sm83s1-4852

Mediterranean demersal resources and ecosystems:
25 years of MEDITS trawl surveys

M.T. Spedicato, G. Tserpes, B. Mérigot and E. Massutí (eds)

Large-scale distribution of a deep-sea megafauna community along Mediterranean trawlable grounds

Ulla Fernandez-Arcaya 1, Isabella Bitetto 2, Antonio Esteban 3, M. Teresa Farriols 1, Cristina García-Ruiz 4, Luis Gil de Sola 4, Beatriz Guijarro 1, Angélique Jadaud 5, Stefanos Kavadas 6, Giuseppe Lembo 2, Giacomo Milisenda 7,8, Irida Maina 6, Slavica Petovic 9, Letizia Sion 10, Sandrine Vaz 5, Enric Massutí 1

1 Instituto Español de Oceanografía, Centre Oceanogràfic de les Balears, Moll de Ponent s/n, 07015 Palma de Mallorca, Illes Baleares, Spain.
(UF-A) (corresponding author) E-mail: fernandez.arcaya@gmail.com. ORCID iD: https://orcid.org/0000-0002-5588-3520
(MTF) E-mail: tfarriols@gmail.com. ORCID iD: https://orcid.org/0000-0002-7704-6504
(BG) E-mail: beatriz.guijarro@ieo.es. ORCID iD: https://orcid.org/0000-0002-2083-4681
(EM) E-mail: enric.massuti@ieo.es. ORCID iD: https://orcid.org/0000-0002-9524-5873
2
COISPA Tecnologia & Ricerca, Bari, Italy.
(IB) E-mail: bitetto@coispa.it. ORCID iD: https://orcid.org/0000-0002-8497-1642
(GL) E-mail: lembo@coispa.it. ORCID iD: https://orcid.org/0000-0002-9899-6189
3 Instituto Español de Oceanografía, Centro Oceanográfico de Murcia, Varadero n 1, Apt. 2230740 San Pedro del Pinatar, Murcia, Spain.
(AE) E-mail: antonio.esteban@ieo.es. ORCID iD: https://orcid.org/0000-0002-2896-7972
4 Instituto Español de Oceanografía, Centro Oceanográfico de Malaga, Puerto pesquero s/n 29640 Fuengirola, Malaga, Spain.
(CG-R) E-mail: cristina.garcia@ieo.es. ORCID iD: https://orcid.org/0000-0003-2767-4200
(LGS) E-mail: gildesola@ieo.es. ORCID iD: https://orcid.org/0000-0003-1987-9716
5 UMR Marbec, Ifremer, IRD, Université de Montpellier, CNRS, Avenue Jean Monnet - CS 30171 - 34203 Sète Cedex, France.
(AJ) E-mail: Angelique.Jadaud@ifremer.fr. ORCID iD: https://orcid.org/0000-0001-6858-3570
(SV) E-mail: Sandrine.Vaz@ifremer.fr. ORCID iD: https://orcid.org/0000-0002-7365-8335
6 Institute of Marine Biological Resources and Inland Waters, Hellenic Centre for Marine Research (IMBRIW/HCMR), 46.7 km Athens, Greece.
(SK) E-mail: stefanos@hcmr.gr. ORCID iD: https://orcid.org/0000-0003-3473-9084
(IM) E-mail: imaina@hcmr.gr. ORCID iD: https://orcid.org/0000-0001-5244-2722
7 Institute for Coastal Marine Environment (IAMC), National Research Council (CNR), Via L. Vaccara n 61, Mazara del Vallo (TP), 91026, Italy.
8 Present address; Stazione Zoologica Anton Dohrn di Napoli, Villa Comunale, 80121 Naples, Italy.
(GM) E-mail: giacomo.milisenda@gmail.com. ORCID iD: https://orcid.org/0000-0003-1334-9749
9 University of Montenegro-Institute of Marine Biology, Dobrota bb, 85330 Kotor, Montenegro.
(SP) E-mail: kascelanslavica@gmail.com. ORCID iD: https://orcid.org/0000-0001-6080-1959
10 University of Bari Aldo Moro (UNIBA), Department of Biology, Via Orabona 4, 70125 Bari, Italy.
(LS) E-mail: letizia.sion@uniba.it. ORCID iD: https://orcid.org/0000-0002-0308-1841

Summary: The large-scale distribution pattern of megafauna communities along the Mediterranean middle slope was explored. The study was conducted between 500 and 800 m depth where deep-water fishery occurs. Although community studies carried out deeper than 500 m are partly available for some geographic areas, few large-scale comparative studies have been carried out. Within the framework of the MEDITS survey programme, we compared the megafauna community structure in ten geographical sub-areas (GSAs) along the Mediterranean coasts. Additionally, the spatial distribution of fishing was analysed using vessel monitoring by satellite information. Overall, the community showed a significant difference between sub-areas, with a decreasing eastward pattern in abundance and biomass. Longitude was the main factor explaining variation among sub-areas (by generalized additive models). However, we found a region which did not follow the general pattern. GSA 6 (northern Spain) showed significantly lower abundance and a different composition structure to the adjacent areas. The decrease in community descriptors (i.e. abundance and biomass) in this area is probably a symptom of population changes induced by intense fishery exploitation. Overall, a combination of environmental variables and human-induced impacts appears to influence the bentho-pelagic communities along the slope areas of the Mediterranean.

Keywords: distribution pattern; fishing impact; continental slope; deep sea; megafauna; red shrimp; community.

Distribución espacial a gran escala de la megafauna de aguas profundas en fondos arrastrables del Mediterráneo

Resumen: En este estudio se describe la estructura y patrones de distribución de la comunidad de megafauna que habita en el margen continental medio a lo largo del Mediterráneo. El estudio se realizó entre los 500 y 800 m, coincidiendo espacialmente con las pesquerías de profundidad. A pesar de que se conoce parcialmente la estructura de las comunidades que habitan por debajo de 500 m, existe la necesidad de estudiar estas comunidades a una escala espacial más amplia. Dentro del marco del proyecto internacional MEDITS, se comparó la estructura de las comunidades en diez sub-áreas geográficas (GSAs) a lo largo de las costas mediterráneas. Además se analizó la distribución espacial del esfuerzo pesquero utilizando la información de los datos de seguimiento de buques. En general los resultados mostraron diferencias significativas entre subáreas mostrando un patrón decreciente en los valores de biomasa hacia el este, siendo la longitud el principal factor explicativo del modelo de distribución (GAMs). Sin embargo, encontramos una subárea que no seguía el patrón general, la GSA6 (norte de España). La GSA6 mostró una biomasa y estructura de la comunidad diferente a las áreas adyacentes. La disminución de la biomasa en esta área parece ser un síntoma de los cambios poblaciones causados por la elevada intensidad de pesca en la zona. Los resultados sugieren que la distribución y estructura de las comunidades bento-pelágicas parecen estar moduladas por la combinación de las variables ambientales y los impactos producidos por la actividad humana.

Palabras clave: distribución; impacto pesca; margen continental; mar profundo; megafauna; gamba roja; comunidad.

Citation/Cómo citar este artículo: Fernandez-Arcaya U., Bitetto I., Esteban A., Farriols M.T., García-Ruiz C., Gil de Sola L., Guijarro B., Jadaud A., Kavadas S., Lembo G., Milisenda G., Maina I., Petovic S., Sion L., Vaz S., Massutí E. 2019. Large-scale distribution of a deep-sea megafauna community along Mediterranean trawlable grounds. Sci. Mar. 83S1: 175-187. https://doi.org/10.3989/scimar.04852.14A

Editor: B. Mérigot.

Received: March 14, 2018. Accepted: August 29, 2018. Published: April 9, 2019.

Copyright: © 2019 CSIC. This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) License.

Contents

Summary
Resumen
Introduction
Materials and methods
Results
Discussion
Acknowledgements
References

INTRODUCTIONTop

The continental slopes are the connecting habitat between the shelf (200 m) and the deep basins (4000 m). They play an important role in the global carbon cycle, cycling nutrient and providing valuable food and energy resources (Levin and Dayton 2009Levin L.A., Dayton P.K. 2009. Ecological theory and continental margins: where shallow meets deep. Trends Ecol. Evol. 24: 606-617.). These biological systems cannot support high levels of exploitation due to their low productivity and the presence of productive but not yet well-identified habitats (de Juan and Lleonart 2010De Juan S., Lleonart J. 2010. A conceptual framework for the protection of vulnerable habitats impacted by fishing activities in the Mediterranean high seas. Ocean Coast. Manage. 53: 717-723., Norse et al. 2012Norse E.A., Brooke S., Cheung W.W., et al. 2012. Sustainability of deep-sea fisheries. Mar. Policy 36: 307-320., Watson and Morato 2013Watson R.A., Morato T. 2013. Fishing down the deep: Accounting for within-species changes in depth of fishing. Fish. Res. 140: 63-65.). Several deep-water species have biological characteristics that make them more vulnerable to fishing exploitation: K-type life-history traits, low fecundity and aggregation behaviour in restricted topographic areas (Merrett and Haedrich 1997Merrett N.R., Haedrich R.L. 1997. Deep-sea demersal fish and fisheries. Chapman and Hall, London., Clark et al., 2016Clark M.R., Althaus F., Schlacher T.A., et al. 2016. The impacts of deep-sea fisheries on benthic communities: a review. ICES J. Mar. Sci. 73: i51-i69., Fernandez-Arcaya et al. 2016Fernandez-Arcaya U., Drazen J.C., Murua H., et al. 2016. Bathymetric gradients of fecundity and egg size in fishes: A Mediterranean case study. Deep-Sea Res. Part I 116: 106-117.). However, several major sources of impacts are threatening continental slopes around the world (i.e. fishing, marine litter, chemical contamination, species invasion, ocean acidification and climate change–related stressors) (Galil 2009Galil B. 2009. Taking stock: inventory of alien species in the Mediterranean Sea. Biol. Invasions 11: 359-372., Pham et al. 2014Pham C.K., Ramirez-Llodra E., Alt C.H., et al. 2014. Marine litter distribution and density in European seas, from the shelves to deep basins. PLoS ONE 9: e95839., Fernandez-Arcaya et al. 2017Fernandez-Arcaya U., Ramirez-Llodra E., Aguzzi J., et al. 2017. Ecological role of submarine canyons and need for canyon conservation: a review. Front. Mar. Sci. 4: 5.), including those of the Mediterranean Sea, whose physical characteristics make it particularly sensitive to these impacts (Coll et al. 2012Coll M., Piroddi C., Albouy C., et al. 2012. The Mediterranean Sea under siege: spatial overlap between marine biodiversity, cumulative threats and marine reserves. Global Ecol. Biogeogr. 21: 465-480., Ramirez-Llodra et al. 2010Ramirez-Llodra E., Brandt A., Danovaro R., et al. 2010. Deep, diverse and definitely different: unique attributes of the world’s largest ecosystem. Biogeosciences 7: 2851-2899., 2013Ramirez-Llodra E., De Mol B., Company J.B., et al. 2013. Effects of natural and anthropogenic processes in the distribution of marine litter in the deep Mediterranean Sea. Prog. Oceanogr. 118: 273-287.). The Mediterranean is a semi-enclosed area characterized by oligotrophic conditions (Margalef 1985Margalef R. (ed.). 1985. Western Mediterranean. Pergamon Press, Oxford. 363 pp.). The biological production decreases from north to south and west to east and is inversely related to the increase in temperature and salinity, being the eastern basin one of the poorest marine areas in the world (Azov 1991Azov Y. 1991. Eastern Mediterranean a marine desert? Mar. Pollut. Bull. 23: 225-232., Danovaro et al. 2010Danovaro R., Company J.B., Corinaldesi C., et al. 2010. Deep-Sea Biodiversity in the Mediterranean Sea: The Known, the Unknown, and the Unknowable. PLoS ONE 5: e11832.).

Among the human activities that are impacting the Mediterranean continental slope and its associated biological communities, bottom trawling is the most important and the cause of most concern (Guijarro et al. 2017Guijarro B., Ordines F., Massutí E. 2017. Improving the ecological efficiency of the bottom trawl fishery in the Western Mediterranean: It’s about time! Mar. Policy 83: 204-214., Piroddi et al. 2017Piroddi C., Coll M., Liquete C., et al. 2017. Historical changes of the Mediterranean Sea ecosystem: modelling the role and impact of primary productivity and fisheries changes over time. Sci. Rep. 7: 44491.). Mediterranean deep-water fisheries began in the first decades of the last century, coinciding with the development of new technologies that made fisheries in deeper waters possible (Relini and Orsi Relini 1987Relini G., Orsi Relini L. 1987. The decline of blue red shrimps stocks in the gulf of Genoa. Invest. Pesq. 51: 245-260., Spedicato et al. 1995Spedicato M. T., Greco S., Lembo G., et al. 1995. Prime valutazioni sulla struttura dello stock di Aristeus antennatus (Risso, 1816) nel Tirreno Centro Meridionale. Biol. Mar. Medit. 2: 239-244., Sardà and Demestre 1987Sardà F., Demestre M. 1987. Estudio biológico de la gamba Aristeus antennatus (Risso, 1816) en el Mar Catalán (NE de España). Inv. Pesq. 51: 213-232.). Larger vessels with more powerful winches and stronger cables were increasingly used from Mediterranean harbours (Farrugio et al. 1993Farrugio H., Oliver P., Biagi F. 1993. An overview of the history, knowledge, recent and future research trends in Mediterranean fisheries. Sci. Mar. 57: 105-119., Guijarro et al. 2011Guijarro B., Tserpes G., Moranta J., et al. 2011. Assessment of the deep water trawl fishery off the Balearic Islands (western Mediterranean): from single to multi-species approach. Hydrobiologia 670: 67-85., Quetglas et al. 2017Quetglas A., Merino G., González J., et al. 2017. Harvest strategies for an ecosystem approach to fisheries management in western Mediterranean demersal fisheries. Front. Mar. Sci. 4: 106.). Two main deep-sea bottom fisheries have extended along the Mediterranean continental slope: (i) an upper slope (~200-600 m) fishery targeting Nephrops norvegicus and Parapenaeus longirostris, and ii) a middle slope (~400-800 m) fishery targeting Aristaeomorpha foliacea and Aristeus antennatus (Sardà et al. 2004aSardà F., D’Onghia G., Politou C.Y., et al. 2004a. Deep-sea distribution, biological and ecological aspects of Aristeus antennatus (Risso, 1816) in the western and central Mediterranean Sea. Sci. Mar. 68: 117-127.).

The scientific assessment conducted on deep-sea Mediterranean shrimp fisheries is giving rise to alarm about overexploitation and major damage to the associated fauna (Gorelli et al. 2016Gorelli G., Sardà F., Company J.B. 2016. Fishing Effort Increase and Resource Status of the Deep-Sea Red Shrimp Aristeus antennatus (Risso 1816) in the Northwest Mediterranean Sea Since the 1950s. Rev Fish. Sci-Aquac. 24: 192-202., Colloca et al. 2017Colloca F., Scarcella G., Libralato S. 2017. Recent Trends and Impacts of Fisheries Exploitation on Mediterranean Stocks and Ecosystems. Front. Mar. Sci. 4: 244., Vielmini et al. 2017Vielmini I., Perry A.L., Cornax M.J. 2017. Untying the Mediterranean Gordian Knot: A Twenty First Century Challenge for Fisheries Management. Front. Mar. Sci. 4: 195.). However, the community associated with red shrimp is not well known and large spatial scale analysis is still lacking. Mediterranean Sea community studies carried out in continental margin areas deeper than 500 m are partly available for some geographic areas. Most of these studies have been conducted in the NW Mediterranean Sea, which is currently one of the most studied deep-sea regions of the word (Sardà et al. 2004bSardà F., Calafat A., Flexas M.M., et al. 2004b. An introduction to Mediterranean deep-sea biology. Sci. Mar. 68: 7-38., Massutí and Reñones 2005Massutí E., Reñones O. 2005. Demersal resource assemblages in the trawl fishing grounds off the Balearic Islands (western Mediterranean). Sci. Mar. 69: 167-181., Fernandez-Arcaya et al. 2016Fernandez-Arcaya U., Drazen J.C., Murua H., et al. 2016. Bathymetric gradients of fecundity and egg size in fishes: A Mediterranean case study. Deep-Sea Res. Part I 116: 106-117., among others). Additionally, the published data focus on specific taxonomic groups such as crustaceans (Company et al. 2004Company J.B., Maiorano P., Plaity W., et al. 2004. Deep-sea decapod crustaceans in the western and central Mediterranean Sea: preliminary aspects of species distribution, biomass and population structure. Sci. Mar. 68(Suppl. 3): 73-86., Follesa et al. 2009Follesa M.C., Porcu C., Gastoni A., et al. 2009. Community structure of bathyal decapod crustaceans off South-Eastern Sardinian deep-waters (Central-Western Mediterranean). Mar. Ecol. 30s1: 188-199.), cephalopods (Keller et al. 2016Keller S., Bartolino V., Hidalgo M., et al. 2016. Large-scale spatio-temporal patterns of Mediterranean cephalopod diversity. PLoS ONE 11: e0146469.) and fishes (D’Onghia et al. 2004D’Onghia G., Politou C.Y., Bozzano A., et al. 2004. Deep-water fish assemblages in the Mediterranean Sea. Sci. Mar. 68(Suppl. 3): 87-99., Moranta et al. 2008Moranta J., Quetglas A., Massutí E., et al. 2008. Spatio-temporal variations in deep-sea demersal communities off the Balearic Islands (western Mediterranean). J. Mar. Syst. 71: 346-366., Granger et al. 2015Granger V., Fromentin J.-M., Bez N., et al. 2015. Large-scale spatio-temporal monitoring highlights hotspots of demersal fish diversity in the Mediterranean Sea. Prog. Oceanogr. 130: 65-74.), while studies of non-crustacean invertebrate communities are still very limited (Cartes et al. 2009Cartes J., Maynou F., Fanelli E., et al. 2009. Long-term changes in the composition and diversity of deep-slope megabenthos and trophic webs off Catalonia (western Mediterranean): Are trends related to climatic oscillations? Prog. Oceanogr. 82: 32-46., Gori et al. 2013Gori A., Orejas C., Madurell T., et al. 2013. Bathymetrical distribution and size structure of cold-water coral populations in the Cap de Creus and Lacaze-Duthiers canyons (northwestern Mediterranean). Biogeosciences 10: 2049., Mecho et al. 2014Mecho A., Billett D.S., Ramírez-Llodra E., et al. 2014. First records, rediscovery and compilation of deep-sea echinoderms in the middle and lower continental slope of the Mediterranean Sea. Sci. Mar. 78: 281-302.). Thus, there is an increasing need for better understanding of the community distribution patterns as a whole, in particular in the context of an ecosystem management approach that assesses the whole community rather than evaluating single resources (Quetglas et al. 2017Quetglas A., Merino G., González J., et al. 2017. Harvest strategies for an ecosystem approach to fisheries management in western Mediterranean demersal fisheries. Front. Mar. Sci. 4: 106.). Additionally, it is essential to identify the main drivers affecting the spatial distribution of deep-sea communities in order to evaluate their distribution patterns (Navarro et al. 2016Navarro J., Cardador L., Fernández Á.M., et al. 2016. Differences in the relative roles of environment, prey availability and human activity in the spatial distribution of two marine mesopredators living in highly exploited ecosystems. J. Biogeogr. 43:440-450., Rowden et al. 2017Rowden A.A., Anderson O.F., Georgian S.E., et al. 2017. High-Resolution Habitat Suitability Models for the Conservation and Management of Vulnerable Marine Ecosystems on the Louisville Seamount Chain, South Pacific Ocean. Front. Mar. Sci. 4: 335., Allen et al. 2018Allen R.M., Metaxas A., Snelgrove P.V. 2018. Applying movement ecology to marine animals with complex life cycles. Annu. Rev. Mar. Sci. 10: 19-42.). This information is also needed in order to identify the major impacts and implement effective management plans within deep-sea habitats. Previous studies suggest that, in addition to the environmental variables, human-induced impacts also affect species composition, abundance and distribution (Worm et al. 2006Worm B., Barbier E.B., Beaumont N., et al. 2006. Impacts of Biodiversity Loss on Ocean Ecosystem Services. Science 314: 787-790., Colloca et al. 2017Colloca F., Scarcella G., Libralato S. 2017. Recent Trends and Impacts of Fisheries Exploitation on Mediterranean Stocks and Ecosystems. Front. Mar. Sci. 4: 244., Navarro et al. 2016Navarro J., Cardador L., Fernández Á.M., et al. 2016. Differences in the relative roles of environment, prey availability and human activity in the spatial distribution of two marine mesopredators living in highly exploited ecosystems. J. Biogeogr. 43:440-450.). However, these patterns are far from being well understood.

The objective of the present work is to describe and compare abundance, biomass and assemblage structure of the whole megafauna community along the Mediterranean continental slope, using independent MEDITS fishing cruise data. A second objective is to analyse the relationship between environmental variables, fishing intensity and the megabenthic community distribution in deep-water shrimp fishing grounds in order to better understand the dominant forces driving the distribution patterns of deep-sea assemblages.

MATERIALS AND METHODSTop

The study area comprised a wide area of the Mediterranean Sea, from the Alboran Sea to the western Ionian Sea (Fig. 1). The study covers ten geographical sub-areas (GSAs) with specific environmental and biological characteristics defined by the General Fisheries Commission for the Mediterranean (GFCM): the northern Alboran Sea (GSA 1), Alboran Island (GSA2), the Balearic Islands (GSA 5), northern Spain (GSA 6), the Gulf of Lions (GSA 7), eastern Corsica (GSA 8), the central-southern Tyrrhenian Sea (GSA10), the Strait of Sicily (GSA 16), the southern Adriatic Sea (GSA 18) and the western Ionian Sea (GSA 19).

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Fig. 1. – Map of the Mediterranean Sea showing the sampling stations in each GSA. The number of hauls in each GSA is shown in parenthesis. GSA 1 (48), GSA 2 (16), GSA 5 (40), GSA 6 (35), GSA 7 (17), GSA 8 (11), GSA 10 (92), GSA 16 (122), GSA 18 (60), GSA 19 (119).

The sampling of benthic megafauna was carried out with an experimental bottom trawl net (IFREMER reference GOC73), the standard sampler for study of deep-sea megafauna (Cartes et al. 2017Cartes J.E., Schirone A., Barsanti M., et al. 2017. Recent reconstruction of deep-water macrofaunal communities recorded in Continental Margin sediments in the Balearic Basin. Deep-Sea Res. Part I 125: 52-64., Foveau et al. 2017Foveau A., Vaz S., Desroy N., et al. 2017. Process-driven and biological characterisation and mapping of seabed habitats sensitive to trawling. PLoS ONE 12: e0184486.), following a standardized survey design and sampling methodology. The average haul rate for all the GSAs was proportional to the total surface area (one station per 60 km²). The details of sampling methodology can be found on Bertrand et al. 2002aBertrand J., Leonori I., Dremière P.Y., et al. 2002a. Depth trajectory and performance of a trawl used for an international bottom trawl survey in the Mediterranean. Sci. Mar. 66(Suppl. 2): 169-182., bBertrand J.A., Gil de Sola, L., Papaconstantinou C., et al. 2002b. The general specifications of the MEDITS surveys. Sci. Mar. 66: 9-17. and in the MEDITS Handbook (http://www.sibm.it/MEDITS%202011/principaledownload.htm).

Only hauls between 500 and 800 m (559) were selected, in order to analyse the preferred habitat of deep shrimp fishing grounds (Sardà et al. 2004aSardà F., D’Onghia G., Politou C.Y., et al. 2004a. Deep-sea distribution, biological and ecological aspects of Aristeus antennatus (Risso, 1816) in the western and central Mediterranean Sea. Sci. Mar. 68: 117-127.) from 2012 to 2015. The total catch from each haul was sorted, identified to the lowest taxonomical level possible, counted and weighed following the MEDITS survey protocol. Only taxonomical groups that were appropriately sampled and identified in all GSAs were included. The species were grouped by phylum, except for Actinopterygii and Mollusca, which were grouped by subgroups because of their different life history and moving capacity. As a result, nine groups were used for the analysis: Osteichthyes, Chondrichthyes, Crustacea, Cephalopoda, other Mollusca, Echinodermata, Cnidaria, Porifera and Tunicata.

Total abundance (n km–2) and biomass (g km–2) indexes of each species were standardized by swept area (in km2). Net horizontal opening and recorded distances were used to calculate the swept area. After standardization, specific data were placed in the above groups and their percentage and biomass index descriptors were box-plotted by GSAs.

One-way ANOVA tests on log10-transformed data of abundance and biomass indexes of the entire community, followed by pairwise Tukey honestly significant difference tests, were applied to test for significant (Ndifferences among GSAs. Previously, all data were tested for normality using the Shapiro-Wilk test. In this and forward analyses, the selected index was biomass because for several groups it can be complicated to enumerate the individuals caught, as is the case of colonial organisms (like corals or tunicates) or sponges (see Results section for more details).

In addition, data matrices (species biomass vs haul) were square-root transformed and similarity between all samples was calculated using the Bray-Curtis measure. A group average cluster analysis on transformed biomass indices was carried out, and a similarity profile test (SIMPROF) permutation routine (1000 restarts) was applied to test for the significance of genuine clustering. Similarities between sampled hauls were also visualized using a multidimensional scaling plot (MDS) and similarity percentage (SIMPER) analyses were run to determine species contributions to the observed communities. Analysis of similarity (ANOSIM) was used to test for differences in community composition by zones and years. Ecological analyses were performed with the PRIMER-E 6 and PERMANOVA software (Clarke and Gorley 2006Clarke K., Gorley R. 2006. PRIMER v6: User Manual/Tutorial, Plymouth.).

Generalized additive models (GAMs) were used to determine significant relationships between biomass index (response variables) and latitude and longitude of the hauls (explanatory variables) for each group and for the entire community. The models were defined as follows: (y) ~β0 + s1(x1) + s2(x2), where β0 is the intercept, s represents a polynomial smooth function, substituting the slope parameter in a linear regression, and x represents explanatory variables (Wood 2006Wood S.N. 2006. On confidence intervals for generalized additive models based on penalized regression splines. Aust. New Zeal. J. Stat. 48: 445-464.). The response variable (biomass index) was log-transformed to approximate normal distribution. The most parsimonious models were identified for the forward selection using the GCV scores (Burnham and Anderson 2003Burnham K.P., Anderson D.R. 2003. Model selection and multimodel inference: a practical information-theoretic approach. Springer Science & Business Media.). The mgcv statistical package in R statistical software (R3.3.2) (http://www.r-project.org/) was used to fit the models.

Fishing effort

The fishing effort in the area was assessed by means of the Vessel Monitoring System (VMS) . To reduce the spatial derived effect on community distribution (e.g. the longitude effect), we used the available VMS data from the Spanish Mediterranean Area (GSAs 1, 2, 5 and 6) for the two-years study period (2013 and 2014). VMS data were provided by the Spanish Ministry of Agriculture, Food and Environment and consisted of records containing data on the geographic position, date, time and instantaneous velocity for each boat, approximately every two hours. Bottom trawlers usually fish at velocities of between 2 and 3.5 knots, so only signals showing these velocities were included in the analysis so as to remove VMS signals from boats transiting to fishing grounds or ports. To estimate the fishing effort, a grid of 0.03×0.03 degrees was created around each haul to calculate the number of VMS signals associated with it.

GAM models were applied to analyse the effect of fishing effort and spatial distribution (latitude and longitude) on the community biomass (see above for more details).

RESULTSTop

A total of 432 species belonging to 9 different taxonomical groups were selected. The overall taxonomic composition showed that the most diverse groups were Osteichthyes (127 sp.) and Crustacea (91 sp.), followed by the other 6 groups (54 Echinodermata, 38 Cephalopoda, 36 Cnidaria, 26 Chondrichthyes, 36 Mollusca (non-cephalopod), 10 Tunicata and 8 Porifera). The percentages of abundance and biomass for each taxonomic group for all GSAs are shown in Figure 2. In abundance, Osteichthyes and Crustacea dominated the fauna overall, except in Alboran Sea (GSAs 1 and 2) where Chondrichthyes were the dominant taxa (33.7% and 43%, respectively, considering the biomass indexes). In terms of biomass Osteichthyes and Chondrichthyes (mostly Galeus melastomus species) dominated the community in these GSAs. The more sessile taxonomical groups (benthic species) showed a lower contribution to the overall community. They were therefore plotted separately in order to visualize their patterns of dominance (Fig. 2C, D). Echinodermata and Cnidaria dominated the benthic fauna in terms of abundance and biomass. However, abundance and biomass showed different patterns, possibly because of the high weight of some hauls conducted over mud facies of corals, such as Isidella. In fact, biomass was composed of Cnidaria in the central basin (GSA 8, 99.5%, GSA 10, 79%, GSA 16, 73.7%, GSA 18, 95%), mostly the coral Isidella elongata, and of the actinia Actinauge richardi in GSA 16 (Fig. 2D). In contrast, the biomass in the western GSAs was dominated by several species of holothurians (Molpadia musculus and Parastichopus regalis), ophiouras (Leptometra sp. and Hymenodiscus coronata) and sea-urchins (Cidaris cidaris) (all the mentioned species together: GSA 1, 69.7%; GSA 2, 66.6%; GSA 5, 56.8%; and GSA 7, 64.5%) (Fig. 2D). In terms of abundance, in GSA 6 (northern Spain) other Mollusca represent more than 50% of the community. This percentage was mostly caused by the high densities of the species Aporrhais serresianus (Fig. 2C).

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Fig. 2. – Percentage of abundance (N km–2) (A) and biomass (g km–2) indexes (B) for each taxonomic group by GSAs. Below, detailed figure of abundance (C) and biomass indexes (D) of the most sessile taxonomic groups. Ostei, Osteichthyes; Chon, Chondrichthyes; Crus, Crustacea; Cepha, Cephalopoda; Cnid, Cnidaria; Echi, Echinodermata; OtherMol, other Mollusca (non-cephalopod); Porif, Porifera; Tunic, Tunicata.

The overall community box-plot (Fig. 3) showed a significant difference between areas (one-way ANOVA, F=227.9, p<0.001), with a decreasing eastward pattern in abundance and biomass indices, except in GSA 6 (northern Spain). GSA 6 showed lower levels than the rest of the sub-areas of the western Mediterranean (GSAs 1, 2, 5, 7 and 8, with no significant differences), and equivalent ones to those in the more eastern areas. The sampled sub-areas in the eastern area (GSAs 10, 16, 18 and 19) showed no significant difference among them (Table 1, Fig. 3). The spatial pattern was consistent within all taxa, showing significantly lower values for demersal (e.g. Osteichthyes, Chondrichthyes Crustacea and Cephalopoda) and benthic taxa (Cnidaria, Echinodermata, other Mollusca, Porifera and Tunicata) in GSAs 6, 10, 16, 18 and 19 (Fig. 4). A haul conducted over the crinoid beds (Leptometra sp.) in 2013 was responsible for the abundance peak (and high standard error) observed in GSA 7 (Fig 4B). A close-up of Figure 4D showed a peak of biomass values in GSAs 8 and 18 caused by several hauls conducted over an octocoralline community of I. elongata and a peak of Echinodermata Holothuria tubulosa (GSA 2).

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Fig. 3. – Total catch in the ten sampled GSAs, considering standardized abundance (N km–2) and biomass (g km–2) indexes. Boxes are the lower to the upper quartile and the centre line is the median with whiskers from minimum to maximum values.

Table 1. – P values of Tukey post hoc tests after one-way ANOVA for biomass with GSAs as fixed factors, F=227.9. * significant differences p<0.01.

GSA 1 2 5 6 7 8 10 16 18
1
2 0.29
5 0.88 0.02
6 * * *
7 * * 0.20 *
8 0.99 0.39 0.99 * *
10 * * * 1.0 * 0.25
16 * * * 0.59 * * 0.24
18 * * * 0.70 * * 0.34 0.96
19 * * * 0.16 * * 0.16 0.98 *

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Fig. 4. – Abundances (N km–2) and biomass (g km–2) indexes by GSAs of demersal taxonomic groups (A and B) and more sessile taxonomic groups (C and D) (values are mean ±SE). Ostei, Osteichthyes; Chon, Chondrichthyes; Crus, Crustacea; Cepha, Cephalopoda; Cnid, Cnidaria; Echi, Echinodermata; OtherMol, other Mollusca (non-cephalopod); Porif, Porifera; Tunic, Tunicata.

A group average sorting dendrogram showing the percentage similarity of the megabenthic community and the corresponding MDS ordination at each station sampled is shown in Figure 5. Grouping appeared to be strongly influenced by zone and suggests a longitudinal pattern of species distribution. The analysis delineated five clusters in two main community-level groups at the 25% level of similarity (Fig. 5A). These two main groups delineated species from the western and central basin as follows: Group a) a more heterogeneous group formed by samples from the western Mediterranean Basin (GSAs 1, 2, 5, 7 and 8); and Group b) a more homogeneous group formed by samples from the central Mediterranean Basin (GSA 10, 16, 18 and 19) and northern Spain (GSA 6). Three subgroups were formed by western basin samples, based again on longitude. These subgroups overlapped with GSAs, except GSA 7, which is widely distributed in space and showed a transitional zone between the Balearic basin and Corsica (Fig. 5B, C). From Group b, all hauls from the central basin were clustered together and separated by samples from northern Spain (Fig. 5A).

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Fig. 5. – Cluster sorting dendrogram showing the percentage similarity of the hauls in relation to the fauna collected (A) and the corresponding two-dimensional MDS ordination (B) by the sorting cluster based upon an arbitrary level of similarity of 0.35; a and b are the two main groups. C, a map of the Mediterranean Sea showing the haul distribution by sorting cluster. ALBO, Alboran Sea and Alboran Island; ESPN, northern Spain; GL-COR, Gulf of Lions and Corsica; CENTM, central Mediterranean Basin; BAL-GL, Balearic basin and Gulf of Lions.

Ordination of data showed good correspondence with clusters, with the samples being adequately represented (stress=0.16) in two-dimensional space (Fig. 5B). The ANOSIM test performed on the groupings showed that the clusters were significantly different from one another (global R=0.86, p<0.01; Table 2). Analysis of similarities of the complete data set showed an overall significant difference between GSAs (R=0.67, p<0.01; Table 3). In contrast, there were no significant temporal differences among samples (R=0.03, p=0.1).

Table 2. – Pairwise test conducted by ANOSIM using the factor Cluster. p<0.01 for all pairwise comparisons. Global R=0.85.

Clusters CENTM ALBO BAL-GL COR-GL
CENTM
ALBO 1.00
BAL-GL 0.92 0.76
COR-GL 0.94 0.95 0.67
ESPN 0.57 1.00 0.62 0.99

Table 3. – Pairwise test conducted by ANOSIM using the factor GSA. p<0.01 for all pairwise comparisons. ´ no significant difference (p=36.1). Global R=0.67.

GSA 10 1 16 18 19 2 5 6 7
10
1 1.00
16 0.40 0.99
18 0.73 0.98 0.31
19 0.43 0.99 0.33 0.24
2 1.00 0.02´ 1.00 1.00 1.00
5 0.97 0.82 0.96 0.96 0.94 0.80
6 0.83 0.97 0.76 0.84 0.69 1.00 0.74
7 1.00 0.66 0.96 0.96 0.96 0.69 0.69 0.92
8 1.00 0.77 0.92 0.93 0.97 0.99 0.83 1.00 0.57

SIMPER analysis was used to identify the species that contributed to the highest similarity within clusters (Supplementary material, Table S1). The clusters formed exclusively by areas, such as ALBO (Alboran Sea and Alboran Island) and ESPN (northern Spain) showed the highest values of average similarity, 55.6% and 48. 3% respectively, and three other clusters showed a similar percentage of similarity (close to 40%). According to SIMPER, although 43 species were listed, there were four dominant species: Phycis blennoides Galeus melastomus, Plesionika martia and Todarodes sagittatus. These four species showed a wide range of distribution, appearing within all clusters. However, they showed a decreasing eastward pattern in their average biomass, except Plesionika martia, which showed an opposite trend (Supplementary material Table S1). The analysis also showed the presence of species exclusive to certain zones: for example, Nezumia sclerorhyncus appeared only in Corsica and the central basin (clusters GL-COR and CENTM), while Nezumia aequalis was limited to the western Mediterranean (ALBO, ESPN and BAL-GL). Aristaeomorpha foliacea contributed greatly to the community of the central Mediterranean (CENTM), while Aristeus antennatus did so to the community of northern Spain and the Balearic Islands (BAL-GL and ESPN) and Nephrops norvegicus to the cluster of the Gulf of Lions and Corsica (GL-COR). Six species of Chondrichthyes (G. melastomus, Galeus atlanticus, Etmopterus spinax, Chimaera monstrosa, Dipturus oxyrinchus and Scyliorhinus canicula) contributed to the overall similarity within groups. G. melastomus and S. canicula showed the highest percentage of contribution in the northern Spain cluster (ESPN). In contrast, E. spinax contributed to all clusters except ESPN. G. atlanticus contributed exclusively to ALBO, and D. oxyrinchus exclusively to GL-COR. Additionally, one species of Cnidaria, Isidella elongata, and the Gastropoda Galeodea rugosa contributed to the overall similarity within GL-COR and ALBO, respectively.

Based on generalized cross-validation and Aikake information criterion values, the best models explained 85.2% of the deviance variability of total biomass, including the additive effect of latitude and longitude (Table 4). The GAM models identified a significant statistical decrease in biomass eastward, but with minimum values in the longitude corresponding to GSA6 (i.e. –1° to 3.16°, Fig. 6B). Longitude was the single variable which explained the highest variability for biomass. These results were observed for the overall community as well as for all species groups analysed (Table 4). For latitude, the highest values seem to be related to higher latitude, although there was also a maximum around 36-37°, around which both low and high values were found (Fig. 6B), as they correspond to different trends found in the Alboran area (GSAs 1 and 2) and the Strait of Sicily (GSA 16).

Table 4. – Generalized additive models (GAM) fitted to assess the effect of latitude and longitude on biomass index for the overall sampled community (Total) and by species group. GCV, Generalized cross-validation; AIC, Akaike Information Criterion; Num, Number of samples; %Dev, percentage of explained deviance. Ostei, Osteichthyes; Chon, Chondrichthyes; Crus, Crustacea; Cepha, Cephalopoda; Cnid, Cnidaria; Echi, Echinodermata; OtherMol, other Mollusca (non-cephalopod).

Species group Response variable Factor GCV AIC Num %Dev p
Total LogBiom (g km–2) ~ lat 0.29 854 534 24.4 <0.001
LogBiom (g km–2) ~ long 0.08 214 534 77.2 <0.001
LogBiom (g km–2) ~ (lat, long ) 0.06 17 534 85.2 <0.001
Cnid LogBiom (g km–2) ~ lat 0.92 816 296 23.9 <0.001
LogBiom (g km–2) ~ long 0.51 643 296 57.8 <0.001
LogBiom (g km–2) ~ (lat, long ) 0.45 603 296 66.5 <0.001
Cepha LogBiom (g km–2) ~ lat 0.46 984 476 14.2 <0.001
LogBiom (g km–2) ~ long 0.34 848 476 36.2 <0.001
LogBiom (g km–2) ~ (lat, long ) 0.31 801 476 45.5 <0.001
Crus LogBiom (g km–2) ~ lat 0.17 568 534 13.8 <0.001
LogBiom (g km–2) ~ long 0.11 346 534 43.6 <0.001
LogBiom (g km–2) ~ (lat, long ) 0.08 213 534 58.7 <0.001
Echi LogBiom (g km–2) ~ lat 0.71 592 237 16.3 <0.001
LogBiom (g km–2) ~ long 0.36 429 237 58.7 <0.001
LogBiom (g km–2) ~ (lat, long ) 0.34 417 237 64.5 <0.001
Chon LogBiom (g km–2) ~ lat 0.44 1072 532 21.2 <0.001
LogBiom (g km–2) ~ long 0.18 623 532 66.3 <0.001
LogBiom (g km–2) ~ (lat, long ) 0.15 512 532 74.4 <0.001
OtherMoll LogBiom (g km–2) ~ lat 0.64 510 212 5.08 <0.05
LogBiom (g km–2) ~ long 0.21 277 212 69.9 <0.001
LogBiom (g km–2) ~ (lat, long ) 0.2 268 212 74.2 <0.001
Oste LogBiom (g km–2) ~ lat 0.64 993 534 21.3 <0.001
LogBiom (g km–2) ~ long 0.21 455 534 71.5 <0.001
LogBiom (g km–2) ~ (lat, long ) 0.2 310 534 79.8 <0.001

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Fig. 6. – Results of significant regression models fitted for overall community to assess the connection of log-transformed biomass (g km–2) index with latitude (A), longitude (B; negative values: West, positive values: East), and with the interaction of latitude and longitude (C). Shadowed areas represent 95% confidence intervals. The colour gradient of the geographical effect codes from low values (darker colours) to high values (lighter colours). The statistical summary of all models for the entire community and for different groups is summarized in Table 4.

Regarding the assessment of the possible effect of fishing effort on biomass values, the best models explained 90.7% of the deviance variability of total biomass, including latitude, longitude and fishing effort (Table 5). Spatial distribution explained higher variability than fishing effort. However, a significant decreasing pattern between biomass index and fishing effort was found, explaining 16.4% of the variability (Table 5, Fig 7A). The spatial effect in biomass and fishing effort showed opposite patterns, with the highest biomass in the areas with the lowest fishing effort (GSA 1), and the lowest biomass overlapped with the highest fishing effort (north of GSA 6) (Fig. 7B, C). An exception was found in GSA2, which was relatively highly impacted but showed high biomass values.

Table 5. – Summary of regression models results assessing the effects of fishing effort (FE), latitude and longitude on mean biomass values for the Spanish area.

Response variable Factor GCV AIC Num %Dev p
LogBiom (g km–2) ~ lat 0.11 46.3 68 84.5 <0.001
LogBiom (g km–2) ~ long 0.09 34.5 68 86.7 <0.001
LogBiom (g km–2) ~ FE 0.53 150.6 68 16.4 <0.001
LogBiom (g km–2) ~ s(FE) + s(lat, long ) 0.06 10.4 68 90.7 <0.001

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Fig. 7. – Partial effects of fishing effort (FE), and spatial distribution on the biomass index (g km–2) in the western Mediterranean (GSAs 1, 2, 5 and 6) using logarithmic transformation of the biomass index (A). The colour gradient of the geographical effect codes from low values (darker colours) to high values (lighter colours) (B). The statistical summary of plots is summarized in Table 5.

DISCUSSIONTop

The present study explores long-term distribution patterns of megafauna in the Mediterranean Basin and how it may be affected by fishing. The results, overall, showed an eastward decreasing pattern in the abundance of megafauna assemblages collected with a trawl net of 500 to 800 m on the Mediterranean continental slope. This finding was observed for all the analysed taxonomic groups (Osteichthyes, Chondrichthyes, Crustacea, Echinodermata, Cephalopoda, other Mollusca, Tunicata and Porifera).

The decreasing eastward pattern observed is consistent with the available information limited to a single studied taxon (Cartes et al. 2002Cartes J., Abelló P., Lloris D., et al. 2002. Analysis of feeding guilds of fish and decapod crustaceans during the MEDITS-99 cruise along the Iberian Peninsula Mediterranean coasts. Sci. Mar. 66: 209-220., Company et al. 2004Company J.B., Maiorano P., Plaity W., et al. 2004. Deep-sea decapod crustaceans in the western and central Mediterranean Sea: preliminary aspects of species distribution, biomass and population structure. Sci. Mar. 68(Suppl. 3): 73-86., D’Onghia et al. 2004D’Onghia G., Politou C.Y., Bozzano A., et al. 2004. Deep-water fish assemblages in the Mediterranean Sea. Sci. Mar. 68(Suppl. 3): 87-99.) and with results reported for deeper areas (below 800 m depth) (Danovaro et al. 2010Danovaro R., Company J.B., Corinaldesi C., et al. 2010. Deep-Sea Biodiversity in the Mediterranean Sea: The Known, the Unknown, and the Unknowable. PLoS ONE 5: e11832., Tecchio et al. 2011aTecchio S., Ramírez-Llodra E., Sardà F. 2011a. Biodiversity of deep-sea demersal megafauna in western and central Mediterranean basins. Sci. Mar. 75: 341-350.), and is primarily related to a decreasing west-east gradient of biological production (Coll et al. 2010Coll M., Piroddi C., Steenbeek J., et al. 2010. The Biodiversity of the Mediterranean Sea: Estimates, Patterns, and Threats. PLoS ONE 5: e11842.). The Mediterranean Sea is characterized by a well-known west to east decrease in nutrient concentration, phytoplankton biomass and surface primary production (Moutin and Raimbault 2002Moutin T., Raimbault P. 2002. Primary production, carbon export and nutrients availability in western and eastern Mediterranean Sea in early summer 1996 (MINOS cruise). J. Mar. Syst. 33: 273-288.) that seems to be mirrored by a similar decrease in benthic megafaunal biomass. The contrasting results in community descriptors obtained between the western and central Mediterranean basins in this study suggest that differences in biological production (or more generally, in food availability) between the two basins might be the strongest driver for community abundance and biomass. However, other drivers such as fishing effort may also modulate the pattern.

We observed that communities from northern Spain (GSA 6) do not follow the general eastward decreasing trend, showing different compositions and lower abundance values in all the studied taxonomic groups in comparison with adjacent areas. It is well known that the deep NW Mediterranean Basin is an area of high productivity in comparison with the other parts of the Mediterranean Sea, because of higher surface productivity, coastal inputs and exposure to massive inputs of organic matter caused by cyclic cascading events (Margalef 1985Margalef R. (ed.). 1985. Western Mediterranean. Pergamon Press, Oxford. 363 pp., Canals et al. 2006Canals M., Puig P., de Madron X.D., et al. 2006. Flushing submarine canyons. Nature 444: 354., 2009Canals M., Danovaro R., Heussner S., et al. 2009. Cascades in Mediterranean submarine grand canyons. Oceanography 22: 26-43.). However, deep-water bottoms in this area have been intensively trawled during the last century (Gorelli et al. 2016Gorelli G., Sardà F., Company J.B. 2016. Fishing Effort Increase and Resource Status of the Deep-Sea Red Shrimp Aristeus antennatus (Risso 1816) in the Northwest Mediterranean Sea Since the 1950s. Rev Fish. Sci-Aquac. 24: 192-202., Pitcher et al. 2017Pitcher C.R., Ellis N., Jennings S., et al. 2017. Estimating the sustainability of towed fishing-gear impacts on seabed habitats: a simple quantitative risk assessment method applicable to data-limited fisheries. Methods Ecol. Evol. 8: 472-480.), and thus the presence of the lowest biomass values in these communities inhabiting more productive waters suggest that fishing exploitation might have an important impact on communities in this area. In fact, our results showed that deep trawl-fishing exploitation in GSA 6 is two to four times higher than that in adjacent areas of the Spanish continental slope margin, with the exception of Alboran Island (Fig. 7B). These results suggest that in this area human activity is an important factor in describing species community and partially modulates community descriptors. This is particularly true on the continental margins, where the life-history characteristics of several deep-sea species make them potentially more vulnerable to human impacts. These results are in accordance with those of previous studies showing that trawl-fishing exploitation in GSA 6 is very intense and much higher, for instance, than in the Balearic Islands (GSA 5) and the Alboran Sea (GSA 1), two sites that were also found to have healthier communities (Ramírez-Amaro et al. 2016Ramírez-Amaro S., Ordines F., Terrasa B., et al. 2016. Demersal chondrichthyans in the western Mediterranean: assemblages and biological parameters of their main species. Mar. Freshw. Res. 67: 636-652., Quetglas et al. 2017Quetglas A., Merino G., González J., et al. 2017. Harvest strategies for an ecosystem approach to fisheries management in western Mediterranean demersal fisheries. Front. Mar. Sci. 4: 106.). Following the present study trends but in a whole Mediterranean context, Colloca et al. (2017)Colloca F., Scarcella G., Libralato S. 2017. Recent Trends and Impacts of Fisheries Exploitation on Mediterranean Stocks and Ecosystems. Front. Mar. Sci. 4: 244. identified GSA 6 (with GSA 9 and 17) as the fisheries with the lowest ecosystem sustainability. Moreover, Company et al. (2004)Company J.B., Maiorano P., Plaity W., et al. 2004. Deep-sea decapod crustaceans in the western and central Mediterranean Sea: preliminary aspects of species distribution, biomass and population structure. Sci. Mar. 68(Suppl. 3): 73-86. in a comparative study of Mediterranean decapods, found the same general eastward decreasing pattern in species dwelling below 1000 m depth, but not in species from the middle slope (between 600 and 800 m depth), also potentially due to the intense fishing activity targeting A. antennatus (western Mediterranean) and A. foliacea (in Greek waters). Note that in the present study the results of the fishing pressure in deep-water communities were skewed by the high effort values found at Alboran Island: in fact, if we deleted the eight trawls conducted in this area, the fishing effort explained 34% of the biomass variability. Alboran Island is a seamount of volcanic origin characterized by high productivity (Maldonado and Comas 1992Maldonado A., Comas M. 1992. Geology and geophysics of the Alboran Sea: An introduction. Geo-Mar. Lett. 12: 61-65.) that has a special fishing regulation (BOE 1998Boletín Oficial del Estado (BOE). 1998. de 29 de Septiembre. Orden 22628 de 8 de Septiembre, n. 223, p. 32541.). While it is becoming increasingly clear that human activities are impacting deep-sea Mediterranean communities (Cartes et al. 2004Cartes J., Maynou F., Sardà F., et al. 2004. The Mediterranean deep-sea ecosystems: an overview of their diversity, structure, functioning and anthropogenic impacts. In: The Mediterranean deep-sea ecosystems, Part I. WWF and IUCN (eds), pp. 9-38., Navarro et al. 2015Navarro J., Coll M., Cardador L., et al. 2015. The relative roles of the environment, human activities and spatial factors in the spatial distribution of marine biodiversity in the Western Mediterranean Sea. Prog. Oceanogr. 131: 126-137., Piroddi et al. 2017Piroddi C., Coll M., Liquete C., et al. 2017. Historical changes of the Mediterranean Sea ecosystem: modelling the role and impact of primary productivity and fisheries changes over time. Sci. Rep. 7: 44491.), in order to set up effective mitigation strategies, the effects of fishing impacts need to be better quantified. Thus, these results are still preliminary and an analysis of a wider spatial scale will be conducted.

The longitudinal gradient found in this study for biomass and abundance was also observed in the assemblage composition. The MDS results showed samples clearly grouped among geographic sub-areas, except again for samples from northern Spain (GSA 6). The cluster analysis showed different species in the community composition between the western and central Mediterranean (the most significant examples were the two species of Nezumia spp. and Aristeids: N. aequalis was exclusively found in the western basin and N. sclerorhynchus in the central basin of Mediterranean; A. antennatus dominated the Balearic Sea, while A. foliacea was more abundant in Adriatic and Ionian Sea communities). These species could be preferentially distributed due to their biology and fishing could also potentially alter the community compositions in highly exploited areas (e.g. GSA 6). Additionally, we found higher homogeneity between samples from the central basin than those from the western basin. The more complex oceanographic dynamism of the western Mediterranean Basin (Béranger et al. 2005Béranger K., Mortier L., Crépon M. 2005. Seasonal variability of water transport through the Straits of Gibraltar, Sicily and Corsica, derived from a high-resolution model of the Mediterranean circulation. Prog. Oceanogr. 66: 341-364.) and the human-induced changes may have driven the observed results and may indicate that each sub-area is characterized by the presence of a specific assemblage with high biogeographic complexity.

An increase in small and fast-growing species has been observed to be a general community response to trawling (Hiddink et al. 2006Hiddink J., Hutton T., Jennings S., et al. 2006. Predicting the effects of area closures and fishing effort restrictions on the production, biomass, and species richness of benthic invertebrate communities. ICES J. Mar. Sci. 63: 822-830.). The dominance of crustaceans (which are show the highest percentage of the community) throughout the Mediterranean middle slope suggests that they may be more competitive in a overfishing context than other megabenthos groups (e.g. elasmobranchs and non-crustacean invertebrates). High values of crustacean density have been related to medium and high levels of fishing effort (Guijarro et al. 2011Guijarro B., Tserpes G., Moranta J., et al. 2011. Assessment of the deep water trawl fishery off the Balearic Islands (western Mediterranean): from single to multi-species approach. Hydrobiologia 670: 67-85.) and, in fact, high catches of A. antennatus have been related to the ability of fishermen to remove competitors at a higher rate (Sardà and Maynou 1998Sardà F., Maynou F. 1998. Assessing perceptions: do Catalan fishermen catch more shrimp on Fridays? Fish. Res. 36: 149-157.). Interestingly, the only exception was the Alboran Basin (GSA 1 and 2) where the community was dominated by Chondrichthyes. The dominance of species characterized by slow population growth, such as sharks and rays, might be due to the fact that that the open slope has remained almost unexploited at depths lower than 500 m (Torres et al. 2001Torres P., González M., Rey J., et al. 2001. Rose shrimp fishery’s associated fauna in not exploited grounds on the Alboran Sea slope (Western Mediterranean Sea). Rapp. Comm. Int. Mer Médit. 36: 330., Rey et al. 2005Rey J., Gil de Sola L., Massutí E. 2005. Distribution and biology of the blackmouth catshark Galeus melastomus in the Alboran Sea (Southwestern Mediterranean). J. Northw. Atl. Fish. Sci. 35: 215-223., Ramírez-Amaro et al. 2016Ramírez-Amaro S., Ordines F., Terrasa B., et al. 2016. Demersal chondrichthyans in the western Mediterranean: assemblages and biological parameters of their main species. Mar. Freshw. Res. 67: 636-652.), in addition to the particular oceanographic conditions, river discharges and the presence of submarine canyon which result in very productive areas (Millot 1999Millot C. 1999. Circulation in the Western Mediterranean Sea. J. Mar. Syst. 20: 423-442., Moranta et al. 2007Moranta J., Massutí E., Palmer M., et al. 2007. Geographic and bathymetric trends in abundance, biomass and body size of four grenadier fishes along the Iberian coast in the western Mediterranean. Prog. Oceanogr. 72: 63-83.). Moreover, sessile fauna has been suggested to be the first to undergo the negative effects of fishing (Jennings and Kaiser 1998Jennings S., Kaiser M.J. 1998. The effects of fishing on marine ecosystems. Adv. Mar. Biol. 34: 201-352., Roberts 2002Roberts C.M. 2002. Deep impact: the rising toll of fishing in the deep sea. Trends Ecol. Evol. 17: 242-245.). In accordance, the abundance and biomass of invertebrate non-crustaceans was much lower than that of more mobile fauna, such as fish and crustacean decapods, in the whole Mediterranean continental slope, except for punctual peaks in the values of Echinodermata (GSA 7) and Cnidaria (GSAs 8 and 18). The high densities and biomasses of these two taxonomic groups were caused by isolated hauls conducted over Leptometra sp. grounds and deep coral facies of Isidella elongata. The compact mud facies with Isidella elongata have been listed by the GFCM as sensitive habitats because of their importance as an essential habitat for certain crustacean species (Aristeus antennatus and Aristaeomorpha foliacea) (GFCM 2009General Fisheries Commission for the Mediterranean (GFCM), SAC 2009. Criteria for the identification of sensitive habitats of relevance for the management of priority species. vol. 3 pp. 3, Málaga., Fabri et al. 2014Fabri M.C., Pedel L., Beuck L., et al. 2014. Megafauna of vulnerable marine ecosystems in French mediterranean submarine canyons: Spatial distribution and anthropogenic impacts. Deep-Sea Res. Part II 104: 184-207.). Recent studies have shown that I. elongata is only present in areas where the fishing effort is low or absent (Maynou and Cartes 2012Maynou F., Cartes J.E. 2012. Effects of trawling on fish and invertebrates from deep-sea coral facies of Isidella elongata in the western Mediterranean. J. Mar. Biol. Assoc. U.K. 92: 1501-1507., Lauria et al. 2017Lauria V., Garofalo G., Fiorentino F., et al. 2017. Species distribution models of two critically endangered deep-sea octocorals reveal fishing impacts on vulnerable marine ecosystems in central Mediterranean Sea. Sci. Rep. 7: 8049.), a finding that may explain the isolated presence of this species in the present study. This apparent impact of fishing on the Mediterranean continental slope is consistent with earlier descriptions of deep-sea communities in some areas of the Mediterranean (e.g. the Balearic Islands, Farriols et al. 2017Farriols M.T., Ordines F., Somerfield P.J., et al. 2017. Bottom trawl impacts on Mediterranean demersal fish diversity: Not so obvious or are we too late? Cont. Shelf Res. 137: 84-102.) and recent analyses of sediment cores from the NW Mediterranean continental slope (Cartes et al. 2017Cartes J.E., Schirone A., Barsanti M., et al. 2017. Recent reconstruction of deep-water macrofaunal communities recorded in Continental Margin sediments in the Balearic Basin. Deep-Sea Res. Part I 125: 52-64.), which found significant quantities of deep-water coral aggregates that have almost disappeared, indicating their previous/historic presence in these areas. However, further analysis, including the combined use of different gears (e.g. OTMS and the Agassiz dredge or benthic sledge) would be required in order to provide an integrated image of the megafaunal compartment, particularly regarding non-crustacean invertebrates (i.e. echinoderms), for which little information is currently available on their distribution (Tecchio et al. 2011bTecchio S., Ramírez-Llodra E., Sardà F., et al. 2011b. Drivers of deep Mediterranean megabenthos communities along longitudinal and bathymetric gradients. Mar. Ecol. Prog. Ser. 439: 181-192., Mecho et al. 2015Mecho A., Fernandez-Arcaya U., Aguzzi J., et al. 2015. Reproductive biology of the seastar Ceramaster grenadensis from the deep north-western Mediterranean Sea. J. Mar. Biol. Assoc. U.K. 95: 805-815.).

In conclusion, the present study is the first attempt to describe the middle slope community along a wide spatial scale. It is in agreement with previous works which report a general eastward decreasing pattern in community descriptors (e.g. Coll et al. 2010Coll M., Piroddi C., Steenbeek J., et al. 2010. The Biodiversity of the Mediterranean Sea: Estimates, Patterns, and Threats. PLoS ONE 5: e11842., Keller et al. 2016Keller S., Bartolino V., Hidalgo M., et al. 2016. Large-scale spatio-temporal patterns of Mediterranean cephalopod diversity. PLoS ONE 11: e0146469.) potentially related to environmental drivers (primary production and temperature). In addition, fishing activity also potentially modulates the deep Mediterranean community. This statement is particularly reflected in highly impacted areas, such as the northwestern Spanish middle slope, where the community does not and may be no longer follow the general eastward decreasing pattern, suggesting that the human activity has largely modified the community structure in this area.

Further investigations would require high-spatial resolution data (i.e. data from VMS or the Automatic Information System coupled to information on gear impact on the seabed) to determine the potential impact of fishing on a large spatial scales (Eigaard et al. 2015Eigaard O.R., Bastardie F., Breen M., et al. 2015. Estimating seabed pressure from demersal trawls, seines, and dredges based on gear design and dimensions. ICES J. Mar. Sci. 73: i27-i43., 2017Eigaard O.R., Bastardie F., Hintzen N.T., et al. 2017. The footprint of bottom trawling in European waters: distribution, intensity, and seabed integrity. ICES J. Mar. Sci. 74: 847-865.). Other alternative approaches need to be developed in order to assess the impact on ecosystem functioning and the response to fishing pressure and other human stressors. These could be based on life-history and biological traits of impacted species (de Juan and Demestre 2012de Juan S., Demestre M. 2012. A Trawl Disturbance Indicator to quantify large scale fishing impact on benthic ecosystems. Ecol. Indicators 18: 183-190., Rijnsdorp et al. 2016Rijnsdorp A.D., Bastardie F., Bolam S.G., et al. 2016. Towards a framework for the quantitative assessment of trawling impact on the seabed and benthic ecosystem. ICES J. Mar. Sci. 73: i127-i138.) or on community functional diversity indicators (Mouillot et al. 2013Mouillot D., Graham N.A.J., Villéger S., et al. 2013. A functional approach reveals community responses to disturbances. Trends Ecol. Evol. 28: 167-177., Beauchard et al. 2017Beauchard O., Veríssimo H., Queirós A.M., et al. 2017. The use of multiple biological traits in marine community ecology and its potential in ecological indicator development. Ecol. Indicators 76: 81-96.). They could be based on modelling approaches that estimate the reduction in community biomass or the shift in community composition corresponding to the estimated fishing intensity relative to system carrying capacity and natural disturbances (Pitcher et al. 2017Pitcher C.R., Ellis N., Jennings S., et al. 2017. Estimating the sustainability of towed fishing-gear impacts on seabed habitats: a simple quantitative risk assessment method applicable to data-limited fisheries. Methods Ecol. Evol. 8: 472-480.). Additionally, the use of habitat suitability modelling, which predicts the suitability of a location for a species or group of species, based on their observed relationship with environmental conditions (Davies et al. 2015Davies J.S., Stewart H.A., Narayanaswamy B.E., et al. 2015. Benthic Assemblages of the Anton Dohrn Seamount (NE Atlantic): Defining Deep-Sea Biotopes to Support Habitat Mapping and Management Efforts with a Focus on Vulnerable Marine Ecosystems. PLoS ONE 10: e0124815., Rowden et al. 2017Rowden A.A., Anderson O.F., Georgian S.E., et al. 2017. High-Resolution Habitat Suitability Models for the Conservation and Management of Vulnerable Marine Ecosystems on the Louisville Seamount Chain, South Pacific Ocean. Front. Mar. Sci. 4: 335.), could help in spatially managing the impact of fishing on Mediterranean continental margins.

ACKNOWLEDGEMENTSTop

This paper was prepared in the framework of the MEDITS survey programme within the Data Collection Framework (DCF). The European Union and the Member States involved in the DCF are thankfully acknowledged. Fernandez-Arcaya was funded by a post-doctoral grant co-funded by the Regional Government of the Balearic Islands and the European Social Fund 2014–2020. The present study could not have been done without the projects supporting this research (ECLIPSAME; CTM2012-37701; CLIFISH: CTM2015-66400-C3-1-R MINECO/FEDER) and the FPI Fellowship granted to Maria Teresa Farriols (BES-2013-065112), both funded by the Spanish Ministry of Economy and Competitiveness. Sandrine Vaz and Angélique Jadaud received additional financial support from EU DG Environment funded the IDEM project (Implementation of the MSFD to the Deep Mediterranean Sea) under grant agreement 11.0661/2017/750680/SUB/ENV.C2.

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Supplementary MateriAL

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Table S1. – Results of similarity percentage analysis (SIMPER) of the overall community on each GSA. Av.Abund (average abundance), Av.Sim (average similarity), Sim/SD (ratio of the average similarity and the standard deviation), Contrib% (percentage contribution), Cum% (cumulative percentages).



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