COLLABORATIVE RESEARCH: EAGER-NEON: How do Microscale Biophysical Processes Mediate Ecosystem Shifts during Climate Change-driven Drought?

森林景观因气候变化、火灾状况和土地使用以及它们之间的反馈而改变。影响加州的前所未有的干旱提供了一个及时的自然实验，以提高我们对长期干旱影响下森林变化的认识。研究人员将利用国家生态观测网络（氖）数据与他们的小气候测量，树种建立的实验数据和生态系统模型协同作用，以了解森林对干旱的反应如何可能导致干旱西部的景观变化。关键是要了解受全球变化驱动的区域森林动态如何受到当地地形对山区气候的影响的调节。例如，树苗可能会在凉爽、潮湿的朝北山坡上找到干旱条件的避难所。目前的干旱预示着在21世纪世纪变暖的情况下，预计干旱状况将扩大，并提供了一个极好的机会来回答有关北美西部水资源有限的森林生态系统恢复力的关键问题。预测能力对于预测和规划全球变化对包括流域保护在内的森林生态系统服务的影响至关重要。这项研究的结果将支持土地管理者和政策制定者对森林进行适应性管理，并有助于将地方努力维持森林生物多样性和生态系统服务与区域和全球减缓计划联系起来。具体而言，研究问题是：1）如何小气候（太阳辐射，表面温度和土壤水分状况）变化在精细的空间和时间尺度横跨南部山脉内华达州山麓丘陵和山脉的太平洋西南氖域？2)如何当地的小气候和植被冠层覆盖之间的关系发生在这个地区的山麓丘陵到亚高山气候梯度的变化？3)干旱引起的树木死亡率如何影响微环境条件，以及死亡率和冠层间隙形成的模式如何影响随后的森林动态？由氖机载观测平台（AOP）获得的图像提供了一个无与伦比的数据源，以支持对植被组成、条件和结构的跨尺度观测，再加上适当的地面数据，将使研究人员能够模拟小气候、植被、植物群落和生态系统动态之间的联系。将利用氖机载图像数据，根据成像光谱学和机载激光扫描数据的融合，绘制森林组成和结构的精细地图。绘制的植被结构将作为一个预测，沿着气候，在幼苗建立模型。绘制的森林组成图将为景观干扰和演替的森林群落模拟模型设定初始条件，模拟中将使用全球变化情景下的幼苗建立概率。拟议中的研究将加深我们的理解，当地规模的生物物理变化的知识可以纳入大规模生态系统动态模型。该项目解决了EAGER-氖的目标，即利用氖数据与其他数据相结合，以扩展潜在变革性研究的空间和时间维度。

Forested landscapes are transformed by changing climate, fire regimes and land use as well as feedbacks among them. The unprecedented drought affecting California provides a timely natural experiment for advancing our knowledge of forest change under the effects of prolonged drought. The investigators will leverage National Ecological Observatory Network (NEON) data in synergy with their microclimate measurements, experimental data on tree species establishment, and ecosystem models to understand how forest response to drought may lead to landscape change in the drought-stricken West. It is critical to understand how regional forest dynamics, driven by global change, are moderated by the effects of local topography on climate in mountainous landscapes. For example, tree seedlings may find refuge from drought conditions on cooler, moister north-facing slopes. The current drought foreshadows the expanding drought conditions anticipated under 21st century warming and offers an excellent opportunity to answer key questions about ecosystem resilience in water-limited forests of western North America. Predictive capability is critical for anticipating and planning for global change effects on forest ecosystem services that include watershed protection. Results form this research will support adaptive management of forests by land managers and policy makers and help bridge local efforts to maintain forest biodiversity and ecosystem services to regional and global mitigation plans.The investigators will test the hypothesis that microenvironments exert a strong influence on macroecological patterns of forest dynamics. Specifically, the research questions are: 1) How do microclimates (solar insolation, surface temperature, and soil moisture regime) vary at fine spatial and temporal scales across the southern Sierra Nevada foothills and mountains of the Pacific Southwest NEON Domain? 2) How does the relationship between local microclimate and vegetation canopy cover change across the foothills to subalpine climate gradient that occur within this region? 3) How does drought-induced tree mortality affect microenvironmental conditions, and how do patterns of mortality and canopy gap formation affect subsequent forest dynamics? Imagery acquired by the NEON Airborne Observation Platform (AOP) offers an unparalleled data source to support cross-scale observation of vegetation composition, condition, and structure that, coupled with appropriate ground data, will allow the investigators to model the connections between microclimate, vegetation, plant communities and ecosystem dynamics. NEON airborne image data will be used to develop a fine-grained map of forest composition and structure based on fusion of imaging spectroscopy and airborne laser scanning data. Mapped vegetation structure will be used as a predictor, along with climate, in seedling establishment models. Mapped forest composition will set the initial conditions for a forest community simulation model of landscape disturbance and succession, and seedling establishment probabilities under global change scenarios will be used in the simulations. The proposed research will deepen our understanding of how knowledge of local scale biophysical variation can be incorporated into models of large-scale ecosystem dynamics. This project addresses the EAGER-NEON objective of leveraging NEON data in combination with other data to extend the spatial and temporal dimensions of potentially transformative research.