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Collaborative Research EAGER-NEON: Probabilistic Forecasting of Biodiversity Response to Intensifying Drought by Combining NEON, National Climate, Species, and Trait Data Bases

Collaborative Research EAGER-NEON: Probabilistic Forecasting of Biodiversity Response to Intensifying Drought by Combining NEON, National Climate, Species, and Trait Data Bases
合作研究 EAGER-NEON:结合 NEON、国家气候、物种和性状数据库,对生物多样性对加剧干旱的反应进行概率预测
批准号:
1550907
负责人:
Roland Kays
金额:
$3.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2015
资助国家:
美国
项目状态:
已结题
起止时间:
2015-09-01 至 2018-08-31

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中文摘要
翻译
干旱是对生物多样性的全国性威胁,也是推动国家生态观测站网络(NEON)发展的挑战之一。 干旱已经影响到从微生物到脊椎动物和高等植物的生物体。 长期后果是不可预测的,因为每个物种都会对其他物种做出反应,就像它们也会对干旱做出反应一样。 例如,如果一个对干旱不敏感的物种以它为食的植物或捕食它的捕食者对干旱做出反应,那么它仍然会做出反应。 生态学家可以通过开发工具来整合许多物种对气候和彼此做出反应的信息,从而更好地预测干旱影响。 利用 NEON 监测的关键分类群的数据,研究人员将使用一种新方法,即物种和干旱的联合建模,来开发生物多样性分析的预测框架。使用相关的 NEON,将开发结合多个物种、功能类型和功能性状的预测模型,以确定物种对不断变化的干旱反应的共性,将数千个物种的维度减少到可以预测的群体。 在计划的建模活动中将强调物种相互作用的间接影响。 例如,只有当其他树种减少时,某个树种才会在拥挤的林分中增加。 温度的影响通常取决于降水量。这种涉及生态学和统计学的合作结果不仅会引起生态学家的兴趣,而且会引起所有全球变化科学家和政策制定者的兴趣。
英文摘要
Drought is a nationwide threat to biodiversity, one of the challenges that motivated development of the National Ecological Observatory Network (NEON). Droughts are already affecting organisms from microbes to vertebrates and higher plants. The long-term consequences are unpredictable because each species responds to other species, as they too respond to drought. For example, a species that is insensitive to drought will still respond if the plants on which it feeds or the predators that consume it respond to drought. Ecologists could better anticipate drought effects by developing tools to integrate the information from many species as they respond both to climate and each other. With data from key taxonomic groups monitored by NEON the researchers will use a new approach, joint modeling of species and drought, to develop a predictive framework for biodiversity analysis. Using relevant NEON, predictive models, which combine multiple species, functional types, and functional traits, will be developed to identify commonalities in species responses to changing drought, reducing the dimensionality of thousands of species to groups that can be predicted. Indirect effects of species interactions will be emphasized in planned modeling activities. For example, a tree species may increase in crowded stands only when others decrease. The effects of temperature usually depend on precipitation. The results of this collaboration involving ecology and statistics will be of interest not only ecologists, but for all global change scientists and policy makers.
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