Dataset for: Cattle aggregations at shared resources create potential parasite exposure hotspots for wildlife
Data files
Nov 15, 2023 version files 185.31 KB
Abstract
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.
README: Dataset for Cattle aggregations at shared resources create potential parasite exposure hotspots for wildlife
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) fec_data.csv: A dataframe containing parasite fecal egg count values for focal species in the study.
- 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:
- Period: The dung survey period (numbered based on number of months elapsed).
- Date: The initial survey date.
- Date2: The initial survey date plus 90 days, used to create the window to assess camera trapping activity.
- Treatment: One of (WPC = Water pan that remained filled, CONT = matrix site with no water)
- Site: Site name (One of five different sites: Tangi, Kambi, Oscar, Sidai, Jericho)
- choice: Focal herbivore species identified from camera trapping
- dung_density: Mean dung density (cm3/m2) for the inner 50m area surveyed around water pans or center of matrix site.
- Activity: The type of activity identified from camera trapping (dcount = presence, ddrink = drinking, dgraze = grazing).
- Ind_Secs: The average daily individual-seconds that a species was observed performing the activity
- 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:
- Host: Species 1
- name: Species compared to species 1
- value: The degree to which parasites are shared [0,1].
- 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.