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Hierarchical mark‐recapture distance sampling to estimate moose abundance
Author(s) -
Oyster Jared H.,
Keren Ilai N.,
Hansen Sara J.K.,
Harris Richard B.
Publication year - 2018
Publication title -
the journal of wildlife management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.94
H-Index - 111
eISSN - 1937-2817
pISSN - 0022-541X
DOI - 10.1002/jwmg.21541
Subject(s) - distance sampling , abundance (ecology) , wildlife , transect , mark and recapture , environmental science , aerial survey , sampling (signal processing) , habitat , geography , physical geography , ecology , statistics , cartography , biology , mathematics , computer science , population , demography , filter (signal processing) , sociology , computer vision
Estimating the abundance of wide‐ranging wildlife, difficult under any circumstances, is particularly challenging when detection is low and affected by factors that also influence density and distribution. In northeastern Washington, moose ( Alces alces ) have evidently increased since the 1970s but spend most of their time under coniferous cover that makes detection from the air difficult. We used a Bayesian hierarchical approach to incorporate habitat use (in the form of availability as a function of canopy closure) into a detection model within a mark‐recapture distance sampling framework to estimate moose density. Our model of availability used a latent density surface employing habitat use data obtained from 17 adult female moose wearing global positioning system (GPS) collars. Distance sampling data, obtained from helicopter surveys in winters 2014, 2015, and 2016, consisted of double‐observer detections of 166 moose groups along 2,241 km of systematically placed line transects within 29 survey blocks selected using a stratified‐random design. We estimated moose density over the entire survey area as 0.49/km 2 (95% credible interval = 0.33–0.67/km 2 ). Extrapolated to the 10,513‐km 2 survey area, we estimated 5,169 moose (95% credible interval = 3,510–7,034). Our methodology allowed us to adjust for availability bias and produce an estimate even where detection was difficult but required many hours of helicopter flights, acceptable weather conditions, and the availability of GPS collared‐moose. © 2018 The Wildlife Society.