Finding Regulation Among Seemingly Unregulated Populations: A Practical Framework for Analyzing Multivariate Population Time Series for Their Interactions

Patterns in ecological communities often are interpreted as being strongly influenced through trophic interactions, traditionally labeled as bottom-up and top-down control. Previous approaches to identify these processes often assume each population of the community is itself regulated, i.e., it follows a stationary process. However, complex community structure and a lack of regulation in individual population dynamics can result in inappropriate inferences based on traditional approaches. Here, we introduce a statistical framework to analyze potentially non-stationary time series that are collectively regulated, and demonstrate the method with catch-per-unit-effort (CPUE) time series data of selected populations in the Gulf of Mexico. In the Gulf, we found that most of the time series data, which span 26 years, were individually unregulated. Species interaction patterns were location-dependent, but where brown shrimp interacted significantly with other species, we identified significant bottom-up forcing. On the other hand, we find weak evidence of top-down forcing throughout the study areas.