team-individual.html",
@@ -268,7 +268,7 @@
"description": "Lead: Dr. Sarah Benhaiem & Dr. Sonja Metzger (field coordination)<\/b> \nAssistance: Dagmar Thierer & Stephan Karl<\/b> \nIn collaboration with Dr. Marion L. East & Prof. Heribert Hofer (co-founders of the Serengeti Hyena Project)",
"author": [],
"contents": "\r\n\r\n\r\n\r\n\r\n\r\nWelcome! We study the behaviour, ecology and health of three clans of spotted hyenas (Crocuta crocuta) in the Serengeti National Park in Tanzania since 1987. We are currently interested in the impact of early life conditions, infections and human activities on individual performance and fitness at all life stages. With our collaborators we also study the role of epigenetic mechanisms in mediating the effects of the social environment on life history trade-offs, hormones and immunity, and the demographic consequences of disturbances. Our interdisciplinary research applies non-invasive or minimally invasive methods and to further this aim we have developed and verified several faecal assays for spotted hyenas.\r\n\r\n\r\nFigure: M. Gicquel (from Gicquel et al. 2022 Ecosphere)Why are spotted hyenas so interesting to study?\r\nThis highly social mammal has several unusual traits: female social dominance, an erectile ‘pseudopenis’ in females (similar to that of the male penis), an exceptionally long lactation period and intense sibling competing. It is a keystone carnivore in the ecosystem, which both hunts and scavenges. All these aspects make hyenas an interesting model species to study social behaviour, sexual conflict, maternal effects, host-pathogen interactions, immunology or endocrinology.\r\nOur study population experiences extreme and unpredictable fluctuations in prey abundance throughout the year, because of the migratory movements of its main prey (wildebeest, zebras and Thompson’s gazelles) and the low abundance of resident herbivores. We discovered that Serengeti hyenas solve this problem by commuting long distances to forage throughout the year. Individuals leave their clan territory and travel to areas up to 70 km to locate areas with large aggregations of migratory herbivores where they feed before returning to their clan territory. In the context of global change, the commuting system of Serengeti hyenas is particularly valuable to study how animals cope with a variable and uncertain resource.\r\nUnfortunately, commuting hyenas in the Serengeti can get killed by wire snares set illegally by bushmeat hunters along some borders of the Park or become victims of road accidents. These anthropogenic threats are likely to intensify with the expected increases in local human populations and traffic volume associated with tourism. Changes in rainfall patterns driven by global warming may also have cascading effects on this large slow-reproducing mammal.\r\n\r\n\r\n\r\n\r\nRunning Projects\r\n\r\nBehavioural Ecology, Ecology, and Demography\r\n\r\nEcological, social and maternal effects on individual performance, population dynamics and resilience\r\n\r\n\r\nCurrent team & collaborators: Morgane Gicquel, Dagmar Thierer, Stephan Karl, Sonja Metzger, Sarah Benhaiem, Marion L. East, Heribert Hofer, Viktoriia Radchuk (Dept. 6, IZW), Oliver Höner (Dept. 1, IZW), Adam Clark (University of Graz), Stephanie Kramer-Schadt (Dept. 6, IZW)\r\nWe investigate how ecological and social conditions (e.g. rainfall, maternal rank, litter size), behaviours (e.g. infanticides), and disturbances (e.g. epidemics, droughts) influence the reproductive performance and survival prospects of spotted hyenas at different life stages, and their demographic resilience.\r\n\r\nKey Publications:\r\n\r\nBenhaiem et al. (2018) COMMUN BIOL\r\n\r\n\r\nBenhaiem et al. (2018) FRONT VET SCI\r\n\r\n\r\nEast et al. (2022) FRONT ECOL EVOL\r\n\r\n\r\nGicquel et al. (2022) J ANIM ECOL\r\n\r\n\r\nMarescot et al. (2018) FUNCT ECOL\r\n\r\n\r\n\r\nDisease ecology\r\n\r\nDisease ecology: consequences of infections on allostatic load and fitness\r\n\r\n\r\nCurrent team & collaborators: Miguel Veiga, Susana Soares, Dagmar Thierer, Stephan Karl, Sonja Metzger, Joshua Dalijono (student helper), Marion L. East, Heribert Hofer, Gábor Á. Czirják (Dept. 3, IZW), Sarah Benhaiem, Jella Wauters (Dept. 4, IZW)\r\nWe investigate the interactions between spotted hyenas and their pathogens, including their gastrointestinal parasitic community and viruses. We are particularly interested in the causes and consequences of infections in individuals, immunosenescence and the interactions between allostatic load (“stress”), immunity and infections.\r\n\r\nKey Publications:\r\n\r\nDavidian et al. (2015) METHODS ECOL EVOL\r\n\r\n\r\nFerreira et al. (2019) ECOL EVOL\r\n\r\n\r\nFerreira et al. (2021) ECOL EVOL\r\n\r\n\r\nMarescot et al. (2021) J ANIM ECOL\r\n\r\n\r\nOlarte‐Castillo et al. (2021) MOL ECOL\r\n\r\n\r\n\r\nConservation\r\n\r\nHuman-wildlife conflicts and climate change in the Serengeti\r\n\r\n\r\nCurrent team & collaborators: Marwan Naciri (former MSc student), Montan Kalyahe, Morgane Gicquel, Dagmar Thierer, Stephan Karl, Sonja Metzger, Sarah Benhaiem, Marion L. East, Heribert Hofer, Aimara Planillo (Dept. 6, IZW), Sarah Cubaynes (CEFE, Montpellier)\r\nWe are interested in assessing the effects of illegal bushmeat hunting (snaring), roadkills and changes in rainfall patterns driven by global warming on spotted hyenas. We also investigate the factors that influence the likelihood of predation on livestock and consumption of discarded livestock ‘waste’.\r\n\r\nKey Publications:\r\n\r\nBenhaiem et al. (2022) ANIM CONSERV\r\n\r\n\r\nGicquel et al. (2022) ECOSPHERE\r\n\r\n\r\nKalyahe et al. (2022) ENVIRON CONSERV\r\n\r\n\r\n\r\nSocial Epigenetics\r\n\r\nEpigenetic stability and plasticity of social environmental effects\r\n\r\n\r\nCurrent team & collaborators: Alexandra Weyrich (Dept. 2, IZW, PI), Colin Vullioud (Dept. 2, IZW), Jörns Fickel (Dept. 2, IZW), Lena Ruf (Dept. 2, IZW), Nick Mewes (Dept. 2, IZW), Sarah Benhaiem, Marion L. East, Heribert Hofer, Gábor Á. Czirják (Dept. 2, IZW), Emmanuel Heitlinger (Humboldt University), Jerzy Adamski (Helmholtz-Center Munich), Alexander Cecil (Helmholtz-Center Munich), Moshe Szyf (McGill University), Yoav Soen (Weizmann Institute of Science)\r\nWe investigate if DNA methylation is a main mechanism through which an individual’s social environment regulates gene expression and physiological responses. We hypothesize that changes in social status will led to changes in epigenetic patterns. To test our hypotheses, we study the DNA methylation patterns in the spotted hyena.\r\n\r\nKey Publications:\r\n\r\nGuerrero et al. (2020) CURR ZOOL\r\n\r\n\r\nHeitlinger et al. (2017) FRONT CELL INFECT MICROBIOL\r\n\r\n\r\n\r\n\r\nGeneral Information\r\nGet our information leaflet about the Serengeti Spotted Hyaena Project!\r\n\r\n\r\n\r\n\r\n\r\n → English version\r\n → Deutsche Version (in German)\r\n → Toleo la Kiswahili (in Swahili)\r\n\r\n\r\nHere is an overview of our research interests, methods and partners since the establishment of the project in 1987:\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n",
- "last_modified": "2023-10-09T17:12:01+02:00"
+ "last_modified": "2023-10-10T10:26:45+02:00"
},
{
"path": "team-population.html",
@@ -276,7 +276,7 @@
"description": "Lead: Dr. Stephanie Kramer-Schadt & Dr. Viktoriia Radchuk<\/b> \nAssistance: Dr. Conny Landgraf & Moritz Wenzler<\/b>",
"author": [],
"contents": "\r\n\r\n\r\n\r\n\r\n\r\nWildlife has to cope with many challenges in the Anthropocene, but data are often too scarce and messy to predict the future fate of populations and communities under global change. To disentangle processes and drivers behind ecological and evolutionary dynamics of wildlife populations and communities, we combine field work with advanced data analysis and the development of concepts with designing stochastic simulation models. We use forecasting techniques to project scenarios of population and community change under disturbances. With this, we contribute to applied and theoretic ecology and biodiversity conservation under global change.\r\n\r\n\r\nDr. Stephanie Kramer-Schadt, Department and Team Lead — applied ecologist, population and disease dynamics at the landscape scale, passionate about wildlife per se, carnivores in particular, D6 and movement ecology, uses models as tools to communicate management issues.\r\nDr. Viktoriia Radchuk, Team Lead — quantitative ecologist, stability of populations and communities under global change, interested in theory, synthesis, and integration of data with models to assist conservation.\r\nDr. Conny Landgraf, Coordination — organizes us, behavioral ecologist, interested in sensory and acoustic cues of animals.\r\nMoritz Wenzler-Meya, GIS-Lab— geodata analyst, responsible for the GIS lab, providing geodata and supporting coding.\r\n\r\n\r\n\r\n\r\nRunning Projects\r\n\r\nTheory and Synthesis\r\n\r\nStability under global change and across levels of organization\r\n\r\n\r\nDr. Cédric Scherer, Thibault Fronville\r\nTo understand how populations and communities react to global change we study how their stability is affected by disturbances. To this end we model disturbances of different types and intensity and measure several stability metrics.\r\nAnimal responses to climate change\r\nEnvironmental variation effects on stability of populations and communities\r\n\r\nKey Publications:\r\n\r\nRadchuk et al. (2019) ECOL LETT\r\n\r\n\r\nRadchuk et al. (2019) NAT COMMUN\r\n\r\n\r\n\r\nWildlife disease dynamics: Linking host and pathogen traits\r\n\r\n\r\nDr. Cédric Scherer, Tobias Kürschner, Marius Grabow\r\nPathogens are an integral part of biodiversity, influencing population dynamics of their hosts and playing an important functional role in shaping community structure. Here, our aim is to understand the effect that species as ‘mobile pathogen links’ with their different movement types and life-history strategies have on disease distribution, spread, persistence and evolution.\r\n → see also BioMove Graduate School\r\nMovement effects on pathogen spread and disease persistence\r\nEvolution of pathogenic strains in dynamic landscapes\r\nPathogen-induced movement strategies and fitness consequences\r\n\r\nKey Publications:\r\n\r\nKürschner et al. (2021) ECOL EVOL\r\n\r\n\r\nScherer et al. (2020) OIKOS\r\n\r\n\r\nScherer et al. (2019) J ANIM ECOL\r\n\r\n\r\nMarescot et al. (2018) FUNCT ECOL\r\n\r\n\r\nKramer-Schadt et al. (2009) OIKOS\r\n\r\n\r\n\r\nApplied Ecology\r\n\r\nUrban wildlife ecology: How do animals respond to novel environments?\r\n\r\nDr. Aimara Planillo, Dr. Julie Louvrier, Sinah Drenske, Simon Moesch\r\nUrbanisation poses risks and opportunities for wildlife. We investigate how species cope with these everyday challenges by analysing the spatial factors and species interactions that underlie their distributions along a rural to urban gradient and by making inference on their behavioral plasticity.\r\n → see also BIBS — rural-urban coupling\r\n → see also WT Impact\r\nBridging spatial data in community distribution models\r\nEffects of species interactions and human disturbance on community compositions\r\nEcology of red foxes (Vulpes vulpes) in anthropogenic landscapes\r\nHuman perceptions of urban wildlife\r\n\r\nKey Publications:\r\nPlanillo et al. (2021) LANDSC URBAN PLA\r\n\r\n\r\nPlanillo, Kramer-Schadt, et al. (2020) DIVERS DISTRIB\r\n\r\n\r\nGras et al. (2018) FRONT ECOL EVOL\r\n\r\n\r\nStillfried et al. (2017) FRONT ECOL EVOL\r\n\r\n\r\n\r\nWildlife distributions, population dynamics, and conservation\r\n\r\nDr. Julie Louvrier, Dr. Aimara Planillo, Dr. Cédric Scherer, Dr. Joe Premier, Ana Patricia Calderon, Eva Sánchez Arribas\r\nWildlife faces big challenges persisting in human-dominated landscapes. We model their population dynamics, viability and connectivity using individual-based models on a spatially-explicit basis, with the aim of supporting wildlife management and conservation.\r\nWolf population dynamics and establishment in Germany\r\nJaguar connectivity and conservation prioritization in Central America\r\nModelling genetic processes to support the conservation management of Eurasian lynx\r\n\r\nKey Publications:\r\n\r\nPremier et al. (2020) MOV ECOL\r\n\r\n\r\nHeurich, Schultze-Naumburg et al. (2018) BIOL CONSERV\r\n\r\n\r\nRadchuk, Ims & Andreassen (2016) ECOLOGY\r\n\r\n\r\nStruebig et al. (2015) CURR BIOL\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n",
- "last_modified": "2023-10-09T17:12:02+02:00"
+ "last_modified": "2023-10-10T10:26:46+02:00"
}
],
"collections": ["posts/posts.json", "posts_geodata/posts_geodata.json"]
diff --git a/docs/site_libs/header-attrs-2.23/header-attrs.js b/docs/site_libs/header-attrs-2.23/header-attrs.js
new file mode 100644
index 00000000..dd57d92e
--- /dev/null
+++ b/docs/site_libs/header-attrs-2.23/header-attrs.js
@@ -0,0 +1,12 @@
+// Pandoc 2.9 adds attributes on both header and div. We remove the former (to
+// be compatible with the behavior of Pandoc < 2.8).
+document.addEventListener('DOMContentLoaded', function(e) {
+ var hs = document.querySelectorAll("div.section[class*='level'] > :first-child");
+ var i, h, a;
+ for (i = 0; i < hs.length; i++) {
+ h = hs[i];
+ if (!/^h[1-6]$/i.test(h.tagName)) continue; // it should be a header h1-h6
+ a = h.attributes;
+ while (a.length > 0) h.removeAttribute(a[0].name);
+ }
+});
diff --git a/docs/teaching.html b/docs/teaching.html
index 4a149ce7..9fc38354 100644
--- a/docs/teaching.html
+++ b/docs/teaching.html
@@ -2644,7 +2644,7 @@
color: var(--hover-color, white);
}
-
+
diff --git a/guidelines.Rmd b/guidelines.Rmd
index fb86616d..c43fe525 100644
--- a/guidelines.Rmd
+++ b/guidelines.Rmd
@@ -26,7 +26,7 @@ knitr::opts_chunk$set(echo = TRUE)
- Create the project folder structure with our [d6 package](https://ecodynizw.github.io/posts/d6package/): `d6::new_project()`.
- For consistent style, we ask you to use our corporate [d6 theme](): `d6::theme_d6()`.
- At the end of a project, transfer [your repository](https://ecodynizw.github.io/guidelines.html#repository) to our [EcoDynIZW GitHub account](https://github.com/EcoDynIZW/).
-- Ask Moritz Wenzler (wenzler[at]izw-berlin.de) for help of needed.
+- Ask Moritz Wenzler-Meya (wenzler[at]izw-berlin.de) for help if needed.
### Information for Students (BSc | MSc | PhD)
@@ -52,14 +52,13 @@ knitr::opts_chunk$set(echo = TRUE)
* [General Information](#general)
* [Conducting BSc/MSc/PhD Projects](#theses)
* [Organizing Workflows](#workflows)
-* [Scripting](#scripting)
-* [Spatial Data](#spatial)
+* [Project Folders](#projectfolders)
* [Data Backup](#backup)
* [Manuscript Submissions/Revisions](#manuscripts)
* [GitHub repository](#repository)
* [Appendices](#appendices)
- * [Folder Structure for Project Folders](#appendixA)
- * [Detailed Spatial Data Information](#appendixB)
+ * [Scripting](#appendixA)
+ * [Spatial Data Information](#appendixB)
* [What Nature Says…](#appendixC)
@@ -74,7 +73,7 @@ knitr::include_graphics("img/banner-mv-csf-top.png")
The department is composed of three teams on (1) Individual Dynamics, (2) Population Dynamics and (3) Biodiversity Dynamics.
-Stephanie Kramer-Schadt is the department head and leader of the Population Dynamics team. Conny Landgraf is the assistant of the department head; she can assist with administrative duties (e.g. contracts, travel sheets, etc.). Moritz Wenzler and Jan Axtner are responsible for data management, data storage and the working group’s R code collection. As each department member has a specific area of expertise, we created an expert list (see 1.3) if you need help on specific topics. PhD students and scientists are obliged to update this expert list with their own skills and responsibilities as well.
+Stephanie Kramer-Schadt is the department head and leader of the Population Dynamics team. Conny Landgraf is the assistant of the department head; she can assist with administrative duties (e.g. contracts, travel sheets, etc.). Moritz Wenzler-Meya and Jan Axtner are responsible for data management, data storage and the working group’s R code collection. As each department member has a specific area of expertise, we created an expert list (see 1.3) if you need help on specific topics. PhD students and scientists are obliged to update this expert list with their own skills and responsibilities as well.
For information on the Department, check [our webpage](https://www.ecological-dynamics-izw.com) or subscribe to [our Twitter account](https://www.twitter.com/EcoDynIZW) (\@EcoDynIZW) for news about papers, helpful R-code, courses or scientific positions.
@@ -144,7 +143,7 @@ To store data and results, the IZW follows the DFG-guidelines for good scientifi
Contact the Data Managers (Jan Axtner or Moritz Wenzler-Meya) of the respective teams to organize your project ID, get server access and how to arrange your workspace best. To setup a project folder, we ask you to follow the setup:
-* **Use the standardized project folder** structure! (see [Appendix A](#appendixA), cf. [`d6` R package](https://github.com/EcoDynIZW/d6) and [GitHub](https://github.com/))
+* **Use the standardized project folder** structure! (see [Project Folder Structure](#projectfolder), [`d6` R package](https://github.com/EcoDynIZW/d6) and [GitHub](https://github.com/))
* Make an outline of the structure separately in your **electronic lab-book** (see 3.3.1), to indicate what to find in each folder and keep it updated.
* Please **hand over the raw data to the data manager before starting your project analysis**, to avoid accidental data losses.
* Store the raw data, e.g. data from field work, in the folder named `data-raw`. Use a folder named `output` to store data created from the raw data (e.g. after data cleaning or editing). This should also be the place where the `master table` is located, i.e. the data set of all subsequent analyses. If needed you can have a temporary subfolder in the “output” folder for everyday work and analysis trials. Empty the temporary folder regularly. Plots and figures should be stored in the `plots` folder. Scripts should be stored in the `R` folder. Documents like manuscripts, proposals, etc. should be stored in the `docs` folder. Save important, computational or labour intensive interim results or final results. Use appropriate subfolders such as `interim-results_` or `final-results_`.
@@ -166,122 +165,14 @@ To document scripting we recommend to use R Markdown (`.rmd`) files if possible.
[↑ Jump back to top.](#toc)
-
-## Scripting {#scripting}
-
-### General recommendations
-
-* Write the author, name and date in a header (you can use the d6 package templates for this as well).
-* Keep code in scripts as concise as possible.
-* Use in-line comments to explain your code that others can follow your code.
-* If possible, use dynamic paths (i.e. see R-package [`here`](https://here.r-lib.org/)).
-* Always set variables/ parameters at the top of your script; do not set values somewhere inside the code as this is error prone, because these values tend to be forgotten to get changed when updating a script. The same applies to loading packages. Please also make sure to only load packages that are really needed and remove those that you are not using for the final analysis.
-* Save the output of a script as .rds file to smoothly load it in the next script. Additionally, save the output in a file format usable beyond R, e.g. use .csv or .txt if you want to save tabular data or GeoTiff if you want to save a raster map.
-* Use separate scripts to create figures of publishable quality (700 dpi) from the results. Use a vector graphics format like pdf.
-* For simulation studies: Include all scripts, e.g. additional model code, batch files with simulated parameters, simulated landscapes and simulation results, and files used for the analyses.
-
-
-### R
-
-* Stick to the [Rstudio style guide](https://style.tidyverse.org/index.html) to ensure readability of code.
-* If you are using RStudio, make sure to set the following under `Tools > Global Options > General > Basic`:
- * untick "Restore .RData into workspace at startup"
- * set "Save workspace to .RData on exit:" to "Never"
- * untick "Always save history (even when not saving .RData)" (recommended)
-
-{width="65%" height="65%"}
-
-* We recommend using R-Studio projects and R Markdown documents when scripting in R. If you use another “integrated development environment” (IDE) make sure you can provide versioned plain R scripts using a relative path to the used data files.
-* Implement version control by using GitHub. If you install packages or use scripts and code chunks from GitHub provided by others, be aware to acknowledge the code developer prior to publication of scripts.
-* Do not save the R history or the R environment. Always start a fresh and an empty R session to avoid artifacts by using objects of functions that were not defined in your script. More details here: https://www.tidyverse.org/blog/2017/12/workflow-vs-script/.
-* If possible use log files to document messages and errors.
-
-
-### Python
-
-In general we recommend using Jupyter notebooks.
-[under construction]
-
-
-### Netlogo
-
-[under construction]
-
-
-### QGIS
-
-In general we recommend doing GIS analyses in R. If you have to use QGIS use Python as scripting language. However, the RQGIS package provides a great opportunity to script complete workflows in QGIS by using R. Moreover, you can include R scripts in the QGIS toolbox.
-
-[under construction]
-
-[↑ Jump back to top.](#toc)
-
-
-## Spatial Data {#spatial}
-
-If you are working with spatial data please have the following in mind:
-
-* Always check the projection (cartographic reference system (CRS)) of your data. Depending on what you want to do it could be necessary to change the CRS system, i.e. from an angular unit (like GPS data) to a projected unit in meters. BUT sometimes you cannot easily change it or it will drastically change your data.
-* If you want to save you spatial data, please save it as Geopackage (`.gpkg`) or raster data GeoTiff (`.tif`). Please give a clear name, document the filename in your lab book and add the EPSG code of your CRS to the file name. Always use `utf-8` as file encoding.
-* If you are not sure how to handle your spatial data please contact Moritz Wenzler, the GIS manager, for help.
-
-For detailed information about Spatial data go to [Appendix B](#appendixB)).
-
-[↑ Jump back to top.](#toc)
-
-
-## Data Backup {#backup}
-
-**Important:** backup your work! Make copies of raw data/files and scripts and save it in another location if you work on private computers. PhD students should work on the M-drive or the U-drive, never directly on the C-drive of the computer.
-
-
-## Manuscript Submissions/Revisions {#manuscripts}
-
-When you are submitting a manuscript create a copy of the related subproject folder and add a suffix `submission_1_`. This copy shall be stored and never changed—we recommend to zip this folder! When conducting a revisions or resubmission, copy the folder to `submission_2_` and revise the paper.
-
-Please find additional information on ‘how to write a scientific paper’, how to avoid statistical pitfalls or how to organize workflows [here](https://wolke.izw-berlin.de/index.php/apps/files/?dir=/Abteilung-Department%206/LabGuidelines&fileid=346243).
-
-
-## GitHub repository {#repository}
-
-The final step after your paper gets published is to make the GitHub repository public (or create a repository if you haven't before). The repository should contain clean code and data that runs properly. If you are using R, please make sure to use a R-Project with the given folder structure (see appendix A).
-
-The title of the repository should contain the last name of the first author, the year, and the abbreviation of the journal (e.g. `Smith_2023_Science`). Please add the title of the paper as the description (in quotation marks). Please provide the reference of the paper, including the DOI as a hyperlink, and the abstract in the README file. Add further notes on the files contained and the scripts if needed. Please use this template:
-
-```text
-# Smith et al. (2023) *Science*
-
-> **Richard Smith**, Don Joe Radchuk & **Jane Head** (2023): Study title.
-*Science* 1-2. DOI: [doi-goes-here](https://doi.org/doi-goes-here)
-
-Abstract text.
-
-## Scripts
-
-... more notes if needed
-
-```
-
-Add the title in quotation marks as the description and the DOI as link to the repository about (right upper corner). For examples see [study repositories on our GitHub](https://github.com/orgs/EcoDynIZW/repositories)).
-
-Finally, make sure to turn the visibility to public and transfer the ownership to the EcoDynIZW GitHub organization. If you have need help or have questions please ask the data manager for help.
-
-
-[↑ Jump back to top.](#toc)
-
-
----
-
-## Appendices {#appendices}
-
-## Appendix A) Folder Structure for Project Folders {#appendixA}
+## Project Folder Structure {#projectfolders}
A new project can be started by installing the [d6 R-package](https://github.com/EcoDynIZW/d6). Running `new_project()` with a unique and descriptive name for your project (see below) will create a full scaffolding structure for all your future analysis steps. If you like, you can also specify a path and the project will be created there.
Please create repositories on the EcoDynIZW account and not on your private
account!
-### Root project folder
+#### Root project folder
Name it like:
@@ -353,10 +244,107 @@ additional files looks like this:
[↑ Jump back to top.](#toc)
+
+## Data Backup {#backup}
+
+**Important:** backup your work! Make copies of raw data/files and scripts and save it in another location if you work on private computers. PhD students should work on the M-drive or the U-drive, never directly on the C-drive of the computer.
+
+
+## Manuscript Submissions/Revisions {#manuscripts}
+
+When you are submitting a manuscript create a copy of the related subproject folder and add a suffix `submission_1_`. This copy shall be stored and never changed—we recommend to zip this folder! When conducting a revisions or resubmission, copy the folder to `submission_2_` and revise the paper.
+
+Please find additional information on ‘how to write a scientific paper’, how to avoid statistical pitfalls or how to organize workflows [here](https://wolke.izw-berlin.de/index.php/apps/files/?dir=/Abteilung-Department%206/LabGuidelines&fileid=346243).
+
+
+## GitHub repository {#repository}
+
+The final step after your paper gets published is to make the GitHub repository public (or create a repository if you haven't before). The repository should contain clean code and data that runs properly. If you are using R, please make sure to use a R-Project with the given folder structure (see appendix A).
+
+The title of the repository should contain the last name of the first author, the year, and the abbreviation of the journal (e.g. `Smith_2023_Science`). Please add the title of the paper as the description (in quotation marks). Please provide the reference of the paper, including the DOI as a hyperlink, and the abstract in the README file. Add further notes on the files contained and the scripts if needed. Please use this template:
+
+```text
+# Smith et al. (2023) *Science*
+
+> **Richard Smith**, Don Joe Radchuk & **Jane Head** (2023): Study title.
+*Science* 1-2. DOI: [doi-goes-here](https://doi.org/doi-goes-here)
+
+Abstract text.
+
+## Scripts
+
+... more notes if needed
+
+```
+
+Add the title in quotation marks as the description and the DOI as link to the repository about (right upper corner). For examples see [study repositories on our GitHub](https://github.com/orgs/EcoDynIZW/repositories)).
+
+Finally, make sure to turn the visibility to public and transfer the ownership to the EcoDynIZW GitHub organization. If you have need help or have questions please ask the data manager for help.
+
+
+[↑ Jump back to top.](#toc)
+
+
---
-## Appendix B) Detailed Spatial Data Information {#appendixB}
+## Appendices {#appendices}
+
+## Appendix A) Scripting {#appendixA}
+### General recommendations
+
+* Write the author, name and date in a header (you can use the d6 package templates for this as well).
+* Keep code in scripts as concise as possible.
+* Use in-line comments to explain your code that others can follow your code.
+* If possible, use dynamic paths (i.e. see R-package [`here`](https://here.r-lib.org/)).
+* Always set variables/ parameters at the top of your script; do not set values somewhere inside the code as this is error prone, because these values tend to be forgotten to get changed when updating a script. The same applies to loading packages. Please also make sure to only load packages that are really needed and remove those that you are not using for the final analysis.
+* Save the output of a script as .rds file to smoothly load it in the next script. Additionally, save the output in a file format usable beyond R, e.g. use .csv or .txt if you want to save tabular data or GeoTiff if you want to save a raster map.
+* Use separate scripts to create figures of publishable quality (700 dpi) from the results. Use a vector graphics format like pdf.
+* For simulation studies: Include all scripts, e.g. additional model code, batch files with simulated parameters, simulated landscapes and simulation results, and files used for the analyses.
+
+
+### R
+
+* Stick to the [Rstudio style guide](https://style.tidyverse.org/index.html) to ensure readability of code.
+* If you are using RStudio, make sure to set the following under `Tools > Global Options > General > Basic`:
+ * untick "Restore .RData into workspace at startup"
+ * set "Save workspace to .RData on exit:" to "Never"
+ * untick "Always save history (even when not saving .RData)" (recommended)
+
+{width="65%" height="65%"}
+
+* We recommend using R-Studio projects and R Markdown documents when scripting in R. If you use another “integrated development environment” (IDE) make sure you can provide versioned plain R scripts using a relative path to the used data files.
+* Implement version control by using GitHub. If you install packages or use scripts and code chunks from GitHub provided by others, be aware to acknowledge the code developer prior to publication of scripts.
+* Do not save the R history or the R environment. Always start a fresh and an empty R session to avoid artifacts by using objects of functions that were not defined in your script. More details here: https://www.tidyverse.org/blog/2017/12/workflow-vs-script/.
+* If possible use log files to document messages and errors.
+
+
+### Python
+
+In general we recommend using Jupyter notebooks.
+[under construction]
+
+
+### Netlogo
+
+[under construction]
+
+
+### QGIS
+
+In general we recommend doing GIS analyses in R. If you have to use QGIS use Python as scripting language. However, the RQGIS package provides a great opportunity to script complete workflows in QGIS by using R. Moreover, you can include R scripts in the QGIS toolbox.
+
+[under construction]
+
+[↑ Jump back to top.](#toc)
+
+## Appendix B) Spatial Data {#appendixB}
+
+If you are working with spatial data please have the following in mind:
+
+* Always check the projection (cartographic reference system (CRS)) of your data. Depending on what you want to do it could be necessary to change the CRS system, i.e. from an angular unit (like GPS data) to a projected unit in meters. BUT sometimes you cannot easily change it or it will drastically change your data.
+* If you want to save you spatial data, please save it as Geopackage (`.gpkg`) or raster data GeoTiff (`.tif`). Please give a clear name, document the filename in your lab book and add the EPSG code of your CRS to the file name. Always use `utf-8` as file encoding.
+* If you are not sure how to handle your spatial data please contact Moritz Wenzler-Meya, the GIS manager, for help.
* When using spatial data give clear names for maps ≤ 13 characters without special characters or spaces.
* Write down the cartographic reference system (CRS) at the end of the file name, e.g. `filename_4326`.
* Always use `utf-8` encoding, **NEVER** use the system setting. If you have to use different character encoding settings, then name the used encoding in the filename.
@@ -366,7 +354,7 @@ additional files looks like this:
* Always include the Coordinate Reference System as EPSG code (e.g. 4326 for log/lat WGS84 Coordinates) at the end of a file name, e.g. `my_env_variable_4326.gpkg`.
* Please save all your geo data into geopackage files (`.gpkg`) format to save and process your data. In general, if you export data from R please save it as an R Studio file (`.rds`). It will be saved without any losses.
* Store all point/line/polygon data as WGS84 (EPSG 4326).
-* If you do not understand this paragraph, contact the geodata-manager (Moritz Wenzler) before doing anything involving geodata.
+* If you do not understand this paragraph, contact the geodata-manager (Moritz Wenzler-Meya) before doing anything involving geodata.
[↑ Jump back to top.](#toc)
-
-