sm83s1-4977

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

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

Spatio-temporal trends in diversity of demersal fish assemblages in the Mediterranean

M. Teresa Farriols 1, Francesc Ordines 1, Pierluigi Carbonara 2, Loredana Casciaro 2, Manfredi Di Lorenzo 3, Antonio Esteban 4, Cristina Follesa 5, Cristina García-Ruiz 6, Igor Isajlovic 7, Angélique Jadaud 8, Alessandro Ligas 9, Chiara Manfredi 10, Bojan Marceta 11, Panagiota Peristeraki 12,13, Nedo Vrgoc 14, Enric Massutí 1

1 Intituto Español de Oceanografía, Centre Oceanogràfic de les Balears, Moll de Ponent s/n, 07015 Palma de Mallorca, Illes Baleares, Spain.
(MTF) (corresponding author) E-mail: mt.farriols@ieo.es. ORCID iD: https://orcid.org/0000-0002-7704-6504
(FO) E-mail: xisco.ordinas@ieo.es. ORCID iD: https://orcid.org/0000-0002-2456-2214
(EM) E-mail: enric.massuti@ieo.es. ORCID iD: https://orcid.org/0000-0002-9524-5873
2 COISPA Tecnologia and Ricerca, Stazione Sperimentale per lo Studio delle Risorse del Mare, Bari, Italy.
(PC) E-mail: carbonara@coispa.it. ORCID iD: https://orcid.org/0000-0002-2529-2535
(LC) E-mail: casciaro@coispa.eu. ORCID iD: https://orcid.org/0000-0003-4876-9874
3 CNR-IAMC, Mazara del Vallo, Via Vaccara 61, Mazara del Vallo, TP, Italy.
(MDL) E-mail: manfredi.dilorenzo@libero.it. ORCID iD: https://orcid.org/0000-0003-3786-5772
4 Instituto Español de Oceanografía (IEO), Centro Oceanográfico de Murcia, Murcia, Spain.
(AE) E-mail: antonio.esteban@ieo.es. ORCID iD: https://orcid.org/0000-0002-2896-7972
5 Dipartimento di Biologia Animale ed Ecologia, Università di Cagliari, Cagliari, Italy.
(CF) E-mail: follesac@unica.it. ORCID iD: https://orcid.org/0000-0001-8320-9974
6 Instituto Español de Oceanografía (IEO), Centro Oceanográfico de Málaga, Fuengirola, Málaga, Spain.
(CG-R) E-mail: cristina.garcia@ieo.es. ORCID iD: https://orcid.org/0000-0003-2767-4200
7 Institute of Oceanography and Fisheries Split, Šetalište Ivana Meštrovića 63, 21000 Split, Croatia.
(II) E-mail: igor@izor.hr. ORCID iD: https://orcid.org/0000-0001-7101-9575
8 Institut Français de Recherche pour l’Exploitation de la Mer (Ifremer), UMR 212 Ecosystèmes Marins Exploités (EME), Centre de Recherche halieutique Méditerranéenne et Tropicale, 34203 Sète, France.
(AJ) E-mail: Angelique.Jadaud@ifremer.fr. ORCID iD: https://orcid.org/0000-0001-6858-3570
9 Centro Interuniversitario di Biologia Marina ed Ecologia Applicata, Viale Nazario Sauro 4, 57128 Leghorn, Italy.
(AL) E-mail: ligas@cibm.it. ORCID iD: https://orcid.org/0000-0003-1036-3553
10 Laboratorio di Biologia Marina e Pesca di Fano, Dip.to B.E.S., Università di Bologna, Fano, Italy.
(CM) E-mail: chiara.manfredi3@unibo.it. ORCID iD: https://orcid.org/0000-0002-2852-4856
11 Fishery Research Institute of Slovenia, Ljubljana-Smartno, Slovenia.
(BM) E-mail: bojan.Marceta@zzrs.si. ORCID iD: https://orcid.org/0000-0001-8137-4474
12 Hellenic Center for Marine Research, Iraklion, Crete, Greece.
13 University of Crete, Biology Department, Stavrakia, Heraklion, Crete.
(PP) E-mail: notap@hcmr.gr. ORCID iD: https://orcid.org/0000-0002-8608-078X
14 Institute of Oceanography and Fisheries, Split, Croatia.
(NV) E-mail: vrgoc@izor.hr. ORCID iD: https://orcid.org/0000-0002-528-4512

Summary: The high species richness, coupled with high proportion of endemism, makes the Mediterranean one of the world’s ‘biodiversity hotspots’. However, the continuous increase in fisheries in the last few decades has led to the overexploitation of their main commercial stocks. Using fishery-independent data collected under the framework of the MEDITS trawl surveys carried out over the last 20 years, we study the demersal fish diversity pattern in the Mediterranean at a large spatial and temporal scale to determine whether it is being affected by the general fishing overexploitation of the demersal resources. The detected diversity trends are compared with the spatio-temporal variation in bottom trawl fishing effort in the Mediterranean. Our results show a stability and even recovery of demersal fish diversity in the Mediterranean together with higher diversity values on the continental shelves of the Balearic Islands, Sardinia, Sicily and the Aegean Sea. At large temporal and spatial scales, the high diversity of demersal assemblages in the Mediterranean is associated with a reduction in bottom trawl fishing effort. The inclusion of species other than target ones through diversity indices is important in the implementation of an ecosystem-based fisheries management.

Keywords: biodiversity; fish assemblages; MEDITS; bottom trawling; fishing effort; Mediterranean Sea.

Tendencias espacio-temporales en la diversidad de peces demersales del Mediterráneo

Resumen: Debido a su alta riqueza específica y su gran proporción de organismos endémicos, el Mediterráneo es considerado un punto caliente de biodiversidad. No obstante el continuo crecimiento de las pesquerías en las últimas décadas ha desembocado en una sobrexplotación de sus principales stocks comerciales. A través de datos independientes de las pesquerías recogidos en el marco de las campañas MEDITS desarrolladas durante las dos últimas décadas se ha estudiado el patrón de diversidad de peces demersales en el Mediterráneo a través de largas escalas temporales y espaciales para evaluar si este patrón se ve afectado por el estado general de sobrexplotación de sus recursos demersales. A continuación las tendencias detectadas en la diversidad han sido comparadas a la variación espacio-temporal del esfuerzo de la pesca de arrastre a través del Mediterráneo. Nuestros resultados muestran una estabilidad e incluso recuperación de la diversidad de peces demersales en el Mediterráneo junto a valores altos de diversidad en las plataformas continentales de las Islas Baleares, Cerdeña, Sicília y el mar Egeo. La alta diversidad de las asociaciones de peces demersales a escala tanto espacial como temporal está asociada a una reducción del esfuerzo pesquero. La inclusión de especies distintas a las objetivo a través de índices de diversidad es relevante en la implementación de la aproximación ecosistémica a la gestión de las pesquerías.

Palabras clave: biodiversidad; asociaciones de peces; MEDITS; arrastre de fondo; esfuerzo pesquero; mar Mediterráneo.

Citation/Cómo citar este artículo: Farriols M.T., Ordines F., Carbonara P., Casciaro L., Di Lorenzo M., Esteban A., Follesa C., García-Ruiz C., Isajlovic I., Jadaud A., Ligas A., Manfredi C., Marceta B., Peristeraki P., Vrgoc N., Massutí E. 2019. Spatio-temporal trends in diversity of demersal fish assemblages in the Mediterranean. Sci. Mar. 83S1: 189-206. https://doi.org/10.3989/scimar.04977.13A

Editor: M.T. Spedicato.

Received: April 18, 2018. Accepted: July 11, 2019. Published: September 26, 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 Mediterranean is considered one of the Large Marine Ecosystems of the world, owing to its bathymetry, hydrography, productivity and trophic webs (Duda and Sherman 2002Duda A.M., Sherman K. 2002. A new imperative for improving management of large marine ecosystems. Ocean Coast. Manage. 45: 797-833.). It is a semi-enclosed sea connected to the Atlantic Ocean through the Gibraltar Strait, to the Black Sea through the Dardanelles Strait and to the Red Sea through the artificial Suez Channel (Fig. 1). It acts as a concentration basin, and evaporation is higher in its eastern basin, causing the water level to decrease and salinity to increase from west to east (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.). While temperature also increases eastwards (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.), surface productivity, organic matter availability at the seafloor and the biomass of megabenthic fauna of deep ecosystems decrease eastwards (Bosc et al. 2004Bosc E., Bricaud A., Antoine D. 2004. Seasonal and interannual variability in algal biomass and primary production in the Mediterranean Sea, as derived from 4 years of SeaWiFS observations. Global Biogeochem. Cycles 18: GB1005., Danovaro et al. 1999Danovaro R., Dinet A., Duineveld G., et al. 1999. Benthic response to particulate fluxes in different trophic environments: a comparison between the Gulf of Lions-Catalan Sea (western-Mediterranean) and the Cretan Sea (eastern-Mediterranean). Progr. Oceanogr. 44: 287-312., Tecchio et al. 2011Tecchio S., Ramírez-Llodra E., Sardà F., et al. 2011. Drivers of deep Mediterranean megabenthos communities along longitudinal and bathymetric gradients. Mar. Ecol. Prog. Ser. 439: 181-192.). The Mediterranean has narrow continental shelves and a large area of open sea. In fact, the continental shelf covers about 20% of the Mediterranean bottoms, whereas the slope covers about 60% (Sardà et al. 2004Sardà F., Calafat A., Flexas M.M., et al. 2004. An introduction to Mediterranean deep-sea biology. Sci. Mar. 68: 7-38.). Therefore, a large part of this basin can be classified as deep sea (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 high species richness, coupled with a high proportion of endemism, makes the Mediterranean one of the world’s ‘biodiversity hotspots’ (Moranta et al. 2008Moranta J., Quetglas A., Massutí E., et al. 2008. Research trends on demersal fisheries oceanography in the Mediterranean. In: Mertens L.P. (ed), Biological Oceanograpgy Research Trends. Nova Science Publishers, New York, pp. 9-65., 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., Lejeusne et al. 2010Lejeusne C., Chevaldonné P., Pergent-Martini C., et al. 2010. Climate change effects on a miniature ocean: the highly diverse, highly impacted Mediterranean Sea. Trends Ecol. Evol. 25: 250-260.). Environmental variables such as temperature, productivity and distance from the Strait of Gibraltar have been shown to be causes of fish species richness distribution (Ben Rais Lasram et al. 2009Ben Rais Lasram F., Guilhaumon F., Mouillot D. 2009. Fish diversity patterns in the Mediterranean Sea: deviations from a mid-domain model. Mar. Ecol. Prog. Ser. 376: 253-267., Meléndez et al. 2017Meléndez M.J., Báez J.C., Serna-Quintero J.M., et al. 2017. Historical and ecological drivers of the spatial pattern of Chondrichthyes species richness in the Mediterranean Sea. PLoS ONE 12: e1075699.). However, this high biodiversity is presently threatened by the combined action of anthropogenic impacts, introduction of alien species and climate change (Bianchi et al. 2012Bianchi C.N., Morri C., Chiantore M., et al. 2012. Mediterranean Sea biodiversity between the legacy from the past and a future of change. In: Stambler N. (ed), Life in the Mediterranean Sea: a look at habitat changes. Nova Science Publishers, New York, pp. 1-55.). Among human activities, fisheries are one of the most important factors affecting marine resources and ecosystems.

It is well known that fisheries have profoundly modified the structure of marine ecosystems (Dayton et al. 1995Dayton P.K., Thrush S.F., Agardy M.T., et al. 1995. Environmental effects of marine fishing. Aquat. Conserv. 5: 205-232., Hall 1999Hall S.J. 1999. The Effects of Fishing on Marine Ecosystems and Communities. Blackwell Science, Oxford. 274 pp., Kaiser and de Groot 2000Kaiser M.J., de Groot S.J. 2000. The effects of fishing on non-target species and habitats. Biological, conservation and socio-economics issues. Blackwell Science, Oxford, 399 pp.). Effects of fishing on marine ecosystems include shifts in the food-web structure due to changes in predator-prey relationships (Kaiser et al. 2002Kaiser M.J., Collie J.S., Hall S.J., et al. 2002. Modification of marine habitats by trawling activities: prognosis and solutions. Fish Fish. 3: 114-136.); changes in size structure due to vulnerability and selection of fishing for large individuals (Gislason 2002Gislason H. 2002. The effects of fishing on non-target species and ecosystem structure and function. In: Sinclair M., Valdimarsson G. (eds), Responsible Fisheries in the Marine Ecosystem. CAB International, Wallingford, pp. 255-274., Jennings and Dulvy 2005Jennings S., Dulvy N.K. 2005. Reference points and reference directions for size-based indicators of community structure. ICES J. Mar. Sci. 62: 397-404., Daan et al. 2005Daan N., Gislason H., Pope J.G., et al. 2005. Changes in the North Sea fish community: evidence of indirect effects of fishing? ICES J. Mar. Sci. 62: 177-188.); genetic selection of species with particular life-history traits, such as a higher growth rate and earlier age-at-maturity (Fromentin and Fonteneau 2001Fromentin J.M., Fonteneau A. 2001. Fishing effects and life history traits: A case study comparing tropical versus temperate tunas. Fish. Res. 53: 133-150., Jørgensen et al. 2007Jørgensen C., Enberg K., Dunlop E.S., et al. 2007. Managing Evolving Fish Stocks. Science 318: 1247-1248.); changes in the spatial distribution of target species (e.g. Ciannelli et al. 2013Ciannelli L., Fisher J.A.D., Skern-Mauritzen M., et al. 2013. Theory, consequences and evidence of eroding population spatial structure in harvested marine fishes: a review. Mar. Ecol. Prog. Ser. 480: 227-243.); effects on the population of non-target species (Pranovi et al. 2001Pranovi F., Raicevich S., Franceschini G., et al. 2001. Discard analysis and damage to non-target species in the ‘rapido’ trawl fishery. Mar. Biol. 139: 863-875., Ordines et al. 2014Ordines F., Farriols M.T., Lleonart J., et al. 2014. Biology and population dynamics of by-catch fish species of the bottom trawl fishery in the western Mediterranean. Mediterr. Mar. Sci. 15: 613-625.); and decrease of habitat complexity and changes on the benthic community structure (e.g. Callaway et al. 2002Callaway R., Alsvâg J., de Boois I., et al. 2002. Diversity and community structure of epibenthic invertebrates and fish in the North Sea. ICES J. Mar. Sci. 59: 1199-1214.).

The natural resources of the Mediterranean have been subject to human exploitation since ancient times, when coastal communities started to use different fishing gears, some of which are still in use (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.). Dramatic long-term changes in marine communities took place before the industrialization of fisheries that occurred in the 1950s, and have already been documented in some areas, such as the Adriatic Sea (Fortibuoni et al. 2010Fortibuoni T., Libralato S., Raicevich S., et al. 2010. Coding Early Naturalists’ Accounts into Long-Term Fish Community Changes in the Adriatic Sea (1800-2000). PLoS ONE 5: e15502.). Until 1950, the exploitation of Mediterranean resources was limited to fishing areas shallower than 200 m depth. In the last few decades, with the decline of stocks on the continental shelf, increasing market demand and the introduction of new technologies, trawl fisheries have expanded offshore and towards the deeper waters of the continental slope (Roberts 2002Roberts C.M. 2002. Deep impact: the rising toll of fishing in the deep sea. Trends Ecol. Evol. 17: 242-245., Morato et al. 2006Morato T., Watson R., Pitcher T.J., et al. 2006. Fishing down the deep. Fish Fish. 7: 24-34.) to target valuable resources such as red shrimps (e.g. Demestre and Martín 1993Demestre M., Martín P. 1993. Optimum exploitation of a demersal resource in the western Mediterranean: the fishery of the deep-water shrimp Aristeus antennatus (Risso, 1816). Sci. Mar. 57: 175-182., Guijarro et al. 2008Guijarro B., Massutí E., Moranta J., et al. 2008. Population dynamics of the red shrimp Aristeus antennatus in the Balearic Islands (western Mediterranean): Short spatio-temporal differences and influence of environmental factors. J. Mar. Syst. 71: 385-402., Masnadi et al. 2018Masnadi F., Criscoli A., Lanteri L., et al. 2018. Effects of environmental and anthropogenic drivers on the spatial distribution of deep-sea shrimps in the Ligurian and Tyrrhenian Seas (NW Mediterranean). Hydrobiologia 816: 165-178.).

In this area, fisheries are assessed within the framework of the General Fisheries Commission for the Mediterranean (GFCM), the regional fisheries management organization of the Mediterranean. Of the 27 Mediterranean stocks of fishing target species assessed by the GFCM in its last report, about 80% were considered overexploited (GFCM 2016General Fisheries Commission for the Mediterranean (GFCM). 2016. Report of the Working Group on Stock Assessment of Demersal Species (WGSAD). Rome. ). The presence of a high diversity of species and the absence of large monospecific stocks comparable to those inhabiting some wide areas of the open oceans are characteristic of the Mediterranean demersal fisheries (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.). Assessment at a community level is therefore crucial, particularly due to the multispecies nature of the bottom trawl fishery and also because a decline in the diversity of demersal assemblages has been reported due to fishing exploitation (e.g. Ungaro et al. 1998Ungaro N., Marano G., Marsan R., et al. 1998. Demersal fish assemblage biodiversity as an index of fishery resources exploitation. Ital. J. Zool. 65: 511-516., Sabatini et al. 2013Sabatini A., Locci I., Deiana A.M., et al. 2013. Temporal trends in biodiversity of the middle-slope assemblages in Sardinian seas (Central-Western Mediterranean). J. Mar. Biol. Ass. U.K. 93: 1739-1752., 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.). Assessment at a community level is also a requirement for the implementation of an ecosystem-based management of fisheries (Browman and Stergiou 2004Browman H.I., Stergiou K.I. 2004. Perspectives on ecosystem-based approaches to the management of marine resources. Mar. Ecol. Prog. Ser. 274: 269-303.).

The aim of this work is to study the demersal fish diversity pattern in the Mediterranean at a large spatial and temporal scale and to assess whether this pattern is being affected by the general fishing overexploitation of demersal resources in the area. To do so, we used fishery-independent data collected under the framework of the MEDITS trawl surveys carried out during the last 20 years. The detected trends were compared with the spatio-temporal variation in bottom trawl fishing effort in the Mediterranean Sea.

MATERIALS AND METHODSTop

Data

Demersal fish were collected during MEDITS bottom trawl surveys conducted from 1994 to 2015 in 14 geographical sub-areas (GSAs) along the European coasts of the Mediterranean Sea. Some GSAs have gaps in their sampling years: i) GSA 5 started sampling in 2001; ii) there are no data in 2002 for GSA 8 (technical problem of the boat); and iii) there are no data for 2002, 2007, 2009-2013 and 2015 for GSAs 20, 22 and 23. Sampling was performed during spring-summer in daylight hours using the GOC73 experimental gear, whose efficiency for catching demersal species has been tested by Fiorentini et al. (1999)Fiorentini L., Dremière P.Y., Leonori I., et al. 1999. Efficiency of the bottom trawl used for the Mediterranean international trawl survey (MEDITS): Efficacite du chalut de fond utilise pour le programme international d’evaluation des ressources halieutiques de Mediterranee (MEDITS). Aquat. Living. Resour. 12: 187-205. and Dremière et al. (1999)Dremière P.Y., Fiorentini L., Cosimi G., et al. 1999. Escapement from the main body of the bottom trawl used for the Mediterranean international trawl survey (MEDITS). Aquat. Living Resour. 12: 207-217.. For more details about the sampling strategy and protocol see Bertrand et al. (2002)Bertrand J.A., Gil de Sola L., Papakonstantinou C., et al. 2000. Contribution on the distribution of elasmobranchs in the Mediterranean (from the MEDITS surveys). Biol. Mar. Mediterr. 7: 385-399. and the MEDITS handbook, instruction manual version 9 (MEDITS Working Group 2017MEDITS Working Group. 2017. MEDITS-Handbook, Version n. 9. MEDITS Working Group, 106 pp. http://www.sibm.it/MEDITS%202011/principaledownload.htm).

A total of 17540 hauls performed between 46 and 866 m depth were analysed (Table 1, Fig. 1). Hauls shallower than 46 m depth were excluded from the analysis because they could not be found for all GSAs. The catch of each sample was sorted, identified to species level, counted, weighed and standardized to square km by using the horizontal opening of the net and the distance covered in each haul. Species with a pelagic or mesopelagic behaviour, like most species of the families Myctophydae (e.g. Ceratoscopelus maderensis) and Cupleidae (e.g. Engraulis encrasicolus), were excluded from the analysis. A species accumulation curve for each GSA was performed and we confirmed that differences in number of species were not due to differences in the number of hauls considered for each GSA (Table 1, Fig. S1).

Table 1. – Name of the areas and number of samples analysed for each GSA.

GSA Area Samples
GSA 1 Northern Alboran Sea 743
GSA 5 Balearic Islands 650
GSA 6 Northern Spain 1459
GSA 7 Gulf of Lions 1143
GSA 8 Corsica 451
GSA 9 Ligurian, northern and central Tyrrhenian Sea 2468
GSA 10 Central and southern Tyrrhenian Sea 1333
GSA 11 Sardinia 1811
GSA 16 Strait of Sicily 1492
GSA 17 Northern Adriatic Sea 2296
GSA 18 Southern Adriatic Sea 1684
GSA 20 Eastern Ionian Sea 308
GSA 22 Aegean Sea 1427
GSA 23 Crete 175

figure

Full size image

Fig. 1. – Map of the study area showing the 17540 hauls sampled between 1994 and 2015 in 15 geographical sub-areas (GSAs). Each colour corresponds to one of the GSAs defined by the GFCM (http://www.gfcm.org). The smaller map shows the location of the Mediterranean and its connections to the Atlantic Ocean through the Gibraltar Strait (A), the Black Sea through the Dardanelles Strait (B) and the Red Sea through the artificial Suez Channel (C).

Fish assemblages and diversity

Cluster analysis was used to analyse the structure of demersal fish assemblages and to identify different assemblages according to depth strata in each GSA. Relationships among samples were detected by hierarchical agglomerative clustering with group-average linkage after a forth root transformation of the data. The distance used to make groups was the Bray-Curtis similarity. These analyses were performed using PRIMER 7 (Clarke et al. 2014Clarke K.R., Gorley R.N., Somerfield P.J., et al. 2014. Change in marine communities: an approach to statistical analysis and interpretation. PRIMER-E, Plymouth, 260 pp.). The calculus of diversity indices explained below was made taking into account the groups of samples obtained from the cluster analysis.

The N90 diversity index was calculated following the procedure described by Farriols et al. (2015)Farriols M.T., Ordines F., Hidalgo M., et al. 2015. N90 index: a new approach to biodiversity based on similarity and sensitive to direct and indirect fishing impact. Ecol. Indic. 52: 245-255.. It is the mean number of species contributing up to 90% of within-group similarity calculated from abundance data expressed as N km–2 and assigned a priori to groups. The calculation of N90 starts with the calculation of the contribution of each species to the within-group similarity using the Bray-Curtis similarity index (Bray and Curtis 1957Bray J.R., Curtis J.T. 1957. An ordination of the upland forest communities of southern Wisconsin. Ecol. Monogr. 27: 325-349.), as proposed by Clarke (1993)Clarke K.R. 1993. Non-parametric multivariate analyses of changes in community structure. Aust. J. Ecol. 18: 117-143.:

S jk (i)=100× 2×min( y ij , y ik ) Σ i=1 p ( y ij + y ik )

where yij is the abundance of the species i at the sampling site j, yik is the abundance of the species i at the sampling site k, p is the total number of species in j and k, and min (yij, yik) is the minimum value of the abundance of species i between the sampling sites j and k, also considering zeros.

The contribution of each species i to the total similarity of the group Si is the mean value of Sjk (i) for the assigned group, and the total similarity in a group (Sim) is the addition of Si for all the species in the group:

Sim= Σ i=1 p S i .

Then, the contribution of Si is calculated as a percentage of Sim. Species contributions are calculated for each re-sampling in a jack-knife routine, which removes a number of samples each time, producing lists of contribution to similarity by species in each re-sampling. Because the groups of samples for each GSA, strata and year were large, we removed 10% of the samples in each re-sampling with a 50% replacement. That is, 50% of samples removed in a re-sampling must be different from previous ones. In this way, we obtain values of deviation for N90 other than 0 for groups with a large number of observations. The N90 diversity index is the mean number of species which accumulate up to 90% of within-group similarity in all the re-samplings. N90 was calculated using R scripts, version 3.1.1 (R Core Team 2014R Core Team. 2014. R: A Language and Environment for Statistical Computing. http://www.r-project.org/). Similarity percentage analysis (SIMPER) for each group of samples was also undertaken to see their species composition.

Diversity indices, such as species richness (S) and Pielou evenness (J’), which have shown some kind of response to fishing impact for demersal fish assemblages in the Mediterranean (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.), were also included in this work. These traditional indices are also helpful for comparison with previous works. S is the raw number of species in each haul and J’ was calculated as follows:

J = Σ i=1 S p i ln p i lnS ;

where pi is the proportion of all individuals belonging to species i and S is the total number of species in the sample.

Fishing effort

Information on annual fishing effort was collected from the working group reports of the GFCM (http://www.fao.org/gfcm/data/safs/en/) and the Scientific, Technical and Economic Committee for Fisheries (STECF, https://stecf.jrc.ec.europa.eu/reports/medbs). Fishing effort data were compiled by trawl fleet targeting different species. The units vary between the different reports, being mainly provided in terms of number of vessels, kilowatts per days at sea and gross tonnage per days at sea (see Table S1).

To estimate fishing effort in each depth stratum obtained from cluster analysis, the strata were associated with the main target species of the fleets. Because target species varied between GSAs, we considered i) Mullus barbatus or Mullus surmuletus for the continental shelf; ii) Nephrops norvegicus or Parapenaeus longirostris for the shelf break/upper slope; and iii) Aristeus antennatus or Aristaeomorpha foliacea for the lower slope.

To compare temporal trends in fishing effort and demersal fish diversity, the longest series of fishing effort available for each GSA and depth stratum regardless of the kind of units were selected. When we found no values of fishing effort for a certain GSA, experts were contacted to obtain a trend in number of vessels in that area.

Temporal and spatial analysis

In order to analyse temporal trends in diversity, linear regressions were fitted to the mean values of S, J’ and N90 for each year, GSA and depth stratum. Linear regression analyses with the annual values of fishing effort in each GSA (see Fishing effort section in Materials and Methods) and depth stratum were also performed. The exploration of the scatter plots of the time series together with the comparison of Pearson (assuming linear pattern) and Spearman (suitable also for other monotonic patterns than the linear) correlation coefficients were done. The values of both correlation coefficients were similar, indicating that the detected trends could be fitted using a simple linear model. Thus, the linear regression and the Pearson coefficient of correlation were presented along with the coefficient of determination (i.e. variance explained). These analyses were carried out with R, version 3.1.1 (R Core Team 2014R Core Team. 2014. R: A Language and Environment for Statistical Computing. http://www.r-project.org/).

In order to observe spatial differences in diversity by GSA, time series of mean values and standard deviation of each diversity index (see Data section for years included in each GSA) were plotted. For those series with a significant temporal trend, the diversity values at the beginning and the end of the time series were plotted instead of mean values and standard deviation.

SIMPER analysis for each group of samples from N90 was also performed to see differences in species composition in each GSA. The percentage of contribution of each species to within-group similarity was calculated as the mean value of species contributions to similarity, taking all groups of observations by year and stratum for each GSA into account.

RESULTSTop

Community structure

Results from cluster analysis detecting main fish assemblages for each GSA are shown in Figure 2. Three groups of samples were selected from most GSAs, corresponding to a level of similarity of between 30% and 40%. Maximum, minimum and mean depths of each cluster group per GSA were obtained. According to these depth values, samples were grouped in three different depth strata: shelf, shelf break/upper slope and lower slope (Table 2, Fig. 2). For GSAs 17 and 23 only two groups were selected. GSA 17 has no samples below 350 m, and GSA 23 has a negligible sample number over 496 m (Table 2). For GSAs 7 and 20 samples in the lower slope group were not enough to calculate the N90 throughout the time series, so both lower slope groups were omitted from the temporal and spatial analysis.

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Fig. 2. – Cluster of samples obtained from MEDITS surveys. The data used for the cluster analysis were the double root transformation of abundances of demersal fish species for each sample during the sampling period of each GSA. The dashed line shows the similarity level used to classify the depth strata: shelf, shelf break/upper slope (SB/US) and lower slope. The number in brackets represents the number of samples in each depth stratum.

Table 2. – Minimum, maximum and mean depth of samples grouped in each depth stratum (shelf, shelf break/upper slope and lower slope) from cluster analysis for each GSA.

GSA Strata Minimum depth Maximum depth Mean depth
GSA 1 Shelf 50 168 76
Shelf break/upper slope 118 373 203
Lower slope 219 807 519
GSA 5 Shelf 46 258 108
Shelf break/upper slope 316 698 402
Lower slope 581 756 678
GSA 6 Shelf 50 147 84
Shelf break/upper slope 82 392 183
Lower slope 257 798 505
GSA 7 Shelf 55 155 93
Shelf break/upper slope 214 705 421
Lower slope 414 866 699
GSA 8 Shelf 56 158 94
Shelf break/upper slope 261 510 350
Lower slope 405 583 510
GSA 9 Shelf 50 399 118
Shelf break/upper slope 141 640 340
Lower slope 364 757 559
GSA 10 Shelf 50 350 125
Shelf break/upper slope 170 616 365
Lower slope 339 693 594
GSA 11 Shelf 50 292 97
Shelf break/upper slope 109 357 198
Lower slope 219 725 496
GSA 16 Shelf 51 220 94
Shelf break/upper slope 108 654 333
Lower slope 436 794 630
GSA 17 Shelf 50 235 91
Shelf break/upper slope 62 332 180
GSA 18 Shelf 50 349 104
Shelf break/upper slope 111 397 270
Lower slope 247 732 501
GSA 20 Shelf 55 189 94
Shelf break/upper slope 149 664 379
Lower slope 483 800 654
GSA 22 Shelf 50 340 109
Shelf break/upper slope 107 708 336
Lower slope 337 791 579
GSA 23 Shelf 57 155 91
Shelf break/upper slope 115 496 245

In 9 out of the 12 GSAs showing lower slope samples, samples from the shelf break/upper slope clustered with samples from the lower slope. The exceptions were GSAs 6, 11 and 22, where samples from the shelf break/upper slope clustered with those from the continental shelf. Minimum, maximum and mean depths for each group of samples from cluster analysis are shown in Table 2. Mean depth of continental shelf samples ranged from 76 m in GSA 1 to 125 m in GSA 10, while for the shelf break/upper slope they ranged from 180 m in GSA 17 to 421 m in GSA 7, and for the lower slope between 496 m in GSA 11 and 699 m in GSA 7.

Temporal trends

Although the analysis of temporal evolution for N90, S and J’ showed no significance in most GSAs and depth strata (Table 3, Fig. 3 and Figs S2-S4), some trends were detected. N90 increased on the continental shelf of GSAs 1, 8 and 20, the shelf break/upper slope of GSAs 7, 11 and 18 and the lower slope of GSA 11 and only decreased on the shelf break/upper slope of GSA 5 (Table 3, Fig. 3 and Fig. S2). S increased on the continental shelf of GSAs 8 and 10, the shelf break/upper slope of GSAs 7, 8, 10 and 22 and the lower slope of GSAs 8, 10, 11, 16 and 18 and decreased on the shelf break/upper slope of GSA 17 and the lower slope of GSA 9 (Table 3, Fig. 3 and Fig. S3). J’ increased on the continental shelf of GSA 7, the shelf break/upper slope of GSAs 7 and 8 and the lower slope of GSA 11 and decreased on the continental shelf of GSAs 10 and 16, the shelf break/upper slope of GSAs 5 and 22 and the lower slope of GSAs 1 and 8 (Table 3, Fig. 3 and Fig. S4). These trends were confirmed when the last year of the time series (2014) for GSAs 20, 22 and 23 was excluded (Table 3).

Table 3. – Results of linear regression analysis of the time series for N90, species richness (S) and Pielou evenness (J’) for each GSA and depth stratum (shelf, shelf break/upper slope and lower slope). Slope values of the adjusted linear regressions (b), adjusted R-squared values and p-values (p) are presented. *, p <0.05; **, p <0.01; ***, p <0.001. For GSAs 20, 22 and 23: a results for time series 1994-2006; and b results for time series 1994-2014.

Index GSA Shelf Shelf break/upper slope Lower slope
b Adjusted R2 p b Adjusted R2 p b Adjusted R2 p
N90 GSA 1 0.209 0.051 * 0.047 –0.050 0.383 0.001 0.430 0.955
GSA 5 –0.090 –0.010 0.287 –0.286 0.473 ** 0.037 –0.052 0.565
GSA 6 –0.027 –0.029 0.683 0.063 –0.034 0.321 –0.112 0.031 0.059
GSA 7 0.041 0.200 0.462 0.079 0.391 *
GSA 8 0.195 –0.052 ** 0.089 0.294 0.070 0.041 0.376 0.175
GSA 9 –0.005 –0.044 0.923 –0.027 0.105 0.483 –0.013 –0.049 0.493
GSA 10 –0.101 0.463 0.128 0.068 0.005 0.121 –0.014 0.025 0.523
GSA 11 0.084 –0.031 0.136 0.090 0.119 * 0.083 0.338 *
GSA 16 –0.066 0.455 0.398 0.019 0.025 0.593 0.012 –0.044 0.540
GSA 17 0.012 0.088 0.540 0.013 0.083 0.798
GSA 18 –0.036 0.004 0.647 0.141 –0.046 * –0.036 0.031 0.111
GSA 20a 0.487 0.503 ** 0.115 –0.066 0.553
GSA 20b 0.315 –0.066 ** 0.225 0.007 0.069
GSA 22a 0.054 –0.065 0.577 –0.110 0.023 0.289 –0.053 –0.003 0.351
GSA 22b 0.064 –0.070 0.279 0.044 0.344 0.579 0.015 0.045 0.706
GSA 23a 0.075 0.061 0.231 –0.156 –0.007 0.360
GSA 23b 0.099 –0.090 0.098 0.038 0.152 0.740
S GSA 1 –0.044 –0.040 0.658 0.010 –0.049 0.898 0.036 0.005 0.305
GSA 5 0.013 –0.082 0.914 –0.136 0.092 0.154 –0.089 –0.005 0.351
GSA 6 –0.030 –0.044 0.728 0.090 0.018 0.254 –0.017 –0.041 0.674
GSA 7 –0.055 –0.017 0.427 0.142 0.331 **
GSA 8 0.161 0.169 * 0.149 0.180 * 0.134 0.203 *
GSA 9 –0.027 –0.026 0.504 –0.023 –0.026 0.505 –0.061 0.151 *
GSA 10 0.122 0.138 * 0.197 0.411 *** 0.165 0.336 **
GSA 11 0.064 0.026 0.226 0.041 –0.017 0.433 0.080 0.227 *
GSA 16 0.026 –0.035 0.600 0.112 0.101 0.082 0.105 0.145 *
GSA 17 0.010 –0.048 0.861 –0.130 0.196 *
GSA 18 0.041 –0.031 0.550 0.109 0.055 0.152 0.142 0.278 **
GSA 20a 0.297 0.149 0.118 0.582 0.492 **
GSA 20b 0.166 0.072 0.182 0.230 0.117 0.136
GSA 22a 0.099 –0.042 0.471 0.359 0.410 * –0.251 0.465 *
GSA 22b 0.089 0.019 0.286 0.304 0.546 ** –0.031 –0.077 0.712
GSA 23a –0.021 –0.111 0.957 –0.095 –0.088 0.742
GSA 23b 0.274 0.035 0.257 0.134 –0.034 0.466
J’ GSA 1 0.003 0.051 0.160 0.000 –0.050 0.988 –0.004 0.430 ***
GSA 5 –0.003 –0.010 0.370 –0.020 0.473 ** 0.002 –0.052 0.562
GSA 6 0.001 –0.029 0.533 0.001 –0.034 0.589 –0.002 0.031 0.210
GSA 7 0.004 0.200 * 0.007 0.391 **
GSA 8 0.000 –0.052 0.937 0.004 0.294 ** –0.004 0.376 **
GSA 9 0.001 –0.044 0.745 0.002 0.105 0.077 0.000 –0.049 0.874
GSA 10 –0.008 0.463 *** 0.002 0.005 0.304 –0.002 0.025 0.229
GSA 11 –0.001 –0.031 0.554 0.004 0.119 0.064 0.004 0.338 **
GSA 16 –0.005 0.455 *** 0.002 0.025 0.230 0.000 –0.044 0.729
GSA 17 –0.002 0.088 0.098 –0.004 0.083 0.104
GSA 18 0.002 0.004 0.312 –0.001 –0.046 0.790 –0.001 0.031 0.211
GSA 20a –0.003 –0.023 0.406 –0.003 –0.090 0.688
GSA 20b –0.001 –0.066 0.663 0.004 0.007 0.320
GSA 22a –0.002 –0.059 0.549 –0.013 0.673 *** –0.003 –0.042 0.461
GSA 22b 0.001 –0.070 0.710 –0.007 0.344 * –0.004 0.045 0.237
GSA 23a –0.004 –0.065 0.548 –0.018 0.329 *
GSA 23b 0.000 –0.090 0.937 –0.009 0.152 0.093

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Fig. 3. – Trends obtained from linear regression of N90, species richness (S), Pielou evenness (J’) and fishing effort (FE) per GSA and depth stratum (shelf, shelf break/upper slope and lower slope). Trends obtained from the analysis are in continuous lines and trends from expert knowledge in discontinuous line and grey background. n.s., non-significant trends; -, no data available. For GSAs 20, 22 and 23 trends of time series 1994-2006 and 1994-2014 are presented. When results of trends differ, trends from 1994-2006 are presented on the left and trends from 1994 to 2014 on the right of the cell.

When quantitative analysis in temporal evolution of fishing effort could be made, the detected significance mainly showed a decreasing trend (Table 4, Fig. 3). This is the case of the continental shelf in GSAs 1, 5, 6 and 7, the shelf break/upper slope in GSAs 1, 11, 17 and 18 and the lower slope in GSAs 5 and 11. It increased only on the continental shelf and the lower slope of GSA 18. Expert knowledge suggested increasing trends in fishing effort for the lower slope in GSAs 20, 22 and 23 and decreasing trends on the continental shelf of GSAs 8, 9, 16, 20, 22 and 23 and on the lower slope of GSAs 1, 7 and 8 (Table 4, Fig. 3).

Table 4. – Results of linear regression analysis of the time series of fishing effort of the longest series available for each GSA and depth stratum (shelf, shelf break/upper slope and lower slope). Slope values of the adjusted linear regressions (b), adjusted R-squared values and p-values (p) are presented. Qualitative values of slopes are obtained from expert knowledge. *, p <0.05; **, p <0.01; ***, p <0.001; ns, non-significant.

GSA Shelf Shelf break/upper slope Lower slope
b Adjusted R2 p b Adjusted R2 p b Adjusted R2 p
GSA 1 –8.800 0.717 * –10.890 0.865 *** Decreasing
GSA 5 –5.118 0.898 *** 7.500 0.163 0.175 –7.530 0.526 **
GSA 6 –11.659 0.808 *** 3.248 0.071 0.204 0.000 0.510 0.117
GSA 7 –13.821 0.765 ** Decreasing
GSA 8 Decreasing Decreasing
GSA 9 Decreasing 1.820 –0.081 0.874 8.109 –0.088 0.669
GSA 10 Increasing ns –7.385 0.197 0.063 Decreasing ns
GSA 11 63.572 0.390 0.058 –13.226 0.372 * –25.227 0.867 ***
GSA 16 Decreasing –4.700 0.167 0.272
GSA 17 9.617 –0.054 0.467 –6.822 0.360 * Decreasing ns
GSA 18 75.448 0.644 ** –14.548 0.581 * 29.516 0.301 *
GSA 20 Decreasing Increasing
GSA 22 Decreasing Increasing
GSA 23 Decreasing Increasing

In 6 of the 7 cases in which an increment of N90 was detected, it coincided with a decrease in fishing effort (Tables 3-4, Fig. 3). Of the 11 cases showing increases in species richness, S, only in 3 cases was the increase in S coupled with a decrease in fishing effort. In 5 cases there was no trend in fishing effort, while in only one case the increase in S was coupled with an increase in fishing effort. In 2 cases, no information on the temporal evolution of fishing effort was available (Tables 3-4, Fig. 3). 10 GSAs showed significant trends in Pielou eveness, J’; in 2 of them J’ increased and fishing effort decreased, while 3 GSAs showed a decrease in both J’ and fishing effort. Two GSAs showed a decrease in J’ coupled with no trend in fishing effort, while no information on fishing effort trend was available in 3 cases (Tables 3-4, Fig. 3).

Spatial patterns

Mean values of N90, S and J’ showed differences between GSAs and depth strata (Fig. 4). Regarding N90, the continental shelf of GSAs 5, 11, 16 and 22 showed higher values than the rest of the GSAs in this depth stratum and even than the shelf break/upper slope and lower slope values. Within the shelf break/upper slope, the highest values of N90 were estimated in GSAs 7, 16, 17, 18, 20 and 22, while on the lower slope the highest values were for GSAs 6, 8 and 18. S showed similar values on the continental shelf of all GSAs, with the exception of GSA 10, which showed a lower value. A similar situation was observed on the shelf break/upper slope, with similar values of S in all GSAs, except for GSA 17 with a lower value, and GSAs 7 and 8, which showed the highest values. On the lower slope, the values of S were similar in all GSAs, with the exception of GSAs 9, 10 and 16, which showed lower values. J’ showed similar values on the continental shelf in all GSAs, except GSAs 9 and 10, which showed lower values. The same scenario was observed on the shelf break/upper slope, with similar values of J’ in all GSAs with the exception of GSAs 1, 5, 6 and 11, which showed lower values. On the lower slope, GSA 11 showed the lowest value of J’, while similar values were obtained in the rest of the GSAs.

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Fig. 4. – Mean values and standard deviations of N90, species richness (S) and Pielou evenness (J’) during the whole time series considered for each GSA and depth strata (shelf, shelf break/upper slope and lower slope). In series with a significant temporal trend, values at the beginning and end of the time series are presented in red. Red arrows point to the last value of the time series. For GSAs 20, 22 and 23 the whole time series were taken into account (1994-2014). Note that in some cases the trend of time series does not match the arrow’s direction (see Table 2).

The similarity percentage (SIMPER) analysis also showed differences in the species contribution between GSAs and depth strata (Tables 5 and 6). The species with the highest percentage contribution to within-group similarity on the continental shelf, shelf break/upper slope and lower slope, respectively, were the following: Serranus hepatus, Gadiculus argenteus and Galeus melastomus in GSA 1; Scyliorhinus canicula, G. argenteus and Phycis blennoides in GSA 5; Merluccius merluccius, Micromesistius poutassou and P. blennoides in GSA 6; Mullus barbatus, G. argenteus and G. melastomus in GSA 8; M. merluccius, G. argenteus and P. blennoides in GSA 9; Glossanodon leioglossus, Chlorophthalmus agassizi and Hymenocephalus italicus in GSA 10; S. hepatus, G. leioglossus and P. blennoides in GSA 11; M. merluccius, G. argenteus and Nezumia sclerorhynchus in GSA 16; M. merluccius, Helicolenus dactylopterus and P. blennoides in GSA 18; and S. hepatus, Argentina sphyraena and N. sclerorhynchus in GSA 22 (Table 5). The species with the highest percentage contribution to within-group similarity were T. minutus on the continental shelf and G. argenteus on the shelf break/upper slope in GSA 7; Lepidotrigla cavillone on the continental shelf and C. agassizi on the shelf break/upper slope in GSA 20; and L. cavillone on the continental shelf and A. sphyraena on the shelf break/upper slope in GSA 23. In GSA 17, M. merluccius was the species with the highest contribution on both the continental shelf and the shelf break/upper slope (Table 5).

Table 5. – Similarity Percentage analysis (SIMPER) summary table of species appearing in the 90% cut-off of within-group similarity. A is the mean abundance (individuals km–2) of each species, and %C is the mean value of the percentage contribution of each species to within-group similarity, taking into account each SIMPER made by group of GSA, depth strata and year. Depth strata are shelf, shelf break/upper slope (SB/US) and lower slope.

GSA 1 Shelf A %C GSA 1 SB/US A %C GSA 1 Lower slope A %C
Serranus hepatus 1629 31 Gadiculus argenteus 7829 37 Galeus melastomus 2533 26
Pagellus acarne 4684 24 Helicolenus dactylopterus 2509 16 Nezumia aequalis 2046 22
Merluccius merluccius 418 8 Micromesistius poutassou 7519 12 Hoplostethus mediterraneus 1460 15
Cepola macrophthalma 687 6 Lepidopus caudatus 6280 9 Coelorinchus caelorhincus 1315 13
Mullus barbatus 1237 6 Merluccius merluccius 1217 8 Phycis blennoides 364 8
Callionymus maculatus 514 3 Phycis blennoides 706 5 Etmopterus spinax 245 3
Arnoglossus laterna 237 3 Scyliorhinus canicula 491 3 Trachyrincus scabrus 744 2
Serranus cabrilla 338 2 Coelorinchus caelorhincus 873 2 Micromesistius poutassou 299 2
Arnoglossus thori 544 2
Scyliorhinus canicula 158 2
Lesueurigobius sanzi 255 1
Trachinus draco 103 1
GSA 5 Shelf A %C GSA 5 SB/US A %C GSA 5 Lower slope A %C
Scyliorhinus canicula 1348 25 Gadiculus argenteus 24060 68 Phycis blennoides 425 30
Serranus hepatus 1464 12 Galeus melastomus 2222 9 Galeus melastomus 440 24
Serranus cabrilla 743 11 Coelorinchus caelorhincus 1592 5 Nezumia aequalis 226 19
Trachinus draco 548 9 Chlorophthalmus agassizi 2906 5 Hymenocephalus italicus 174 7
Mullus surmuletus 1163 6 Phycis blennoides 461 3 Notacanthus bonaparte 55 4
Lepidotrigla cavillone 741 5 Helicolenus dactylopterus 506 3 Lepidion lepidion 93 4
Merluccius merluccius 1007 5 Symphurus ligulatus 45 3
Glossanodon leioglossus 28236 5
Chelidonichthys cuculus 893 5
Trigloporus lastoviza 448 4
Scorpaena notata 163 1
Pagellus erythrinus 179 1
Mullus barbatus 312 1
GSA 6 Shelf A %C GSA 6 SB/US A %C GSA 6 Lower slope A %C
Merluccius merluccius 2955 45 Micromesistius poutassou 57532 40 Phycis blennoides 698 43
Trisopterus minutus 2248 19 Gadiculus argenteus 9766 20 Galeus melastomus 381 22
Cepola macrophthalma 514 7 Merluccius merluccius 4285 19 Micromesistius poutassou 300 4
Mullus barbatus 487 7 Trisopterus minutus 1754 6 Nezumia aequalis 79 4
Serranus hepatus 408 7 Helicolenus dactylopterus 914 3 Trachyrincus scabrus 166 4
Lepidotrigla cavillone 250 3 Scyliorhinus canicula 811 3 Hymenocephalus italicus 55 3
Pagellus erythrinus 98 1 Gadiculus argenteus 422 3
Lophius budegassa 56 1 Symphurus nigrescens 67 2
Scyliorhinus canicula 130 2
Coelorinchus caelorhincus 128 2
Gaidropsarus biscayensis 58 2
GSA 7 Shelf A %C GSA 7 SB/US A %C GSA 7 Lower slope A %C
Trisopterus minutus 6435 47 Gadiculus argenteus 6804 39
Merluccius merluccius 3239 19 Galeus melastomus 1470 11
Eutrigla gurnardus 1651 12 Micromesistius poutassou 7815 10
Serranus hepatus 896 5 Phycis blennoides 561 8
Lepidotrigla cavillone 1297 4 Coelorinchus caelorhincus 1068 7
Cepola macrophthalma 561 2 Helicolenus dactylopterus 719 7
Lesueurigobius friesii 513 2 Lepidorhombus boscii 417 6
Trigla lyra 565 5
GSA 8 Shelf A %C GSA 8 SB/US A %C GSA 8 Lower slope A %C
Mullus barbatus 4127 20 Gadiculus argenteus 17009 47 Galeus melastomus 1246 29
Lepidotrigla cavillone 1287 19 Galeus melastomus 2979 11 Hymenocephalus italicus 535 19
Scyliorhinus canicula 941 15 Chlorophthalmus agassizi 4386 9 Coelorinchus caelorhincus 405 12
Serranus hepatus 1157 14 Micromesistius poutassou 2373 8 Phycis blennoides 248 8
Pagellus erythrinus 538 10 Scyliorhinus canicula 1119 7 Helicolenus dactylopterus 169 6
Chelidonichthys cuculus 352 5 Lepidotrigla dieuzeidei 1147 4 Nezumia sclerorhynchus 223 6
Serranus cabrilla 283 3 Argentina sphyraena 842 3 Hoplostethus mediterraneus 254 6
Mullus surmuletus 373 2 Etmopterus spinax 196 4
Trigloporus lastoviza 162 1 Chlorophthalmus agassizi 280 4
Lepidotrigla dieuzeidei 432 1
GSA 9 Shelf A %C GSA 9 SB/US A %C GSA 9 Lower slope A %C
Merluccius merluccius 4334 55 Gadiculus argenteus 5253 52 Phycis blennoides 490 27
Trisopterus minutus 1076 16 Merluccius merluccius 4894 13 Hymenocephalus italicus 527 27
Mullus barbatus 551 8 Phycis blennoides 564 12 Galeus melastomus 439 22
Serranus hepatus 274 4 Chlorophthalmus agassizi 896 6 Nezumia sclerorhynchus 239 9
Lepidotrigla cavillone 271 4 Galeus melastomus 289 4 Etmopterus spinax 105 7
Arnoglossus laterna 110 3 Micromesistius poutassou 1322 4
Glossanodon leioglossus 4801 2
GSA 10 Shelf A %C GSA 10 SB/US A %C GSA 10 Lower slope A %C
Glossanodon leioglossus 16087 12 Chlorophthalmus agassizi 11376 61 Hymenocephalus italicus 1152 49
Merluccius merluccius 2725 57 Phycis blennoides 479 8 Nezumia sclerorhynchus 351 19
Lepidotrigla cavillone 598 3 Hymenocephalus italicus 1128 7 Phycis blennoides 199 11
Mullus barbatus 502 7 Gadiculus argenteus 1290 7 Galeus melastomus 255 10
Serranus hepatus 490 4 Merluccius merluccius 1039 6 Etmopterus spinax 70 4
Lepidopus caudatus 463 2 Helicolenus dactylopterus 226 2
Trisopterus minutus 236 2
Cepola macrophthalma 91 3
Arnoglossus laterna 80 2
GSA 11 Shelf A %C GSA 11 SB/US A %C GSA 11 Lower slope A %C
Serranus hepatus 1751 26 Glossanodon leioglossus 77021 51 Phycis blennoides 879 31
Merluccius merluccius 2903 22 Merluccius merluccius 6301 13 Hymenocephalus italicus 818 20
Lepidotrigla cavillone 1131 9 Trisopterus minutus 5084 11 Gadiculus argenteus 8361 18
Trisopterus minutus 2474 9 Argentina sphyraena 4673 9 Galeus melastomus 987 12
Mullus barbatus 840 7 Lepidotrigla dieuzeidei 1590 5 Chlorophthalmus agassizi 3734 5
Serranus cabrilla 344 4 Scyliorhinus canicula 1175 4 Etmopterus spinax 122 3
Chelidonichthys cuculus 368 3 Merluccius merluccius 848 2
Scyliorhinus canicula 335 3
Mullus surmuletus 200 2
Trigloporus lastoviza 191 2
Trachinus draco 105 2
Argentina sphyraena 2800 2
Citharus linguatula 227 1
GSA 16 Shelf A %C GSA 16 SB/US A %C GSA 16 Lower slope A %C
Merluccius merluccius 970 25 Gadiculus argenteus 5100 26 Nezumia sclerorhynchus 982 40
Serranus hepatus 785 11 Merluccius merluccius 1622 20 Hymenocephalus italicus 573 19
Lepidotrigla cavillone 1327 10 Chlorophthalmus agassizi 3368 14 Galeus melastomus 318 17
Chelidonichthys cuculus 548 7 Coelorinchus caelorhincus 1231 10 Nezumia aequalis 383 7
Mullus barbatus 580 7 Hymenocephalus italicus 768 8 Hoplostethus mediterraneus 134 5
Mullus surmuletus 261 5 Phycis blennoides 314 7 Phycis blennoides 79 3
Raja miraletus 302 5 Lepidopus caudatus 2220 6
Serranus cabrilla 181 4
Citharus linguatula 234 3
Argentina sphyraena 912 2
Trisopterus minutus 280 2
Trigloporus lastoviza 131 2
Arnoglossus laterna 116 2
Lepidotrigla dieuzeidei 588 2
Scyliorhinus canicula 102 2
Zeus faber 52 2
Trachinus draco 77 1
GSA 17 Shelf A %C GSA 17 SB/US A %C GSA 17 Lower slope A %C
Merluccius merluccius 931 28 Merluccius merluccius 2155 43
Mullus barbatus 1344 20 Micromesistius poutassou 3434 33
Trisopterus minutus 861 18 Trisopterus minutus 312 5
Serranus hepatus 1150 13 Lepidopus caudatus 489 5
Cepola macrophthalma 327 6 Gadiculus argenteus 379 3
Lepidotrigla cavillone 359 2 Lesueurigobius friesii 201 2
Merlangius merlangus 161 2
Eutrigla gurnardus 108 2
GSA 18 Shelf A %C GSA 18 SB/US A %C GSA 18 Lower slope A %C
Merluccius merluccius 939 43 Helicolenus dactylopterus 466 11 Phycis blennoides 405 20
Trisopterus minutus 424 20 Chlorophthalmus agassizi 663 10 Nezumia sclerorhynchus 305 14
Mullus barbatus 317 7 Micromesistius poutassou 823 8 Galeus melastomus 282 13
Serranus hepatus 175 6 Glossanodon leioglossus 2993 7 Hoplostethus mediterraneus 319 11
Lepidotrigla cavillone 376 4 Argentina sphyraena 1378 6 Coelorinchus caelorhincus 318 10
Chelidonichthys cuculus 232 4 Lepidopus caudatus 338 4 Hymenocephalus italicus 254 10
Arnoglossus laterna 106 3 Gadiculus argenteus 587 4 Etmopterus spinax 167 9
Cepola macrophthalma 81 2 Phycis blennoides 109 4 Helicolenus dactylopterus 117 4
Lesueurigobius friesii 74 2 Chelidonichthys cuculus 470 4
Scyliorhinus canicula 146 3
Lepidorhombus boscii 65 2
Arnoglossus rueppelii 153 2
Lepidotrigla cavillone 238 2
Merluccius merluccius 895 25
GSA 20 Shelf A %C GSA 20 SB/US A %C GSA 20 Lower slope A %C
Lepidotrigla cavillone 1299 26 Chlorophthalmus agassizi 6565 28
Serranus hepatus 1416 24 Gadiculus argenteus 9073 24
Mullus barbatus 1145 15 Argentina sphyraena 3257 14
Merluccius merluccius 527 11 Merluccius merluccius 860 6
Arnoglossus laterna 329 5 Lepidopus caudatus 444 4
Trisopterus minutus 359 3 Helicolenus dactylopterus 361 4
Pagellus erythrinus 272 2 Scyliorhinus canicula 187 3
Argentina sphyraena 2318 2 Peristedion cataphractum 714 2
Citharus linguatula 142 2 Coelorinchus caelorhincus 588 2
Hymenocephalus italicus 677 2
Phycis blennoides 129 2
GSA 22 Shelf A %C GSA 22 SB/US A %C GSA 22 Lower slope A %C
Serranus hepatus 1774 19 Argentina sphyraena 12691 27 Nezumia sclerorhynchus 626 43
Trisopterus minutus 1666 13 Gadiculus argenteus 5823 18 Hymenocephalus italicus 575 14
Merluccius merluccius 1890 11 Merluccius merluccius 505 10 Trachyrincus scabrus 251 9
Citharus linguatula 569 11 Micromesistius poutassou 2037 7 Phycis blennoides 119 8
Lepidotrigla cavillone 887 10 Chlorophthalmus agassizi 5423 6 Coelorinchus caelorhincus 317 8
Mullus barbatus 785 5 Phycis blennoides 169 5 Hoplostethus mediterraneus 105 6
Chelidonichthys cuculus 968 4 Scyliorhinus canicula 372 5 Etmopterus spinax 66 4
Lophius budegassa 178 4 Lepidorhombus boscii 151 4
Argentina sphyraena 3244 4 Coelorinchus caelorhincus 1395 4
Serranus cabrilla 221 3 Hymenocephalus italicus 801 3
Scyliorhinus canicula 195 3 Helicolenus dactylopterus 148 2
Arnoglossus laterna 164 2 Lepidopus caudatus 431 2
Dentex maroccanus 458 2
Mullus surmuletus 246 1
GSA 23 Shelf A %C GSA 23 SB/US A %C GSA 23 Lower slope A %C
Lepidotrigla cavillone 2773 38 Argentina sphyraena 16100 49
Mullus barbatus 3330 21 Chlorophthalmus agassizi 9753 10
Serranus hepatus 2784 12 Merluccius merluccius 1305 9
Citharus linguatula 262 7 Chelidonichthys cuculus 758 6
Pagellus erythrinus 627 6 Coelorinchus caelorhincus 657 6
Arnoglossus laterna 855 4 Helicolenus dactylopterus 330 5
Serranus cabrilla 263 3 Lepidotrigla cavillone 400 2
Phycis blennoides 109 2
Gadiculus argenteus 3003 2

Table 6. – Number of years that each species contributed to the 90% cut-off of within-group similarity, taking into account each similarity percentage analysis (SIMPER) by GSA, depth stratum and year during the time series. Depth strata are shelf, shelf break/upper slope (SB/US) and lower slope.

Stratum Species GSA
1 5 6 7 8 9 10 11 16 17 18 20 22 23
Shelf Argentina sphyraena - - - - 3 4 1 9 13 - 2 9 6 -
Arnoglossus imperialis - - - - - - - - 4 - - - - -
Arnoglossus laterna 8 - 3 6 - 12 10 - 10 4 12 11 8 4
Arnoglossus rueppelii - 2 - - - - - - - - - - - -
Arnoglossus thori 7 3 - - 5 - - 6 4 - - - - -
Callionymus maculatus 12 - 1 2 - - - - - 2 3 - - -
Cepola macrophthalma 16 - 18 11 - 4 13 4 1 18 11 - 3 -
Chelidonichthys cuculus - 14 - - 17 - 1 15 19 3 13 7 12 -
Chelidonichthys obscurus - - - - - - - - 7 - - - - -
Citharus linguatula - - 2 1 - 1 - 6 18 1 - 4 14 12
Deltentosteus collonianus - - - - - - - 1 - - - - - -
Deltentosteus quadrimaculatus 1 3 1 - 4 - 1 5 - - - - - 2
Dentex maroccanus - - - - - - - - - - - 1 6 -
Diplodus annularis - - - - - - - 1 - - - 2 1 -
Eutrigla gurnardus - - 1 22 - - - - - 5 3 1 3 -
Glossanodon leioglossus - 12 - - - 8 17 - - - - - - -
Gymnammodytes cicerelus - - - - - - - 1 - - - - - -
Helicolenus dactylopterus - - - - - - 2 - - - - - - -
Lepidopus caudatus 1 - - - - 1 8 - 1 - 2 - - -
Lepidotrigla cavillone 4 14 12 18 20 15 16 22 22 9 15 14 14 13
Lepidotrigla dieuzeidei 1 - - - 4 - - 1 6 - - 3 2 -
Lesueurigobius friesii - - 1 7 - 4 1 - - 2 6 - 3 -
Lesueurigobius sanzi 6 - 1 - - - - - - - - - - -
Lesueurigobius suerii - - - - - - 4 - - - - - - -
Lophius budegassa - - 6 2 - - - - - 2 6 - 14 1
Merlangius merlangus - - - - - - - - - 10 - - - -
Merluccius merluccius 21 14 22 22 2 22 22 22 22 22 22 13 14 1
Microchirus boscanion 1 - - - - - - - - - - - - -
Micromesistius poutassou - - - 1 - - - - - - 3 - - -
Mullus barbatus 17 4 20 2 20 21 20 22 19 22 17 14 14 13
Mullus surmuletus - 14 - - 7 - - 10 17 - - - 4 1
Ophichthus rufus 2 - 2 - - - - - - - - - - -
Pagellus acarne 21 - 2 - 2 - - - 1 - - - - 4
Pagellus bogaraveo 5 - - - - - - - - - - - - -
Pagellus erythrinus 3 5 3 - 21 - 5 3 4 2 - 8 - 12
Phycis blennoides - - - - - - 3 - - - 1 - - -
Pomatoschistus marmoratus 1 - - - - - - - - - - - - -
Pomatoschistus microps 1 - - - - - - - - - - - - -
Raja clavata - 2 - - - - - - - - - - 2 -
Raja miraletus - - - - 4 - - 2 22 - - - - -
Scorpaena notata 1 4 - - - - - 2 - - - - - -
Scorpaena scrofa - 3 - - - - - - - - - - - -
Scyliorhinus canicula 5 14 - - 21 - - 15 12 - - - 12 -
Serranus cabrilla 10 14 - - 13 - - 20 21 - - 2 14 4
Serranus hepatus 22 14 20 20 20 22 18 22 21 22 18 13 14 5
Symphurus nigrescens 2 - 1 - - - - - - - 1 - 2 -
Trachinus draco 6 14 - - - - - 12 8 - - - - -
Trigloporus lastoviza - 14 - - 2 - - 11 11 - - - - -
Trisopterus luscus - - 1 - - - - - - - - - - -
Trisopterus minutus - 2 20 22 - 22 6 22 5 22 22 7 14 -
Uranoscopus scaber - - - - - - - - 3 - - - - -
Zeus faber - 3 - - 1 - - 1 10 - - 1 - -
SB/US Argentina sphyraena - - 6 3 10 3 - 19 5 - 6 12 14 14
Arnoglossus rueppelii 1 - 2 - - - - - - - 10 - - 1
Callionymus maculatus 2 - - - - - - - - - - - - -
Cepola macrophthalma - - 1 - - - - - - 3 - - - -
Chelidonichthys cuculus - - - - 1 - - 1 - 1 11 - 1 10
Chlorophthalmus agassizi - 12 - 3 18 18 22 - 20 - 15 11 8 6
Coelorinchus caelorhincus 5 8 - 20 4 3 5 - 20 - - 3 12 2
Epigonus denticulatus 1 - - - - - - - - - - - - -
Epigonus telescopus - - - - - - - - 1 - - - - -
Gadiculus argenteus 21 14 20 22 21 22 19 1 21 8 6 12 13 5
Galeorhinus galeus - - - - - - - - - - - - - 1
Galeus melastomus - 10 - 22 20 15 2 - - - - 1 1 -
Glossanodon leioglossus - - - - 2 - - 22 - - 7 - - -
Helicolenus dactylopterus 17 4 11 21 1 7 5 - 7 1 22 8 9 5
Hoplostethus mediterraneus - - - - - - - - - - - 1 - 1
Hymenocephalus italicus - 2 - - - 1 19 - 20 - - 5 11 2
Lepidopus caudatus 10 - 1 - - 1 5 - 15 10 5 5 2 -
Lepidorhombus boscii - 2 - 19 5 1 - - - - 7 3 9 2
Lepidorhombus whiffiagonis - - - - - - - - - 1 1 - - -
Lepidotrigla cavillone - - - - - - - - - - 2 - - 3
Lepidotrigla dieuzeidei - - - - 9 - - 9 - - 3 3 1 1
Lesueurigobius friesii - - - - - - - - - 7 2 - - 1
Lophius budegassa - - 1 - - - - - - 2 - - 2 1
Merluccius merluccius 15 - 22 2 4 22 18 21 22 22 22 10 14 10
Micromesistius poutassou 10 4 22 21 18 11 3 2 - 22 16 - 10 2
Mullus barbatus - - 3 - - - - - - 2 7 - - -
Mullus surmuletus - - - - - - - - - - - - - 1
Nezumia sclerorhynchus - - - - - - - - - - - 2 1 -
Pagellus bogaraveo 5 - - 1 - - - - - - 1 - 2 -
Peristedion cataphractum - - - - - - - - - - 4 8 - 1
Phycis blennoides 9 7 4 22 1 21 22 - 21 5 13 4 9 4
Scorpaena elongata 1 - - - - - - - - - - - - -
Scyliorhinus canicula 10 - 8 1 20 - - 8 - - 10 4 13 -
Serranus hepatus 3 - - - - - - - - - - - - -
Symphurus nigrescens 1 - - - - - 1 - - - 1 - - -
Synchiropus phaeton - 1 - 1 - - - - - - - - - -
Trachyrincus scabrus - - - 1 - - - - - - - - - -
Trigla lyra - - - 14 1 - - - - - 2 - - -
Trisopterus minutus - - 12 - - 1 - 19 - 14 - 3 4 -
Zeus faber - - - - - - - - - - 1 - - 1
Lower slope Alepocephalus rostratus 1 - - - - - - - - - - - - -
Argentina sphyraena - - - - - - - 1 - - - - - -
Chimaera monstrosa - - - - - - - - 1 - 3 - 2 -
Chlorophthalmus agassizi - - - - 10 - - 16 - - 6 - - -
Coelorinchus caelorhincus 22 - 9 - 21 - 1 - 7 - 21 - 10 -
Epigonus denticulatus 5 - 5 - - - - - - - - - - -
Etmopterus spinax 13 7 2 - 13 21 7 16 1 - 20 - 5 -
Gadiculus argenteus 2 - 15 - 4 - - 22 - - - - - -
Gaidropsarus biscayensis - - 6 - - - - - - - - - - -
Galeus melastomus 22 14 22 - 21 22 21 22 22 - 22 - 2 -
Glossanodon leioglossus - - - - - - - 1 - - - - - -
Helicolenus dactylopterus 5 - 9 - 19 - - 7 1 - 16 - - -
Hoplostethus mediterraneus 22 - 1 - 15 2 4 - 17 - 21 - 7 -
Hymenocephalus italicus - 11 13 - 21 22 21 22 21 - 20 - 13 -
Lepidion lepidion - 6 3 - - - - - - - - - - -
Lepidopus caudatus 1 - 1 - - - - - - - - - - -
Lepidorhombus boscii - - 3 - 1 - - 1 - - - - 1 -
Lophius budegassa - - - - - - - - - - - - 1 -
Merluccius merluccius - - - - - - - 8 - - 3 - 1 -
Micromesistius poutassou 6 - 20 - - - - - - - 1 - - -
Mora moro - 3 - - - - - 1 - - - - - -
Nettastoma melanurum - - - - - - 1 - - - - - - -
Nezumia aequalis 22 14 18 - - 1 - - 3 - - - - -
Nezumia sclerorhynchus - - - - 16 21 21 4 19 - 22 - 13 -
Notacanthus bonaparte - 5 5 - - - - - - - - - - -
Pagellus bogaraveo - - 1 - 1 - - - - - - - - -
Phycis blennoides 21 14 22 - 19 22 22 22 13 - 21 - 13 -
Polyacanthonotus rissoanus - 1 - - - - - - - - - - - -
Scyliorhinus canicula - - 12 - - - - - - - - - - -
Symphurus ligulatus - 3 2 - - - 1 - - - - - - -
Symphurus nigrescens - - 8 - - - - 2 - - - - 1 -
Trachyrincus scabrus 11 - 13 - 2 3 - - - - 1 - 9 -

Some species showed a high percentage contribution to within-group similarity in most years of the time series and for most of the GSAs (Table 6). On the continental shelf, these species were S. hepatus, L. cavillone, M. barbatus and M. merluccius. On the shelf break/upper slope, only G. argenteus was present in all GSAs, while on the lower slope those species were P. blennoides, G. melastomus and Etmopterus spinax.

DISCUSSIONTop

The results have confirmed that demersal fish assemblages are highly structured in the Mediterranean. In fact, we were able to identify three common assemblages in most GSAs corresponding to the continental shelf, shelf break/upper slope and lower slope strata of each area. There were only two GSAs, the northern Adriatic Sea and Crete, that did not present lower slope assemblages, due to the shallower depth surveyed in these areas compared with the rest of GSAs. Although the number of samples was not enough to follow their temporal series, the Gulf of Lions and the eastern Ionian Sea also followed this depth structure. The results confirm the findings of previous works on the structure of demersal assemblages in the Mediterranean, showing that for fishes (Ungaro et al. 1999Ungaro N., Marano G., Marsan R., et al. 1999. Analysis of demersal assemblages from trawl surveys in the South Adriatic Sea. Aquat. Living. Resour. 12: 177-185., Labropoulou and Papaconstantinou 2004Labropoulou M., Papaconstantinou C. 2004. Community structure and diversity of demersal fish communities: the role of fishery. Sci. Mar. 68: 215-226., García-Ruiz et al. 2015García-Ruiz C., Lloris D., Rueda J.L., et al. 2015. Spatial distribution of ichthyofauna in the northern Alboran Sea (western Mediterranean). J. Nat. Hist. 49: 1191-1224.) and other taxonomic groups (Tserpes et al. 1999Tserpes G., Peristeraki P., Potamias G., et al. 1999. Species distribution in the southern Aegean sea based on bottom-trawl surveys, Aquat. Living Resour. 12: 167-175., Colloca et al. 2003Colloca F., Cardinale M., Belluscio A., et al. 2003. Pattern of distribution and diversity of demersal assemblages in the central Mediterranean Sea. Est. Coast. Shelf Sci. 56: 469-480., 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.) they are strongly organized along a depth gradient.

Despite the similar bathymetric gradient along the Mediterranean, the results showed differences in the bathymetric limitations and composition of demersal fish assemblages between GSAs. This is not surprising considering that oceanographic conditions vary between GSAs, and bathymetric distributions of communities respond according to these variations. In fact, we incorporated cluster analysis to escape from the assumption that communities are structured according to MEDITS strata, and we made an analysis based on real assemblages for each GSA. Therefore, the analysis of demersal fish diversity based on cluster analysis for each particular area of the Mediterranean is more accurate than the assignation of a depth stratum to the samples analysed for the whole Mediterranean, the method that has been generally used up to now.

Our results show a stability and even recovery of demersal fish diversity in the Mediterranean. Of the 114 temporal series analysed, only 27% showed a significant trend, with an increasing pattern in 71% of the cases showing significant trends. N90 and species richness (S) showed increasing trends in most cases (87.5% and 84.6%, respectively), while Pielou evenness (J’) was the indicator that showed the highest proportion of decreasing trends (60%). This stability was also shown in the only study analysing long temporal series from bottom trawl survey data (1994-2012) for the whole Mediterranean (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.). These authors took into account three scales of analysis corresponding to 18 GSAs, 7 biogeographical zones and 2 basins at a depth ranging from 10 to 800 m. The assemblages by depth were not considered, which could explain why they did not detect any recovery.

The continuous increase in fisheries in the last few decades has led to the overexploitation of the main commercial stocks in most Mediterranean areas (Colloca et al. 2013Colloca F., Cardinale M., Maynou F., et al. 2013. Rebuilding Mediterranean fisheries: toward a new paradigm for ecological sustainability in single species population models. Fish Fish. 14: 89-109., Sartor et al. 2014Sartor P., Colloca F., Maravelias C., et al. 2014. Critical assessment of the current understanding/knowledge of the framework of the Ecosystem Approach to Fisheries in the Mediterranean and Black Seas. Sci. Mar. 78: 19-27.). However, bottom trawl fisheries in the Mediterranean have decreased recently, due to the economic losses of this activity (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.; Table 4) and the implementation of additional management measures, such as the prohibition of bottom trawling within 1.5 nautical miles of the coast (EC Regulation 1967/2006). However, this recent measure has possibly displaced part of the trawl fishing effort from the shelf to deeper bathymetric zones (Tserpes et al. 2011Tserpes G., Tzanatos E., Peristeraki P. 2011. Spatial management of the Mediterranean bottom-trawl fisheries: the case of the southern Aegean Sea. Hydrobiologia 670: 267-274.). Our results show that increasing trends in N90 and S and decreasing trends in J’ coincide in some cases with decreasing trends in bottom trawl fishing effort. There could therefore be a cause and effect relation, because it is in accordance with the expected effect of fishing on biodiversity. The increasing trend in N90 with decreasing fishing effort reinforces the previous results that confirm the usefulness of this index for detecting the effects of fishing on demersal fish diversity. The increase of evenness with increasing fishing effort has been suggested by some authors (Murawski 2000Murawski S.A. 2000. Definitions of overfishing from an ecosystem perspective. ICES J. Mar. Sci. 57: 649-658., Zhou et al. 2010Zhou S., Smith A.D.M., Punt A.E., et al. 2010. Ecosystem-based fisheries management requires a change to the selective fishing philosophy. PNAS 107: 9485-9489.) due to the reduction of dominant species by fishing (Cury et al. 2000Cury P., Bakun A., Crawford R.J.M., et al. 2000. Small pelagics in upwelling systems: patterns of interaction and structural changes in ‘’wasp-waist’’ ecosystems. ICES J. Mar. Sci. 57: 603-618., Rice 2000Rice J.C. 2000. Evaluating fishery impacts using metrics of community structure. ICES J. Mar. Sci. 57: 682-688.) and has been confirmed by the study of the effects of fishing on evenness indices (D’Onghia et al. 2003D’Onghia G., Mastrototaro F., Matarrese A., et al. 2003. Biodiversity of the upper slope demersal community in the eastern Mediterranean: preliminary comparison between two areas with and without trawl fishing. J. Northwest Atlantic Fish. Sci. 31: 263-273., 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.). However, the expected increase in S and decrease in J’ with decreasing fishing effort are not always observed in our results. There are some differences in the aspects of diversity that each of these indices capture. Increasing N90 values with decreasing fishing effort indicate an increase in the frequency of occurrence and the evenness of the distribution of species abundances due to expansion to areas with the most favourable environmental conditions. On the other hand, an increase in S and a decrease in J’ with decreasing fishing effort implies an increase in the number of species and an increase in the dominance of some species, respectively. Although both number of species and evenness are also affecting N90, the calculation of each of these indices is extremely different. N90 takes into account the homogeneity or heterogeneity of all the samples of a stratum and year for each GSA in its calculation and involves the most frequent and abundant species in the group without losing species identity through the comparison among all the samples in the group. In contrast, S and J’ in a group are calculated from their mean values and consequently species identity is lost. This may explain why extreme values of fishing effort were needed to detect the effects of fishing in S and J’ in previous works (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.). In some cases, N90 showed no trend when there was a trend in fishing effort and viceversa. This finding could be due to several causes. It is either too early to detect the effects of decreasing fishing effort on demersal fish diversity or the decrease is not sufficiently important to change the diversity trend. Similarly, increasing trends in fishing effort could not result in a decrease in fish diversity due to the adaptation of demersal fish communities to fishing exploitation.

It must also be considered that there is a high complexity in the evaluation of fishing effort in the whole area. Available temporal series used to analyse fishing effort do not cover the whole time series of demersal fish diversity in all cases (see Table S1), and the inclusion of more years of the temporal series to the analysis could lead to different trends of fishing effort. In addition, as the nominal spatio-temporal pattern of fishing effort on a Mediterranean-wide level is not available, the use of different effort estimates in the areas may increase the uncertainty of the model. Moreover, number of fishing vessels is a poor proxy for effort, because does not account for other capacity changes (e.g. length overall, or kilowatts), because it does not account for technological creep and or temporal and spatial changes of fishing operations (Anticamara et al. 2011Anticamara J.A., Watson R., Gelchu A., et al. 2011. Global fishing effort (1950-2010): Trends, gaps, and implications. Fish. Res. 107: 131-136.). For instance, though the regulation decreasing fishing capacity has been in place since 1991, the gross tonnage of the fleets may be increasing because boats are decreasing in number (decommissioning) but increasing in size over time (e.g. Fortibuoni et al. 2017Fortibuoni T., Giovanardi O., Pranovi F., et al. 2017. Analysis of Long-Term Changes in a Mediterranean Marine Ecosystem Based on Fishery Landings. Front. Mar. Sci. 4: 33.) or because vessels have increased trawling time. This issue is enormously relevant for the Mediterranean Sea, where fisheries are managed by effort control and technical measures in contrast to quotas (northern EU seas; see Cardinale and Scarcella 2017Cardinale M., Scarcella G. 2017. Mediterranean Sea: A Failure of the European Fisheries Management System. Front. Mar. Sci. 4: 72.) and should be considered when the results are interpreted. However, in the Spanish and French Mediterranean, restrictions on hours of trawling would not permit an unlimited increase in fishing effort with a decreasing number of vessels (REAL DECRETO 1440/1999, de 10 de septiembre; Arrêté n° 99-162 du 10 juin 1999). In any case, a more appropriate indicator than number of vessels should be used for fishing effort whenever possible.

Regarding spatial patterns, we did not find the expected longitudinal decreasing west-east pattern in species richness observed in previous works on fish communities (Quignard and Tomasini 2000Quignard J.P., Tomasini J.A. 2000. Mediterranean fish diversity. Biol. Mar. Mediterr. 7: 1-66., 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.). Nor was this trend observed for N90 and J’ in any depth stratum. The absence of a western/eastern decreasing trend further suggests that primary production or temperature regime are possibly not the major factor explaining large-scale patterns of diversity in demersal fish assemblages, as suggested by Gaertner et al. (2007)Gaertner J.C., Bertrand J.A., Relini G., et al. 2007. Spatial pattern in species richness of demersal fish assemblages on the continental shelf of the northern Mediterranean Sea: A multiscale analysis. Mar. Ecol. Prog. Ser. 341: 191-203.. However, it is difficult to compare our results with diversity values obtained with non-standardized data mainly collected from fish inventories from other works. Moreover, due to the limited sampling approach (i.e. data concerning only one guild of fishes or limited to specific depths, gear or habitat), some of regional inventories are useless for comparative studies (Psomadakis et al. 2012Psomadakis P.N., Giustino S., Vacchi M. 2012. Mediterranean fish biodiversity: An updated inventory with focus on the Ligurian and Tyrrhenian seas. Zootaxa 3263: 1-46.). Recent studies based mainly on standardized time series data also question the previously considered west-east decreasing diversity trend in the Mediterranean (Gaertner et al. 2013Gaertner J.C., Maiorano P., Mérigot B., et al. 2013. Large-scale diversity of slope fishes: pattern inconsistency between multiple diversity indices. PloS ONE 8: e66753., 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., Peristeraki et al. 2017Peristeraki P., Tserpes G., Lampadariou N., et al. 2017. Comparing demersal megafaunal species diversity along the depth gradient within the South Aegean and Cretan Seas (Eastern Mediterranean). PLoS ONE 12: e0184241.).

The highest diversity values were found on the continental shelf of insular areas, such as the Balearic Islands, Sardinia, Sicily and the Aegean Sea. This higher diversity can be explained by taking into account the peculiarities of the distinct biogeographic sectors within the Mediterranean (Lejeusne et al. 2010Lejeusne C., Chevaldonné P., Pergent-Martini C., et al. 2010. Climate change effects on a miniature ocean: the highly diverse, highly impacted Mediterranean Sea. Trends Ecol. Evol. 25: 250-260.), which can be characterized by the shallow water biota (Bianchi et al. 2012Bianchi C.N., Morri C., Chiantore M., et al. 2012. Mediterranean Sea biodiversity between the legacy from the past and a future of change. In: Stambler N. (ed), Life in the Mediterranean Sea: a look at habitat changes. Nova Science Publishers, New York, pp. 1-55.). In the Strait of Sicily, for example, the meeting of western and eastern Mediterranean species produces a peak in fish species richness in the central Mediterranean (Ben Rais Lasram et al. 2009Ben Rais Lasram F., Guilhaumon F., Mouillot D. 2009. Fish diversity patterns in the Mediterranean Sea: deviations from a mid-domain model. Mar. Ecol. Prog. Ser. 376: 253-267., Garofalo et al. 2007Garofalo G., Fiorentino F., Gristina M., et al. 2007. Stability of spatial pattern of fish species diversity in the Strait of Sicily (central Mediterranean). Hydrobiologia 580: 117-124.). The greater sampling effort of the present work compared with previous ones (Morri et al. 1999Morri C., Bianchi C.N., Cocito S., et al. 1999. Biodiversity of marine sessile epifauna at an Aegean island subject to hydrothermal activity: Milos, Eastern Mediterranean Sea. Mar. Biol. 135: 729-739., Koukouras et al. 2001Koukouras A., Voultsiadou E., Kitsos M.S., et al. 2001. Macrobenthic fauna diversity in the Aegean Sea, affinities with other Mediterranean regions and the Black Sea. Bios 6: 61-76.) could affect the unexpectedly high diversity values found in the Aegean Sea. The presence of algae facies deeper than 50 m around the Balearic Islands is likely to enhance demersal fish diversity in this area. Coralligenous and maerl communities are very characteristic of the Mallorca-Menorca continental shelf up to 85-90 m depth (Canals and Ballesteros 1997Canals M., Ballesteros E. 1997. Production of carbonate particles by phytobenthic communities on the Mallorca-Menorca shelf, northwestern Mediterranean Sea. Deep-Sea Res. Part II 44: 611-629., Ordines and Massutí 2009Ordines F., Massutí E. 2009. Relationships between macro-epibenthic communities and fish on the shelf grounds of the western Mediterranean. Aquat. Conserv.: Mar. Freshw. Ecosyst. 19: 370-383.), and this has been pointed out as a plausible reason for the differences observed between the coastal demersal resources of the Balearic Islands and the adjacent Iberian Peninsula (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.). In fact, habitat type has been shown to affect the distribution of demersal species, most of them being more abundant and showing a better condition in maerl and Peyssonnelia beds (Ordines and Massutí 2009Ordines F., Massutí E. 2009. Relationships between macro-epibenthic communities and fish on the shelf grounds of the western Mediterranean. Aquat. Conserv.: Mar. Freshw. Ecosyst. 19: 370-383., Ordines et al. 2009Ordines F., Quetglas A., Massutí E., et al. 2009. Habitat preferences and life history of the red scorpion fish, Scorpaena notata, in the Mediterranean. Est. Coast. Shelf Sci. 85: 537-546., 2015Ordines F., Bauzá M., Sbert M., et al. 2015. Red algal beds increase the condition of nekto-benthic fish. J. Sea Res. 95: 115-123.), which have also shown high diversity of fish.

The results of SIMPER analyses reinforce the idea of maerl and Peyssonnelia beds causing high diversity values also on the continental shelves of Sicily, Sardinia and the Aegean Sea. The species Serranus cabrilla, Scyliorhinus canicula and Mullus surmuletus, which in the Balearic Islands have shown to be more abundant in these habitats (Ordines and Massutí 2009Ordines F., Massutí E. 2009. Relationships between macro-epibenthic communities and fish on the shelf grounds of the western Mediterranean. Aquat. Conserv.: Mar. Freshw. Ecosyst. 19: 370-383.) contribute to N90 mainly in this archipelago, Sardinia, Sicily and the Aegean Sea. Similar habitats to those found on the Balearic shelf have been reported in some of these areas, like the Aegean Sea (Georgiadis et al. 2009Georgiadis M., Papatheodoroy G., Tzanatos E., et al. 2009. Coralligene formations in the eastern Mediterranean SeaQ Morphology, distribution mapping and relations to fisheries in the South Aegean Sea (Greece) based on high-resolution acoustics. J. Exper. Biol. Ecol. 368: 44-58.). The presence of a higher number of vulnerable species like demersal chondrichthyans in the Balearic Islands, Sardinia, Sicily and the Aegean Sea (Bertrand et al. 2000Bertrand J.A., Gil de Sola L., Papakonstantinou C., et al. 2000. Contribution on the distribution of elasmobranchs in the Mediterranean (from the MEDITS surveys). Biol. Mar. Mediterr. 7: 385-399., Damalas and Vassilopoulou 2011Damalas D., Vassilopoulou V. 2011. Chondrichthyan by-catch and discards in the demersal trawl fishery of the central Aegean Sea (Eastern Mediterranean). Fish. Res. 108: 142-152., Ramírez-Amaro et al. 2015Ramírez-Amaro S., Ordines F., Terrasa B., et al. 2015. Demersal chondrichthyans in the western Mediterranean: Assemblages and biological parameters of their main species. Mar. Freshw. Res. 67: 636-652.) compared with adjacent areas could also contribute to the higher fish diversity values found there.

The spatial distribution of the bottom trawl fishing effort by GSA shows that the number of vessels per km2 is low on the continental shelf of the Balearic Islands, Sardinia and the Aegean Sea (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.). The coincidence of areas with a low fishing effort with areas with a high diversity is in accordance with previous works, in which higher values of N90 and S and lower values of J’ were associated with areas with a low fishing effort (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.). The lower fishing effort exerted by the relatively smaller bottom trawl fleets in these areas could have preserved, at least to some extent, their fish diversity along with a better conservation of their sensitive and essential habitats, such as maerl and Peyssonnelia beds. These habitats are precisely those most affected by the low selectivity and damaging collateral effects of bottom trawling on seabed communities, which decrease the presence of biogenic habitats, leading to a reduction in the biodiversity on exploited bottoms (e.g. Norse and Watling 1999Norse E.A., Watling L. 1999. Impacts of mobile fishing gear: the biodiversity perspective. Am. Fish. Soc. Symp. 22: 31-40., Smith et al. 2000Smith C., Papadopoulou K.N., Diliberto S. 2000. Impact of otter trawling on an eastern Mediterranean commercial trawl fishing ground. ICES J. Mar. Sci. 57: 1340-1351., Hiddink et al. 2006Hiddink J.G., Jennings S., Kaiser M.J., et al. 2006. Cumulative impacts of seabed trawl disturbance on benthic biomass, production, and species richness in different habitats. Can. J. Fish. Aquat. Sci. 63: 721-736.).

Spatial patterns of demersal fish diversity on the shelf-break/upper slope and lower slope of the Mediterranean are different to those detected on the continental shelf. Areas with the highest diversity values on the continental shelf do not coincide with areas with the highest diversity values on the shelf break/upper slope and lower slope. Although the assignment of depth strata was different in previous works and the comparison is not straightforward, a different pattern on shelf and slope areas was also observed for species richness (Gaertner et al. 2007Gaertner J.C., Bertrand J.A., Relini G., et al. 2007. Spatial pattern in species richness of demersal fish assemblages on the continental shelf of the northern Mediterranean Sea: A multiscale analysis. Mar. Ecol. Prog. Ser. 341: 191-203., 2013Gaertner J.C., Maiorano P., Mérigot B., et al. 2013. Large-scale diversity of slope fishes: pattern inconsistency between multiple diversity indices. PloS ONE 8: e66753.). This is likely due to differences in the distribution of cumulative threats to marine biodiversity, which are mainly concentrated in coastal areas and on the continental shelf of the Mediterranean (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.), and to the presence of particular habitats on the shelf break and slope bottoms, which may represent potential hot spots of biodiversity (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.). Although the distribution of deep-sea diversity is different to that on the continental shelf, it is affected by similar factors: changes in spatial distribution of fishing effort together with habitat type. For example, higher N90 values on the slope of northern Spain could be related to the presence of submarine canyons in the area where high values of biodiversity have been reported (see Fernández-Arcaya et al. 2017Fernández-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. for a review). However, the description of deep-sea habitats has just been implemented for some particular areas of the Mediterranean, and this information is not exhaustive at all (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.). Moreover, an intensive habitat mapping based on MEDITS samples would be useful to relate demersal fish assemblages to their corresponding habitats, as has been done in some continental shelf areas (e.g. Ordines and Massutí 2009Ordines F., Massutí E. 2009. Relationships between macro-epibenthic communities and fish on the shelf grounds of the western Mediterranean. Aquat. Conserv.: Mar. Freshw. Ecosyst. 19: 370-383.).

The outcomes of the present study show that at large temporal and spatial scales bottom trawl fisheries have reduced the diversity of demersal assemblages in the Mediterranean. However, in recent decades a generally stable scenario or even a slight recovery trend have been highlighted. This result would have not been expected if the alarming overexploitation status of Mediterranean stocks were taken into account, which underlines the importance of using diversity indices to study the effects of fishing on demersal assemblages. Therefore, a change from the assessment of demersal resources based on exploited monospecfic stocks to one based on the study of whole demersal fish assemblages is needed due to the high multispecificity of the bottom trawl fishery in the Mediterranean (Caddy 1993Caddy J.F. 1993. Some future perspectives for assessment and management of Mediterranean fisheries. Sci. Mar. 57: 121-130., Lleonart and Maynou 2003Lleonart J., Maynou F. 2003. Fish stock assessments in the Mediterranean: state of the art. Sci. Mar. 67: 37-49.). The inclusion of species other than target ones made in this work through diversity indices is therefore important for the implementation of an ecosystem-based fisheries management (Browman and Stergiou 2004Browman H.I., Stergiou K.I. 2004. Perspectives on ecosystem-based approaches to the management of marine resources. Mar. Ecol. Prog. Ser. 274: 269-303.).

ACKNOWLEDGEMENTSTop

The present study could not have been done without the work of all participants and crew in the MEDITS scientific surveys, funded by the European Union Data Collection Framework for the Common Fisheries Policy, the funding projects supporting this research (ECLIPSAME Project CTM2012-37701 and CLIFISH project CTM2015-66400-C3-1-R MINECO/FEDER) and the FPI Fellowship (BES-2013-065112) from the Spanish Ministry of Economy and Competitiveness granted to MTF.

REFERENCESTop

Anticamara J.A., Watson R., Gelchu A., et al. 2011. Global fishing effort (1950-2010): Trends, gaps, and implications. Fish. Res. 107: 131-136.
https://doi.org/10.1016/j.fishres.2010.10.016

Ben Rais Lasram F., Guilhaumon F., Mouillot D. 2009. Fish diversity patterns in the Mediterranean Sea: deviations from a mid-domain model. Mar. Ecol. Prog. Ser. 376: 253-267.
https://doi.org/10.3354/meps07786

Bertrand J.A., Gil de Sola L., Papakonstantinou C., et al. 2000. Contribution on the distribution of elasmobranchs in the Mediterranean (from the MEDITS surveys). Biol. Mar. Mediterr. 7: 385-399.

Bertrand J.A., Gil de Sola L., Papaconstantinou C., et al. 2002. The general specifications of the MEDITS surveys. Sci. Mar. 66: 9-17.
https://doi.org/10.3989/scimar.2002.66s29

Bianchi C.N., Morri C., Chiantore M., et al. 2012. Mediterranean Sea biodiversity between the legacy from the past and a future of change. In: Stambler N. (ed), Life in the Mediterranean Sea: a look at habitat changes. Nova Science Publishers, New York, pp. 1-55.

Bosc E., Bricaud A., Antoine D. 2004. Seasonal and interannual variability in algal biomass and primary production in the Mediterranean Sea, as derived from 4 years of SeaWiFS observations. Global Biogeochem. Cycles 18: GB1005.
https://doi.org/10.1029/2003GB002034

Bray J.R., Curtis J.T. 1957. An ordination of the upland forest communities of southern Wisconsin. Ecol. Monogr. 27: 325-349.
https://doi.org/10.2307/1942268

Browman H.I., Stergiou K.I. 2004. Perspectives on ecosystem-based approaches to the management of marine resources. Mar. Ecol. Prog. Ser. 274: 269-303.
https://doi.org/10.3354/meps274269

Caddy J.F. 1993. Some future perspectives for assessment and management of Mediterranean fisheries. Sci. Mar. 57: 121-130.

Callaway R., Alsvâg J., de Boois I., et al. 2002. Diversity and community structure of epibenthic invertebrates and fish in the North Sea. ICES J. Mar. Sci. 59: 1199-1214.

Canals M., Ballesteros E. 1997. Production of carbonate particles by phytobenthic communities on the Mallorca-Menorca shelf, northwestern Mediterranean Sea. Deep-Sea Res. Part II 44: 611-629.
https://doi.org/10.1016/S0967-0645(96)00095-1

Cardinale M., Scarcella G. 2017. Mediterranean Sea: A Failure of the European Fisheries Management System. Front. Mar. Sci. 4: 72.
https://doi.org/10.3389/fmars.2017.00072

Ciannelli L., Fisher J.A.D., Skern-Mauritzen M., et al. 2013. Theory, consequences and evidence of eroding population spatial structure in harvested marine fishes: a review. Mar. Ecol. Prog. Ser. 480: 227-243.
https://doi.org/10.3354/meps10067

Clarke K.R. 1993. Non-parametric multivariate analyses of changes in community structure. Aust. J. Ecol. 18: 117-143.
https://doi.org/10.1111/j.1442-9993.1993.tb00438.x

Clarke K.R., Gorley R.N., Somerfield P.J., et al. 2014. Change in marine communities: an approach to statistical analysis and interpretation. PRIMER-E, Plymouth, 260 pp.

Coll M., Piroddi C., Steenbeek J., et al. 2010. The biodiversity of the Mediterranean Sea: estimates, patterns, and threats. PloS ONE 5: e11842.
https://doi.org/10.1371/journal.pone.0011842

Coll 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.
https://doi.org/10.1111/j.1466-8238.2011.00697.x

Colloca F., Cardinale M., Belluscio A., et al. 2003. Pattern of distribution and diversity of demersal assemblages in the central Mediterranean Sea. Est. Coast. Shelf Sci. 56: 469-480.
https://doi.org/10.1016/S0272-7714(02)00196-8

Colloca F., Cardinale M., Maynou F., et al. 2013. Rebuilding Mediterranean fisheries: toward a new paradigm for ecological sustainability in single species population models. Fish Fish. 14: 89-109.
https://doi.org/10.1111/j.1467-2979.2011.00453.x

Colloca F., Scarcella G., Libralato S. 2017. Recent Trends and Impacts of Fisheries Exploitation on Mediterranean Stocks and Ecosystems. Front. Mar. Sci. 4: 244.
https://doi.org/10.3389/fmars.2017.00244

Cury P., Bakun A., Crawford R.J.M., et al. 2000. Small pelagics in upwelling systems: patterns of interaction and structural changes in ‘’wasp-waist’’ ecosystems. ICES J. Mar. Sci. 57: 603-618.
https://doi.org/10.1006/jmsc.2000.0712

Daan N., Gislason H., Pope J.G., et al. 2005. Changes in the North Sea fish community: evidence of indirect effects of fishing? ICES J. Mar. Sci. 62: 177-188.
https://doi.org/10.1016/j.icesjms.2004.08.020

Damalas D., Vassilopoulou V. 2011. Chondrichthyan by-catch and discards in the demersal trawl fishery of the central Aegean Sea (Eastern Mediterranean). Fish. Res. 108: 142-152.
https://doi.org/10.1016/j.fishres.2010.12.012

Danovaro R., Dinet A., Duineveld G., et al. 1999. Benthic response to particulate fluxes in different trophic environments: a comparison between the Gulf of Lions-Catalan Sea (western-Mediterranean) and the Cretan Sea (eastern-Mediterranean). Progr. Oceanogr. 44: 287-312.
https://doi.org/10.1016/S0079-6611(99)00030-0

Danovaro 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.
https://doi.org/10.1371/journal.pone.0011832

Dayton P.K., Thrush S.F., Agardy M.T., et al. 1995. Environmental effects of marine fishing. Aquat. Conserv. 5: 205-232.
https://doi.org/10.1002/aqc.3270050305

Demestre M., Martín P. 1993. Optimum exploitation of a demersal resource in the western Mediterranean: the fishery of the deep-water shrimp Aristeus antennatus (Risso, 1816). Sci. Mar. 57: 175-182.

D’Onghia G., Mastrototaro F., Matarrese A., et al. 2003. Biodiversity of the upper slope demersal community in the eastern Mediterranean: preliminary comparison between two areas with and without trawl fishing. J. Northwest Atlantic Fish. Sci. 31: 263-273.
https://doi.org/10.2960/J.v31.a20

Dremière P.Y., Fiorentini L., Cosimi G., et al. 1999. Escapement from the main body of the bottom trawl used for the Mediterranean international trawl survey (MEDITS). Aquat. Living Resour. 12: 207-217.
https://doi.org/10.1016/S0990-7440(00)88471-5

Duda A.M., Sherman K. 2002. A new imperative for improving management of large marine ecosystems. Ocean Coast. Manage. 45: 797-833.
https://doi.org/10.1016/S0964-5691(02)00107-2

Farriols M.T., Ordines F., Hidalgo M., et al. 2015. N90 index: a new approach to biodiversity based on similarity and sensitive to direct and indirect fishing impact. Ecol. Indic. 52: 245-255.
https://doi.org/10.1016/j.ecolind.2014.12.009

Farriols 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.
https://doi.org/10.1016/j.csr.2016.11.011

Farrugio 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.

Fernández-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.
https://doi.org/10.3389/fmars.2017.00005

Fiorentini L., Dremière P.Y., Leonori I., et al. 1999. Efficiency of the bottom trawl used for the Mediterranean international trawl survey (MEDITS): Efficacite du chalut de fond utilise pour le programme international d’evaluation des ressources halieutiques de Mediterranee (MEDITS). Aquat. Living. Resour. 12: 187-205.
https://doi.org/10.1016/S0990-7440(00)88470-3

Fortibuoni T., Libralato S., Raicevich S., et al. 2010. Coding Early Naturalists’ Accounts into Long-Term Fish Community Changes in the Adriatic Sea (1800-2000). PLoS ONE 5: e15502.
https://doi.org/10.1371/journal.pone.0015502

Fortibuoni T., Giovanardi O., Pranovi F., et al. 2017. Analysis of Long-Term Changes in a Mediterranean Marine Ecosystem Based on Fishery Landings. Front. Mar. Sci. 4: 33.
https://doi.org/10.3389/fmars.2017.00204

Fromentin J.M., Fonteneau A. 2001. Fishing effects and life history traits: A case study comparing tropical versus temperate tunas. Fish. Res. 53: 133-150.
https://doi.org/10.1016/S0165-7836(00)00299-X

Gaertner J.C., Bertrand J.A., Relini G., et al. 2007. Spatial pattern in species richness of demersal fish assemblages on the continental shelf of the northern Mediterranean Sea: A multiscale analysis. Mar. Ecol. Prog. Ser. 341: 191-203.
https://doi.org/10.3354/meps341191

Gaertner J.C., Maiorano P., Mérigot B., et al. 2013. Large-scale diversity of slope fishes: pattern inconsistency between multiple diversity indices. PloS ONE 8: e66753.
https://doi.org/10.1371/journal.pone.0066753

García-Ruiz C., Lloris D., Rueda J.L., et al. 2015. Spatial distribution of ichthyofauna in the northern Alboran Sea (western Mediterranean). J. Nat. Hist. 49: 1191-1224.
https://doi.org/10.1080/00222933.2014.1001457

Garofalo G., Fiorentino F., Gristina M., et al. 2007. Stability of spatial pattern of fish species diversity in the Strait of Sicily (central Mediterranean). Hydrobiologia 580: 117-124.
https://doi.org/10.1007/s10750-006-0460-1

Georgiadis M., Papatheodoroy G., Tzanatos E., et al. 2009. Coralligene formations in the eastern Mediterranean SeaQ Morphology, distribution mapping and relations to fisheries in the South Aegean Sea (Greece) based on high-resolution acoustics. J. Exper. Biol. Ecol. 368: 44-58.
https://doi.org/10.1016/j.jembe.2008.10.001

General Fisheries Commission for the Mediterranean (GFCM). 2016. Report of the Working Group on Stock Assessment of Demersal Species (WGSAD). Rome.
http://www.fao.org/gfcm/reports/technical-meetings/detail/en/c/471253/

Gislason H. 2002. The effects of fishing on non-target species and ecosystem structure and function. In: Sinclair M., Valdimarsson G. (eds), Responsible Fisheries in the Marine Ecosystem. CAB International, Wallingford, pp. 255-274.
https://doi.org/10.1079/9780851996332.0255

Granger 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.
https://doi.org/10.1016/j.pocean.2015.08.002

Guijarro B., Massutí E., Moranta J., et al. 2008. Population dynamics of the red shrimp Aristeus antennatus in the Balearic Islands (western Mediterranean): Short spatio-temporal differences and influence of environmental factors. J. Mar. Syst. 71: 385-402.
https://doi.org/10.1016/j.jmarsys.2007.04.003

Hall S.J. 1999. The Effects of Fishing on Marine Ecosystems and Communities. Blackwell Science, Oxford. 274 pp.

Hiddink J.G., Jennings S., Kaiser M.J., et al. 2006. Cumulative impacts of seabed trawl disturbance on benthic biomass, production, and species richness in different habitats. Can. J. Fish. Aquat. Sci. 63: 721-736.
https://doi.org/10.1139/f05-266

Jennings S., Dulvy N.K. 2005. Reference points and reference directions for size-based indicators of community structure. ICES J. Mar. Sci. 62: 397-404.
https://doi.org/10.1016/j.icesjms.2004.07.030

Jørgensen C., Enberg K., Dunlop E.S., et al. 2007. Managing Evolving Fish Stocks. Science 318: 1247-1248.
https://doi.org/10.1126/science.1148089

Kaiser M.J., de Groot S.J. 2000. The effects of fishing on non-target species and habitats. Biological, conservation and socio-economics issues. Blackwell Science, Oxford, 399 pp.

Kaiser M.J., Collie J.S., Hall S.J., et al. 2002. Modification of marine habitats by trawling activities: prognosis and solutions. Fish Fish. 3: 114-136.
https://doi.org/10.1046/j.1467-2979.2002.00079.x

Koukouras A., Voultsiadou E., Kitsos M.S., et al. 2001. Macrobenthic fauna diversity in the Aegean Sea, affinities with other Mediterranean regions and the Black Sea. Bios 6: 61-76.

Labropoulou M., Papaconstantinou C. 2004. Community structure and diversity of demersal fish communities: the role of fishery. Sci. Mar. 68: 215-226.
https://doi.org/10.3989/scimar.2004.68s1215

Lejeusne C., Chevaldonné P., Pergent-Martini C., et al. 2010. Climate change effects on a miniature ocean: the highly diverse, highly impacted Mediterranean Sea. Trends Ecol. Evol. 25: 250-260.
https://doi.org/10.1016/j.tree.2009.10.009

Lleonart J., Maynou F. 2003. Fish stock assessments in the Mediterranean: state of the art. Sci. Mar. 67: 37-49.
https://doi.org/10.3989/scimar.2003.67s137

Masnadi F., Criscoli A., Lanteri L., et al. 2018. Effects of environmental and anthropogenic drivers on the spatial distribution of deep-sea shrimps in the Ligurian and Tyrrhenian Seas (NW Mediterranean). Hydrobiologia 816: 165-178.
https://doi.org/10.1007/s10750-018-3581-4

Massutí E., Reñones O. 2005. Demersal resource assemblages in the trawl fishing grounds off the Balearic Islands (western Mediterranean). Sci. Mar. 69: 167-181.
https://doi.org/10.3989/scimar.2005.69n1167

MEDITS Working Group. 2017. MEDITS-Handbook, Version n. 9. MEDITS Working Group, 106 pp.
http://www.sibm.it/MEDITS%202011/principaledownload.htm

Meléndez M.J., Báez J.C., Serna-Quintero J.M., et al. 2017. Historical and ecological drivers of the spatial pattern of Chondrichthyes species richness in the Mediterranean Sea. PLoS ONE 12: e1075699.
https://doi.org/10.1371/journal.pone.0175699

Moranta J., Quetglas A., Massutí E., et al. 2008. Research trends on demersal fisheries oceanography in the Mediterranean. In: Mertens L.P. (ed), Biological Oceanograpgy Research Trends. Nova Science Publishers, New York, pp. 9-65.

Morato T., Watson R., Pitcher T.J., et al. 2006. Fishing down the deep. Fish Fish. 7: 24-34.
https://doi.org/10.1111/j.1467-2979.2006.00205.x

Morri C., Bianchi C.N., Cocito S., et al. 1999. Biodiversity of marine sessile epifauna at an Aegean island subject to hydrothermal activity: Milos, Eastern Mediterranean Sea. Mar. Biol. 135: 729-739.
https://doi.org/10.1007/s002270050674

Murawski S.A. 2000. Definitions of overfishing from an ecosystem perspective. ICES J. Mar. Sci. 57: 649-658.
https://doi.org/10.1006/jmsc.2000.0738

Norse E.A., Watling L. 1999. Impacts of mobile fishing gear: the biodiversity perspective. Am. Fish. Soc. Symp. 22: 31-40.

Ordines F., Massutí E. 2009. Relationships between macro-epibenthic communities and fish on the shelf grounds of the western Mediterranean. Aquat. Conserv.: Mar. Freshw. Ecosyst. 19: 370-383.
https://doi.org/10.1002/aqc.969

Ordines F., Quetglas A., Massutí E., et al. 2009. Habitat preferences and life history of the red scorpion fish, Scorpaena notata, in the Mediterranean. Est. Coast. Shelf Sci. 85: 537-546.
https://doi.org/10.1016/j.ecss.2009.09.020

Ordines F., Farriols M.T., Lleonart J., et al. 2014. Biology and population dynamics of by-catch fish species of the bottom trawl fishery in the western Mediterranean. Mediterr. Mar. Sci. 15: 613-625.
https://doi.org/10.12681/mms.812

Ordines F., Bauzá M., Sbert M., et al. 2015. Red algal beds increase the condition of nekto-benthic fish. J. Sea Res. 95: 115-123.
https://doi.org/10.1016/j.seares.2014.08.002

Peristeraki P., Tserpes G., Lampadariou N., et al. 2017. Comparing demersal megafaunal species diversity along the depth gradient within the South Aegean and Cretan Seas (Eastern Mediterranean). PLoS ONE 12: e0184241.
https://doi.org/10.1371/journal.pone.0184241

Pranovi F., Raicevich S., Franceschini G., et al. 2001. Discard analysis and damage to non-target species in the ‘rapido’ trawl fishery. Mar. Biol. 139: 863-875.
https://doi.org/10.1007/s002270100646

Psomadakis P.N., Giustino S., Vacchi M. 2012. Mediterranean fish biodiversity: An updated inventory with focus on the Ligurian and Tyrrhenian seas. Zootaxa 3263: 1-46.
https://doi.org/10.11646/zootaxa.3263.1.1

Quetglas 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.
https://doi.org/10.3389/fmars.2017.00106

Quignard J.P., Tomasini J.A. 2000. Mediterranean fish diversity. Biol. Mar. Mediterr. 7: 1-66.

R Core Team. 2014. R: A Language and Environment for Statistical Computing. http://www.r-project.org/

Ramírez-Amaro S., Ordines F., Terrasa B., et al. 2015. Demersal chondrichthyans in the western Mediterranean: Assemblages and biological parameters of their main species. Mar. Freshw. Res. 67: 636-652.
https://doi.org/10.1071/MF15093

Rice J.C. 2000. Evaluating fishery impacts using metrics of community structure. ICES J. Mar. Sci. 57: 682-688.
https://doi.org/10.1006/jmsc.2000.0735

Roberts C.M. 2002. Deep impact: the rising toll of fishing in the deep sea. Trends Ecol. Evol. 17: 242-245.
https://doi.org/10.1016/S0169-5347(02)02492-8

Sabatini A., Locci I., Deiana A.M., et al. 2013. Temporal trends in biodiversity of the middle-slope assemblages in Sardinian seas (Central-Western Mediterranean). J. Mar. Biol. Ass. U.K. 93: 1739-1752.
https://doi.org/10.1017/S0025315413000258

Sardà F., Calafat A., Flexas M.M., et al. 2004. An introduction to Mediterranean deep-sea biology. Sci. Mar. 68: 7-38.
https://doi.org/10.3989/scimar.2004.68s37

Sartor P., Colloca F., Maravelias C., et al. 2014. Critical assessment of the current understanding/knowledge of the framework of the Ecosystem Approach to Fisheries in the Mediterranean and Black Seas. Sci. Mar. 78: 19-27.
https://doi.org/10.3989/scimar.04021.17B

Smith C., Papadopoulou K.N., Diliberto S. 2000. Impact of otter trawling on an eastern Mediterranean commercial trawl fishing ground. ICES J. Mar. Sci. 57: 1340-1351.
https://doi.org/10.1006/jmsc.2000.0927

Tecchio S., Ramírez-Llodra E., Sardà F., et al. 2011. Drivers of deep Mediterranean megabenthos communities along longitudinal and bathymetric gradients. Mar. Ecol. Prog. Ser. 439: 181-192.
https://doi.org/10.3354/meps09333

Tserpes G., Peristeraki P., Potamias G., et al. 1999. Species distribution in the southern Aegean sea based on bottom-trawl surveys, Aquat. Living Resour. 12: 167-175.
https://doi.org/10.1016/S0990-7440(00)88468-5

Tserpes G., Tzanatos E., Peristeraki P. 2011. Spatial management of the Mediterranean bottom-trawl fisheries: the case of the southern Aegean Sea. Hydrobiologia 670: 267-274.
https://doi.org/10.1007/s10750-011-0667-7

Ungaro N., Marano G., Marsan R., et al. 1998. Demersal fish assemblage biodiversity as an index of fishery resources exploitation. Ital. J. Zool. 65: 511-516.
https://doi.org/10.1080/11250009809386876

Ungaro N., Marano G., Marsan R., et al. 1999. Analysis of demersal assemblages from trawl surveys in the South Adriatic Sea. Aquat. Living. Resour. 12: 177-185.
https://doi.org/10.1016/S0990-7440(00)88469-7

Zhou S., Smith A.D.M., Punt A.E., et al. 2010. Ecosystem-based fisheries management requires a change to the selective fishing philosophy. PNAS 107: 9485-9489.
https://doi.org/10.1073/0pnas.0912771107

SUPPLEMENTARY MATERIAL

The following supplementary material is available through the online version of this article and at the following link:
http://scimar.icm.csic.es/scimar/supplm/sm04977esm.pdf

Table S1. – Temporal series of fishing effort measures in number of vessels, kilowatt per day at sea (kW*days at sea) and gross tonnage per days at sea (GT*days at sea) for each GSA and species. Species considered in each depth stratum are i) Mullus barbatus or Mullus surmuletus for the continental shelf; ii) Nephrops norvegicus or Parapenaeus longirostris for the shelf break/upper slope; and iii) Aristeus antennatus or Aristaeomorpha foliacea for the lower slope. Effort measures used to calculate trends in fishing effort for each GSA and stratum are marked with (*). References are listed below the table.

Fig. S1. – Species accumulation curves for each GSA. Note that for all GSAs asymptotic values of species counts are reached.

Fig. S2. – Mean values of N90 diversity index during the period 1994–2015 for each GSA and depth strata. Black dots, shelf; blue dots, shelf break/upper slope; red dots, lower slope.

Fig. S3. – Mean values of species richness (S) during the period 1994–2015 for each GSA and depth strata. Black dots, shelf; blue dots, shelf break/upper slope; red dots, lower slope.

Fig. S4. – Mean values of Pielou evennes (J’) during the period 1994–2015 for each GSA and depth strata. Black dots, shelf; blue dots, shelf break/upper slope; red dots, lower slope.



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