Can we model distribution of population abundance from wildlife–vehicles collision data?

Autor: Javier Fernández‐López, José A. Blanco‐Aguiar, Joaquín Vicente, Pelayo Acevedo
Přispěvatelé: Ministerio de Ciencia, Innovación y Universidades (España), Agencia Estatal de Investigación (España), National Science Foundation (US), European Commission
Rok vydání: 2022
Předmět:
Zdroj: Digital.CSIC. Repositorio Institucional del CSIC
instname
ISSN: 1600-0587
0906-7590
DOI: 10.1111/ecog.06113
Popis: Reliable estimates of the distribution of species abundance are a key element in wildlife studies, but such information is usually difficult to obtain for large spatial or long temporal scales. Wildlife–vehicle collision (WVC) data is systematically registered in many countries and could be used as a proxy of population abundance if the number of WVC in each territory increase with the population abundance. However, factors such as road density or human population should be controlled to obtain accurate abundance estimations from WVC data. Here, we propose a hierarchical modeling approach using the Royle–Nichols model for detection–non-detection data to obtain population abundance indices from WVC. Relative abundance and individual detectability were modeled for two species, wild boar Sus scrofa and roe deer Capreolus capreolus at 10 × 10 km cells in mainland Spain from WVC data using environmental, anthropological and temporal covariates. For each cell, a detection was annotated if at least one WVC was recorded at each month (used as survey occasion). The predicted abundance indices were compared with raw hunting statistics at region level to assess the performance of the modeling approach. Site specific covariates such as road density or administrative region and the month of the year, affected individual detectability, with higher WVC probability between October and December for wild boar and between April and July for roe deer. Wild boar and roe deer abundance can be explained by both, bioclimatic and land cover covariates. Abundance indices obtained from WVC data were significantly positively correlated with regional raw hunting yields for both species. We presented empirical evidence supporting that accurate wildlife abundance indices at fine spatial resolution can be generated from WVC data when individual detectability is considered in the modeling process.
This research was funded by the Spanish Ministry of Science (Project: ‘Armonización de los datos poblacionales de la fauna silvestre en España: aplicaciones a la vigilancia sanitaria y control de enfermedades compartidas con el ganado.' Ref. PID2019-111699RB-I00, HAWIPO). JFL was partially funded by the grant NSF – 1759940, and currently by the grant Margarita Salas from the European Union – NextGenerationEU through the Complutense University.
Databáze: OpenAIRE
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