Jellyfish Ghada El Serafy

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Jellyfish Ghada El Serafy Contents lists available at ScienceDirect Ecological Modelling journal homepage: www.elsevier.com/locate/ecolmodel Modelling the effect of behavior on the distribution of the jellyfish Mauve stinger (Pelagianoctiluca) in the Balearic Sea using an individual-based model Joe El Rahia,b,1,⁎, Marc P. Weebera, Ghada El Serafya a Deltares, PO Box 177, 2600 MH Delft, The Netherlands b Department of Civil Engineering, Ghent University, Technologiepark 904, B-9052 Zwijnaarde, Belgium ARTICLE INFO ABSTRACT Keywords: Jellyfish behavior and physiology significantly influence spatial distribution and aggregations in the marine Pelagia noctiluca environment. However, current models used to study these transport patterns have a limited incorporation of Agent-based model these physiological and behavioral variables. In this paper, the life cycle and movement of the mauve stinger, Behavior Pelagia noctiluca, is simulated from fertilized egg up to the adult stage using an individual-based model (IBM). Balearic Sea Our model combines available knowledge on the mauve stinger with inputs of ocean currents and temperature Diurnal vertical migration from the CMEMS hydrodynamic model. Horizontal transport is solely governed by ocean currents, but vertical Development stage distribution is controlled by diel vertical migration, motility and stage of development. Particle agents are re- leased along the submarine canyons in the Spanish Mediterranean waters during the spring reproduction period, to later disperse and develop through an interplay between physical and biological processes. When compared with a simpler model, that omits behavior and physiology, the biophysical model is able to qualitatively better predict stranding events in the Balearic Sea. Our results expose the potential for operational life stage and distribution modelling of jellyfish. 1. Introduction noctiluca (Cnidaria: Scyphozoa, Forskal, 1775) which tend to form in the Western Mediterranean (Brotz and Pauly, 2012; Mills, 2001) and Jellyfish are a known nuisance for tourism, fisheries and water in- cause harm to the tourism and fishing industries through beach clo- takes (Graham et al., 2014; Purcell et al., 2007; Richardson et al., sures, clogged fishing nets and economic harm to aquaculture 2009). Although they are a natural feature of a healthy ecosystem, an (Aznar et al., 2017; Bosch-Belmar et al., 2017; Ghermandi et al., 2015). increasing trend in jellyfish blooms is caused by a combination of Pelagia noctiluca (hereinafter referred to as P. noctiluca), also known as warmer waters, eutrophication, over fishing and disturbance to natural the mauve-stinger, resides offshore in deep waters and is characterized habitats (Mills, 2001; Pauly et al., 2009). Better prediction of these by a holoplanktonic life cycle, diel vertical migrations and reproduction blooms and their area of impact will support the previously mentioned by direct development without a benthic stage (Ferraris et al., 2012; industries to mitigate their effect or alter their course of action. Mariottini et al., 2008). Jellyfish are gelatinous zooplankton, present in a large variety of To model biological impact on the horizontal displacement of P. marine environments where their transport is controlled by the flow noctiluca, one must consider the ontogenetic development and include direction and velocity of their surrounding environment (e.g., ocean the effects of life stages, swimming speeds and behavioral patterns and tidal currents) (Graham et al., 2001). However, the biology of (Werner et al., 2015). Starting with non-motile fertilized eggs, free jellyfish can also strongly influence their vertical displacement swimming planulae hatch to later develop into ephyrae and then adult (Fossette et al., 2015; Lilley et al., 2014), which, combined by en- medusae. Throughout these stages, swimming capabilities develop, due vironmental forces, effects their horizontal movement (Werner et al., to increased pulsations and bell size, and behavioral patterns are es- 2015). In view of this, understanding biophysical jellyfish displacement tablished, shaping a well-defined diel vertical migration pattern. While would improve knowledge on their biology, dispersion, and stranding horizontal transport is critically dependent on the physical environment locations. (currents) (Chapman et al., 2011; Qiu et al., 2010); P. noctiluca can One instance of jellyfish nuisance is the invading swarms of Pelagia actively swim in the vertical direction (diving during the day and ⁎ Corresponding author. E-mail address: [email protected] (J.E. Rahi). 1 Permanent address: Ghent University, Department of Civil Engineering, Technologiepark 60, B-9052 Ghent, Belgium. https://doi.org/10.1016/j.ecolmodel.2020.109230 Received 11 December 2019; Received in revised form 17 July 2020; Accepted 27 July 2020 J.E. Rahi, et al. Fig. 1. Study area and model boundaries. Coastlines are classified geographically according to the administrative units (NUTS2016) published by Eurostat, the statistical office of the European Union. Regions with in situ observations of stranding events are highlighted with green. surfacing at night) in a pattern that reduces predation and provides a model results we determine if the accuracy with which models can feeding advantage (Berline et al., 2013; Ferraris et al., 2012). predict stranding events is improved by incorporation of: (1) detailed Numerical modelling has been successfully applied to simulate: (i) behavioral and motility information and (2) the full life cycle. the spatial and temporal variations in distributions of jellyfish (Ferrer and Pastor, 2017; Jaspers et al., 2018; Johnson et al., 2014; J. 2. Methods and materials Moon et al., 2010),(ii) and biophysical processes such as growth, fe- fi cundity or mortality in other marine organisms like sh (e.g., integra- In this study we will develop an individual-based Lagrangian par- tion of bioenergetics in an individual-based model for anchovy, (Bueno- ticle model to predict the stranding events of the jellyfish species P. Pardo et al., 2019)). Thus, complex biophysical models have the ca- noctiluca. These models have been widely used to simulate the bio- ff fi pacity to include the e ect of jelly sh biology on distribution, a feature physical behavior of organisms (Bueno-Pardo et al., 2019; Garcia et al., ignored in previous models which strictly treated released particle 2013; Le Port et al., 2014; Santos et al., 2018). The developed bio- fi agents as jelly sh in the adult form (Berline et al., 2013; Dupont et al., physical model (available online on https://github.com/joeelrahi/ 2009; Moon et al., 2010; Wei et al., 2015) . As a result, such models pelagianoctiluca) is built over the general Python-based framework (e.g., P. noctiluca model of Berline et al. (2013)) over simplify vertical for Lagrangian particle modelling, OpenDrift (Dagestad, Röhrs, Breivik, migration by ignoring the effect of development stages, bell size, and & Ådlandsvik, 2018, github.com/opendrift). Changes in the biological motility on swimming speeds and diving limits. While using the prin- characteristics of jellyfish (e.g., development stage) will be added to our ciples of physiological ecology is the norm to incorporate this biological model through a growth function which in turn influences swimming growth, our work uses a data driven approach based on field observa- speed, buoyancy and diurnal migration. This approach is effective in tions and laboratory studies of P. noctiluca (Augustine et al., 2014; reproducing the transport of jellyfish under the influence of environ- Avian, 1986; Rosa et al., 2012; Sandrini and Avian, 1983). The Medi- mental cues (currents) and abiotic factors like temperature and lu- terranean Coastal waters of Spain, including the Balearic Islands, were minosity. selected for the biophysical modelling approach to study the mauve Our “Methods and Materials section” consists of four subsections: fi stinger, a jelly sh native to these waters (Fuentes et al., 2010; “Study area”, “Model description”, “Comparison with alternative model Rosa et al., 2012). This study area is well known for its high de- structures” and “Model validation”. Of these subsections our model pendency on tourism and coastal economic activities; two sectors im- description follows the ODD (Overview, Design concepts, Details) pacted by P. noctiluca blooms (Ghermandi et al., 2015). protocol for describing individual- and agent-based models The aim of this study is to improve jellyfish distribution and (Grimm et al., 2020, 2006). stranding modelling by including jellyfish specific behavior and de- velopment. For this we developed an individual-based Lagrangian 2.1. Study area particle model for P. noctiluca distribution based on life cycle, motility and behavior applied to the Spanish Mediterranean Coast. Based on the The Mediterranean Coastal waters of Spain, including the Balearic J.E. Rahi, et al. Islands, were selected for the biophysical modelling approach to study 2.2.3. Process overview and scheduling the mauve stinger. The predominant circulation patterns in the Spanish The biophysical model runs in discrete time steps, and in each step Mediterranean waters are a characteristic of the Western Mediterranean all entities and their corresponding state variables are updated. The basin, a semi isolated oceanic system exchanging water with the North processes included are spawning, development stage, diurnal vertical Atlantic Ocean. Marine water from the Atlantic flows through the strait migration, horizontal transport, and stranding.
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