Spatiotemporal Modeling of Nursery Habitat Using Bayesian Inference: Environmental Drivers of Juvenile Blue Crab Abundance
A. Challen Hyman, Grace S. Chiu, Mary C. Fabrizio, Romuald N., Lipcius

TL;DR
This study uses Bayesian models on 21 years of data to identify key nursery habitats for juvenile blue crabs in Chesapeake Bay, emphasizing the importance of salt marshes over seagrass beds at large scales.
Contribution
The paper introduces a Bayesian spatiotemporal modeling approach to assess nursery habitat value across large areas and timeframes, highlighting the significance of salt marshes for blue crab juveniles.
Findings
Out-of-sample predictions favor a fully nonseparable spatiotemporal model.
Salt marsh surface area and turbidity positively correlate with juvenile abundance.
Seagrass area was not associated with juvenile blue crab abundance.
Abstract
Nursery grounds are favorable for growth and survival of juvenile fish and crustaceans through abundant food resources and refugia, and enhance secondary production of populations. While small-scale studies remain important tools to assess nursery value of habitats, targeted applications that unify survey data over large spatiotemporal scales are vital to generalize inference of nursery function, identify highly productive regions, and inform management strategies. Using 21 years of GIS and spatiotemporally indexed field survey data on potential nursery habitats, we constructed five Bayesian models with varying spatiotemporal dependence structures to infer nursery habitat value for juveniles of the blue crab C. sapidus within three tributaries in lower Chesapeake Bay. Out-of-sample predictions of juvenile counts from a fully nonseparable spatiotemporal model outperformed predictions…
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Taxonomy
TopicsMarine and fisheries research · Coral and Marine Ecosystems Studies · Marine Biology and Ecology Research
