Forecasting community reassembly using climate‐linked spatio‐temporal ecosystem models

Ecosystems are increasingly impacted by human activities, altering linkages among physical and biological components. Spatial community reassembly occurs when these impacts modify the spatial overlap between system components, there is need for practical tools to forecast at landscape scales using monitoring data. To illustrate a new approach, we extend generalization of empirical orthogonal function (EOF) analysis, which involves spatio-temporal ecosystem model that approximates coupled physical, dynamics. We then demonstrate its application five trophic levels eastern Bering Sea fitting multiple, spatially unbalanced datasets measuring characteristics (temperature measurements climate-linked forecasts), primary producers (spring fall size-fractionated chlorophyll-a), secondary (copepods), juveniles (age-0 walleye pollock), adult consumers (five commercially important fishes), activities (seasonal fishing effort) mobile predators (seabirds). identify niche each component, as well dominant modes variability highly correlated with known bottom–up driver measure interacting variables (using Schoener's-D) age-0 pollock have decreased copepods increased during warm years, also arrowtooth flounder catcher–processor effort years. Given warming conditions projected coming decade, forecasts prey competitor involving (between pollock, flounder) copepod forage base fishery future warming. recommend joint species distribution models be extended incorporate ‘ecological teleconnections' (correlations distant locations arising from mechanisms) behavioral adaptation animals passive advection nutrients planktonic juvenile stages.