Disequilibrium and Transient Dynamics: Disentangling Responses to Climate Change versus Broader Anthropogenic Impacts on Eastern Forests

美国森林面临着前所未有的一系列威胁。科学家通常孤立地研究这些威胁，但很明显，下个世纪树种分布和丰度的变化将取决于广泛的人类影响的累积影响。这项拟议的研究将把现有的、有充分记录和测试的森林动态模型与美国林业局森林调查和分析计划维护的大陆规模森林调查数据联系起来。新的框架将扩展该模型，以评估人类对美国东部森林的一系列影响，包括(1)气候变化，(2)伐木制度的变化，(3)引入的害虫和病原体，以及(4)增加氮(N)沉积和二氧化碳浓度。初步结果表明，在未来50-100年，仅气候变化对美国东部树种分布和丰度的直接影响将相对较小，部分原因是气候对成年树木存活的直接影响相对较小。然而，增加成年树木自然死亡率的过程，如采伐或害虫或病原体的传播，预计将通过打开林冠并允许建立新物种，与气候变化的影响相互作用。这项研究解决了资源管理者和政策制定者对透明的、数据驱动的模型的明显需求，这些模型可以用来理解和预测森林对广泛的人类影响的反应。例如，新的模型将能够预测拟议提高森林采伐率以生产能源生物质对后续森林生产力的影响，以及这种影响如何与其他人为影响相结合，如意外引入害虫和病原体。该项目还将为学生和管理专业人员提供使用和应用这一可持续利用国家森林的新工具的培训和讲习班。

U.S. forests face an unprecedented array of threats. Scientists have typically studied these threats in isolation, but it is clear that changes in the distribution and abundance of tree species over the next century will depend on the cumulative impacts of a wide range of human impacts. The proposed research will link an existing, well documented and tested model of forest dynamics to the continental-scale forest inventory data maintained by the U.S. Forest Service Forest Inventory and Analysis Program. The new framework will expand the model to assess the effects of a broad suite of human impacts on eastern U.S. forests, including (1) climate change, (2) changes in logging regimes, (3) introduced pests and pathogens, and (4) increasing nitrogen (N) deposition and CO2 concentrations. Preliminary results suggest that the direct effects of climate change alone on the distribution and abundance of tree species in the eastern U.S .will be relatively small over the next 50-100 years, in part because direct climate impacts on adult tree survival are relatively small. However, processes that increase the natural mortality rates of adult trees, such as harvesting or the spread of pests or pathogens, are expected to interact with the effects of climate change by opening the forest canopy and allowing the establishment of new species. This research addresses a clear need of resource managers and policy makers for transparent, data-driven models that can be used to understand and predict forest response to a broad range of human impacts. For instance, the new model will be able to project the effects of proposed increases in forest harvest rates for production of energy biomass on subsequent forest productivity, and how the effects could change in combination with other human-caused impacts such as the accidental introduction of pests and pathogens. The project will also provide training and workshops for students and management professionals in the use and application of this new tool for sustainable use of the nation's forests.