Quantifying and forecasting tree mortality risks and uncertainties of Canadian boreal forests under a changing climate

量化和预测气候变化下加拿大北方森林的树木死亡风险和不确定性

• 批准号: RGPIN-2019-06547
• 负责人: Peng, Changhui
• 金额: $ 4.33万
• 依托单位: Université du Québec à Montréal
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=765316
• 关键词: Quantifying; forecasting; tree; mortality; risks

Climate-induced tree mortality has emerged as a global concern that is expected to increase under the projections of future climate change. Canadian boreal forests, which occupy 77% of Canada's total forest land, play a critical role in the Earth's surface albedo and the global carbon budget. Recent studies suggested that Canadian boreal forests may be highly vulnerable to rapid increases in tree mortality due to warmer temperatures and more severe droughts and defoliation by spruce budworm. Forecasting the potential impacts of increasing tree mortality on carbon budgets requires both local and regional scale. These impacts, however, have generally been ignored in large-scale carbon cycle modeling studies because data on tree mortality over large areas are expensive to collect, and therefore not widely available. There is an urgent need to develop a better scientific understanding and to quantify and forecasting the impacts of future climate change and associated insect disturbances on boreal forest ecosystems in Canada, including ecosystem productivity, tree mortality and changes in the timing and magnitude of fluxes between the land and the atmosphere. To my knowledge, no comparable studies on changes in tree mortality rates have been conducted in boreal forests using a model-data fusion (MDF) approach which integrates observed forest plots and remote sensing data with climate data and a process-based forest model in Canada. The central objective of this 5 year research program is to develop and use state-of-the-art of TRIPLEX-mortality to 1) better understand and predict forest growth, mortality and biomass carbon; and 2) quantify and reduce risks and uncertainties by using new model-data fusion approach on the loss of forest growing stock and biomass carbon due to tree mortality in the face of climate change. Our approach will provide a powerful and tractable way of incorporating tree mortality into forest models to reduce uncertainty over the fate of Canadian boreal forest ecosystems in a changing climate. The present research program will focus on the boreal forests of eastern Canada. This work will fill in our knowledge gaps in the area of the direct effects of climate change on tree mortality, biomass, and carbon balance of Canada's boreal forests. This study will pave the way for better quantifying and forecasting drought and insect impacts and better understanding of how climate change will alter Earth's forests in the 21st century. The knowledge gained from this research will be transferred to forest managers, industry partners and policy makers. This Discovery program will contribute to the training of 15 highly qualified personnel (10 undergraduates, 2 MSc, 2 PhDs and 1 post-doctorate) in the areas of forest growth, mortality, remote sensing, climate change and biomass/carbon relationships.

气候引起的树木死亡率已成为一个全球关注，预计将在未来气候变化的预测下增加。加拿大北方森林占加拿大林地的77％，在地球表面反照率和全球碳预算中起着至关重要的作用。最近的研究表明，加拿大北方森林可能高度容易受到由于温度升高，更严重的干旱和云杉芽虫的脱叶而迅速增加的树木死亡率。预测增加树木死亡率对碳预算的潜在影响需要本地和区域规模。然而，这些影响通常在大规模的碳循环建模研究中被忽略，因为大面积的树木死亡率的数据很昂贵，因此不可广泛使用。迫切需要建立更好的科学理解，并量化和预测未来气候变化的影响以及相关的昆虫干扰对加拿大北方森林生态系统的影响，包括生态系统的生产力，树木死亡率以及土地和大气之间的通量的时机和幅度的变化。据我所知，没有使用模型数据融合（MDF）方法在北方森林中对树木死亡率变化进行的可比研究，该方法将观察到的森林图和遥感数据与气候数据和加拿大的基于过程的森林模型整合在一起。这项5年研究计划的核心目标是开发和使用三重历史的最先进，以更好地理解和预测森林的生长，死亡率和生物量碳； 2）通过使用新的模型数据融合方法来量化和降低风险和不确定性，以涉及面对气候变化的树木死亡率造成的森林生长库存和生物量碳的损失。我们的方法将提供一种强大且可探讨的方式，将树木死亡率纳入森林模型，以减少在不断变化的气候下加拿大北方森林生态系统命运的不确定性。本研究计划将重点关注加拿大东部的北方森林。这项工作将填补我们在气候变化对树木死亡率，生物量和加拿大北方森林碳平衡的直接影响领域的知识空白。这项研究将为更好地量化和预测干旱以及昆虫的影响铺平道路，并更好地理解气候变化将如何改变21世纪地球森林。从这项研究中获得的知识将转移到森林经理，行业合作伙伴和政策制定者中。该发现计划将在森林增长，死亡率，遥感，气候变化和生物量/碳关系中对15名高素质人员（10名本科生，2名MSC，2 phds和1个命令后）的培训。