Collaborative Research: Will changes in vegetation composition slow climate-driven wildfire growth in the boreal forests of northwestern North America?

北极和寒带森林、苔原和寒冷的底层土壤共同储存了世界陆地碳的30%，是目前大气中储存量的两倍。 随着气候变暖，北极和北方野火变得更加频繁和激烈，燃烧更大的地区。 这些火灾向大气中释放了较老的碳，这样做可能会影响全球气候，改变森林生态系统，并可能减缓气候驱动的火灾活动增加。该项目正在探索这些系统级的火灾和植被之间的反馈，也称为火灾自我调节，使用生态系统生态学，遥感，地质统计学和模拟建模技术。该团队正在开发新的模型，以更准确地预测生态系统，景观和区域变化。该团队正在与阿拉斯加火灾科学联盟合作，开发新的地图，以增强区域土地使用和火灾管理的工具，并为土地管理人员提供新的培训机会。该项目还促进生态科学家的跨学科培训和专业发展，并支持早期职业科学家和学生的职业发展，包括代表性不足的群体成员。该项目解决两个主要问题：（1）火自我调节的生态过程的现有证据是什么，它能减缓气候变暖对火活动的影响吗？(2)考虑火的自我调节如何影响对未来生态系统和景观结构、功能和气候强迫的预测？多线的证据正在开发，以测试假设火的自我调节，在北方森林的内部阿拉斯加，美国和加拿大西北地区，寒冷地区的不连续的永久冻土地面上，最近经历了前所未有的火灾活动。该小组正在结合实地和遥感数据，以量化燃烧的十年模式，并估计火灾自我调节过程的方向和规模。研究人员正在将统计推断与基于过程的模拟建模相结合，以预测当前和未来的生态动态和反馈。该奖项反映了NSF的法定使命，并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，被认为值得支持。

Arctic and boreal forests, tundra, and cold underlying soils together store 30% of the world’s terrestrial carbon, an amount twice that currently stored in the atmosphere. As the climate warms, Arctic and boreal wildfires are becoming more frequent and intense, burning larger areas. These fires release older carbon to the atmosphere, and by doing so could affect global climate, change the forest ecosystems, and possibly slow climate-driven increases in fire activity. This project is exploring these system-level feedbacks between fire and vegetation, also called fire self-regulation, using techniques from ecosystem ecology, remote sensing, geostatistics, and simulation modeling. The team is producing new models that will enable more accurate forecasts of ecosystem, landscape, and regional change. The team is partnering with the Alaska Fire Science Consortium to develop new maps that enhance tools available for regional land-use and fire management and provide new training opportunities to land managers. The project also promotes interdisciplinary training and professional development for ecological scientists and supports career development of early career scientists and students, including members of underrepresented groups.This project is addressing two primary questions: (1) What is the current evidence for the ecological process of fire self-regulation, and can it slow the effects of climate warming on fire activity? (2) How does consideration of fire self-regulation affect projections of future ecosystem and landscape structure, function, and climate forcing? Multiple lines of evidence are being developed to test hypotheses about fire self-regulation in boreal forests of Interior Alaska, USA, and Northwest Territories, Canada, cold regions on discontinuous permafrost ground that have recently experienced unprecedented fire activity. The team is combining field and remote sensing data to quantify decadal patterns of burning and estimate the direction and magnitude of fire self-regulation processes. Researchers are integrating statistical inference with simulation modeling that is process-based and landscape-scale to predict current and future ecological dynamics and feedbacks. The results are informing improved tools for wildland and fire managers across Alaska, assisting with efforts to mitigate wildfire effects on residents and critical infrastructure.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.