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      Predictive habitat suitability models to aid conservation of elasmobranch diversity in the central Mediterranean Sea

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          Abstract

          Commercial fisheries have dramatically impacted elasmobranch populations worldwide. With high capture and bycatch rates, the abundance of many species is rapidly declining and around a quarter of the world’s sharks and rays are threatened with extinction. At a regional scale this negative trend has also been evidenced in the central Mediterranean Sea, where bottom-trawl fisheries have affected the biomass of certain rays (e.g. Raja clavata) and sharks (e.g. Mustelus spp.). Detailed knowledge of elasmobranch habitat requirements is essential for biodiversity conservation and fisheries management, but this is often hampered by a poor understanding of their spatial ecology. Habitat suitability models were used to investigate the habitat preference of nine elasmobranch species and their overall diversity (number of species) in relation to five environmental predictors (i.e. depth, sea surface temperature, surface salinity, slope and rugosity) in the central Mediterranean Sea. Results showed that depth, seafloor morphology and sea surface temperature were the main drivers for elasmobranch habitat suitability. Predictive distribution maps revealed different species-specific patterns of suitable habitat while high assemblage diversity was predicted in deeper offshore waters (400–800 m depth). This study helps to identify priority conservation areas and diversity hot-spots for rare and endangered elasmobranchs in the Mediterranean Sea.

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          Most cited references 13

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          Predicting species distributions for conservation decisions

          Species distribution models (SDMs) are increasingly proposed to support conservation decision making. However, evidence of SDMs supporting solutions for on-ground conservation problems is still scarce in the scientific literature. Here, we show that successful examples exist but are still largely hidden in the grey literature, and thus less accessible for analysis and learning. Furthermore, the decision framework within which SDMs are used is rarely made explicit. Using case studies from biological invasions, identification of critical habitats, reserve selection and translocation of endangered species, we propose that SDMs may be tailored to suit a range of decision-making contexts when used within a structured and transparent decision-making process. To construct appropriate SDMs to more effectively guide conservation actions, modellers need to better understand the decision process, and decision makers need to provide feedback to modellers regarding the actual use of SDMs to support conservation decisions. This could be facilitated by individuals or institutions playing the role of ‘translators’ between modellers and decision makers. We encourage species distribution modellers to get involved in real decision-making processes that will benefit from their technical input; this strategy has the potential to better bridge theory and practice, and contribute to improve both scientific knowledge and conservation outcomes.
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            Predicting ecological consequences of marine top predator declines.

            Recent studies document unprecedented declines in marine top predators that can initiate trophic cascades. Predicting the wider ecological consequences of these declines requires understanding how predators influence communities by inflicting mortality on prey and inducing behavioral modifications (risk effects). Both mechanisms are important in marine communities, and a sole focus on the effects of predator-inflicted mortality might severely underestimate the importance of predators. We outline direct and indirect consequences of marine predator declines and propose an integrated predictive framework that includes risk effects, which appear to be strongest for long-lived prey species and when resources are abundant. We conclude that marine predators should be managed for the maintenance of both density- and risk-driven ecological processes, and not demographic persistence alone.
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              Climate impact on plankton ecosystems in the Northeast Atlantic.

              It is now widely accepted that global warming is occurring, yet its effects on the world's largest ecosystem, the marine pelagic realm, are largely unknown. We show that sea surface warming in the Northeast Atlantic is accompanied by increasing phytoplankton abundance in cooler regions and decreasing phytoplankton abundance in warmer regions. This impact propagates up the food web (bottom-up control) through copepod herbivores to zooplankton carnivores because of tight trophic coupling. Future warming is therefore likely to alter the spatial distribution of primary and secondary pelagic production, affecting ecosystem services and placing additional stress on already-depleted fish and mammal populations.
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                Author and article information

                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group
                2045-2322
                14 August 2015
                2015
                : 5
                Affiliations
                [1 ]Institute for Coastal Marine Environment (IAMC), National Research Council (CNR) , Via L. Vaccara n 61, Mazara del Vallo (TP), 91026, Italy
                [2 ]Marine Institute, Plymouth University , Level 3, Marine Building, Drake Circus, Plymouth, PL4 8AA.
                Author notes
                Article
                srep13245
                10.1038/srep13245
                4536484
                26272502
                dce5e59c-a464-40f0-8bef-6d041c9b5e11
                Copyright © 2015, Macmillan Publishers Limited

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

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