Species Distribution Models (SDMs) are commonly used statistical tools in conservation biology, global change assessment, and reserve prioritization. Correlative SDMs relate species occurrences to environmental conditions, and it is common to model heterogeneity in the data with coarse-scale spatial and temporal predictors. However, this approach neglects the fine-scale environmental conditions experienced by most organisms. Further, most SDMs use occurrence data from short-term studies but make long-term predictions of future conditions. We compare four modeling frameworks that varied the temporal extent (short-term [1 year] versus long-term [10 years]) and resolution of environmental data (fine versus coarse). We expected that long-term data and finer temporal resolution of environmental variables would provide more accurate model predictions because they integrate variability in population sizes under varying microclimatic conditions. We built SDMs for 37 bird species in the H. J. Andrews Experimental Forest, Cascade Range, Oregon (USA). We used a 10-year (2010-2019) time series of annual observations during breeding season across 184 sites as response variables and gridded maps of hourly below forest canopy microclimate temperatures and LiDAR-derived vegetation variables as predictors. We evaluated the interannual transferability of long- versus short-term models and fine versus coarse-resolution temperature models; we also tested whether species’ functional traits affected the performance of models. Temporally dynamic (long-term) models with higher-resolution microclimate data outperformed static and short-term approaches in terms of performance (AUC difference ~ 0.10, TSS difference ~ 0.12). Model performance and similarity between spatial predictions were higher for dynamic rather than static models, especially for migratory species. Models for small bird species performed better as temporal resolution increased, whereas for long-lived species with larger body sizes, dynamic approaches performed similarly to static models. We advocate for increased use of fine-scale, long-term data in SDMs to boost the performance and reliability of future predictions under global change.

Small mammal abundances are frequently limited by resource availability but predators can exert strong lethal (direct mortality) and non-lethal limitations (e.g. depressed site-level activity). Artificially increasing resource availability for small mammals provides a unique opportunity to examine predator-prey interactions. We monitored the 3-year response of arboreal rodents and their predators at nest platforms (n = 598; 23 young forest sites), using annual inspections and remote cameras (n = 168). One year after adding nest platforms we found a 2.9 to 9.2-fold increase in red tree vole (Arborimus longicaudus) use at the site-level, but little use by potential predators. Predator use of nest platforms began in year two and increased in year three of the study. Most potential nest predators were positively correlated with tree vole presence at nest platforms but effect size and direction varied with temporal grain considered (e.g. hour vs day time-bin widths). Flying squirrels (Glaucomys humboldtensis) were positively correlated with disturbances caused by digging birds. Using a Cormack-Jolly-Seber model and encounter histories produced from visual re-captures of marked tree voles, we estimated apparent annual survival to be 0.099 ± 0.057 (x̄ ± 1 SE) for females and 0.005 ± 0.014 for males. Weasels (Mustela spp.), an active seeking predator, preyed upon tree voles most frequently with 10% of weasel detections resulting in mortality of a tree vole (n = 8) whereas owls, an ambush predator, did not prey upon tree voles at nest platforms even though they were detected at similar frequencies as weasels. Weasels also exerted potential non-lethal effects and we observed a >10-fold reduction in the number of tree vole detections per week after weasel detection. Our evidence indicates that predators exert direct and indirect effects on tree vole populations with active seeking predators being the most important predators at nest sites.