Abstract
Monitoring populations is challenging for cryptic species with seasonal life cycles, where data from multiple field techniques are commonly collected and analyzed as multiple lines of evidence. Data integration can provide comprehensive inferences while improving accuracy, precision, and scope but faces challenges in modeling misaligned resolutions and observational uncertainties. We developed a multi-scale, integrated species distribution model (MS-iSDM) for North American bats to combine data across monitoring types and seasons using joint likelihood methods, observational models with false-negatives and false-positives, and seasonal migratory connectivity. We applied this model to 11 years of data for an imperiled bat species (tricolored bat, Perimyotis subflavus). Relative abundance and occupancy were linked with multi-scale predictors, revealing clear patterns of population declines, but with important differences in spatial trends (abundance: corresponded with white-nose syndrome impacts, occupancy: at the range periphery) and overall severity (abundance: -74.8%, 95% CRI: -79.7% to -69.3%; occupancy: -35.5%, 95% CRI: -41.1% to -30.2%). The asynchrony between occupancy trends and population impacts was explained as an emergent pattern of spatiotemporal variation in abundance in the integrated distribution model. Compared to multiple lines of evidence, the integrated model provided consensus-estimates, increased precision and spatiotemporal scope, and strengthened evidence of population declines.