气候速度影响下中国周边海域鲨鱼保护优先区识别

鲨鱼在气候变化和人类活动等因素的影响下面临着种群衰退的风险,开展鲨鱼保护优先区研究是鲨鱼保护行动的重要工作.将气候速度引入鲨鱼保护优先区的识别过程,旨在阐明中国周边海域鲨鱼现状保护成效和保护空缺,并预测气候速度影响下的鲨鱼保护优先区空间格局及其变化趋势.以集成物种分布模型模拟的146种鲨鱼栖息地作为保护对象,以2015年至2100年两种气候变化情景下的气候速度作为保护的机会成本,基于系统保护规划理论模拟现状和未来情景下的鲨鱼保护优先区选址方案.研究结果表明：（1）长江口以南至台湾海峡和北部湾近岸海域为鲨鱼多样性分布的主要区域,台湾海峡区域亦为珍稀濒危物种的重要分布区;（2）在两种气候情景下,南海中南部将面临较高的气候变化风险,而长江口以南至珠江口的近岸海域气候速度均相对较低,提示了这些区域或能成为气候变化影响下的生物避难所;（3）现有保护区仅保护了1.33%的海域和不到4%的鲨鱼物种,尚存在较大的保护空缺.当保护海域比例提升至10%时,可覆盖绝大多数鲨鱼物种.而当比例提升至30%时,珍稀濒危物种的栖息地将得到有效保护;（4）气候变化影响下保护优先区选址将发生不同程度的变化,尤其是在中国南海区域,如在保护规划时兼顾气候速度,可在满足相似保护目标的前提下减少保护优先区内25%以上的气候压力,以使其具有较强的应对气候变化潜力。     

Climate‐induced changes in the distribution of freshwater fish: observed and predicted trends

1. Climate change could be one of the main threats faced by aquatic ecosystems and freshwater biodiversity. Improved understanding, monitoring and forecasting of its effects are thus crucial for researchers, policy makers and biodiversity managers. 2. Here, we provide a review and some meta‐analyses of the literature reporting both observed and predicted climate‐induced effects on the distribution of freshwater fish. After reviewing three decades of research, we summarise how methods in assessing the effects of climate change have evolved, and whether current knowledge is geographically or taxonomically biased. We conducted multispecies qualitative and quantitative analyses to find out whether the observed responses of freshwater fish to recent changes in climate are consistent with those predicted under future climate scenarios. 3. We highlight the fact that, in recent years, freshwater fish distributions have already been affected by contemporary climate change in ways consistent with anticipated responses under future climate change scenarios: the range of most cold‐water species could be reduced or shift to higher altitude or latitude, whereas that of cool‐ and warm‐water species could expand or contract. 4. Most evidence about the effects of climate change is underpinned by the large number of studies devoted to cold‐water fish species (mainly salmonids). Our knowledge is still incomplete, however, particularly due to taxonomic and geographic biases. 5. Observed and expected responses are well correlated among families, suggesting that model predictions are supported by empirical evidence. The observed effects are of greater magnitude and show higher variability than the predicted effects, however, indicating that other drivers of changes may be interacting with climate and seriously affecting freshwater fish. 6. Finally, we suggest avenues of research required to address current gaps in what we know about the climate‐induced effects on freshwater fish distribution, including (i) the need for more long‐term data analyses, (ii) the assessment of climate‐induced effects at higher levels of organisation (e.g. assemblages), (iii) methodological improvements (e.g. accounting for uncertainty among projections and species’ dispersal abilities, combining both distributional and empirical approaches and including multiple non‐climatic stressors) and (iv) systematic confrontation of observed versus predicted effects across multi‐species assemblages and at several levels of biological organisation (i.e. populations and assemblages).     

Why is the choice of future climate scenarios for species distribution modelling important?

Species distribution models (SDMs) are common tools for assessing the potential impact of climate change on species ranges. Uncertainty in SDM output occurs due to differences among alternate models, species characteristics and scenarios of future climate. While considerable effort is being devoted to identifying and quantifying the first two sources of variation, a greater understanding of climate scenarios and how they affect SDM output is also needed. Climate models are complex tools: variability occurs among alternate simulations, and no single 'best' model exists. The selection of climate scenarios for impacts assessments should not be undertaken arbitrarily - strengths and weakness of different climate models should be considered. In this paper, we provide bioclimatic modellers with an overview of emissions scenarios and climate models, discuss uncertainty surrounding projections of future climate and suggest steps that can be taken to reduce and communicate climate scenario-related uncertainty in assessments of future species responses to climate change.     

Conservation physiology of marine fishes: advancing the predictive capacity of models

At the end of May, 17 scientists involved in an EU COST Action on Conservation Physiology of Marine Fishes met in Oristano, Sardinia, to discuss how physiology can be better used in modelling tools to aid in management of marine ecosystems. Current modelling approaches incorporate physiology to different extents, ranging from no explicit consideration to detailed physiological mechanisms, and across scales from a single fish to global fishery resources. Biologists from different sub-disciplines are collaborating to rise to the challenge of projecting future changes in distribution and productivity, assessing risks for local populations, or predicting and mitigating the spread of invasive species.     

The future of terrestrial mammals in the Mediterranean basin under climate change

The Mediterranean basin is considered a hotspot of biological diversity with a long history of modification of natural ecosystems by human activities, and is one of the regions that will face extensive changes in climate. For 181 terrestrial mammals (68% of all Mediterranean mammals), we used an ensemble forecasting approach to model the future (approx. 2100) potential distribution under climate change considering five climate change model outputs for two climate scenarios. Overall, a substantial number of Mediterranean mammals will be severely threatened by future climate change, particularly endemic species. Moreover, we found important changes in potential species richness owing to climate change, with some areas (e.g. montane region in central Italy) gaining species, while most of the region will be losing species (mainly Spain and North Africa). Existing protected areas (PAs) will probably be strongly influenced by climate change, with most PAs in Africa, the Middle East and Spain losing a substantial number of species, and those PAs gaining species (e.g. central Italy and southern France) will experience a substantial shift in species composition.     

中国植物分布模拟研究现状

在过去的20年里, 物种分布模型已广泛应用于动植物地理分布的模拟研究。该文以植物物种分布模拟为例, 利用中国知网、维普网以及Web of Science文献数据库的检索与统计, 分析了2000-2018年间, 中国研究人员利用各种物种分布模型对植物物种分布模拟研究的发文量、模拟模型、物种类型、数据来源、研究目的等信息。最终共收集到366篇有效文献, 分析表明2011年以来中国的物种分布模型应用发展迅速, 且以最近5年最为迅猛, 在生态学、中草药业、农业和林业等行业部门应用广泛。在使用的33种模型中, 应用最广的为最大熵模型(MaxEnt)。有一半研究的环境数据仅包含气候数据, 另一半研究不仅包含气候数据还包括地形与土壤等数据; 环境及物种数据的来源多样, 国际及本土数据库均得到使用。模拟涉及有明确清单的562个植物种, 既有木本植物(52.7%), 也有草本植物(41.8%), 其中中草药、果树、园林植物、农作物等占比较高。研究目的主要集中在过去、现在和未来气候变化对植物种分布的影响及预测, 以及物种分布评估与生物多样性评价(包括入侵植物风险评估)两大方面。预测物种潜在分布范围与气候变化影响等基础研究, 与模拟物种适生区与推广种植等应用研究并重, 物种分布模型在生态学与农业、林业和中草药业等多学科、多行业开展多种应用, 多物种、多模型和多来源数据共同参与模拟与比较, 开发新的机理性物种分布模型, 拓展新的物种分布模拟应用领域, 是今后研究的重点发展方向。