Detection and density estimation for a cryptic species
Publication Name
Austral Ecology
Abstract
Detection of animals is influenced by species traits, environment, season and the methods used. Analytical techniques can address imperfect detection, such as false absences, but data limitations hinder accurate density estimation. Identifying field survey methods that optimize detectability is therefore a high research priority, especially for species of conservation concern. We consider a model species, the sugar glider Petaurus notatus, to evaluate how optimizing detections can affect survey outcomes. A literature meta-analysis found little innovation in baiting approaches for sugar gliders over four decades. Honey-based baits prevailed, despite emerging evidence of opportunistic carnivory. We compared sugar glider detection probabilities using honey and fish-based baits in a spatially explicit capture-recapture study. Fish bait increased detections 33-fold, and density estimation (0.12 ha−1) was only possible using the fish-baited data – detections were too sparse using honey-bait to facilitate analysis. Other factors that influence detectability include trap height and habitat connectivity, which were top moderators in our meta-analysis, but these may be secondary to the bait or lure used. By using (i) species-specific bait that accounts for the biology of the target species, and (ii) analytical tools to account for imperfect detection and heterogeneous movement of animals, we achieved good enough detection probabilities to undertake detailed analysis of the spatial ecology of sugar gliders. Compared to honey-based baits (the prevailing approach of other studies on this species), the high detection probability attained with fish-based baits provides an improvement on conventional practices. Our study is an important reminder that accounting for the biology of the target species during survey effort may mean the difference between collecting enough data for analysis or not. In the context of species conservation, optimizing detection likelihoods is critical for answering ecological questions about cryptic species, and our results demonstrate the need to reappraise generic approaches when better information is available.
Open Access Status
This publication may be available as open access
Volume
49
Issue
2
Article Number
e13467
Funding Number
A2020/35
Funding Sponsor
Cradle Coast NRM