Changgao Cheng

We present a multiscale geospatial dataset that links nighttime activity indicators with meteorological exposure for Chinese listed firms from 2012 to 2019. The dataset integrates annual firm location anchors, daily nighttime light observations from the Visible Infrared Imaging Radiometer Suite Black Marble VNP46A2 product, ERA5-Land meteorology and official calendar classifications. It contains 25,054 annual firm location anchors, 8,613,913 daily nighttime light records, 2,854,413 integrated daily exposure records, 290,629 firm-month records and 25,054 firm-year records. Nighttime activity is identified by comparing each firm pixel with temporal and spatial radiance baselines, and activity shares are calculated from days with all required observations. Meteorological variables include UTC day temperature summaries, fixed local time means, relative humidity, precipitation, solar radiation and absolute and percentile heat indicators. The release provides linked daily, monthly, annual and spatial products, together with field dictionaries, manifests, validation reports and reconstruction code. These resources can support reproducible research on the spatial and temporal relationships among firm activity, weather conditions and heat exposure.

Expanding transboundary protected areas is crucial to biodiversity conservation and maintenance of ecosystem services. Quantifying border gradients of species richness is essential to aligning ecological and management boundaries to enable the gradual integration of biodiversity hotspots in conservation strategies that include cross‐border areas that buffer the effects of extensive infrastructure. For the China–Myanmar border region (Gaoligong Mountains), we developed a conservation plan based on threatened species, ecosystem services, border gradient characteristics (i.e., spatial changes in ecological variables with increasing distance from a boundary), and ecological connectivity of protected areas. Although 20.2% of existing protected areas were in the north, 27.7% of identified priority conservation areas were outside these protected areas and only 2.93% were protected. Threatened plant and animal richness exhibited a positive spatial correlation (coefficient = 0.12), but their richness hotspots were spatially mismatched. The richness of threatened species was positively correlated with carbon storage and soil retention, but negatively correlated with water retention. In contrast, threatened animal diversity showed the opposite pattern. Threatened species richness decreased as distance from the border increased (strong linear relationship, R ² = 0.95 for plants and 0.59 for animals). Based on our results, we propose an ecological gradient–based conservation strategy that prioritizes areas where the richness of threatened species overlaps in the central and southern regions and that protects biodiversity hotspots and creates corridors. The framework is applicable to other transboundary regions and supports global biodiversity conventions.