Context

Understanding habitat dynamics is essential for effective conservation as landscapes rapidly change. In a companion paper in this issue, Shirk et al. (2023) introduced an automated habitat monitoring system using Google Earth Engine and applied this framework to develop a dynamic model of Mexican spotted owl (Strix occidentalis lucida) habitat across the southwestern US from 1986 to 2020.

Objectives

We explored the application of this dynamic model of Mexican spotted owl habitat in the context of the species’ ecology.

Methods

We evaluated environmental correlates of Mexican spotted owl habitat, assessed potential spatial non-stationarity in habitat selection, estimated long-term trends in habitat by quantifying changes in habitat amount and quality between 1986 and 2020, and evaluated the extent to which habitat changes over the past 35 years have been driven by wildfire.

Results

Topography and climate appeared to outweigh reflectance-based (vegetation) metrics in describing Mexican spotted owl habitat and habitat selection was non-stationary across modeling sub-regions. Total habitat area for Mexican spotted owls declined by ~ 21% since 1986 (0.6% annually), but trends varied spatially and some even reversed over the past decade. Wildfire was responsible for between 8 and 35% of total habitat loss, depending on the sub-region considered.

Conclusions

The automated habitat monitoring system allowed trend estimation and accurate assessment of current habitat status for Mexican spotted owls; maps were accurate, spatially detailed, and current. The ability to continually produce accurate maps for large land areas for threatened species such as the Mexican spotted owl facilitates science-based land management on public lands in the southwestern US.