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，包括清洁水、木材、空气净化、气候调节、土壤保持、食物和住所。然而，在目前全球环境变化的情况下，森林和这些服务正在受到危害。景观退化、污染、病虫害的传入以及气候变化都是全球变化因素，使森林面临前所未有的压力。为了使社会保护这些生态系统服务，科学界需要就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。森林整合了从分子到全球的跨尺度和从大气到陆地到人类的跨系统相互作用的过程。因此，影响评估和相应的解决方案需要考虑到这一复杂性。该项目将开发工具，以评估森林对全球变化压力源的脆弱性，确定科普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。（生长和存活）对于估计森林生态系统的生产力、评估可持续的开采率、评价森林的其他价值、预测生态系统对气候变化和干扰的响应。然而，对树木的人口统计学研究通常只持续几年，远远低于树木的寿命。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如何有助于整个种群表现的全面观点的发展。尽管如此，详细的生命阶段的具体动态和阶段之间的过渡是准确预测未来的森林组成，结构和功能的关键。这项研究将利用广泛的树木人口统计数据和模型进行综合工作，目的是生成一个建模框架，以评估长寿物种的完整种群动态，作为不同全球变化因素的函数。这项工作的成果将被用于制定树种种群轨迹的方案，这些方案还包括人类对森林变化的行为反应的信息，通过管理，这可能会塑造未来的森林。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估来支持。

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.