EAGER: Quantifying the relative importance of reproduction in forest dynamics under historical and future climate change

EAGER：量化历史和未来气候变化下森林动态繁殖的相对重要性

• 批准号: 2135448
• 负责人: Rebecca Snell
• 金额: $ 19.41万
• 依托单位: Ohio University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2135448&HistoricalAwards=false
• 关键词: EAGER; Quantifying; relative; importance; reproduction

Environmental change will alter forest dynamics and species composition. Tree reproduction and recruitment are critical processes for tree populations and ultimately, determine the future species composition of forests. Even though tree reproduction is sensitive to climate, the relative importance of this process for forest dynamics is unclear, especially compared to anticipated climate-change effects on tree growth and mortality. Seed production and seedling survival are also determined by individual and stand level properties. For example, seedling survival is affected by light availability. Increasing mortality due to climate change will alter the amount of light hitting the forest floor, and affect seedling survival. Seed production is also affected by size (i.e., larger individuals tend to produce more seed). If tree growth responds positively to climate change, this could indirectly cause an increase in seed production. Thus, to capture all these direct and indirect effects, the project will update a dynamic vegetation model (DVM) to explicitly simulate reproduction as a function of weather and stand structure. Including tree regeneration dynamics in process-based vegetation models is a major research gap and a critical step for accurately projecting forest responses to climate change. The project broader impacts include (1) training for students in computer programming, database management, data analysis, and communicating science, and (2) outreach activities to broaden participation of women in computer science.Using forests located in the Pacific Northwest (PNW) as a case study, the project will quantify the relationships for seed production (as a function of weather and size) and seedling survival (as a function of weather and stand structure), for common tree species in the PNW. These relationships will be incorporated into a forest model, that already includes species-specific simulations of growth, competition and mortality as a function of the environment. The updated model will be used to simulate forest stands located in the PNW under historical climate and various climate change scenarios. By comparing model versions, the research will be able to quantify the relative role of reproduction on forest dynamics and species turnover and identify species vulnerable to climate change.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.

环境变化将改变森林动态和物种组成。树木繁殖和招募是树木种群的关键过程，最终确定森林的未来物种组成。尽管树木的繁殖对气候敏感，但该过程对森林动态的相对重要性尚不清楚，尤其是与预期的气候变化对树木生长和死亡率的影响相比。种子的生产和幼苗生存也由个体和林分水平的特性确定。例如，幼苗生存受光的影响。由于气候变化而导致的死亡率增加将改变撞击森林地面的光的量，并影响幼苗生存。种子生产也受大小的影响（即，较大的个体倾向于产生更多的种子）。如果树木生长对气候变化有积极反应，则可能会间接导致种子产量增加。因此，为了捕获所有这些直接和间接的效果，该项目将更新动态植被模型（DVM），以明确模拟繁殖，这是天气和支架结构的函数。在基于过程的植被模型中包括树木再生动态是一个主要的研究差距，也是准确地预测森林对气候变化的反应的关键步骤。该项目更广泛的影响包括（1）对计算机编程，数据库管理，数据分析和沟通科学的培训，以及（2）外展活动，以扩大妇女参与计算机科学的参与。使用位于太平洋西北（PNW）的森林作为一个案例研究，该项目将作为种子生产的关系（作为天气和幼虫的种类和幼虫的范围）（如天气和幼虫生存）（如天气和幼虫的生存）（如天气和幼虫所处的作用》（如天气和幼虫状态）（如天气和幼虫所处的作用）。这些关系将纳入森林模型，该模型已经包括针对环境的特定物种的生长，竞争和死亡率的模拟。更新的模型将用于模拟在历史气候和各种气候变化方案下位于PNW中的森林林。通过比较模型版本，该研究将能够量化繁殖对森林动态和物种离职的相对作用，并确定容易受到气候变化的物种。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛的影响标准通过评估来获得支持的。