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已成为全球关注的问题，预计在未来气候变化的预测下，这一问题将会增加。加拿大北方森林占加拿大森林总面积的77%，在地球表面反照率和全球碳收支中发挥着关键作用。最近的研究表明，由于气温升高和更严重的干旱以及云杉芽虫的落叶，加拿大北方森林可能极易受到树木死亡率迅速上升的影响。预测树木死亡增加对碳收支的潜在影响需要在地方和区域尺度上进行。然而，这些影响在大规模碳循环模拟研究中通常被忽略，因为收集大面积树木死亡率的数据成本很高，因此无法广泛获得。目前迫切需要发展更好的科学认识，量化和预测未来气候变化和相关昆虫干扰对加拿大北方森林生态系统的影响，包括生态系统生产力、树木死亡率以及陆地与大气之间通量的时间和幅度的变化。据我所知，在加拿大还没有使用模型-数据融合（MDF）方法对北方森林树木死亡率变化进行过可比的研究，该方法将观测到的森林样地和遥感数据与气候数据和基于过程的森林模型结合起来。这项为期5年的研究计划的中心目标是开发和使用最先进的triplex死亡率，以更好地了解和预测森林生长、死亡率和生物量碳；2)利用新的模型-数据融合方法量化和降低气候变化下树木死亡导致的森林蓄积量和生物量碳损失的风险和不确定性。我们的方法将提供一种强大而易于处理的方法，将树木死亡率纳入森林模型，以减少加拿大北方森林生态系统在气候变化中命运的不确定性。目前的研究计划将集中在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加拿大北方森林树木死亡率、生物量和碳平衡的直接影响方面的知识空白。这项研究将为更好地量化和预测干旱和昆虫的影响铺平道路，并更好地了解气候变化将如何改变21世纪的地球森林。从这项研究中获得的知识将转让给森林管理者、工业伙伴和决策者。该探索项目将为森林生长、死亡率、遥感、气候变化和生物量/碳关系等领域培养15名高素质人才（10名本科生、2名硕士、2名博士和1名博士后）。