Predicted Potential Distributions of Two Rare and Critically Endangered Bird Species in China Based on the MaxEnt Model

Biodiversity loss has become a global ecological crisis, and the conservation of Critically Endangered (CR) species is particularly urgent. In response, this study focuses on two CR bird species with markedly contrasting ecological traits, Emberiza aureola and Aythya baeri. Using species occurrence records and 22 environmental variables, we applied the MaxEnt model to simulate their potential suitable habitats. The results indicate that: the distribution of Emberiza aureola is primarily driven by precipitation of the driest month, precipitation seasonality, and slope. Its habitat suitability shows a unimodal response to isothermality and is enhanced in flat plains characterised by higher precipitation in the driest month and moderate precipitation seasonality. In contrast, Aythya baeri is strongly influenced by slope, precipitation of the warmest quarter, and mean temperature of the driest quarter, exhibiting a bimodal response to isothermality. Its suitability peaks under low precipitation conditions in the warmest quarter, reflecting its reliance on shallow, low-disturbance wetlands in open plains. The spatial distribution patterns of the two species differ markedly. Although both are confined to low-relief areas with slopes below 1°, the suitable habitats of Emberiza aureola are more extensive and continuous, with high-suitability areas concentrated in the Northeast China Plain and eastern Inner Mongolia. In contrast, the suitable habitats of Aythya baeri are highly fragmented and concentrated in the coastal wetlands of Liaodong Bay and the lake systems of the middle and lower Yangtze River Basin. By systematically comparing the distributional patterns of these two CR species at a macroecological scale, this study clarifies the constraints imposed by climatic and topographic factors, providing scientific support for optimising China’s protected area networks, implementing targeted wetland restoration, and advancing differentiated habitat management.