OPUS: Enhancing capabilities through synthesis for forecasting tree species population trajectories under changing environments

森林为人类和野生动物提供了无数的生态系统服务，包括清洁的水、木材、空气净化、气候调节、土壤保持、食物和住所。然而，在当前的全球环境变化下，森林和这些服务正在受到威胁。景观退化、污染、虫害和疾病的引入以及气候变化都是将森林推向前所未有的压力水平的全球变化因素。为了让社会保护这些生态系统服务，科学界需要对全球变化对森林的潜在影响提供可靠和有针对性的预测。然而，这些预测的生成受到复杂性的阻碍。森林整合了跨尺度、从分子到全球、跨系统、从大气到陆地再到人类的相互作用过程。因此，影响评估和相应的解决方案需要考虑到这种复杂性。该项目将开发工具，以评估森林对全球变化压力的脆弱性，确定应对未来环境变化所需的森林复原力水平，并考虑通过有针对性的森林管理做法进行适应。树种人口统计数据(生长和存活)对于估计森林生态系统的生产力、评估可持续采摘率、评估森林的其他价值以及预测生态系统对气候变化和干扰的反应至关重要。然而，对树木的人口统计学研究通常只持续几年，远远短于树木的寿命。这限制了对每个生命阶段如何受到环境变化的影响以及这些变化可能如何影响整个种群表现的全面视角的发展。尽管如此，详细的生命阶段特定的动态和阶段之间的过渡对于准确预测未来森林的组成、结构和功能至关重要。这项研究将利用广泛的树木人口统计数据和模型来开展综合工作，目的是生成一个建模框架，允许评估作为各种全球变化因素的函数的长寿物种的全部种群动态。这项工作的成果将被用来开发树种种群轨迹的场景，其中还包括人类通过管理对森林变化的行为反应的信息，这可能会塑造未来的森林。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Forests provide humans and wildlife with a myriad of ecosystem services, including clean water, timber, air purification, climate regulation, soil retention, food, and shelter. However, forests and these services are being jeopardized under current global environmental change. Landscape degradation, pollution, introduction of pests and diseases, and climate change are all global change factors driving forests to unprecedented levels of stress. For society to protect these ecosystem services, the scientific community needs to provide reliable and targeted predictions of potential effects of global change on forests. However, generation of these forecasts is hampered by complexity. Forests integrate processes interacting across scales, from molecular to global, and across systems, from atmospheric to terrestrial to human. Consequentially, impact assessments and corresponding solutions need to account for this complexity. This project will develop tools to assess forest vulnerability to global change stressors, determine levels of forest resilience necessary to cope with future environmental changes, and consider adaptation through targeted forest management practices.Tree species demographic data (growth and survival) are essential to estimate productivity of forest ecosystems, to assess sustainable extraction rates, to evaluate other values of the forest, and to forecast ecosystem responses to climate change and disturbance. However, demographic studies of trees typically last for just a few years, substantially less than tree lifespan. This limits development of a comprehensive perspective of how each life stage is affected by environmental change, and how these changes might contribute to whole population performance. Nonetheless, detailed life-stage specific dynamics and transitions between stages are critical for accurate forecasting of future forest composition, structure, and function. This research will leverage extensive tree demographic data and models to carry out synthesis work with the purpose of generating a modeling framework that allows assessment of the full population dynamics of long-lived species as a function of varying global change factors. Outputs from this work will be used to develop scenarios of tree species population trajectories that also incorporate information on human behavioral responses to forest change, through management, that could shape forests into the future.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.