Density estimates of unmarked mammals: comparing two models and assumptions across multiple species and years
Density estimation is a key goal in ecology, but accurate estimates for unmarked animals remain elusive. Camera trap data can bridge this gap, but accuracy, precision, and concordance varies among estimators. We compared estimates from unmarked spatial capture–recapture (spatial count (SC)) models,...
Published in: | Canadian Journal of Zoology |
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Main Authors: | , , , , |
Other Authors: | |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
Canadian Science Publishing
2024
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Subjects: | |
Online Access: | http://dx.doi.org/10.1139/cjz-2023-0055 https://cdnsciencepub.com/doi/full-xml/10.1139/cjz-2023-0055 https://cdnsciencepub.com/doi/pdf/10.1139/cjz-2023-0055 |
Summary: | Density estimation is a key goal in ecology, but accurate estimates for unmarked animals remain elusive. Camera trap data can bridge this gap, but accuracy, precision, and concordance varies among estimators. We compared estimates from unmarked spatial capture–recapture (spatial count (SC)) models, and time in front of camera (TIFC) models, for four large mammal species in boreal Canada. Species differed in movement rates, behaviours, and sociality—traits related to model assumptions. TIFC densities typically exceeded SC model estimates for all species. Two- to five-fold differences between estimators were common. SC estimates were annually stable for moose and caribou but not for white-tailed deer. TIFC estimates showed high annual variation in some species, sites, and years, and consistency in others. Both models often produced imprecise estimates. Estimates varied from DNA- and aerial survey-based estimates. We contend models diverge, or implausibly vary, due to violations of model assumptions incurred by animal behaviour. Gregarious animals pose challenges to SC, whereas curious animals pose challenges for TIFC models. Simulations can help unravel the role of assumption violations in affecting accuracy of estimates, but field applications across species and landscapes help interpret the outcomes of estimating density from simulated data. |
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