中国海洋生物地理学研究进展和热点:物种分布模型及其应用

海洋生物地理学是研究海洋生物地理分布时空格局、形成过程及其影响因素的学科,对于生物多样性保护、生态系统结构稳定以及海洋资源可持续利用具有重要支撑作用。物种分布模型是研究物种地理分布变化的重要手段,其发展对于海洋生物地理学的发展具有重要的推动作用。本文综述了中国海洋生物地理学的发展历程和现状;提供了物种分布模型的定义、类型、发展历程及相关重要数据库;整理分析了中国海洋生物地理学研究中的部分热点问题,主要涉及全球变化下海洋生物分布区变化、海洋生物谱系地理结构、海洋生物入侵、种群连通性、海洋保护规划、海洋生态修复、海洋生物对极端环境适应、海洋渔业资源管理和海水养殖规划等。本文同时对海洋生物地理学研究的未来发展进行了展望,强调了改进物种分布模型的重要性,提出要强化环境和生物数据库建设,加强海洋生物地理学与其他学科的交叉融合等。本综述对于今后我国海洋生物地理学的研究,尤其是物种分布模型在相关领域中的应用具有参考价值。

Effects of Acute Temperature Stress on mRNA Expression of Transferrin in the Yellow Pond Turtle Mauremys mutica

The yellow pond turtle Mauremys mutica is widely cultured using both greenhouse-reared and outdoor pond-reared models.Individuals from the two models often show different tolerances to dramatic temperature changes caused by extreme weather events.However,the mechanism underlying the difference is unclear.In this study,we found that for greenhouse-reared turtles(GRTs),the expression levels of an immune-related gene for transferrin were significantly different(P<0.05)between the control group and the acute cold stress(ACS)group for most time points(3 h,6 h and 48 h),while at two time points(6 h and 12 h)there was a significant difference(P<0.05)between the control group and the acute heat stress(AHS)group.However,for the outdoor pond-reared turtles(OPTs),we found the opposite pattern:the ACS group showed no significant difference(P>0.05)from the control group for all time points(3 h,6 h,12 h,24 h and 48 h),whereas two time points(12 h and 24 h)were significantly different(P<0.05)for the AHS group.Our results indicate that ACS may influence the immunity of GRTs and have no influence on OPTs,whereas AHS may largely affect the immunity of OPTs and have little influence on GRTs.The findings provide insights into the mechanism underlying the different morbidity and mortality rates of turtles from different culture models after extreme weather events.

Incorporating adaptive genomic variation into predictive models for invasion risk assessment

Global climate change is expected to accelerate biological invasions,necessitating accurate risk forecasting and management strategies.However,current invasion risk assessments often overlook adaptive genomic variation,which plays a significant role in the persistence and expansion of invasive populations.Here we used Molgula manhattensis,a highly invasive ascidian,as a model to assess its invasion risks along Chinese coasts under climate change.Through population genomics analyses,we identified two genetic clusters,the north and south clusters,based on geographic distributions.To predict invasion risks,we employed the gradient forest and species distribution models to calculate genomic offset and species habitat suitability,respectively.These approaches yielded distinct predictions:the gradient forest model suggested a greater genomic offset to future climatic conditions for the north cluster(i.e.,lower invasion risks),while the species distribution model indicated higher future habitat suitability for the same cluster(i.e,higher invasion risks).By integrating these models,we found that the south cluster exhibited minor genome-niche disruptions in the future,indicating higher invasion risks.Our study highlights the complementary roles of genomic offset and habitat suitability in assessing invasion risks under climate change.Moreover,incorporating adaptive genomic variation into predictive models can significantly enhance future invasion risk predictions and enable effective management strategies for biological invasions in the future.