Large-Scale Atmospheric and Oceanic Control on Krill Transport into the St. Lawrence Estuary Evidenced with Three-Dimensional Numerical Modelling

Lavoie, Diane; Chassé, Joël; Simard, Yvan; Lambert, Nicolas; Galbraith, Peter S.; Roy, Nathalie; Brickman, David

doi:10.1080/07055900.2015.1082965

Cited by 27 publications

(32 citation statements)

References 46 publications

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“…Furthermore, improved estimation of spread rates is key to developing effective responses to biological invasions in marine systems. Lawrence [20,21] for different locations in the Northumberland Strait (see…”

Section: Resultsmentioning

confidence: 99%

“…To estimate values for the dispersal parameters (v and D in k 13 ) for a given year, we used a hydrodynamic model consisting of (i) a particle-tracking, individual-based model run within (ii) an ocean circulation model based on the Nucleus for European Modeling of the Ocean (NEMO) system described in detail in Brickman and Drozdowski [20] and Lavoie et al [21].…”

Section: Parameter Estimationmentioning

confidence: 99%

“…In our work, the dispersal heterogeneity includes both variability at the level of individuals and from one year to the next. Specifically, the hydrodynamic model that we used to simulate daily flow fields for a given year and coastal location included an individual-based particle tracking model [20,21,32,33] to obtain daily settler displacements within the larval settlement period.…”

Section: Time-varying Dispersal Parameters In Population Idesmentioning

confidence: 99%

“…Note 6 that we used the term "net rate of displacement" rather than "advection", because behavior and various other processes in addition to passive advection influence how far a disperser is displaced. We then allowed dispersal (specifically, the net rate of displacement and diffusion coefficient of larvae) to vary yearly by parameterizing the dispersal kernels using a 3dimensional hydrodynamic model of the Gulf of St Lawrence [20,21]. The same hydrodynamic model was used for several other biological dispersal studies [22][23][24][25].…”

Section: Introductionmentioning

confidence: 99%

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Stochastic dispersal increases the rate of upstream spread: a case study with green crabs on the northwest Atlantic coast

Gharouni¹,

Barbeau

Chassé

et al. 2017

Preprint

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Dispersal heterogeneity is an important process that can compensate for downstream advection, enabling aquatic organisms to persist or spread upstream. Our main focus was the effect of year-to-year variation in larval dispersal on invasion spread rate. We used the green crab, Carcinus maenas, as a case study. This species was first introduced over 200 years ago to the east coast of North America, and once established has maintained a relatively consistent spread rate against the dominant current. We used a stage-structured, integro-difference equation model that couples a demographic matrix for population growth and dispersal kernels for spread of individuals within a season. The kernel describing larval dispersal, the main dispersive stage, was mechanistically modeled to include both drift and settlement rate components. It was parameterized using a 3-dimensional hydrodynamic model of the Gulf of St Lawrence, which enabled us to incorporate larval behavior, namely vertical swimming. Dispersal heterogeneity was modeled at two temporal scales: within the larval period (months) and over the adult lifespan (years). The kernel models variation within the larval period. To model the variation among years, we allowed the kernel parameters to vary by year. Results indicated that when dispersal parameters vary with time, knowledge of the time-averaged dispersal process is insufficient for determining the upstream spread rate of the population. Rather upstream spread is possible over a number of years when incorporating the yearly variation, even when there are only a few "good years" featured by some upstream dispersal among many "bad years" featured by only downstream dispersal. Accounting for annual variations in dispersal in population models is important to enhance understanding of spatial dynamics and population spread rates. Our developed model also provides a good platform to link the modeling of larval behavior and demography to largescale hydrodynamic models.PLOS ONE | https://doi.org/10.1371/journal.pone

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Section: Resultsmentioning

confidence: 99%

Section: Parameter Estimationmentioning

confidence: 99%

Section: Time-varying Dispersal Parameters In Population Idesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Stochastic dispersal increases the rate of upstream spread: a case study with green crabs on the northwest Atlantic coast

Gharouni¹,

Barbeau

Chassé

et al. 2017

Preprint

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show abstract

“…Outside the SLE, particles that search for and swim towards higher salinity move further downstream than those that have a preference for deeper water or swim in random directions. Lavoie et al (2016) investigate the main physical processes affecting krill transport from the northwest Gulf of St. Lawrence (nwGSL) towards the head of the Lower St. Lawrence Estuary (LSLE). They also use an individualbased numerical model driven by 3D simulated fields of circulation and hydrography produced by NEMO.…”

mentioning

confidence: 99%

Introduction to the Special Issue on Dynamics of the Gulf of St. Lawrence System and its Influence on the Ecosystem: Past, Present, and Future

Jiang

Lefaivre

2016

Atmosphere-Ocean

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How transport shapes copepod distributions in relation to whale feeding habitat: Demonstration of a new modelling framework

Brennan

Maps

Gentleman

et al. 2019

Progress in Oceanography

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Large-Scale Atmospheric and Oceanic Control on Krill Transport into the St. Lawrence Estuary Evidenced with Three-Dimensional Numerical Modelling

Cited by 27 publications

References 46 publications

Stochastic dispersal increases the rate of upstream spread: a case study with green crabs on the northwest Atlantic coast

Stochastic dispersal increases the rate of upstream spread: a case study with green crabs on the northwest Atlantic coast

Introduction to the Special Issue on Dynamics of the Gulf of St. Lawrence System and its Influence on the Ecosystem: Past, Present, and Future

How transport shapes copepod distributions in relation to whale feeding habitat: Demonstration of a new modelling framework

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