Capturing the big picture of Mediterranean marine biodiversity with an end-to-end model of climate and fishing impacts
| Type | Article | ||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Date | 2019-11 | ||||||||||||||||
| Language | English | ||||||||||||||||
| Author(s) | Moullec Fabien1, Velez Laure1, Verley Philippe2, Barrier Nicolas17, Ulses Caroline4, Carbonara Pierluigi5, Esteban Antonio6, Follesa Cristina7, Gristina Michele8, Jadaud Angelique 3, Ligas Alessandro9, Díaz Eduardo López10, Maiorano Porzia11, Peristeraki Panagiota12, 13, Spedicato Maria Teresa5, Thasitis Ioannis14, Valls Maria15, Guilhaumon François1, Shin Yunne-Jai1, 17 |
||||||||||||||||
| Affiliation(s) | 1 : Marine Biodiversity Exploitation and Conservation (MARBEC), Université de Montpellier, IRD, CNRS, Ifremer, Montpellier, France 2 : Botanique et Bioinformatique de l’Architecture des Plantes (AMAP) IRD, CIRAD, Boulevard de la Lironde, 34398 Montpellier Cedex 5, France 3 : Marine Biodiversity Exploitation and Conservation (MARBEC), Université de Montpellier, IRD, CNRS, Ifremer, Sète, France 4 : Laboratoire d’Aérologie, Université de Toulouse, CNRS, UPS, Toulouse, France 5 : COISPA Tecnologia and Ricerca, Stazione Sperimentale per lo Studio delle Risorse del Mare, Bari, Italy 6 : Instituto Español de Oceanografía (IEO), Centro Oceanográfico de Murcia, Murcia, Spain 7 : Dipartimento di Biologia Animale ed Ecologia, Universita di Cagliari, Cagliari, Italy 8 : Institute for the Coastal Marine Environment (CNR), Mazara del Vallo, Italy 9 : Consorzio per il Centro Interuniversitario di Biologia Marina ed Ecologia Applicata ‘G. Bacci’, viale N. Sauro 4, I‐57128 Livorno, Italy 10 : Instituto Español de Oceanografía (IEO), Centro Oceanográfico de Málaga, Fuengirola, Málaga, Spain 11 : Department of Biology, University of Bari, Bari, Italy 12 : Hellenic Center for Marine Research, Iraklion, Crete, Greece 13 : University of Crete, Biology Department, Stavrakia, Heraklion, Crete 14 : Department of Fisheries and Marine Research, Ministry of Agriculture, Natural Resources and Environment, Nicosia, Cyprus 15 : Instituto Español de Oceanografía (IEO), Centre Oceanográfic de les Balears s/n, 07015 Palma, Spain 16 : Marine Research (MA-RE) Institute and Department of Biological Sciences, University of Cape Town, Private Bag X3, Rondebosch 7701, South Africa 17 : Marine Biodiversity Exploitation and Conservation (MARBEC), Université de Montpellier, IRD, CNRS, Ifremer, Sète, France |
||||||||||||||||
| Source | Progress In Oceanography (0079-6611) (Elsevier BV), 2019-11 , Vol. 178 , P. 102179 (18p.) | ||||||||||||||||
| DOI | 10.1016/j.pocean.2019.102179 | ||||||||||||||||
| WOS© Times Cited | 21 | ||||||||||||||||
| Keyword(s) | Ecosystem model, Ecosystem Approach to Fisheries Management, OSMOSE model, NEMOMED model, Eco3M-S model, Global change | ||||||||||||||||
| Abstract | The Mediterranean Sea is one of the main hotspots of marine biodiversity in the world. The combined pressures of fishing activity and climate change have also made it a hotspot of global change amidst increasing concern about the worsening status of exploited marine species. To anticipate the impacts of global changes in the Mediterranean Sea, more integrated modelling approaches are needed, which can then help policymakers prioritize management actions and formulate strategies to mitigate impacts and adapt to changes. The aim of this study was to develop a holistic model of marine biodiversity in the Mediterranean Sea with an explicit representation of the spatial, multispecies dynamics of exploited resources subject to the combined influence of climate variability and fishing pressure. To this end, we used the individual-based OSMOSE model (Object-oriented Simulator of Marine ecOSystEms), including 100 marine species (fish, cephalopods and crustaceans) representing about 95% of the total declared catch, at a high spatial resolution (400 km2) and a large spatial scale (the entire Mediterranean basin) – the first time such a resolution and scale have been modelled. We then combined OSMOSE with the NEMOMED 12 physical model and the Eco3M-S biogeochemical low trophic level model to build the end-to-end model, OSMOSE-MED. We fitted OSMOSE-MED model with observed or estimated biomass and commercial catch data using a likelihood approach and an evolutionary optimization algorithm. The outputs of OSMOSE-MED were then verified against observed biomass and catch data, and compared with independent datasets (MEDITS data, diet composition and trophic levels). The model results – at different hierarchical levels, from individuals to the scale of the ecosystem – were consistent with current knowledge of the structure, functioning and dynamics of the ecosystems in the Mediterranean Sea. While the model could be further improved in future iterations, all the modelling steps – the comprehensive representation of key ecological processes and feedback, the selective parameterization of the model, and the comparison with observed data in the validation process – strengthened the predictive performance of OSMOSE-MED and thus its relevance as an impact model to explore the future of marine biodiversity under scenarios of global change. It is a promising tool to support ecosystem-based fishery management in the Mediterranean Sea. |
||||||||||||||||
| Full Text |
|