Tracking and forecasting ecosystem interactions in real time

TitleTracking and forecasting ecosystem interactions in real time
Publication TypeJournal Article
Year of Publication2016
AuthorsDeyle ER, May R.M, Munch SB, Sugihara G
JournalProceedings of the Royal Society B-Biological Sciences
Volume283
Date Published2016/01
Type of ArticleArticle
ISBN Number0962-8452
Accession NumberWOS:000368441200010
Keywordschanging interaction strength; chaos; climate; community; community matrix; competition; dynamics; empirical dynamics; fluctuations; food-web structure; nonlinear; populations; S-map; series data; stability; state space reconstruction
Abstract

Evidence shows that species interactions are not constant but change as the ecosystem shifts to new states. Although controlled experiments and model investigations demonstrate how nonlinear interactions can arise in principle, empirical tools to track and predict them in nature are lacking. Here we present a practical method, using available time-series data, to measure and forecast changing interactions in real systems, and identify the underlying mechanisms. The method is illustrated with model data from a marine mesocosm experiment and limnologic field data from Sparkling Lake, WI, USA. From simple to complex, these examples demonstrate the feasibility of quantifying, predicting and understanding state-dependent, nonlinear interactions as they occur in situ and in real time-a requirement for managing resources in a nonlinear, non-equilibrium world.

DOI10.1098/rspb.2015.2258
Student Publication: 
No
Research Topics: