Living Earth Collaborative Center for Biodiversity Working Group
Washington University
St. Louis, MO, USA
December 4-7, 2018 and May 5–10, 2019
Participants:
Amanda Koltz (co-organizer), Washington University in St. Louis, USA
Rachel Penczkowski (co-organizer), Washington University in St. Louis, USA
Sharon Deem (co-organizer), Institute for Conservation Medicine, St. Louis Zoo, USA
Vanessa Ezenwa (co-organizer), University of Georgia, USA
Susan Kutz, University of Calgary, Canada
Brandon Barton, Mississippi State University, USA
Zoe Johnson, Mississippi State University, USA
Aimee Classen, University of Vermont, USA
J. Trevor Vannatta, Purdue University, USA
Matt Malishev, Emory University, USA
David Civitello, Emory University, USA
Daniel Preston, University of Wisconsin-Madison, USA
Maris Brenn-White, St. Louis Zoo, USA
Develop a predictive framework for estimating indirect effects of parasites on ecosystem nutrient cycling. Ideas behind this research were developed at the Living Earth Collaborative working group on the effects of parasites on ecosystem nutrient cycling, Washington University, St. Louis, MO, USA, December 4-7, 2018.
1️⃣ Download R and RStudio for your operating system.
2️⃣ Download the model file (right click here and 'Save link as') and run the simulation model in RStudio.
3️⃣ Follow the instructions at the beginning of the R file to run the model.
The bot reads a .txt file of literature entries resulting from a keyword search term query output from a Web of Science database search and returns a new file containing user defined search terms.
Required files:
LEC100testrecords.txt
search_term_inputs.txt
article_col_names.txt
lec_keyword_search.R
lec_keyword_search.pdf
1️⃣ Enter either Title or Abstract to search for the keywords.
extract1 <- "Title"
2️⃣ Enter what data you want to get out of the final results. For example, if you want to know what year in which the resulting papers were published, type in "Year".
Use any search term you specified in the search_terms_input.txt file.
extract2 <- "Year"
3️⃣ Follow the instructions in the lec_keyword_search.pdf file.
The bot scrapes PDF articles (.pdf) based on user defined search terms and returns a local file of meta-analysis data.
Example search terms:
mortality, surviv*, fecund*, body condit*, body, body mass, feed*, feeding rate, feeding amount, waste, faec*, fece*, urin*, ecosystem, plant, soil, nutrie*
Example outputs from meta-analysis:
"Relevance",
"Parasite type",
"Response variable",
"Effect variance",
"Sample size",
"P val"
Required files:
metaanalysis_readpdf.R
title_abstract_terms.txt
1️⃣ Follow the instructions in the metaanalysis_readpdf.R model file.
2️⃣ Set the working path to the dir containing the PDF files for scraping
All troubleshooting and bugs can be sent as a git issue or to matthew.malishev [at] emory.edu.
Matt Malishev
🔍 Website
🐦 @darwinanddavis
📧 matthew.malishev [at] gmail.com