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首页> 外文期刊>Journal of Geophysical Research. Biogeosciences >Ecosystem function in complex mountain terrain: Combining models and long-term observations to advance process-based understanding
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Ecosystem function in complex mountain terrain: Combining models and long-term observations to advance process-based understanding

机译：复杂山地地形中的生态系统功能：结合模型和长期观测，提前进程的理解

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Abiotic factors structure plant community composition and ecosystem function across many different spatial scales. Often, such variation is considered at regional or global scales, but here we ask whether ecosystem-scale simulations can be used to better understand landscape-level variation that might be particularly important in complex terrain, such as high-elevationmountains.We performed ecosystem-scale simulations by using the Community Land Model (CLM) version 4.5 to better understand how the increased length of growing seasons may impact carbon, water, and energy fluxes in an alpine tundra landscape. The model was forced with meteorological data and validated with observations from the Niwot Ridge Long Term Ecological Research Program site. Our results demonstrate that CLM is capable of reproducing the observed carbon, water, and energy fluxes for discrete vegetation patches across this heterogeneous ecosystem. We subsequently accelerated snowmelt and increased spring and summer air temperatures in order to simulate potential effects of climate change in this region. We found that vegetation communities that were characterized by different snow accumulation dynamics showed divergent biogeochemical responses to a longer growing season. Contrary to expectations, wet meadow ecosystems showed the strongest decreases in plant productivity under extended summer scenarios because of disruptions in hydrologic connectivity. These findings illustrate how Earth system models such as CLM can be used to generate testable hypotheses about the shifting nature of energy, water, and nutrient limitations across space and through time in heterogeneous landscapes; these hypotheses may ultimately guide further experimental work and model development. Plain Language Summary Projecting ecosystem response to environmental change presents enormous challenges that are critical to understand for multiple stakeholders. These projections are complicated by complex interactions between physical drivers, like temperature and precipitation, and biotic agents like plants, animals, and soil microbes. Using long-term observations from a heterogeneous alpine ecosystem and a state-of-the-art land model, we explore how the physical environment shapes ecosystem function and how the function of this ecosystem may respond to climate change. We found that the land model was able to capture observed water, energy, and carbon fluxes from this well-studied alpine ecosystem, lending credibility to our results. Our simulations also indicated that earlier snowmelt and warmer summertime temperatures might drive divergent plant responses across the landscape. Notably, climate change may decouple the timing of snowmelt that delivers critical water resources from periods when plants experience the greatest water demand, thus altering plant productivity. Additionally, this work raises ecological questions that can be addressed with additional experimentation and/or model development.
机译：非生物因素结构结构植物群落组成和跨越许多不同空间尺度的生态系统功能。通常，在区域或全球范围内考虑这种变化，但在这里我们询问生态系统规模模拟是否可以用于更好地了解在复杂地形中可能尤为重要的景观级别变化，例如高升高。我们执行了生态系统 - 通过使用社区土地模型（CLM）4.5版，更好地了解增长季节的增加程度可能会影响碳，水和能量通量在高山苔原景观中的增加。该模型被迫使气象数据，并验证了Niwot Ridge长期生态研究计划网站的观察结果。我们的结果表明，CLM能够在这种异质生态系统上再现用于离散植被贴剂的观察到的碳，水和能量势次。我们随后加速了雪花和春季和夏季空气温度，以模拟该地区气候变化的潜在影响。我们发现，植被社区以不同的雪积累动态表现出不同的生物地球化学反应，对更长的生长季节。与期望相反，由于水文连接性中断，湿草甸生态系统表现出在延长的夏季情景下的植物生产率下降。这些发现说明了地球系统模型如CLM如何用于产生关于空间跨空间的能量，水和养分局限性的可测试假设，以及在异构景观中的时间;这些假设可能最终引导进一步的实验工作和模型发展。简单的语言摘要将生态系统对环境变革的反应引起了对多个利益相关者来说至关重要的巨大挑战。这些投影在物理驱动器之间的复杂相互作用，如温度和沉淀，以及植物，动物和土壤微生物等生物剂。使用来自异质高山生态系统和最先进的土地模型的长期观测，我们探讨了物理环境如何塑造生态系统功能以及这种生态系统的功能如何响应气候变化。我们发现土地模型能够从这种学习的高山生态系统中捕获观察到的水，能量和碳通量，借鉴我们的结果。我们的模拟还表明，早期的雪花和较温暖的夏季气温可能会在整个景观中推动发散的植物反应。值得注意的是，气候变化可能会使雪花的时间脱钩，当植物经历最大的水需求时，从时期提供关键水资源，从而改变了植物生产力。此外，这项工作提高了可以通过额外的实验和/或模型开发来解决的生态问题。

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