Dynamic foraging strategy adaptation to heterogeneous environments contributes to social aggregation in snub-nosed monkeys

The dynamics of animal social structures are heavily influenced by environmental patterns of competition and cooperation.In folivorous colobine primates,prevailing theories suggest that larger group sizes should be favored in rainforests with a year-round abundance of food,thereby reducing feeding competition.Yet,paradoxically,larger groups are frequently found in high-altitude or high-latitude montane ecosystems characterized by a seasonal scarcity of leaves.This contradiction is posited to arise from cooperative benefits in heterogeneous environments.To investigate this hypothesis,we carried out a six-year field study on two neighboring groups of golden snub-nosed monkey(Rhinopithecus roxellana),a species representing the northernmost distribution of colobine primates.Results showed that the groups adjusted their movement and habitat selection in response to fluctuating climates and spatiotemporal variability of resources,indicative of a dynamic foraging strategy.Notably,during the cold,resource-scarce conditions in winter,the large group occupied food-rich habitats but did not exhibit significantly longer daily travel distances than the smaller neighboring group.Subsequently,we compiled an eco-behavioral dataset of 52 colobine species to explore their evolutionary trajectories.Analysis of this dataset suggested that the increase in group size may have evolved via home range expansion in response to the cold and heterogeneous climates found at higher altitudes or latitudes.Hence,we developed a multi-benefits framework to interpret the formation of larger groups by integrating environmental heterogeneity.In cold and diverse environments,even smaller groups require larger home ranges to meet their dynamic survival needs.The spatiotemporal distribution of high-quality resources within these expanded home ranges facilitates more frequent interactions between groups,thereby encouraging social aggregation into larger groups.This process enhances the benefits of collaborative actions and reproductive opportunities,while simultaneously optimizing travel costs through a dynamic foraging strategy.

Investigating the dynamics and interactions of surface features on Pine Island Glacier using remote sensing and deep learning

Pine Island Glacier(PIG),the largest glacier in the Amundsen Sea Embayment of West Antarctica,has contributed to over a quarter of the observed sea level rise around Antarctica.In recent years,multiple observations have confirmed its continuous retreat,ice flow acceleration and profound surface melt.Understanding these changes is crucial for accurately monitoring ice mass discharge and future Antarctic contributions to sea level rise.Therefore,it is essential to investigate the complex interactions between these variables to comprehend how they collectively affect the overall stability of the intricate PIG system.In this study,we utilized high-resolution remote sensing data and deep learning method to detect and analyze the spatio-temporal variations of surface melt,ice shelf calving,and ice flow velocity of the PIG from 2015 to 2023.We explored the correlations among these factors to understand their long-term impacts on the glacier's stability.Our findings reveal a retreat of 26.3 km and a mass loss of 1001.6 km^(2) during 2015-2023.Notably,extensive surface melting was observed,particularly in the 2016/2017 and 2019/2020 melting seasons.Satellite data vividly illustrate prolonged and intense melting periods,correlating with a significant retreat in the glacier's terminus position in 2019/2020.Furthermore,the comprehensive analysis of surface melting and the cumulative retreat of the ice shelf from 2017 to 2020 on the PIG shows atemporal relationship with subsequent significant changes in ice fow velocity,ranging from 10.9 to 12.2 m d^(-1),with an average acceleration rate of 12%.These empirical findings elucidate the intricate relationship among surface melt,ice flow velocity,and consequential glacier dynamics.A profound understanding of these interrelationships holds paramount importance in glacier dynamic changes and modeling,providing invaluable insights into potential glacier responses to global climate change.