OPUS: Recovery, resilience and the ecology of change

一个多样化的生态群落是由多种生物组成的，它们都对环境变化作出反应，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。由于一个物种丰度的变化通过群落中的相互作用来传播，从而影响其他物种，因此只了解生物如何直接对环境条件做出反应往往是不够的。同样的挑战也影响到保护和修复从业者对监测信息的利用。有相当多的时间和资源用于监测这些复杂的变化，可能很难辨别这些变化表明的是一个健康的自我维持的系统，还是一个正在衰落和濒临崩溃的系统。生态学之外的其他学科也处理类似的复杂过程，并开发了描述多维系统随时间变化的动力学的指标和分析框架。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。这一项目旨在通过综合突出描述复杂生态系统如何响应环境变化以及群落内物种组织如何在环境变化传播中引起不同动态的方法，从而为多物种群落的时间动态发展一个新的视角。该项目使用一系列八个长期植物群落数据集，重点研究了几个可以描述多物种群落动态稳定性的创新指标。然后，它寻求应用新的方法来描述物种互动的组织，以将动态与群落组织联系起来。该项目的最后部分试图通过与管理人员合作分析长期保护监测数据集，使这一理解更容易为决策者所用。这项研究将与管理人员和培训研究生合作，探索新的方法，以更好地理解如何监测和预测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优势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.