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机构地区:[1]中国科学院植物研究所植被与环境变化国家重点实验室
出 处:《自然杂志》2010年第5期272-278,279,280,共9页Chinese Journal of Nature
基 金:国家自然科学基金重点项目(30590382)
摘 要:生物多样性与生态系统功能对全球变化的响应与适应是极其复杂的,为了更深入了解和认知,需要融合多学科技术、应用协同方法对其进行研究:其中长期定位观测有助于认识有长时间滞后效应的生态过程或具有重要生态功能的缓慢过程;全球变化实验在自然环境条件下可定量区分各环境因子及其相互作用对生态系统动态的影响;梯度研究可以完善不同时空尺度分析之间的耦合;过程研究则是对野外调查、长期观测或控制实验进行有益补充;这四种研究方法可以镶嵌使用,互补互惠,共同为模型结构的建立和完善提供理论认知,并为模型运行提供参数估算和独立验证数据。模型一方面通过集成各种调查、观测、实验等信息,可以提供强大的模拟分析与预测能力;另一方面它又可以反馈信息来指导各种观测、实验和研究的设计与数据收集,是全球变化研究中必不可少的集成分析工具。Changes in multiple global environmental factors potentially trigger complex influences on biodiversity, ecosystem structure and function with feedbacks to climate change. To unravel the complexities, we need to adopt a coordinated multifaceted approach① Long-term monitoring provides invaluable insights and background information on ecosystem lags response or chronic resource alterations to global change. ②Global change experiments are powerful tools that allow for the eluci- dation of cause-and-effect relationships and provide for a mechanistic understanding of the responses of ecosystems to multiple, interacting el- ements of global change. ③Gradient study can improve the coupling be- tween different spatial and temporal scales of analysis. ④Process studies can complement experimental, monitoring and survey to elucidate mech- anisms underlying long-term ecosystem response to global change. The first four research methods are complementary and reciprocal. If they work together, they could give a better service for the model simula- tion. ⑤Assimilated data from long-term experiments and process studies together with information from long-term observations, surveys, and space-for-time studies along environmental and biological gradients, model on the one hand can provide a powerful modeling and forecasting capabilities, to understand long-term ecosystem dynamics in response to global change. On the other hand it can help design experimental, monitoring and survey for future implementation.
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