OPUS: Recovery, resilience and the ecology of change

多样化的生态群落由多种生物体组成，它们都对环境变化做出反应并相互作用。在这个复杂的自然网络中，预测生物多样性将如何随着时间的推移而变化是具有挑战性的。由于一种物种丰度的变化通过群落中的相互作用传播以影响其他物种，因此仅了解生物体如何直接响应环境条件通常是不够的。同样的挑战影响了保护和恢复从业者对监测信息的利用。人们投入了大量的时间和资源来监测这些复杂的变化，但很难辨别这些变化是否表明是一个健康的、自我维持的系统，还是一个正在衰退并濒临崩溃的系统。生态学之外的其他学科也处理类似的复杂过程，并开发了度量和分析框架来描述多维系统随时间的动态变化。在拟议的工作中，这些指标将应用于长期生态数据集，以告知管理者如何利用监测数据集。拟议综合中的数据集还将构成研究生研讨会和交流的基础，以进行跨学科培训并将理论与应用工作联系起来。该项目旨在通过综合强调描述复杂生态系统如何响应环境变化以及群落内的物种组织如何在环境变化传播中引起不同动态的方法，从而开发关于多物种群落时间动态的新视角。该项目重点关注几个可以描述多物种群落动态稳定性的创新指标，使用一系列八个长期植物群落数据集。然后，它寻求应用描述物种相互作用组织的新方法，将动态与群落组织联系起来。该项目的最后一部分旨在通过与管理者合作分析长期保护监测数据集，使这种理解对决策者更有用。该研究将与管理人员合作并培训研究生，探索新的方法，以更好地了解如何监测和预测对环境变化的动态生态反应。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

A diverse ecological community is composed of many species of organisms, all responding to environmental change as well as interacting with each other. In this complex web of nature, predicting how biodiversity will change over time is challenging. Because changes in one species abundance propagate through interactions in the community to affect other species, it is often not sufficient to understand only how organisms respond directly to environmental conditions. This same challenge affects the utilization of monitoring information by conservation and restoration practitioners. Considerable time and resources are devoted to monitoring these complex changes, and it can be difficult to discern whether changes indicate a healthy self-sustaining system or one that is declining and on the verge of collapse. Other disciplines outside ecology also deal with analogous complex processes and have developed metrics and analytical frameworks to describe dynamics of multi-dimensional systems over time. In the proposed work, these metrics will be applied to long-term ecological datasets to inform how managers can utilize monitoring datasets. Datasets in the proposed synthesis will also form the foundation for graduate student seminars and exchanges to train across subdisciplines and connect theory to applied work.This project seeks to develop a new perspective on the temporal dynamics of multispecies communities by highlighting, through synthesis, ways to describe how complex ecological systems respond to environmental change and how species organization within a community may cause different dynamics in the propagation of environmental change. The project focuses on several innovative metrics that can describe dynamic stability of multispecies communities, using a series of eight long-term plant community datasets. It then seeks to apply new methods that describe the organization of species interactions to connect dynamics with community organization. The last part of the project seeks to make this understanding more useable to decision-makers through collaborations with managers on analyses of long-term conservation monitoring datasets. Partnering with managers and training graduate students, the research will explore new ways to arrive at a better understanding of how to monitor and anticipate dynamic ecological responses to environmental change.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.