Frequent, heterogenous fire supports a forest owl assemblage

Abstract

Fire shapes biodiversity in many forested ecosystems, but historical management practices and anthropogenic climate change have led to larger, more severe fires that threaten many animal species where such disturbances do not occur naturally. As predators, owls can play important ecological roles in biological communities, but how changing fire regimes affect individual species and species assemblages is largely unknown. Here, we examined the impact of fire severity, history, and configuration over the past 35 years on an assemblage of six forest owl species in the Sierra Nevada, California, using ecosystem-scale passive acoustic monitoring. While the negative impacts of fire on this assemblage appeared to be ephemeral (1-4 years in duration), spotted owls avoided sites burned at high-severity for up to two decades after a fire. Low- to moderate-severity fire benefited small cavity-nesting species and great horned owls. Most forest owl species in this study appeared adapted to fire within the region's natural range of variation, characterized by higher proportions of low- to moderate-severity fire and relatively less high-severity fire. While some species in this assemblage may be more resilient to severe wildfire than others, novel "megafires" that are larger, more frequent, and contiguously severe may limit the distribution of this assemblage by reducing the prevalence of low- to moderate-severity fire and eliminating habitat for a closed-canopy species for multiple decades. Management strategies that restore historical low- to moderate-severity fire with small patches of high-severity fire and promote a mosaic of forest conditions will likely facilitate the conservation of this assemblage of forest predators.

Keywords: bioacoustics; disturbance; megafire; occupancy; owls; passive acoustic monitoring; wildfire.

FIGURE 1

Sierra Nevada study area and forest owl detections. Colors correspond to validated occurrences of great horned owls, western screech owls, flammulated owls, spotted owls, northern pygmy owls, and northern saw‐whet owls. The regional study area was divided into noncontiguous hexagonal sampling grids across seven national forests (green) and three national parks (brown). In 845 noncontiguous sampling hexagonal cells, we deployed one to three passive autonomous recording units (ARUs). We conducted analyses at the scale of the hexagonal sampling cells for the larger species and at the scale of 250‐m buffers around ARUs for the smaller species. Note that spotted owl detections were all manually vetted, while the other five species were obtained using prediction score and call rate thresholds. The distributions of those five species are likely underestimated as a consequence of eliminating false positives.

FIGURE 2

Covariate effect sizes from top ranked occupancy models for flammulated owls (FLOW), great horned owls (GHOW), northern pygmy owls (NOPO), northern saw‐whet owls (NSWO), spotted owls (SPOW), and western screech owls (WESO). Gray indicates covariates that describe broad spatial associations, red indicates a fire covariate describing high‐severity fire, and orange indicates a fire covariate describing low to moderate severity. Triangles indicate configuration covariates, and the square indicates an interaction between a composition and configuration covariate. Error bars show 85% CIs. The top model describing northern saw‐whet owl occupancy contained estimated effect sizes with large values and CIs that overlapped zero, indicated by the horizontal error bars in the northern saw‐whet panel. Parameter effects with asterisk indicate those that were unique to the first and second best models.

FIGURE 3

Predicted relationships between the proportion and patch density of low‐ to moderate‐severity fire and high‐severity fire and the probability of site occupancy (ψ) for six forest owl species. Solid lines indicate a predicted relationship between either patch density or proportion of both severity classes at each times step, and are shown only for covariates that comprise top models for each species. Dashed lines indicate species‐specific estimates of mean occupancy. FLOW, flammulated owls; GHOW, great horned owls; NOPO, northern pygmy owls; NSWO, northern saw‐whet owls; SPOW, spotted owls; WESO, western screech owls.

FIGURE 4

Validated SPOW detections included in the spotted owl occupancy models within and near the boundaries of the King, Creek, and North Complex Fires. Orange indicates low‐ to moderate‐severity fire and red indicates high‐severity fire. Bold hexes indicate sampling cells that contained at least one detection during the 2021 sampling period. Only a few spotted owls were detected within the boundaries of these fires, and none were detected within areas of contiguous high‐severity fire.