The identification of key trophic interactions and abiotic factors that drive the dynamics of aquatic ecosystems is a first step towards understanding how those systems function and how they could respond to change such as temperature increase, exotic species invasion, fishery exploitation, eutrophication, etc. A multivariate autoregressive (MAR) modeling framework has been successfully applied to time series data from freshwater systems to reveal the network of trophic interactions within planktonic communities and to assess ecosystem stability. As part of NSF and NOAA’s CAMEO project, researchers from NCEAS and NWFSC are working to adapt the MAR framework for application to the low resolution, highly variable data typically gathered from marine systems. As a project participant, I will be compiling existing long-term ecological data sets from a variety of marine systems and using the adapted MAR model to compare trophic structure and stability between different marine environments and between marine and freshwater systems. The ultimate goal of this project is to produce new modeling tools that will help us better understand the underlying structure of a wide variety of marine ecosystems and improve our management strategies for those systems.
