MaxEnt Modeling for Predicting the Potential Wintering Distribution of Eurasian Spoonbill (Platalea leucorodia leucorodia) under Climate Change in China

Abstract

Global climate change has become a trend and is one of the main factors affecting biodiversity patterns and species distributions. Many wild animals adapt to the changing living environment caused by climate change by changing their habitats. Birds are highly sensitive to climate change. Understanding the suitable wintering habitat of the Eurasian Spoonbill (Platalea leucorodia leucorodia) and its response to future climatic change is essential for its protection. In China, it was listed as national grade II key protected wild animal in the adjusted State List of key protected wild animals in 2021, in Near Threatened status. Few studies on the distribution of the wintering Eurasian Spoonbill have been carried out in China. In this study, we simulated the suitable habitat under the current period and modeled the distribution dynamics of the wintering Eurasian Spoonbill in response to climate change under different periods by using the MaxEnt model. Our results showed that the current suitable wintering habitats for the Eurasian Spoonbill are mainly concentrated in the middle and lower reaches of the Yangtze River. Distance from the water, precipitation of the driest quarter, altitude, and mean temperature of the driest quarter contributed the most to the distribution model for the wintering Eurasian Spoonbill, with a cumulative contribution of 85%. Future modeling showed that the suitable distribution of the wintering Eurasian Spoonbill extends to the north as a whole, and the suitable area shows an increasing trend. Our simulation results are helpful in understanding the distribution of the wintering Eurasian Spoonbill under different periods in China and support species conservation.

Unraveling the unknown: Adaptive spatial planning to enhance climate resilience for the endangered Swamp Grass-babbler (Laticilla cinerascens) with habitat connectivity and complexity approach

“…The primary occurrence sources utilized in this scientific study comprised data obtained through field visits and secondary citizen science platforms, including ebird ( n = 477 ) ( https://ebird .org/home), Global Biodiversity Information Facility (GBIF) ( n = 223) ( https://doi .org/10.15468/dl.5e8har), and data retrieved from evaluated scientific literature ( n = 5) [ 54 , 56 , 57 ]. The field survey was conducted between January and December 2022 ( n = 10) at Maguri-Matapung Beel and DSNP.…”

Prediction of Potential Suitable Distribution Areas for an Endangered Salamander in China

“…A larger value indicates higher model accuracy, as well as higher credibility of the model. Models can be considered as having high prediction accuracy when the AUC value is greater than 0.8, and then the prediction results can be adopted [43]. An AUC value greater than 0.9 indicates that the prediction accuracy of the model is extremely high [23].…”

Habitat utilization of the Eurasian spoonbill (Platalea leucorodia) wintering in the Yancheng National Nature Reserve: relative importance of artificial habitats

“…This study was conducted in the core and buffer zones of the YNNR. According to the migration schedules of Eurasian spoonbills (Fu et al, 2023), we conducted line transect surveys to record bird distribution and habitat use in two consecutive wintering seasons for this bird from November to March in 2021-2022 and 2022-2023. Because of the differences among individuals and regions, we confirmed this migration schedule based on local climate conditions and related migration studies (Xi et al, 2021).…”

“…Three subspecies and four biogeographical populations have been identified. Among them, the East Asian population, whose breed range mainly covers Northeast Asia, Mongolia, and China, winters in Southeast China, South Korea, and Japan (Xi et al, 2021;Fu et al, 2023). Recent surveys have considerably improved our knowledge of the Eurasian spoonbill ecology in terms of breeding, feeding habits, and behavioral patterns (Hu et al, 1999;Veen et al, 2012;Li et al, 2014).…”