Aim: We tested the effects of season and migratory status (residents-versus-seasonal migrants) on island biogeography of bird assemblages through partitioning beta diversity into richness and turnover components and community nestedness metrics. We predicted that total beta diversity, the richness component of beta diversity and community nestedness will be lower for bird assemblages in winter than in summer, and lowest of all for winter visitors. These predictions were derived from published ideas about resource availability, movement and habitat choice in birds in different seasons. Location: Thousand Island Lake, China. Methods: Bird species were sampled using line transects on 36 islands during five breeding and winter seasons (2009−2014). Birds were grouped into assemblages of winter residents, winter visitors and summer residents. Associations between beta diversity partitioning, island area, isolation and habitat richness were tested using partial Mantel correlations. We complemented these tests with measures of nestedness and null model approaches. Results: Contrary to expectation, beta diversity, nestedness and difference of beta diversity or its components from null models were higher for winter residents than either summer resident or winter visitor assemblages. As predicted, winter visitors showed little association with habitat richness, and beta diversity was rarely different from null communities. Summer residents had the highest correlations of beta diversity components with habitat richness, but showed the lowest level of total beta diversity, a low richness component and were anti-nested (less nested than random). Main conclusions: Substantial differences were found in the biogeography of winter-versus-summer residents, and seasonal visitor (migratory)-versus-resident bird assemblages, which match expectations derived from bird biology and population ecology. Summer residents highlighted the role of habitat-related niche differences, whereas winter residents showed area-related selective extinction. By contrast, winter visitors appeared to be more randomly distributed.

Wildlife trade poses a major threat to biodiversity, yet the drivers determining which species are traded are not fully understood. Through a comprehensive collection of official and online trade data, we applied a binomial test to identify families that contain an unexpectedly large or small number of traded species. We also analyzed which factors predispose reptile species to be traded and explored whether traded species were more likely to be threatened with extinction. Of the 10,919 reptile species in our dataset, 3889 species (35.6%) were traded. There was strong evidence for taxonomic biases in trade risk. In particular, all turtle and crocodilian families had higher trade risk than other reptiles. Species with large body sizes, habitat generalists, insular endemics, and those found in regions with high gross domestic product were traded in greater quantities and more frequently. Species with small and large ranges were more frequently involved in trade, suggesting a demand for rare and common species in wildlife trade. When connecting trade risk to extinction risk, data-deficient and not-evaluated species had fewer traded species and were less likely to be traded than threatened or nonthreatened ones. Nonetheless, these species warrant special conservation attention considering their rarity, limited range size, and insufficient legal protection. Given the increased attention given to wildlife trade, we suggest implementing stronger regulatory measures to monitor and control the trade of reptile species, particularly those belonging to families with a high risk of being traded. Efforts should also prioritize the protection of species exhibiting traits that make them highly susceptible to exploitation. Finally, promoting international collaboration for stricter enforcement of wildlife trade regulations and support of sustainable trade practices can help mitigate the negative impacts on biodiversity.