DOI: 10.5061/dryad.vdncjsz28
title: Dataset for: Cattle aggregations at shared resources create potential parasite exposure hotspots for wildlife

description: Globally rising livestock populations and declining wildlife numbers are
 likely to dramatically change disease risk for wildlife and livestock,
 especially at resources where they congregate. However, limited
 understanding of interspecific transmission dynamics at these hotspots
 hinders disease prediction or mitigation. In this study, we combined
 gastrointestinal nematode density and host foraging activity measurements
 from our prior work in this system with three estimates of
 parasite-sharing capacity to investigate how interspecific exposures alter
 the relative riskiness of an important resource – water – among cattle and
 five dominant herbivore species in an East African tropical
 savanna.  We found that due to their high parasite output, water
 dependence, and parasite-sharing capacity, cattle greatly increased
 potential parasite exposures at water sources for wild ruminants. When
 untreated for parasites, cattle accounted for over two-thirds of total
 potential exposures around water for wild ruminants, driving 2–23-fold
 increases in relative exposure levels at water sources. Simulated changes
 in wildlife and cattle ratios showed that water sources become
 increasingly important hotspots of interspecific transmission for wild
 ruminants when the relative abundance of cattle parasites increases. These
 results emphasize that livestock have significant potential to alter the
 level and distribution of parasite exposures across the landscape for wild
 ruminants.
description: # Dataset for Cattle aggregations at shared resources create potential
 parasite exposure hotspots for wildlife
 [https://doi.org/10.5061/dryad.vdncjsz28](https://doi.org/10.5061/dryad.vdncjsz28) These data accompany the publication "Cattle aggregations at shared resources create potential parasite exposure hotspots for wildlife" in *Proceedings of the Royal Society B: Biological Sciences* (doi: 10.1098/rspb.2023-2239). ## Description of the data and file structure The data include three data files and code to replicate results of the publication. Specifically, the data files are: 1. 1) fec\_data.csv: A dataframe containing parasite fecal egg count values for focal species in the study. 2. 2) parasite\_risk\_at\_water.csv: A dataframe containing information on parasite exposure estimates for different species over the study period. Columns are as follows: 1. Period: The dung survey period (numbered based on number of months elapsed). 2. Date: The initial survey date. 3. Date2: The initial survey date plus 90 days, used to create the window to assess camera trapping activity. 4. Treatment: One of (WPC = Water pan that remained filled, CONT = matrix site with no water) 5. Site: Site name (One of five different sites: Tangi, Kambi, Oscar, Sidai, Jericho) 6. choice: Focal herbivore species identified from camera trapping 7. dung\_density: Mean dung density (cm3/m2) for the inner 50m area surveyed around water pans or center of matrix site. 8. Activity: The type of activity identified from camera trapping (dcount = presence, ddrink = drinking, dgraze = grazing). 9. Ind\_Secs: The average daily individual-seconds that a species was observed performing the activity 3. sharing\_matrices.csv: A dataframe containing information on the degree to which different herbivore species share parasites using three different sharing estimates. Columns are as follows: 1. Host: Species 1 2. name: Species compared to species 1 3. value: The degree to which parasites are shared [0,1]. 4. type: The type of sharing matrix used (literature, phylogeny, or metabarcoding). ## Sharing/Access information This is a section for linking to other ways to access the data, and for linking to sources the data is derived from, if any. Links to other publicly accessible locations of the data: * https://github.com/gtitcomb/cattle\_exposure\_ratio Data was derived from the following sources: * https://doi.org/10.6073/pasta/2728d61f10b767814b5d95fbd69137fa ## Code/Software R code for analyses are available in the exposure\_ratio\_analyses.R file, which sources the exposure\_ratio\_functions.R file. This code is maintained at the github repository referenced above.