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

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。干旱已经影响到微生物、脊椎动物和高等植物等生物。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，就像它们对干旱做出反应一样。例如，一个对干旱不敏感的物种，如果它赖以为生的植物或捕食它的捕食者对干旱做出反应，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的反应信息，从而更好地预测干旱的影响。利用NEON监测的关键分类群体的数据，研究人员将使用一种新的方法，即物种和干旱的联合建模，来开发一个生物多样性分析的预测框架。利用相关的NEON，结合多种物种、功能类型和功能特征的预测模型将被开发出来，以确定物种对不断变化的干旱反应的共性，将数千种物种的维度降低到可以预测的群体。物种相互作用的间接影响将在计划的建模活动中强调。例如，只有当其他树种减少时，一种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。这项涉及生态学和统计学的合作成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。

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.