Under global climate change, ungulate distributions are generally shifting poleward. However, the dispersal pathways, dynamics of suitable habitat, and environmental drivers of the expanding Milu population in the intensively used coastal wetlands of Jiangsu Province remain poorly understood. To support conservation and management, this study used field occurrence data and environmental variables to predict potentially suitable habitat for Milu under current and future climate scenarios. The Biomod2 ensemble modeling framework was applied to assess spatial changes in habitat suitability, and Geographical Detector was used to identify key environmental drivers. Current potentially suitable habitat showed a belt-like pattern along the coast, with the high suitability area covering 0.035 × 10⁴ km². Under future climate scenarios, potentially suitable habitat for Milu is projected to expand in the central and northern coastal areas of Jiangsu, with a substantial increase in the predicted total suitable habitat area. Dis_coastline, BIO14, BIO4, and Pop_density were identified as key factors influencing the distribution of potential suitable habitat for Milu, among which BIO4 and BIO14 were the principal climatic drivers affecting the northward shift in future suitable areas. These results suggest that Milu habitat suitability is jointly shaped by coastline proximity, temperature and water-availability conditions, and population density. Conservation should prioritize the protection of highly suitable habitats, improve patch connectivity, reduce human disturbance, and strengthen wetland protection and vegetation restoration.

Collisions with overhead power lines are an important source of avian mortality, particularly for migratory and large-bodied birds. Although warning devices are widely installed to increase line visibility, their image-based visibility across viewing distances and directions remains poorly quantified. We evaluated eight power-line bird-collision warning devices using UAV-based multispectral imaging and an avian spectral-response weighting model. Images were acquired at 5, 10, 20, 30, and 50 m under upward-looking, horizontal, and downward-looking viewing geometries. A composite visibility score quantified target–background separation within the multispectral images. Raw mean visibility increased from 0.351 at 5 m to 0.484 at 50 m; however, the distance effect was not significant after accounting for viewing angle and heterogeneous residual variance. Viewing angle was the dominant source of variation at 20–50 m, with substantially higher visibility under downward-looking views than under horizontal and upward-looking views. A significant distance × viewing-angle interaction further showed that distance-response patterns differed among viewing geometries: visibility increased with distance under downward-looking views but remained consistently low under horizontal and upward-looking views. The relative performance of the tested devices also changed under low-visibility conditions, with the self-luminous tag and circular tag B attaining the highest condition-standardized mean scores. These findings identify viewing geometry as a critical determinant of warning-device visibility and demonstrate that averages pooled across observation conditions can obscure important performance differences. Evaluation and deployment should therefore prioritize device visibility from below and during near-horizontal viewing, particularly for overhead ground or shield wires at medium and long distances. This condition-specific framework provides a quantitative basis for improving the design and placement of power-line bird-collision warning devices.