Estimating occupancy probability of moose using hunter survey data. Issue 3 (April 2017)

• Record Type: Journal Article
• Authors: Crum, Nathan J.; Fuller, Angela K.; Sutherland, Christopher S.; Cooch, Evan G.; Hurst, Jeremy
• Is Part Of: Journal of wildlife management. Volume 81:Issue 3(2017)
• Page Start: 521
• Page End: 534
• Publication Date: 2017-04
• Subjects: Alces alces -- citizen science -- distribution -- moose -- New York -- occupancy; Wildlife management -- Periodicals; Zoology -- Periodicals; 333.954
• DOI: 10.1002/jwmg.21207
• Languages: English
• ISSNs: 0022-541X

Abstract

ABSTRACT: Monitoring rare species can be difficult, especially across large spatial extents, making conventional methods of population monitoring costly and logistically challenging. Citizen science has the potential to produce observational data across large areas that can be used to monitor wildlife distributions using occupancy models. We used citizen science (i.e., hunter surveys) to facilitate monitoring of moose ( Alces alces ) populations, an especially important endeavor because of their recent apparent declines in the northeastern and upper midwestern regions of the United States. To better understand patterns of occurrence of moose in New York, we used data collected through an annual survey of approximately 11, 000 hunters between 2012 and 2014 that recorded detection–non‐detection data of moose and other species. We estimated patterns of occurrence of moose in relation to land cover characteristics, climate effects, and interspecific interactions using occupancy models to analyze spatially referenced moose observations. Coniferous and deciduous forest with low prevalence of white‐tailed deer ( Odocoileus virginianus ) had the highest probability of moose occurrence. This study highlights the potential of data collected using citizen science for understanding the spatial distribution of low‐density species across large spatial extents and providing key information regarding where and when future research and management activities should be focused. © 2016 The Wildlife Society. Abstract : Using encounter data from hunter surveys, we describe how landscape characteristics and interspecific interactions influence moose occurrence across New York. Moose detection was negatively associated with the date since the beginning of the hunting season, whereas occurrence was positively associated with coniferous forests and sample site area.