DOI: 10.5061/dryad.h70rxwdpf
title: Data from: Urbanization and primary productivity mediate the predator-prey relationship between deer and coyotes

description: Predator-prey interactions are important to regulating populations and
 structuring communities but are affected by many dynamic, complex factors,
 across larges-scales, making them difficult to study. Integrated
 population models (IPMs) offer a potential solution to understanding
 predator-prey relationships by providing a framework for leveraging many
 different datasets and testing hypotheses about interactive factors. Here,
 we evaluate the coyote-deer (Canis latrans – Odocoileus virginianus)
 predator-prey relationship across the state of North Carolina (NC).
 Because both species have similar habitat requirements and may respond to
 human disturbance, we considered net primary productivity (NPP) and
 urbanization as key mediating factors. We estimated deer survival and
 fecundity by integrating camera trap, harvest, biological and hunter
 observation datasets into a two-stage, two-sex Lefkovich population
 projection matrix. We allowed survival and fecundity to vary as functions
 of urbanization, NPP and coyote density and projected abundance forward to
 test eight hypothetical scenarios. We estimated initial average deer and
 coyote densities to be 11.83 (95% CI: 5.64, 20.80) and 0.46 (95% CI: 0.02,
 1.45) individuals/km2, respectively. We found a negative relationship
 between current levels of coyote density and deer fecundity in most areas
 which became more negative under hypothetical conditions of lower NPP or
 higher urbanization, leading to lower projected deer abundances. These
 results suggest that coyotes could have stronger effects on deer
 populations in NC if their densities rise, but primarily in less
 productive and/or more suburban habitats. Our case study provides an
 example of how IPMs can be used to better understand the complex
 relationships between predator and prey under changing environmental
 conditions.
description: Survival and harvest rates:
 We used the dynamic N-mixture model of Zipkin et al. (2014) to
 estimate stage and sex-based survival and harvest rates from
 stage-at-harvest data collected statewide from 2012-2017 over all 100
 counties of North Carolina. The stage-at-harvest data were collected by
 county each year for two stages for male deer (adults and fawns about to
 transition to adulthood (i.e., button bucks)) and does. We assumed that
 all button bucks were fawns and all females were adults. The census took
 place right before fawns transitioned to adulthood and we considered all
 fawns to reach adulthood at one year of age.
 Fawn:doe ratio: To
 represent hunted populations, we used 2017 hunter observation data from
 each county of NC. Hunters documented what species they observed on their
 hunts, given the number of hours they spent hunting, to get an index of
 abundance. The location of these observations was known only to the county
 level. Hunters were instructed to report their hunting activity even if no
 wildlife was observed (Fuller et al. 2018). For use in our model, we
 removed all observations made over bait and averaged observations of
 hunters that remained in the same hunting stand for multiple days instead
 of treating those days as independent
 samples.<em> </em> Litter
 size: To provide explicit information about
 litter size we used fertility data collected by the NCWRC. Fertility data
 (number of fetuses/doe) are recorded by a subset of hunters each year as
 part of biological data collection.