Strength of correlation between wildlife collision data and hunting bags varies among ungulate species and with management scale

Abstract

Most European ungulate species are increasing in numbers and expanding their range. For the management and monitoring of these species, 64% of European countries rely on indirect proxies of abundance (e.g., hunting bag statistics). With increasing ungulate numbers, data on ungulate-vehicle collisions (UVC) may provide an important and inexpensive, complementary data source. Currently, it is unclear how bag statistics compare with UVC. A direct comparison of these two indices is important because both are used in ungulate management. We evaluated the relationship between UVC and ungulate hunting bags across bioclimatic, regional, and local scales, using five time lags (t(-3)to t(+1)) for the five most common wild ungulate species in Sweden. For all species, hunting bags and UVC correlated positively, but correlation strength and time lags varied across scales and among species. The two indices correlated most strongly at the local management scale. Correlation between both indices was strong for the smaller deer species and wild boar, in particular, but much weaker for moose where we found the best fit using a 2-year time lag. For the other species, indices from the same year correlated best. We argue that the reason for moose data behaving differently is that, in Sweden, moose are formally managed using a 3-year time plan, while the other species are not. Accordingly, moose hunting bags are influenced more strongly by density-independent processes than bags of the other species. Consequently, the mismatch between the two indices may generate conflicting conclusions for management depending on the method applied.

Keywords

Ungulate monitoring; Management units; UVC; Cervids; Census; Sweden

Published in

European Journal of Wildlife Research
2020, volume: 66, number: 6, article number: 86
Publisher: SPRINGER

SLU Authors

• Neumann Sivertsson, Wiebke

  • Department of Wildlife, Fish and Environmental Studies, Swedish University of Agricultural Sciences
    

• Widemo, Fredrik

  • Department of Wildlife, Fish and Environmental Studies, Swedish University of Agricultural Sciences
    

• Singh, Navinder

  • Department of Wildlife, Fish and Environmental Studies, Swedish University of Agricultural Sciences
    

• Seiler, Andreas

  • Department of Ecology, Swedish University of Agricultural Sciences
    

• Cromsigt, Joris

  • Department of Wildlife, Fish and Environmental Studies, Swedish University of Agricultural Sciences
    
  • Nelson Mandela University

UKÄ Subject classification

Ecology
Fish and Wildlife Management

Publication identifier

• DOI: https://doi.org/10.1007/s10344-020-01421-x

Permanent link to this page (URI)

https://res.slu.se/id/publ/108252