Climate change is contributing to biodiversity redistributions and species declines. However, cooler microclimate conditions provided by old‐growth forest structures compared with surrounding open or younger forests have been hypothesized to provide thermal refugia for species that are sensitive to climate warming and dampen the negative effects of warming on population trends of animals (i.e., the microclimate buffering hypothesis). In addition to thermal refugia, the compositional and structural diversity of old‐growth forest vegetation itself may provide resources to species that are less available in forests with simpler structure (i.e., the insurance hypothesis). We used 8 years of breeding bird abundance data from a forested watershed, accompanied with sub‐canopy temperature data, and ground‐ and LiDAR‐based vegetation data to test these hypotheses and identify factors influencing bird population changes from 2011 to 2018. After accounting for imperfect detection, we found that for 5 of 20 bird species analyzed, abundance trends tended to be less negative or neutral at sites with cooler microclimates, which supports the microclimate buffering hypothesis. Negative effects of warming on two species were also reduced in locations with greater forest compositional diversity supporting the insurance hypothesis. We provide the first empirical evidence that complex forest structure and vegetation diversity confer microclimatic advantages to some animal populations in the face of climate change. Conservation of old‐growth forests, or their characteristics in managed forests, could help slow the negative effects of climate warming on some breeding bird populations via microclimate buffering and possibly insurance effects.

Population declines in terrestrial bird species have been reported across temperate regions in the world and are attributed to habitat loss, climate change, or other direct mortality sources. North American and European studies indicate that long-distance migrants, common species, and species associated with grasslands and agricultural lands are declining at the greatest rates. However, data from East Asia on avian population trends and associated drivers are extremely sparse. We modeled changes in occupancy of 52 common breeding landbird species in South Korea between 1997–2005 and 2013–2019. Thirty-eight percent of the species showed evidence of declines, and seven of these were declining severely (46–95%). Occupancy of Black-capped Kingfisher (Halcyon pileata) populations have dropped the most precipitously over the study period. Among declining species, long-distance migrants (9/20) and common species (14/20) showed more rapid declines than other groups. Declines of five species were associated with climate change, and two species appeared to be affected by land-cover change. However, causes of change in occupancy of other species (46/52) remains cryptic. Based on our results, we suggest an immediate re-evaluation of species’ conservation status and legal protection levels for seven severely declining species in South Korea, and a dedicated survey design and analysis effort for the continued monitoring landbird populations. Because many species exhibiting declines migrate from beyond national boundaries, international collaborations will be required to better quantify population trends across the full annual cycle, and to understand mechanisms for these declines.

Thermal imaging drones have transformed wildlife monitoring by facilitating the efficient and noninvasive monitoring of animal populations across large areas. In this study, an optimized flight path design was developed for monitoring wildlife on Guleopdo Island, South Korea using the DJI Mavic 3T drone equipped with a thermal camera. We employed a strata-based sampling technique to reclassify topographical and land cover information, creating an optimal survey plan. Using sampling strata, key waypoints were derived, on the basis of which nine flight paths were designed to cover ~50% of the study area. The results demonstrated that an optimized flight path improved the accuracy of detecting Formosan sika deer (Cervus nippon taiouanus). Population estimates indicated at least 128 Formosan sika deer, with higher detection efficiency observed during cloudy weather. Customizing flight paths based on the habitat characteristics proved crucial for efficient monitoring. This study highlights the potential of thermal imaging drones for accurately estimating wildlife populations and supporting conservation efforts.

Correlative species distribution models (SDMs) are essential tools in conservation biology, global change assessment and reserve prioritization, linking species occurrences with environmental conditions. These models often rely on coarse‐scale spatial and temporal predictors, overlooking fine‐scale environmental conditions experienced by organisms. Additionally, SDMs commonly use short‐term occurrence data to make long‐term predictions, which can reduce reliability. We hypothesized that long‐term and finer temporal resolution data would provide more accurate predictions by capturing population variability under microclimatic conditions. Using data from 37 bird species in the H. J. Andrews Experimental Forest (Oregon, USA), we built SDMs with a 10‐year (2010–2019) dataset of breeding season observations at 184 sites. We evaluated four modelling frameworks that differed in temporal extents (short‐term [1 year] vs. long‐term [10 years]) and resolution (fine vs. coarse) of environmental data. Predictors included hourly microclimate temperatures beneath the forest canopy and LiDAR‐derived vegetation variables. We evaluated interannual transferability and compared model performance based on temporal extent, resolution and species traits. Temporally dynamic (long‐term) models with higher resolution microclimate data outperformed static and short‐term models (AUC and TSS difference ~ 0.06, difference in unreliability index of ~0.04) and were more accurate and spatially consistent, particularly for migratory species. Increased temporal resolution improved performance for small‐bodied species, whereas long‐lived, larger species performed similarly in short‐ and long‐term models. Synthesis and applications . To our knowledge, this is the first empirical study to demonstrate the benefits of long‐term dynamic SDMs with spatially matched predictor variables. If predicting the future of biodiversity under land‐use and climate change is the goal, practitioners should consider additional investment in multi‐year biodiversity monitoring rather than single‐year ‘snapshots’ of species distributions.

Climate change can alter and disrupt the phenology and phenological interaction between organisms from various trophic levels in forest ecosystems. In temperate forests, the breeding phenology of birds is correlated to local microclimate, especially spring temperature to match the timing of food availability. Recent studies revealed that the temperature warming is more pronounced in high-elevation areas (elevation-dependent warming), while the breeding phenology shift of birds in this condition needs further investigation. We studied the annual change in the egg-laying dates of varied tits (Poecile varius) and a pre-breeding temperature index in three plots located along with the elevational gradient in South Korea and a low-elevation plot in Japan. We found strong support for disproportionate rates of changes in higher elevation for warming trends in pre-breeding period and advances in egg-laying dates over the last decade. Next, we compared three segments of 36-year data from Akazu Research Forest. The evidence from pre-breeding temperature during 36 years indicates that we could detect the change in thermal environment and breeding phenology with longer years of data, especially in lower elevation regions. This result shows the need for long-term research to understand the change in local temperatures and the ecology of forest birds. Our study presents evidence of elevation-dependent phenological advance in avian breeding activities and discusses the need for systematic long-term research on multiple taxa and climatic drivers in Asia.