Spatiotemporal Modeling of Nursery Habitat Using Bayesian Inference: Environmental Drivers of Juvenile Blue Crab Abundance

Abstract

Nursery grounds provide conditions 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 structured habitats and environmental factors, targeted applications that unify survey data over large spatial and temporal scales are vital to generalize inference of nursery function, identify highly productive regions, and inform management strategies. Using 21 years of spatio-temporally indexed survey data (i.e., water chemistry, turbidity, blue crab, and predator abundance) and GIS information on potential nursery habitats (i.e., seagrass, salt marsh, and unvegetated shallow bottom), we constructed five Bayesian hierarchical models with varying spatial and temporal dependence structures to infer variation in nursery habitat value for young juveniles (20–40 mm carapace width) of the blue crab Callinectes sapidus within three tributaries (James, York and Rappahannock Rivers) in lower Chesapeake Bay. Out-of-sample predictions of juvenile blue crab counts from a model considering fully nonseparable spatiotemporal dependence outperformed predictions from simpler models. Salt marsh surface area and turbidity were the strongest determinants of crab abundance (positive association in both cases). Highest crab abundances occurred near the turbidity maximum where relative salt marsh area was greatest. Relative seagrass area, which has been emphasized as the most valuable nursery in studies conducted at small spatial scales, was not associated with high crab abundance within the three tributaries. Hence, salt marshes should be considered a key nursery habitat for the blue crab, even where extensive seagrass beds occur. The patterns between juvenile blue crab abundance and environmental variables also indicated that identification of nurseries should be based on investigations at broad spatial and temporal scales incorporating multiple potential nursery habitats, and based on statistical analyses that address spatial and temporal statistical dependence.