Estimating the spawning locations of the deep-sea red and blue shrimp Aristeus antennatus (Crustacea: Decapoda) in the northwestern Mediterranean Sea with a backtracking larval transport model
Introduction
Dispersal is a fundamental characteristic of many marine populations and often occurs during the pelagic larval phase, resulting in translocations of 10s to 100s of kilometers (Cowen et al., 2006; Pineda et al., 2007). In pelagic waters, larvae can be advected by currents and establish connections between physically distant populations, ensuring the renewal of abundances and the genetic heterogeneity needed for the stock stability (Bendsten and Hansen, 2013). There are several knowledge gaps related to the impact of pelagic larval phases on the species life cycles and thus, on deep-sea ecosystem where shrimps can serve as an important trophic group (Cartes et al., 2008). Such gaps can be split into biological factors and physical conditions that can both affect the population dynamics. Hence, knowledge of larval dispersal and connectivity can help elucidate the factors and conditions that promote successful settlement, identify habitats that are important to protect and restore, and understand mechanisms of population structuring (Cowen and Sponaugle, 2009). In addition, linking larval distributions to spawning sites can provide information to support management plans (Bauer et al., 2014) and improve understanding of the stock dynamics (Everett et al., 2017).
Tools for studying larval dispersal and connectivity have improved because of increasing computational power and development of three-dimensional circulation models and Lagrangian model frameworks, all of which are important for simulating larval transport. Larval transport models can predict trajectories either backward or forward in time through advective regimes, mesoscale circulation patterns, and turbulence in marine systems (Christensen et al., 2007; Holliday et al., 2012; Landeira et al., 2017). Additionally, early-stage transport is influenced by biological factors including active vertical displacement and pelagic duration, which can cause differences in larval transport and increase uncertainty around the spawning or settlement locations (Siegel et al., 2008; Robins et al., 2013). Lack of information about larval biology is challenging for connectivity research (Paris et al., 2009), especially when spatial information on larvae is scarce and the spawning habitat of adults is difficult to assess.
In the northwestern (NW) Mediterranean Sea, the deep-sea red-and-blue shrimp Aristeus antennatus (Crustacea: Decapoda) is a valuable species for the economies of Spanish harbors, particularly for the ports of Palamós and Blanes (Gorelli et al., 2014). To maintain the renewal of the stock and label the fishery as sustainable, the fleet of Palamós harbor is regulated by management plans that create restricted areas over which the fishing activity of shrimp is controlled (Boletín Oficial del Estado, 2013; 2018).
Spawning sites of A. antennatus overlap with these restricted areas and within fishing grounds of other harbors’ fleet (Sardà et al., 2003b). The A. antennatus population occupies the continental slope in waters 400 m to more than 2,000 m deep (Sardà et al., 2003a) and is abundant near large submarine canyons. Females are assumed to release eggs near the bottom, which then hatch and develop into nauplial, protozoeal, and finally into mysis stages in pelagic waters, similar to the life cycle of the taxonomically close genus of Penaeid shrimps. Based on the knowledge from the Penaeid larvae and model estimations (Clavel-Henry et al., 2020a), A. antennatus egg incubation time would last a maximum of two days. Then, after hatching, the shrimp larvae would need a period of 18 to 38 days in the pelagic zone to complete metamorphose of the different stages. Because of this time in open-ocean waters, A. antennatus larvae may establish connections between different subpopulations (Carbonell et al., 2010). Until recently, little was known about the actual distribution of A. antennatus larvae, with only a few individuals found in the plankton, all of them near the surface (Heldt, 1955; Carbonell et al., 2010). In 2016, the CONECTA project (Spanish reference: CTM-2014-54648-C2-1-R) sponsored a cruise which used multiple gears and sampled multiple water layers from the border between Spain and France to the Eivissa Channel. More than 6,500 larvae of A. antennatus (99% in protozoeal stages) were caught near the surface (Carretón et al., 2019), providing new and significant insight into larval distributions.
Although previous studies have estimated larval transport of A. antennatus from known spawning sites and have shown the importance of hydrodynamic variability and larval behavior on their transport (Palmas et al., 2017; Clavel-Henry et al., 2019, 2020a), the latest information on the distribution of A. antennatus larvae (Carretón et al., 2019) has not yet been incorporated into model simulations. Larval transport model predictions along with observations from larval sampling could be used to identify spawning locations and spatial patterns of connectivity between shrimp subpopulations. Estimated outcomes of larvae transported over different fishing grounds could help inform management decisions about the size and locations of marine reserves and/or controlled fishing areas if needed in the future.
In the present study, the overarching goal was to estimate the spawning locations of A. antennatus larvae found near the surface during the CONECTA survey in the NW Mediterranean Sea in July and August 2016. A three-dimensional coupled hydrodynamic and larval transport model was used to address the following objectives: 1) to estimate potential spawning locations for protozoeal larvae captured at each station, 2) to assess sources of uncertainty in model estimates through sensitivity studies, and 3) to estimate larval connectivity between fishing areas. These analyses were intended to integrate the latest knowledge of A. antennatus life history and the hydrodynamics of the NW Mediterranean Sea, and provide information to support fishery management strategies of A. antennatus.
Section snippets
Methods
To address the objectives, hydrodynamic and Lagrangian larval transport models were coupled and used to predict the backward-in-time transport of larvae collected during the CONECTA cruise in July and August 2016. First, initial base case model runs were conducted to predict backward trajectories. Next, a sensitivity analysis was undertaken to evaluate turbulence model parameterizations and estimate the uncertainty in model predictions. Finally, the base case simulations were used to estimate
Base case model
In the base case model runs, backward trajectories of particles showed the most notable differences between runs with minimum and maximum PDs (Table 2). For example, when the PD setting was changed from minimum to maximum, median computed PD increased from 3.9 days to 10.3 days, transport distance increased from 10.9 km to 37.6 km, and the spread of particles increased from a median of 5.0 km2 to 26.0 km2, respectively.
The use of a minimum and maximum PD in the base case model runs resulted in
Discussion
For the first time, spawning sites of the deep-sea shrimp A. antennatus in the northwestern Mediterranean Sea were estimated with a backtracking larval transport model. Model results suggested that most larvae collected during the CONECTA cruise came from spawning sites that were located between 10 and 40 km from the sampling stations. Model sensitivity studies indicated that both horizontal and vertical turbulence parameterizations (U+HV) were necessary to adequately simulate sub-scale grid
Conclusions
In summary, numerical backtracking of larvae was used to provide the first estimates of the spawning sites of A. antennatus larvae collected in surface waters of the northwestern Mediterranean Sea. Model results indicated that larvae collected at a single sampling site could have come from one to two spawning locations, and that many of the simulated larvae could have come from spawning sites within ~40 km. Having knowledge of larval origins is useful for determining connectivity between
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgements
We thank University of Maryland Center for Environmental Science Horn Point Laboratory (HPL) and the researchers and staff working there for hosting MC-H and providing support to this research. We are thankful to the Ministerio de Economia, Industria y Competividad from Spain government for supporting the travel of MC-H to HPL. We are grateful to the CONECTA survey members (crew of Garcia del Cid and the technicians, researchers, and students from CSIC) and ICM laboratory workers who sampled
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