Density surface and excursion sets modeling as an approach to estimating population densities

Effective species management and conservation require knowledge of species distribution and status. We used point-transect distance sampling surveys of the endangered palila (Loxioides bailleui), a honeycreeper currently found only on the Island of Hawai'i, USA, to generate robust estimates of total abundance and simultaneously model the distribution, abundance, and spatial correlation of the species as a density surface model (DSM). Point-transect distance sampling is a widely applied method to estimate bird densities accounting for imperfect detection probability. For the DSM we used a generalized additive model framework and soap film smoothers to control the effects of boundary features. This modeling approach allowed us to account for imperfect detection and propagate detection probability uncertainty. We compared the uncertainty in palila abundance estimates using standard point-transect distance sampling to estimates from the DSM. The DSM, accounting for both distance-sampling-derived detection probability variance and the generalized additive model density estimate variance, did not improve population estimator precision; however, it provided insight into the species' distribution, density, and uncertainty. We also applied excursion sets analysis to objectively identify areas where the species occurs in high densities. The 2017 global population of <2,000 individuals was limited to an excursion area of 1,500 ha. Our findings can help management and regulatory agencies by simultaneously mapping a species' distribution and density, improving survey protocols, and providing information important to species conservation.

Automated summary

This study used point-transect distance sampling surveys to estimate the distribution and abundance of the endangered palila species. A density surface model (DSM) was employed to simultaneously model the species' distribution, abundance, and spatial correlation. The results provide valuable information for species conservation, survey protocols improvement, and management.