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CAREER: Models and Algorithms for Strategic Conservation Planning

职业：战略保护规划的模型和算法

基本信息

批准号：
2308687
负责人：
Jorge Sefair
金额：
$ 51.11万
依托单位：
University of Florida
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2022
资助国家：
美国
起止时间：
2022-10-01 至 2026-11-30
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2308687&HistoricalAwards=false
关键词：
CAREER Models Algorithms Strategic Conservation

项目摘要

This Faculty Early Career Development Program (CAREER) award will contribute to the national health, prosperity, and welfare by improving decision-making in conservation planning through new theory, models, algorithms, and visual analytics tools for landscape and conservation ecology. Biodiversity has been declining at rapid rates during the last several decades due to habitat loss, landscape deterioration, environmental change, and human-related activities that directly and indirectly affect natural habitats. In addition to its economic and cultural value, biodiversity plays an important role in keeping an environment’s ecosystem in balance. Disrupting such processes can reduce the provision of natural resources such as food and water, which in turn yields a direct threat to human health. Protecting natural areas is fundamental to preserving biodiversity and to mitigate the effects of ongoing environmental change. This award will contribute quantitative methods to support informed decisions on conservation design and effective land use to support species sustainability. These methods integrate realistic ecological features, specific spatial properties of the selected reserves (e.g., connectivity), population dynamics within the spatial assets, and the impact of current and future threats. The educational plan will improve the skills and diversity of future generations of engineers via technical training and engagement in transdisciplinary research. The outreach activities aim to increase the students’ awareness of current biodiversity and conservation challenges.This award supports fundamental research on the design of portfolios of land or marine patches to support species sustainability. These design problems result in very large mixed-integer linear programs whose solutions require innovative formulations and new large-scale optimization methods. The new models and specialized algorithms will allow decision-makers to solve a variety of realistic large-scale corridor and reserve design problems that include patch-specific conservation decisions under spatial, operational, ecological, and biological requirements. These models will feature realistic objectives faced by practitioners, such as maximization of the protected area or the number of species covered and minimization of the conservation cost. The design models will embed stochastic processes to capture the species’ spatiotemporal movement across the landscape and to assess the effectiveness of conservation plans, including extinction risks, mortality, and ecosystem disturbances. New bi-level and stochastic optimization models and algorithms will support the design of robust conservation areas, i.e., areas that provide acceptable levels of ecological benefits even under future extreme and adverse events affecting the landscape. A visual analytics tool will integrate the developed tools, facilitating the discussion of optimal conservation plans with practitioners, advocates, and experts.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.

该教师早期职业发展计划（CAREER）奖将通过新的理论，模型，算法和景观和保护生态学的视觉分析工具来改善保护规划的决策，从而为国家健康，繁荣和福利做出贡献。在过去的几十年里，由于栖息地丧失、景观恶化、环境变化以及直接和间接影响自然栖息地的人类活动，生物多样性一直在迅速下降。除了其经济和文化价值外，生物多样性在保持环境生态系统平衡方面发挥着重要作用。破坏这一进程会减少粮食和水等自然资源的供应，进而对人类健康构成直接威胁。保护自然区域是保护生物多样性和减轻持续环境变化影响的根本。该奖项将有助于定量方法，以支持保护设计和有效的土地利用，以支持物种的可持续性明智的决定。这些方法结合了现实的生态特征，所选保护区的特定空间特性（例如，连接性）、空间资产内的人口动态以及当前和未来威胁的影响。该教育计划将通过技术培训和参与跨学科研究来提高未来几代工程师的技能和多样性。外展活动旨在提高学生对当前生物多样性和保护挑战的认识。该奖项支持陆地或海洋斑块组合设计的基础研究，以支持物种的可持续性。这些设计问题导致非常大的混合整数线性规划，其解决方案需要创新的配方和新的大规模优化方法。新的模型和专门的算法将使决策者能够解决各种现实的大规模走廊和保护区设计问题，包括空间，操作，生态和生物要求下的特定斑块保护决策。这些模式将突出从业人员所面临的现实目标，例如最大限度地扩大保护区或所覆盖的物种数量，并最大限度地减少养护成本。设计模型将嵌入随机过程，以捕捉物种在景观中的时空运动，并评估保护计划的有效性，包括灭绝风险，死亡率和生态系统干扰。新的双层和随机优化模型和算法将支持稳健保护区的设计，即，即使在未来发生影响景观的极端和不利事件的情况下，也能提供可接受水平的生态效益的地区。可视化分析工具将整合开发的工具，促进与从业者，倡导者和专家讨论最佳保护计划。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。