Spatial Distribution and Drivers of Forest Restoration Reversals and Successes

该奖项是作为NSF社会、行为和经济学博士后研究奖学金(SPRF)计划的一部分提供的。SPRF计划的目标是为学术界、工业界或私营部门和政府的科学职业生涯培养有前途的、早期职业博士水平的科学家。SPRF奖项包括在知名科学家的赞助下进行两年的培训，并鼓励博士后研究员进行独立研究。国家科学基金会致力于促进科学界所有阶层的科学家参与其研究方案和活动，包括那些来自代表性不足的群体的科学家；博士后阶段被认为是实现这一目标的专业发展的一个重要水平。每个博士后研究员都必须解决推动各自学科领域向前发展的重要科学问题。在加州大学伯克利分校Meg Mills-Novoa博士的赞助下，这项博士后奖学金奖支持一名早期职业科学家调查森林恢复的空间分布和驱动因素。森林恢复是捕捉碳和抵消导致全球环境变化的排放的最有效的战略之一。尽管许多森林恢复项目充满希望和机遇，但它们迄今未能实现其所宣称的目标，特别是在长期目标方面。该项目决定了短期恢复与长期恢复的驱动因素。通过对森林恢复目标的监测提供反馈，这项研究将提供建议，以提高森林恢复努力的持久性，并对美国和全球的森林环境解决方案产生影响。这项研究着眼于恢复逆转--后来被砍伐的恢复森林(5-10年内)--和恢复成功--恢复了长期(至少10年)仍有森林的森林，审查了当地森林恢复努力的长期结果。通过进行生物和财产尺度的地理空间分析，确定了森林恢复逆转和成功的空间热点。利用森林变化的空间、政治和社会环境文献，该项目评估了生物群、社区和财产范围内恢复逆转和成功的驱动因素。这个项目在三个关键方面促进了学术知识的发展。首先，关于森林恢复的大量文献仍然侧重于在哪里或为什么进行森林恢复，而较少关注这类倡议的长期结果。这一研究项目将产生关于恢复工作逆转和成功的驱动因素的迫切需要的知识。其次，通过整合多个尺度的数据，该项目分析了在社会环境系统中，森林恢复的驱动因素如何在地方和区域尺度上有所不同。在理解森林恢复的地理空间时，特别忽视了财产尺度分析，而在理解恢复的逆转和成功时，忽视了当地的动态。第三，该项目将结合地理空间科学、政治生态学和综合社会环境系统理论，将定量和定性方法结合起来。地理空间分析将使确定森林恢复热点成为重点，以便收集定性数据。通过更好地理解森林恢复的基本过程(即社会政治和经济驱动因素)，将丰富对地理空间分析模式的解释。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This award was provided as part of NSF's Social, Behavioral and Economic Sciences Postdoctoral Research Fellowships (SPRF) program. The goal of the SPRF program is to prepare promising, early career doctoral-level scientists for scientific careers in academia, industry or private sector, and government. SPRF awards involve two years of training under the sponsorship of established scientists and encourage Postdoctoral Fellows to perform independent research. NSF seeks to promote the participation of scientists from all segments of the scientific community, including those from underrepresented groups, in its research programs and activities; the postdoctoral period is considered to be an important level of professional development in attaining this goal. Each Postdoctoral Fellow must address important scientific questions that advance their respective disciplinary fields. Under the sponsorship of Dr. Meg Mills-Novoa, at University of California Berkeley, this postdoctoral fellowship award supports an early career scientist to investigate spatial distribution and drivers of forest restoration. Forest restoration is one of the most effective strategies to capture carbon and counteract the emissions causing global environmental change. Despite their great promise and opportunity, many forest restoration projects to date have failed to achieve their stated objectives, particularly for the long term. This project determines the drivers of short-term versus long-term restoration. By providing feedback on the monitoring of forest restoration goals, this research will provide recommendations to improve the longevity of forest restoration efforts, with implications for forest-based environmental solutions in the US and across the globe. Focusing on restoration reversals—restored forests that were later deforested (within 5-10 years)—and restoration successes—restored forests that remained forested for the long term (a minimum of 10 years), this research examines the long-term outcomes of forest restoration efforts at the local scale. By conducting biome- and property-scale geospatial analyses, this research determines the spatial hotspots of forest restoration reversals and successes. Drawing upon spatial, political, and socio-environmental literature of forest change, this project evaluates the drivers of restoration reversals and successes across the biome, community, and property scales. This project advances scholarly knowledge in three key ways. First, the substantial literature on forest restoration has remained focused on where or why forest restoration occurs with less attention to the long-term outcomes of such initiatives. This research project will generate much needed knowledge on the drivers of restoration reversals and successes. Second, by integrating data across multiple scales, this project analyzes how the drivers of forest restoration vary across local to regional scales in a socio-environmental system. The property-scale analysis has been particularly neglected in the geospatial understanding of forest restoration and local dynamics have been neglected in understanding restoration reversals and successes. Third, this project will integrate quantitative and qualitative approaches by combining geospatial science, political ecology, and integrated socio-environmental systems theory. A geospatial analysis will enable the identification of forest restoration hotspots to focus on for qualitative data collection. The interpretation of the patterns of geospatial analysis will be enriched by a better understanding of the underlying processes (i.e., socio-political and economic drivers) of forest restoration.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.