2019 journal article
A method for mapping hunting occurrence using publicly available, geographic variables
WILDLIFE SOCIETY BULLETIN, 43(3), 537–545.
author keywords: hunter access; hunting; industrial private land; logistic regression; nonindustrial private land; North Carolina; spatial modeling; urbanization; wildlife population modeling
UN Sustainable Development Goal Categories
14. Life Below Water
(Web of Science)
15. Life on Land
(Web of Science)
Source: Web Of Science
Added: April 20, 2020
ABSTRACTThe spatial distribution of land available for hunting has received scant attention in the literature, but it fundamentally affects the feasibility of wildlife management. Modeling the distribution of hunting lands can be logistically difficult because of data requirements and the dynamic nature of landscapes and landowner preferences. We describe one approach to address this challenge using spatially explicit logistic regression models that accurately predict whether each parcel of land in North Carolina, USA, was hunted using free and publicly available geographic predictors. We collected data to develop and validate models from surveys of nonindustrial (n = 1,936) and industrial (n = 670) private landowners conducted during 2016 in North Carolina. Property size and housing and road density predicted whether hunting occurred correctly on 96% of nonindustrial parcels. Property size, housing and road density, and distance to the nearest city correctly predicted whether hunting occurred for 94% of industrial parcels. These results suggest wildlife managers may be able to accurately map and quantify where hunting occurs using relatively few publicly available geographic predictors. Future refinement of the methodology and model parameters is likely needed in different regions, with independent data sets, before adopting widespread implementation of underlying methods. This mapping method will facilitate assessing the efficacy of hunting as a wildlife management tool for overabundant species. Similarly the mapping approach would improve wildlife population estimates based on hunter harvest data by providing a more rigorous estimate of land that is huntable per harvested animal reported. © 2019 The Wildlife Society.