Spatial Dynamics in an Estuarine System: Modeling Biophysical Components and Interactions to Advance Blue Crab Fishery Management

Abstract

Estuaries are dynamic ecosystems with abiotic environments that exhibit extreme space-time variability. Cyclic variation is somewhat predictable, but hurricanes and large-scale atmospheric disturbances can rapidly and drastically alter anticipated conditions. These disturbances can induce rapid biological responses across large spatial scales and frequently shift distribution patterns of mobile species. Physical conditions recover relatively quickly from climactically driven perturbations, and most physically-induced animal migrations are also temporary and reversible. Nevertheless, in the case of a commercially valuable fish species, even short-term alterations can change their vulnerability (i.e., catchability) to fishery-independent surveys, which provide valuable data used in population assessment.

We examined the effects of salinity and other physical forcing mechanisms on the spatial distribution of ecologically and economically important blue crabs (Callinectes sapidus) in Pamlico Sound, NC. Pamlico Sound is the second largest estuary in the U.S. and is prone to hurricane activity. The blue crab fishery, North Carolina‘s most important, is managed using indices of spawning stock biomass (SSB) and catch-per-unit effort generated from a fishery-independent trawl survey that does not sample shallow (< 2 m deep) regions. If environmental conditions affect the proportion of the population located within the survey region at a given time, then these indices are susceptible to bias resulting from variations in crab catchability. When the majority of the population is distributed in the Pamlico Sound survey area, a relatively high catchability would inflate estimates of relative population size. Likewise, when the population is less aggregated in mainstem Pamlico Sound and distributed further up in shallow water tributaries, relative population size would be underestimated by a relatively low catchability. Our objectives, to investigate the potential existence of aggregations and their environmental causes and to develop ways to account for environmental variability to obtain unbiased estimates of relative population abundance, were accomplished in two parts using three different statistical models.

First, we modeled salinity observations collected in Pamlico Sound over the past 20 years as a function of recent and long-term freshwater influx from four rivers, distance to nearby inlets, and hurricane incidence. Maps of salinity predictions generated by this model illustrated changes in spatial salinity patterns during 40 survey time periods that encompassed a variety of climatic conditions.

Salinity predictions were used to characterize the relationship between salinity and the presence and spatial distribution of blue crab SSB to predict historic distribution patterns. Observed survey SSB was modeled as function of space-time variable environmental factors that likely affect crab catchability in order to estimate time period-specific SSB means that were adjusted for these environmental effects. The time series of estimated means comprise an environmentally-adjusted SSB index that is more suitable for tracking relative population size over time than the index currently used to manage the fishery. This adjustment validated conclusions drawn from previous analyses and field observations that blue crab SSB has decreased over the past 20 years, most notably since 1999.

A second model, including factors that did not change over time but likely affected crab spatial distribution, allowed us to predict SSB at a given space-time location.

Predictions revealed consistent SSB spatial distribution patterns over successive monthly time periods and under variable environmental conditions. This information could help managers station no-take marine reserves to better conserve the blue crab spawning stock. In addition to yielding results that will better inform blue crab fishery managers, this research significantly increases the knowledge base regarding the effects of abiotic forcing events on mobile estuarine species. Furthermore, these methods provide a rigorous and robust analytical template to create future adjustment indices to manage mobile species that change their spatial distribution in response to environmental variables.