Activity center selection by northern spotted owls

Abstract

The federally threatened northern spotted owl (Strix occidentalis caurina) has been intensively studied across its range, and habitat needs for the species have influenced forest management in northwestern North America for decades. Dense forest canopies are often reported in the scientific literature and agency management plans as an important habitat attribute for spotted owls, though the means of measuring forest canopy and interpreting species requirements vary across studies and more importantly, among management plans. We used light detection and ranging (lidar) measurements of canopy cover, canopy surface heterogeneity, and upper canopy surface connectivity, and an index of the presence of a competitive invasive species, the barred owl (S. varia), in multinomial discrete choice models using a Bayesian framework to evaluate selection of forest cover types by spotted owls in Oregon, USA, 2008–2015. We designated yearly activity centers based on the most biologically significant observation during the nesting season (Mar–Aug), generally centered on the nest tree. Spotted owls selected activity centers with more canopy cover and higher heterogeneity of the canopy surface within 100 m than was available within their territories. The average proportion of canopy cover within 100 m of a spotted owl activity center was 0.79 ± 0.12 (SD; range = 0.34–0.99). The presence of barred owls did not explain variability in selection of spotted owl activity centers, but barred owls might not affect third‐order habitat selection within territories, or our index was too spatially coarse to detect these effects on spotted owl resource selection. We demonstrate that lidar provides researchers and managers with a tool that can accurately measure forest canopies over large areas, and assist in mapping spotted owl habitat. © 2019 The Wildlife Society.

Disentangling LiDAR Contribution in Modelling Species–Habitat Structure Relationships in Terrestrial Ecosystems Worldwide. A Systematic Review and Future Directions

“…Furthermore, most of the reviewed studies tended to include direct LiDAR metrics, or easily derived variables, thus valuable information could be missing. Canopy cover traits were found to be significant for all taxonomic groups (e.g., [37,[109][110][111]), while topography was the same for characterizing habitats for amphibians and reptiles (e.g., [25,51]), invertebrates (e.g., [52,58]), and BLF (e.g., [30,112]). Our results highlight the relevance of using understory and shrubland traits for different taxonomic groups, especially for invertebrates (e.g., [46,113]) and BLF (e.g., [27]), but also for mammals (e.g., [90,114]) and, to a lesser extent, for birds (e.g., [13,115]).…”

“…In any case, further efforts should be made to increase LiDAR accuracy in measuring such traits. Finally, canopy vertical distribution traits were relevant for birds (e.g., [103,107]) due to their 3D use of space, but less than canopy height (e.g., [41,84]) and cover (e.g., [109,116]). This unexpected outcome may be due to the canopy vertical distribution metrics requiring more point cloud resolution to penetrate the canopy structure to accurately describe its complexity.…”

Mixed‐severity wildfire and habitat of an old‐forest obligate

“…Studies focused on the subspecies of northern spotted owls suggest that occupancy and survival generally decline after fire, especially if post-fire logging occurs (Clark et al 2011, 2013, Rockweit et al 2017. The effects of fire on individual northern spotted owls and habitat quality are complex and not fully understood ), but clearly suitability of forests for nesting and roosting decreases if canopy cover is reduced and with spatial aggregation of high-severity fire (Davis et al 2016, Rockweit et al 2017, Sovern et al 2019.…”

Barred Owl Effects on Spotted Owl Resource Selection: A Meta‐Analysis

“…Analyses of relations between spotted owl population performance indicators and habitat conditions might also include other covariates that were regularly displayed in RSFs, including lower‐slope topographic positions, and certain species of hardwoods. Fine‐scale forest canopy conditions surrounding nest sites, not measured in our studies, may also matter to spotted owl population performance and can be estimated using light detection and ranging technology, or LiDAR (North et al , Gallagher et al , Sovern et al ). Further, quantifications of edge (Comfort et al ) may also improve predictions of spotted owl population performance.…”