Data to replicate: Forecasting community reassembly using climate-linked spatio-temporal ecosystem models ...

• Main Authors: Thorson, James, Arimitsu, Mayumi, Barnett, Lewis, Cheng, Wei, Eisner, Lisa, Haynie, Alan, Hermann, Albert, Holsman, Kirstin, Kimmel, David, Lomas, Mike, Richar, Jon, Siddon, Elizabeth
• Format: Dataset
• Language: English
• Published: Dryad 2021
• Subjects: spatial community reassembly; joint dynamic species distribution model; empirical orthogonal function analysis; vector autoregressive spatio-temporal model; Ecology; FOS: Biological sciences; Bering Sea; Copepods
• Online Access: https://dx.doi.org/10.5061/dryad.b2rbnzsdc; https://datadryad.org/dataset/doi:10.5061/dryad.b2rbnzsdc

Ecosystems are increasingly impacted by human activities, altering linkages among physical and biological components. Spatial community reassembly occurs when these human impacts modify the spatial overlap between system components, and there is need for practical tools to forecast spatial community reassembly at landscape scales using monitoring data. To illustrate a new approach, we extend a generalization of empirical orthogonal function (EOF) analysis, which involves a spatio-temporal ecosystem model that approximates coupled physical, biological, and human dynamics. We then demonstrate its application to five trophic levels for the eastern Bering Sea by fitting to multiple, spatially unbalanced datasets measuring physical characteristics (temperature measurements and climate-linked forecasts), primary producers (spring and fall size-fractionated chlorophyll-a), secondary producers (copepods), juveniles (age-0 walleye pollock), adult consumers (five commercially important fishes), human activities ... : All data were collected by previous governmental programs, and were described in the main text and appendices. ...