I/UCRC FRP: Collaborative Research: Understanding and Modeling Competition Effects on Tree Growth and Stand Development Across Varying Forest Types and Management Intensities

I/UCRC FRP：合作研究：理解和模拟竞争对不同森林类型和管理强度的树木生长和林分发育的影响

• 批准号: 1534751
• 负责人: Eric Turnblom
• 金额: $ 6.65万
• 依托单位: University of Washington
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-08-01 至 2018-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1534751&HistoricalAwards=false
• 关键词: UCRC; FRP; Collaborative; Research; Understanding

Competition in plant communities is a fundamental ecological process that has been studied through experimentation and by modeling. Given the long time periods over which tree populations interact and the increasing availability of extensive data bases with long-term measurements of tree growth and mortality, this project aims to use advanced modeling methodology to develop enhanced quantitative expressions of competition. Improved models of competition in forest populations are required to further advance our predictive ability for management options in a range of forest types. Understanding competition dynamics is paramount for evaluating management activities such as deploying genetic material, prescribing site preparation treatments and planting density, predicting response to varying levels of inter-and intra-specific competition resulting from vegetation control and thinning, and ameliorating nutrient deficiencies through fertilizer applications. Increased understanding of competition processes and formulation of improved models for quantifying competition effects will enhance evaluation of a wide array of forest management options. These results will have far-reaching implications, not only for forest management decision-making but also for forest conservation and restoration, and for understanding and modeling environmental influences, including climate change, on forests. Additional broader impacts include an enriched educational experience for graduate students and postdoctoral fellows due to the involvement of industry scientists as well as university faculty in the conduct of this research. The overall goal of this research project is to use contemporary modeling and statistical techniques and computing technology to exploit information in forestry field studies in an effort to develop improved quantitative measures of tree- and stand-level competition. Modeling is a powerful tool for integrating and synthesizing existing theory and empirical evidence, identifying knowledge gaps, and suggesting relevant hypotheses regarding underlying plant competition that might be tested through experimentation. Relating resource availability and competition intensity to growth and survival is central to understanding and projecting forest stand dynamics. A key challenge is determining effects of species, genetic variation, microsite heterogeneity, and local neighborhood effects on tree-size variation through time. These effects are confounded, highly interactive, and especially difficult to separate for stands of trees, which interact over long time periods. Furthermore, tree-to-tree competition cannot be measured directly, but rather is inferred based on measurements of overall stand density, relative tree size, and/or point density measures that include sizes of and distances to neighbors. Advanced statistical analyses and modeling techniques will be applied to data bases to deal with the complexity of forest ecosystem dynamics over extended time periods. Gaps in knowledge will be identified and experimental approaches for testing relevant hypotheses regarding competition process will be advanced.

植物群落的竞争是通过实验和建模研究的基本生态过程。鉴于长期以来，树木人群相互作用的长期时间以及对树木生长和死亡率的长期测量的可用性增加，该项目旨在使用先进的建模方法来开发增强的竞争定量表达。 需要改进的森林种群竞争模型，以进一步提高我们在各种森林类型中的管理选择的预测能力。了解竞争动态对于评估管理活动（例如部署遗传物质，开处方现场准备治疗和种植密度），预测对植被控制和稀疏导致不同水平的特异性竞争的反应以及通过肥料施用来改善营养缺乏。对竞争过程和改进的模型的制定量增加，以量化竞争效果，将增强对各种森林管理选项的评估。这些结果将具有深远的影响，不仅对森林管理决策，而且对森林保护和恢复以及对森林的理解和建模环境影响，包括气候变化。由于行业科学家的参与以及大学教职员工的参与，还包括为研究生提供丰富的教育经验和更多的教育经验。该研究项目的总体目标是使用当代建模和统计技术和计算技术来利用林业现场研究中的信息，以努力提高树木和独立级竞争的定量量度。 建模是整合和综合现有理论和经验证据，识别知识差距的强大工具，并提出了有关潜在植物竞争的相关假设，这些假设可能通过实验测试。将资源可用性和竞争强度与增长和生存有关，对于理解和预测森林立场动态至关重要。一个关键的挑战是确定物种，遗传变异，微石异质性以及局部邻居对树大小变化的影响。这些影响是混淆，高度交互式的，并且在长期相互作用的树木架上尤其难以分离。此外，无法直接测量树对树的竞争，而是根据对整个支架密度，相对树大小和/或点密度度量的测量值来推断的，包括对邻居的大小和距离。高级统计分析和建模技术将应用于数据库，以应对延长的时间段的森林生态系统动力学的复杂性。将确定知识的差距，并将提出测试有关竞争过程相关假设的实验方法。