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DISES: Co-produced modeling of socio-environmental dynamics of financialized forestlands and alternative future scenarios

DISES: Co-produced modeling of socio-environmental dynamics of financialized forestlands and alternative future scenarios
DISES:共同制作的金融化林地社会环境动态模型和替代未来情景
批准号:
2205705
负责人:
Jesse Abrams
金额:
$152.21万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-01-01 至 2026-12-31

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中文摘要
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英文摘要
This research addresses the past socio-environmental dynamics and future trajectories of forests in northern Maine. Timberlands in northern Maine were owned by integrated forest products companies for much of the twentieth century, but more recently their ownership has changed as a result of the emergence of new corporate timberland organizations, principally Real Estate Investment Trusts (REITs) and Timber Investment Management Organizations (TIMOs). This ownership change comes at the same time that forests are being included as carbon solutions in state-level climate policies. The researchers on this project will work directly with Maine’s policymakers, tribal and non-tribal forest users, and other key stakeholders to analyze the social and ecological consequences of the timberland ownership transition. These same stakeholders will be included in participatory workshops to assess possible trajectories of these forestlands under different climate and policy scenarios. Ecological analyses and future scenarios will be conducted using spatial science tools that have previously been applied to family forest dynamics elsewhere in New England. The result of this project will be a better understanding of the social and ecological consequences of the timberland ownership transition and the engagement of key stakeholders in assessing the future of these lands.This project is the first major effort to analyze financialized timberlands as integrated socio-environmental systems. The research focuses on financialized timberlands, defined as those owned and managed by financial investors such as the timber investment management organizations (TIMOs) and real estate investment trusts (REITs) that collectively own and manage over 20 million hectares of forestland nationwide. Research efforts integrate qualitative social science, remote sensing-based land change detection, and participatory scenario simulation modeling methods that collectively illuminate the feedback and causal relationships driving timberland system dynamics. Spatial and causal process models representing the consequences of three decades of forest financialization will be developed, then used to co-design future landscape scenarios for collaborative evaluation by key stakeholders. The research builds upon advances in land detection technologies via application of the LandTrendr tool to landscapes that have undergone ownership transitions. It also builds upon scenario modeling tools developed by Harvard Forest that have previously been applied to family-owned forested landscapes in New England and to other forest systems worldwide. The social science component includes a multi-scalar data collection process to inform construction of a causal process model that integrates ecological and sociopolitical variables. By investigating the relationships among human actors (financial firm executives, mid-level governance actors, and tribal and non-tribal forest users) and environmental patterns and processes (forest conditions, disturbances, species distributions, and carbon balances), this research will advance land system science and identify leverage points for effecting systemic change. Research efforts will focus on timberlands in Maine in order to build both place-specific and more generalizable models. The research will provide combined spatial and socioeconomic insights to inform policy and practice deliberations regarding the future ownership and management of these lands.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.
期刊论文(1)
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科研奖励(0)
会议论文
Not-so-random forests: Comparing voting and decision tree ensembles for characterizing partial harvest events
非随机森林:比较投票和决策树集合以表征部分收获事件
DOI: 10.1016/j.jag.2023.103561
发表时间: 2023
期刊: International Journal of Applied Earth Observation and Geoinformation
影响因子: 7.5
作者: [Pasquarella, Valerie J., Morreale, Luca L., Brown, Christopher F., Kilbride, John B., Thompson, Jonathan R.]
通讯作者: Thompson, Jonathan R.
国内基金
海外基金
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