Spatial patterns in the ovigerous Callinectes sapidus spawning migration: results from a coupled behavioral-physical model

Carr, Sarah D.; Hench, James L.; Luettich, Richard A.; Forward, Richard B.; Tankersley, Richard A.

doi:10.3354/meps294213

Cited by 19 publications

(11 citation statements)

References 31 publications

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“…(). The particle tracking model has been applied successfully in numerous studies within our study area (McNinch and Luettich, ; Carr et al ., ; Reyns et al ., , ; Haase et al ., ). The model implemented a fourth‐order Runge–Kutta scheme to determine the trajectory of particle movement due to current velocities.…”

Section: Methodsmentioning

confidence: 99%

“…To simulate barotropic circulation patterns in Pamlico Sound, we used ADCIRC (Advanced CIRCulation) 3D, a nonlinear, finite-element hydrodynamic model developed by Luettich et al (1992) and validated in Pamlico Sound and adjacent estuarine and coastal waters of North Carolina (Luettich et al, 2002;Hench and Luettich, 2003;Carr et al, 2005;Reyns et al, 2006;Haase et al, 2012). ADCIRC solves the shallow water form of the momentum equations over the entire CAPES domain represented by an unstructured grid developed by Reyns et al (2006) consisting of 22 425 nodes and 41 330 elements (resolution = 0.3-1 km).…”

Section: Hydrodynamic Modelmentioning

confidence: 99%

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Larval dispersal and population connectivity among a network of marine reserves

Puckett

Eggleston

Kerr

et al. 2014

Fisheries Oceanography

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A major challenge in marine ecology is describing patterns of larval dispersal and population connectivity, as well as their underlying processes. We used a biophysical model to simulate dispersal of eastern oyster, Crassostrea virginica, larvae and connectivity among a network of 10 no‐take reserves in a shallow, wind‐driven estuary to assess the relative importance of spawning location, spawning date, larval behavior, larval mortality, and adult reproductive output to predicted dispersal and connectivity patterns. The location (i.e., natal reserve) and date of spawning relative to physical processes, particularly frequency of wind reversals, were the dominant drivers of dispersal and connectivity patterns. To a lesser extent, larval behavior (i.e., 3D vertical advection and ontogenetic depth regulation) and mortality modified dispersal and connectivity, whereas spatiotemporal variability in adult reproductive output was of minimal importance. Over a 21‐day larval duration, mean dispersal distance of passive surface particles ranged from 5 to 40 km. Reserves were too small (1 km2) relative to mean dispersal distances to promote extensive local retention (median 2%) and spaced too far apart (typically ~50 km) to promote extensive inter‐reserve connectivity (median 2%). Limited connectivity and local retention may preclude the network from being self‐sustainable, thereby limiting its long‐term conservation and management benefits. In reserve systems characterized by limited connectivity, management efforts should focus on increasing connectivity by increasing the number or size of reserves to realize the benefits of improved adult demographics within reserves.

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Section: Methodsmentioning

confidence: 99%

Section: Hydrodynamic Modelmentioning

confidence: 99%

Larval dispersal and population connectivity among a network of marine reserves

Puckett

Eggleston

Kerr

et al. 2014

Fisheries Oceanography

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“…This time period corresponds well to field observations of maximum spawning activity in the Delaware Bay population of blue crabs (Dittel and Epifanio, 1982;. We released larvae during each tidal cycle because of uncertainties concerning the fine-scale temporal pattern of hatching in the field (Provenzano et al, 1983;Tankersley et al, 1998;Carr et al, 2005;Tilburg et al, in press).…”

Section: Biological Sampling Methodsmentioning

confidence: 41%

High concentrations of blue crab (Callinectes sapidus) larvae along the offshore edge of a coastal current: effects of convergent circulation

Tilburg

Dittel

Epifanio

2009

Fisheries Oceanography

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Using a combination of observations and numerical modeling, we examined the distribution of blue crab (Callinectes sapidus) larvae along the edge of the buoyant plume emanating from the mouth of Delaware Bay along the east coast of the USA. Our observations consisted of larval sampling and hydrographic measurements taken along a series of transects that spanned the plume, the plume edge, and the coastal ocean. The numerical model is a realistic circulation model of Delaware Bay and the adjoining coastal ocean that includes daily wind forcing, daily river discharge, and tides. We tested the hypothesis that the offshore edges of coastal currents are regions of convergence and retention for larvae of estuary dependent species. Collected data showed a marked difference between the distribution of early and late stage larvae. Patches of early stage larvae occurred within lower salinities typical of the estuarine plume and higher salinities associated with the offshore edge of the plume. Late-stage larvae occurred almost entirely in salinities characteristic of the offshore edge. The field study was followed by a modeling component that simulated larval distributions over the spawning season of 2005. Output from the model showed simulated larval distributions that were similar to the observations. This study provides new insight into the distribution of larvae and larval patches in Delaware Bay and any region with extensive buoyancy and tidally driven flow. Results indicate that larvae tend to congregate along the edges of plumes emanating from estuaries due solely to physical mechanisms, regardless of the initial spawning location.

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“…OBGC models are used primarily to estimate the air-sea fluxes of gases like CO 2 , N 2 O or CH 4 , and biological processes like primary production on time scales from one to millions of years (e.g. Maier-Reimer 1993; Suntharalingam and Sarmiento 2000;Carr et al 2005). OBGC models are based on the conservation of elements in the ocean (e.g.…”

Section: Approaches To Model Uncertainty Iv: Examples From Related DImentioning

confidence: 99%

Model uncertainty in the ecosystem approach to fisheries

et al. 2007

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Fisheries scientists habitually consider uncertainty in parameter values, but often neglect uncertainty about model structure. The importance of this latter source of uncertainty is likely to increase with the greater emphasis on ecosystem models in the move to an ecosystem approach to fisheries (EAF). It is therefore necessary to increase awareness about pragmatic approaches with which fisheries modellers and managers can account for model uncertainty and so we review current ways of dealing with model uncertainty in fisheries and other disciplines. These all involve considering a set of alternative models representing different structural assumptions, but differ in how those models are used. The models can be used to identify bounds on possible outcomes, find management actions that will perform adequately irrespective of the true model, find management actions that best achieve one or more objectives given weights assigned to each model, or formalise hypotheses for evaluation through experimentation. Data availability is likely to limit the use of approaches that involve weighting alternative models in an ecosystem setting, and the cost of experimentation is likely to limit its use. Practical implementation of the EAF should therefore be based on management approaches that acknowledge the uncertainty inherent in model predictions and are robust to it. Model results must be presented in a way that represents the risks and trade-offs associated with alternative actions and the degree of uncertainty in predictions. This presentation should not disguise the fact that, in many cases, estimates of model uncertainty may be based on subjective criteria. The problem of model uncertainty is far from unique to fisheries, 3 and coordination among fisheries modellers and modellers from other communities will therefore be useful.Keywords Bayesian methods, Ecosystem Approach to Fisheries, ecosystem models, fisheries management, model uncertainty, operational management procedures. Abstract

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Spatial patterns in the ovigerous Callinectes sapidus spawning migration: results from a coupled behavioral-physical model

Cited by 19 publications

References 31 publications

Larval dispersal and population connectivity among a network of marine reserves

Larval dispersal and population connectivity among a network of marine reserves

High concentrations of blue crab (Callinectes sapidus) larvae along the offshore edge of a coastal current: effects of convergent circulation

Model uncertainty in the ecosystem approach to fisheries

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