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Relating predation mortality to broad‐scale habitat selection
Author(s) -
McLOUGHLIN PHILIP D.,
DUNFORD JESSE S.,
BOUTIN STAN
Publication year - 2005
Publication title -
journal of animal ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.134
H-Index - 157
eISSN - 1365-2656
pISSN - 0021-8790
DOI - 10.1111/j.1365-2656.2005.00967.x
Subject(s) - woodland caribou , predation , habitat , ecology , selection (genetic algorithm) , biology , multivariate statistics , deciduous , geography , statistics , mathematics , artificial intelligence , computer science
Summary1 Few studies have related metrics of fitness to broad‐scale, multivariate patterns of resource selection. 2 Our objective was to relate long‐term predation‐mortality patterns for adult woodland caribou [ Rangifer tarandus caribou (Banfield)] from Alberta, Canada (1991–2002), with patterns of multivariate habitat selection. 3 We first compared probabilities of radio‐tracked caribou dying ( n = 55) from predation in habitats within the home range, controlling for habitat availability, with that expected from habitat selection probabilities for the same animals during life. We then compared survival rates of caribou ( n = 141) possessing dissimilar patterns of habitat selection using a Cox proportional hazards regression model. 4 Patterns in habitat‐specific predation mortality differed significantly from expected given probabilities of habitat selection during life ( P < 0·0001). Cox regression indicated that mortality rates of caribou due to predation were affected significantly by and can be predicted from patterns of selection ( P = 0·02). 5 Our results strongly suggest that uplands (primarily mixed deciduous and coniferous forest) present caribou with higher than expected levels of predation risk, and that caribou can avoid predation by maximizing selection of peatlands (open, conifer‐dominated bogs and fens). 6 Approaches presented in this study may be useful for ecologists interested in assessing the influence of mortality factors on broad‐scale, multivariate resource selection. Linking metrics of fitness to multivariate resource selection will enable us to ask questions of evolutionary ecology once restricted to only the finest ecological scales.