Performance of hunting statistics as spatiotemporal density indices of moose (Alces alces) in Norway
Wildlife managers are often asking for reliable information of population density across larger spatial scales. In this study, we examined the spatiotemporal relationships between moose density as estimated by cohort analysis and the density indices (1) harvest density (HD; hunter kills per km2), (2...
| Published in: | Ecosphere |
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| Main Authors: | , , , , |
| Format: | Article in Journal/Newspaper |
| Language: | English |
| Published: |
2014
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| Subjects: | |
| Online Access: | https://hdl.handle.net/11250/3077492 https://doi.org/10.1890/ES13-00083.1 |
| Summary: | Wildlife managers are often asking for reliable information of population density across larger spatial scales. In this study, we examined the spatiotemporal relationships between moose density as estimated by cohort analysis and the density indices (1) harvest density (HD; hunter kills per km2), (2) moose seen per unit effort (SPUE), seen moose density (SMD; seen moose per km2), and density of moosevehicle accidents (MVA density; e.g., traffic kills per km2) in 16 areas in Norway with 13–42 years of data. HD showed a close positive relationship with moose density both within and between regions. However, the temporal variation in HD was best explained as a delayed reflection of moose density and tended to overestimate its growth and decline. Conversely, SMD and SPUE were unable to predict the spatial variation in moose density with high precision, though both indices were relatively precise temporal reflectors of moose density. However, the SPUE tended to underestimate population growth, probably because of a decrease in searching efficiency with increasing moose density. Compared to the other indices, MVA density performed poor as an index of moose density within regions, and not at all among regions, but may, because of its independent source of data, be used to cross-check population trends suggested by other indices. Our study shows that the temporal trends in moose density can be surveyed over large areas by the use of cheap indices based on data collected by hunters and local managers, and supports the general assumption that the number of moose killed per km2 provides a precise and isometric index of the variation in moose density at the spatial scale of our study. cohort analysis; isometric index; management; monitoring; population reconstruction; precision; saturation; seen per unit effort (SPUE). Performance of hunting statistics as spatiotemporal density indices of moose (Alces alces) in Norway publishedVersion |
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