Occupancy modeling is used to evaluate avian distributions and habitat associations, yet it typically requires extensive survey effort because a minimum of 3 repeat samples are required for accurate parameter estimation. Autonomous recording units (ARUs) can reduce the need for surveyors on-site, yet their utility was limited by hardware costs and the time required to manually annotate recordings. Software that identifies bird vocalizations may reduce the expert time needed if classification is sufficiently accurate. We assessed the performance of BirdNET—an automated classifier capable of identifying vocalizations from >900 North American and European bird species—by comparing automated to manual annotations of recordings of 13 breeding bird species collected in northwestern California. We compared the parameter estimates of occupancy models evaluating habitat associations supplied with manually annotated data (9-min recording segments) to output from models supplied with BirdNET detections. We used 3 sets of BirdNET output to evaluate the duration of automatic annotation needed to approach manually annotated model parameter estimates: 9-min, 87-min, and 87-min of high-confidence detections. We incorporated 100 3-s manually validated BirdNET detections per species to estimate true and false positive rates within an occupancy model. BirdNET correctly identified 90% and 65% of the bird species a human detected when data were restricted to detections exceeding a low or high confidence score threshold, respectively. Occupancy estimates, including habitat associations, were similar regardless of method. Precision (proportion of true positives to all detections) was >0.70 for 9 of 13 species, and a low of 0.29. However, processing of longer recordings was needed to rival manually annotated data. We conclude that BirdNET is suitable for annotating multispecies recordings for occupancy modeling when extended recording durations are used. Together, ARUs and BirdNET may benefit monitoring and, ultimately, conservation of bird populations by greatly increasing monitoring opportunities.

Many bumble bee species (Bombus Latreille) have declined dramatically across North America and the globe, highlighting the need for a greater understanding of the habitat required to sustain or recover populations. Determining bumble bee species’ plant selection is important for retaining and promoting high-quality plant resources that will help populations persist. We used nonlethal methods to sample 413 plots within riparian corridors and meadows in the Sierra Nevada of California for bumble bees during two summers following extremely low and normal precipitation years, respectively. We assessed the five most abundant bumble bee species’ plant selection by comparing their floral use to availability. Additionally, we described the shift in plant selection between years for the most abundant species, Bombus vosnesenskii Radoszkowski. Bumble bee species richness was constant between years (13 species) but abundance nearly tripled from 2015 to 2016 (from 1243 to 3612 captures), driven largely by a dramatic increase in B. vosnesenskii. We captured bumble bees on 104 plant species or complexes, but only 14 were significantly selected by at least one bumble bee species. Each of the five most frequently captured bumble bee species selected at least one unique plant species. Plant blooming phenology, relative availability of flowers of individual plant species, and plant selection by B. vosnesenkii remained fairly constant between the two study years, suggesting that maintaining, seeding, or planting with these ‘bumble bee plants’ may benefit these five bumble bee species.

Riparian corridors can be highly biodiverse but are often degraded by human activities, and are therefore frequent targets of restoration actions. Yet managers often lack clear guidance on how to conserve or restore riparian vegetation structure and composition to promote wildlife biodiversity, due to the difficulty of balancing the needs of multiple species and taxonomic groups. We used independent multi‐species occupancy models to assess the response of riparian bird and bumble bee assemblages, respectively, to variation in vegetation structure and composition in montane riparian corridors. We sought to identify vegetation characteristics associated with relatively high richness across each taxonomic group to define target conditions for habitat restoration. Riparian bird occupancy increased with more willow (Salix spp.) cover and less overstory cover, while bumble bee occupancy increased with greater flowering plant richness, more forb cover, and less shrub cover. Relatively distinct habitat preferences of bumble bees and riparian birds emphasize the value of managing for habitat heterogeneity to promote biodiversity across multiple taxonomic groups. Multi‐species modeling distills the responses of numerous species down to a single estimate of a covariate effect for an assemblage of species and can provide land managers with empirically derived targets for habitat restoration that will benefit many species.

Context Fire transforms, fragments and sometimes maintains forests, creating mosaics of burned and unburned patches. Highly mobile animals respond to resources in the landscape at a variety of spatial scales, yet we know little about their landscape-scale relationships with fire. Objectives We aimed to identify drivers of bat richness in a landscape mosaic of forested and burned areas while identifying spatial scales at which bat richness was most strongly related to extent, configuration, and diversity measures of landscape-level habitat. Methods We used multi-species hierarchical occupancy modelling to relate bat richness to landscape variables at 10 spatial scales, based on acoustic data collected in the Sierra Nevada, United States. We also assessed redundancy among landscape variable type (extent, configuration, and diversity) and between focal patch types (forested and burned). Results Bat richness was positively associated with heterogenous landscapes, shown by positive associations with pyrodiversity, extent and mean area of burned patches, burned and forested edge density and patch density and relationships were generally consistent across scales. Extent of forest cover and burned areas were highly correlated, but configuration and diversity of these patch types diverged. Conclusions Bat communities of our study area appear to be largely resilient to wildfire and adapted to more heterogenous forests and shorter-interval fire regimes that likely predominated before the fire suppression era.

The North West Province in South Africa is an important contributor to the country’s economy with agriculture and mining the main drivers. Droughts regularly affect the region and impact greatly on farming which in turn has negative socio-economic consequences. Multi-temporal satellite remote sensing data is well suited to study changes in vegetation health. Vegetation and temperature indices from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor and rainfall data from the Climate Hazards group Infrared Precipitation with Stations (CHIRPS) between 2010 and 2020 showed good vegetation health in 2010 and 2020, but gradually worsening drought condition in the intervening years. Although the entire North West Province is affected by drought, the central and western portions experience the worst conditions. The vegetation condition index, temperature condition index and vegetation health index show a faster recovery along the western edge of the province in 2018 than the rest of the province, a detail not easily visible in the conventional enhanced vegetation index and land surface temperature data. They also show a gradual decrease in vegetation health between 2010 and 2014. A comparison with geology shows that vegetation health is, in part, also linked to the underlying rock types.