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Modelling climate change impacts on marine fish populations: process-based integration of ocean warming, acidification and other environmental drivers

机译:模拟气候变化对海洋鱼类种群的影响:基于过程的海洋变暖,酸化和其他环境驱动因素的整合

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Global climate change affects marine fish through drivers such as ocean warming, acidification and oxygen depletion, causing changes in marine ecosystems and socioeconomic impacts. While experimental and observational results can inform about anticipated effects of different drivers, linking between these results and ecosystem-level changes requires quantitative integration of physiological and ecological processes into models to advance research and inform management. We give an overview of important physiological and ecological processes affected by environmental drivers. We then provide a review of available modelling approaches for marine fish, analysing their capacities for process-based integration of environmental drivers. Building on this, we propose approaches to advance important research questions. Examples of integration of environmental drivers exist for each model class. Recent extensions of modelling frameworks increase the potential for including detailed mechanisms and improving model projections. Experimental results on energy allocation, behaviour and physiological limitations will advance the understanding of organism-level trade-offs and thresholds in response to multiple drivers. More explicit representation of life cycles and biological traits can improve description of population dynamics and adaptation, and data on food web topology and feeding interactions help to detail the conditions for possible regime shifts. Identification of relevant processes will also benefit the coupling of different models to investigate spatial-temporal changes in stock productivity and integrated responses of social-ecological systems. Thus, a more process-informed foundation for models will promote the integration of experimental and observational results and increase the potential for model-based extrapolations into a future under changing environmental conditions.
机译:全球气候变化通过海洋变暖,酸化和氧气耗竭等因素影响海洋鱼类,造成海洋生态系统变化和社会经济影响。虽然实验和观察结果可以告知不同驱动因素的预期影响,但要将这些结果与生态系统水平的变化联系起来,就需要将生理和生态过程定量整合到模型中,以推进研究并为管理提供信息。我们概述了受环境驱动因素影响的重要生理和生态过程。然后,我们对可用的海洋鱼类建模方法进行了回顾,分析了其基于过程的环境驱动因素整合的能力。在此基础上,我们提出了一些方法来推进重要的研究问题。每个模型类都有集成环境驱动程序的示例。建模框架的最新扩展增加了包含详细机制和改进模型预测的潜力。关于能量分配,行为和生理限制的实验结果将促进对生物水平权衡和阈值的理解,以应对多种驱动因素。生命周期和生物特征的更明确表示可以改善对种群动态和适应性的描述,有关食物网拓扑和进食相互作用的数据有助于详细说明可能的政权转移的条件。确定相关过程还将有利于不同模型的耦合,以调查种群生产力的时空变化和社会生态系统的综合反应。因此,对模型更了解过程的基础将促进实验和观察结果的集成,并在不断变化的环境条件下增加基于模型的外推在未来的潜力。

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