Forest management can be used to increase the local abundance of species of conservation concern. To achieve this goal, managers must be sure that the relationships between the targeted forest attributes and the focal species abundance are based on robust data and inference. This is a critical issue as the same forest attributes could have opposing effects on species abundance and the detectability of individuals, impairing our ability to detect useful habitat quality surrogates and to provide correct forest management recommendations. Using spatially stratified capture-recapture models (a.k.a. multinomial N-mixture models), we evaluated the effects of stand-level forest attributes on detection probability and local abundance for the endangered Southern Darwin's frog (Rhinoderma darwinii), a forest-specialist and fully terrestrial amphibian endemic to the South American temperate forest. Our results show that an increase of stand basal area and a decrease of daily microclimatic fluctuation (i.e. an increase in structural complexity) were positively associated with the local abundance of R. darwinii. These stand-level forest attributes also explained the among-population variation in detection probability, although the relationships were opposite to those for abundance. Consequently, an analysis of raw frog counts (i.e. not adjusted for imperfect detection) did not reveal all the factors associated with local abundance. Our results provide further support to previous claims that raw counts of individuals should not be used, generally, as a proxy of abundance in species inhabiting forest ecosystems and elsewhere. More importantly, the opposite effect of forest attributes on abundance and detectability observed in our study highlights the need to use methods that quantify species-habitat relationships in a robust way and which take habitat-specific imperfect detection into account.
- Habitat degradation
- Multinomial N-mixture model
ASJC Scopus subject areas
- Nature and Landscape Conservation
- Management, Monitoring, Policy and Law