Thursday, March 22, 2012

Article from the group on analysis of marine plankton community structure

Scheef, L.P., D.E. Pendleton, S.E. Hampton, S.L. Katz, E.E. Holmes, M.D. Scheuerell, and D.G. Johns. 2012. Assessing marine plankton community structure from long-term monitoring data with multivariate autoregressive (MAR) models: a comparison of fixed station vs. spatiallydistributed sampling data. Limnology & Oceanography: Methods 10: 54-64.

ABSTRACT: We examined how marine plankton interaction networks, as inferred by multivariate autoregressive (MAR) analysis of time-series, differ based on data collected at a fixed sampling location (L4 station in the Western English Channel) and four similar time-series prepared by averaging Continuous Plankton Recorder (CPR) datapoints in the region surrounding the fixed station. None of the plankton community structures suggested by the MAR models generated from the CPR datasets were well correlated with the MAR model for L4, but of the four CPR models, the one most closely resembling the L4 model was that for the CPR region nearest to L4. We infer that observation error and spatial variation in plankton community dynamics influenced the model performance for the CPR datasets. A modified MAR framework in which observation error and spatial variation are explicitly incorporated could allow the analysis to better handle the diverse time-series data collected in marine environments.

Time-series analysis workshop Sat Aug 5, Portland, OR

Eli, Eric and Mark will offer their 1-day workshop on multivariate time-series analysis using the MARSS package again at the annual ESA meeting (  Workshop is scheduled for the Sat before the meeting.  We are working on new case studies involving incorporation of covariates into analyses.  MARSS 3.0 will be done by then.  This is a major update that allows all parameters to incorporate time-varying covariates.