Collaborative Research: BoCP-Implementation: forecasting functional biodiversity change with satellite remote sensing and modeling

合作研究：BoCP-实施：利用卫星遥感和建模预测功能性生物多样性变化

• 批准号: 2326014
• 负责人: Zhe Zhu
• 金额: $ 96.18万
• 依托单位: University of Connecticut
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-10-01 至 2027-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2326014&HistoricalAwards=false
• 关键词: Collaborative; Research; BoCP; Implementation; forecasting

This project will use satellite imaging and species location records in primary forests of the Caribbean to determine which species are threatened with extinction and how their loss will affect ecosystem function across the landscape. The outcomes will help focus limited resources on protecting the most vulnerable and functionally important species in these highly vulnerable areas. Biodiversity is essential for the processes that support life, including food security, medicines and public health. However, with a changing climate, forests are disappearing around the world, leading to a major loss of species. This research will improve on current methods of assessing extinction risk by increasing precision and automation of methods, and by extending the application to all regional species. The project will also map the location of primary forest habitats, which are regions of original forest not previously disturbed that hold the most biodiversity with the greatest number of ecological functions. An additional outcome of the project will be to identify the most critical areas for better protection of biodiversity. Greater knowledge of functional biodiversity will increase understanding of how ecosystems work and how they will change in coming decades through human modifications of habitat and climate, and through other threats to species. Knowing how, when, and where biodiversity changes will occur will help society prepare for the future and mitigate the losses. This project brings together expertise from satellite remote sensing, distribution modeling, organismal biology, and conservation biology to integratively address biodiversity loss through the development of innovative analytical methods. The project will focus on primary forest, which has more functional diversity than secondary forests, because it includes more structure and ecological specialists. The high-resolution land cover data sets with primary forest included that will be produced are currently rarely available. The system, which updates as new satellite imagery, climatic, and biodiversity data become available, is ideally suited for large areas of biodiversity, where remote sensing and environmental data are the primary sources of information for extinction risk. This project focuses on animals and plants in the Caribbean region to test hypotheses of functional diversity change across landscapes and through time.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.

该项目将使用加勒比海原始森林中的卫星成像和物种位置记录来确定哪些物种受到灭绝的威胁，以及它们的损失将如何影响整个景观的生态系统功能。结果将有助于将有限的资源集中在这些高度脆弱的地区保护最脆弱和功能上最重要的物种上。生物多样性对于支持生活的过程至关重要，包括粮食安全，药品和公共卫生。但是，随着气候变化，森林在世界各地消失，导致物种的重大损失。这项研究将通过提高方法的精度和自动化以及将应用扩展到所有区域物种来评估当前评估灭绝风险的方法。该项目还将绘制主要森林栖息地的位置，这些森林栖息地的位置是原始森林的地区，以前没有打扰最多生物多样性，其生态功能数量最多。该项目的另一个结果将是确定最关键的领域，以更好地保护生物多样性。对功能性生物多样性的了解将增加对生态系统如何工作的理解，以及通过人类对栖息地和气候的修改以及其他对物种的威胁，它们在未来几十年中将如何改变。了解生物多样性发生变化将如何，何时和何处发生变化将有助于社会为未来做准备并减轻损失。该项目汇集了卫星遥感，分布建模，生物生物学和保护生物学的专业知识，以通过开发创新的分析方法来整合生物多样性损失。该项目将集中于比二级森林具有更多功能多样性的原发性森林，因为它包括更多的结构和生态专家。目前很少可用，其中包括将生产的主要森林的高分辨率土地覆盖数据集。该系统更新为新的卫星图像，气候和生物多样性数据可用，非常适合大型生物多样性，在这种生物多样性中，遥感和环境数据是灭绝风险的主要信息来源。该项目侧重于加勒比地区的动物和植物，以测试跨景观和时间上功能多样性变化的假设。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛影响的评估来评估值得支持的。