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

森林景观通过改变气候、火灾制度和土地利用以及它们之间的反馈而发生变化。影响加州的史无前例的干旱为我们提供了一个及时的自然实验，以促进我们对长期干旱影响下的森林变化的了解。研究人员将利用国家生态观测网络(NEON)的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相结合，以了解森林对干旱的反应可能如何导致干旱肆虐的西部地区的景观变化。理解由全球变化驱动的区域森林动态如何因当地地形对山区地貌气候的影响而受到影响，这一点至关重要。例如，树苗可以在更凉爽、更潮湿的北向斜坡上躲避干旱条件。目前的干旱预示着在21世纪变暖下预计会出现不断扩大的干旱条件，并提供了一个极好的机会来回答有关北美西部缺水森林的生态系统弹性的关键问题。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的适应性管理，并有助于将当地维护森林生物多样性和生态系统服务的努力与区域和全球缓解计划联系起来。研究人员将检验微环境对森林动态宏观生态格局产生强烈影响的假设。具体地说，研究问题是：1)太平洋西南霓虹区内华达山脉南部丘陵和山脉的小气候(太阳辐射、地表温度和土壤水分状况)在精细的时空尺度上是如何变化的？2)当地小气候和植被覆盖之间的关系是如何通过该区域内发生的从丘陵到亚高山气候梯度的变化的？3)干旱导致的树木死亡如何影响微环境条件，以及死亡模式和树冠形成模式如何影响随后的森林动态？霓虹灯空中观测平台(AOP)获取的图像提供了一个无与伦比的数据源，支持对植被组成、状况和结构的跨尺度观测，再加上适当的地面数据，将使研究人员能够对小气候、植被、植物群落和生态系统动态之间的关系进行建模。基于成像光谱和机载激光扫描数据的融合，将使用霓虹灯机载图像数据来绘制森林组成和结构的细粒度地图。在苗木建立模型中，绘制的植被结构图将与气候一起用作预测因子。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苗木建立概率。这项拟议的研究将加深我们对如何将局部尺度生物物理变化的知识纳入大尺度生态系统动力学模型的理解。该项目解决了利用霓虹灯数据与其他数据相结合来扩展潜在变革性研究的空间和时间维度这一渴望霓虹灯的目标。

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.