Geographic patterns of biodiversity in European coastal marine benthos

This is a postprint of: Hummel, H., Avesaath, P. van, Wijnhoven, S., Kleine Schaars, L. et al. (2016). Geographic patterns of biodiversity in European coastal marine benthos. Journal of the Marine Biological Association of the United Kingdom, 97, 507-523 Published version: dx.doi.org/10.1017/S0025315416001119 Link NIOZ Repository: www.vliz.be/nl/imis?module=ref&refid=261466 Article begins on next page] The NIOZ Repository gives free access to the digital collection of the work of the Royal Netherlands Institute for Sea Research. This archive is managed according to the principles of the Open Access Movement, and the Open Archive Initiative. Each publication should be cited to its original source - please use the reference as presented. When using parts of, or whole publications in your own work, permission from the author(s) or copyright holder(s) is always needed. Geographic patterns of benthic diversity in Europe Running head: Geographic patterns of benthic diversity in Europe JMBA-01-16-SIEMBS15-0011 Geographic patterns of biodiversity in European coastal marine benthos Herman Hummel1*, Pim van Avesaath1, Sander Wijnhoven1,27, Loran Kleine-Schaars1, Steven Degraer2, Francis Kerckhof2, Natalia Bojanic3, Sanda Skejic3, Olja Vidjak3, Maria Rousou4, Helen Orav-Kotta5, Jonne Kotta5, Jérôme Jourde6, Maria Luiza Pedrotti7, Jean-Charles Leclerc8, Nathalie Simon8, Fabienne Rigaut- Jalabert8, Guy Bachelet9, Nicolas Lavesque9, Christos Arvanitidis10, Christina Pavloudi10, Sarah Faulwetter10, Tasman Crowe11, Jennifer Coughlan11, Lisandro Benedetti-Cecchi12, Martina Dal Bello12, Paolo Magni13, Serena Como13, Stefania Coppa13, Anda Ikauniece14, Tomas Ruginis15, Emilia Jankowska16, Jan Marcin Weslawski16, Jan Warzocha17, Sławomira Gromisz17, Bartosz Witalis17, Teresa Silva18, Pedro Ribeiro19, Valentina Kirienko Fernandes de Matos19, Isabel Sousa-Pinto20, Puri Veiga20, Jesús Troncoso21, Xabier Guinda22, Jose Antonio Juanes de la Pena22, Araceli Puente22, Free Espinosa23, Angel Pérez-Ruzafa24, Matt Frost25, Caroline Louise McNeill25, Ohad Peleg26, Gil Rilov26 1) Monitor Taskforce, Royal Netherlands Institute for Sea Research (NIOZ), Yerseke, the Netherlands, 2) Royal Belgian Institute of Natural Sciences, OD Nature, Marine Ecology and Management, Brussels and Oostende, Belgium, 3) Institute of Oceanography and Fisheries, Split, Croatia, 4) Marine & Environmental Research Lab Ltd, Limassol, Cyprus, 5) Estonian Marine Institute, University of Tartu, Tallinn, Estonia, 6) Observatoire de la biodiversité (OBIONE), LIttoral ENvironnement et Sociétés, CNRS/University of La Rochelle, France, 7) Sorbonne Universités, UPMC Univ. Paris 06, UMR 7093, LOV, Villefranche-sur-mer, France, 8) Sorbonne Universités, UPMC Univ Paris 6, and CNRS, UMR 7144, Station Biologique, Place Georges Teissier, 29680 Roscoff, France, 9) Arcachon Marine Station, CNRS, Université de Bordeaux, EPOC, Arcachon, France, 10) Institute of Marine Biology, Biotechnology and Aquaculture, Hellenic Centre for Marine Research, Heraklion, Crete, Greece, 11) School of Biology and Environmental Science and Earth Institute, University College Dublin, Ireland, 12) Department of Biology, University of Pisa, Pisa, Italy, 13) CNR, Institute for Coastal Marine Environment, Torregrande, Oristano, Italy, 14) Latvian Institute of Aquatic Ecology, Riga, Latvia, 15) Marine Science and Technology Centre, Klaipeda University, Lithuania, Klaipeda, Lithuania, 16) Institute of Oceanology, Polish Academy of Sciences, Sopot, Poland, 17) National Marine Fisheries Research Institute, Gdynia, Poland, 18) Marine and Environmental Sciences Centre (MARE), Laboratório de Ciências do Mar, Universidade de Évora, Sines, Portugal, 19) Marine and Environmental Sciences Centre (MARE) and Institute of Marine Research (IMAR), University of the Azores, Dpt. of Oceanography and Fisheries, Horta, Portugal, 20) Centre for Marine and Environmental Research, CIIMAR, and Faculty of Sciences, University of Porto, Geographic patterns of benthic diversity in Europe Portugal, 21) ECIMAT, Station of Marine Sciences of Toralla, Dpt of Ecology and Animal Biology, University of Vigo, Spain, 22) Environmental Hydraulics Institute, Universidad de Cantabria, Santander, Spain, 23) Universidad de Sevilla, Sevilla, Spain, 24) Dpt. Ecology and Hydrology, Regional Campus of International Excellence "Campus Mare Nostrum", University of Murcia, Spain, 25) Marine Biological Association, Plymouth, UK, 26) National Institute of Oceanography, Israel Oceanographic and Limnological Research, Haifa, Israel, 27) Ecoauthor, Heinkenszand, the Netherlands * Corresponding author: Korringaweg 7, 4401 NT Yerseke, the Netherlands; E-mail: herman.hum[email protected] ABSTRACT Within the COST action EMBOS (European Marine Biodiversity Observatory System) the degree and variation of the diversity and densities of soft-bottom communities from the lower intertidal or the shallow subtidal was measured at twenty-eight marine sites along the European coastline (Baltic, Atlantic, Mediterranean) using jointly-agreed and harmonised protocols, tools and indicators. The hypothesis tested was that the diversity for all taxonomic groups would decrease with increasing latitude. The EMBOS system delivered accurate and comparable data on the diversity and densities of the soft sediment macrozoobenthic community over a large-scale gradient along the European coastline. In contrast to general biogeographic theory, species diversity showed no linear relationship with latitude, yet a bell-shaped relation was found. The diversity and densities of benthos were mostly positively correlated with environmental factors such as temperature, salinity, mud and organic matter content in sediment, or wave height, and related with location characteristics such as system type (lagoons, estuaries, open coast) or stratum (intertidal, subtidal). For some relationships, a maximum (e.g. temperature from 15 to 20 °C; mud content of sediment around 40 %) or bimodal curve (e.g. salinity) was found. In lagoons the densities were twice higher than in other locations, and at open coasts the diversity was much lower than in other locations. We conclude that latitudinal trends and regional differences in diversity and densities are strongly influenced by, i.e. merely the result of, particular sets and ranges of environmental factors and location characteristics specific to certain areas, such as the Baltic, with typical salinity clines (favouring insects) and the Mediterranean, with higher temperatures (favouring crustaceans). Therefore, eventual trends with latitude are primarily indirect and so can be overcome by local variation of environmental factors. KEYWORDS Soft sediment, benthos, species diversity, densities, harmonization of methods, European cline, biogeography, latitudinal diversity gradient (LDG) Geographic patterns of benthic diversity in Europe INTRODUCTION The marine environment is of transboundary nature and needs to be studied at relevant scales of space and time. For instance, along Europe a north - northeast shift in the distribution of several marine species has been observed (Hummel et al., 2000; Beaugrand et al., 2002; Mieszkowska et al., 2006; Jansen et al., 2007). Global climate change is said to be one of the causes. However, the degree and impact of such biodiversity changes and its causes and consequences remain largely unknown (Heip et al., 2009). Question thereby still is whether changes in the level of diversity in an ecosystem really matter, since despite a huge difference in level and type of diversity between different seas e.g. in the Mediterranean (more than 17,000 plant and animal species), the North Sea (more than 1500 species) the central Baltic (only 73 marine species), trophic relationships in these systems are assumed to be similar (Elmgren & Hill, 1995; Coll et al., 2010; Magni et al., 2013; Zettler et al., 2014). Determining the patterns of biodiversity of benthic organisms and the factors that may explain them requires an integrated research strategy, which is beyond the tradition, capabilities and scales of classic research (Heip & Hummel, 2000). The first ideas for such integrated research, involving a large-scale pan-European network of marine observatories, have been formulated during the FP5 (EC 5th Framework Programme) project BIOMARE (Implementation and networking of large scale, long term marine biodiversity research in Europe), which was initiated by the European Network of Marine Research Stations (MARS). The subsequent FP6 Network of Excellence MarBEF (Marine Biodiversity and Ecosystem Functioning) adopted, and focused on, the integration of datasets and joint research (Escaravage et al., 2009; Heip et al., 2009). These projects have led to recommendations for the selection of sites and indicators to monitor marine ecosystems and their biodiversity at a pan-European scale. The aforementioned activities have been taken under the COST Action ES1003 EMBOS (Development and implementation of a pan-European Marine Biodiversity Observatory System), which lasted from 2011 to 2015. EMBOS focused on the following goals: 1) to build a large-scale pan-European network of marine observatories for biodiversity to overcome fragmentation, 2) to facilitate the monitoring of changes in biodiversity at pan-European scales using harmonized methodologies, and, 3) to assess the feasibility of the EMBOS system through pilot studies. In a series of surveys during 2014 and 2015 the forty members of EMBOS, representing 22 European countries, have measured at 28 marine sites along the European coastline (Baltic, Atlantic, Mediterranean) the degree and variation of the diversity and densities of hard and soft bottom communities using jointlyagreed and harmonised protocols, tools and indicators. In this paper, we present an overview of the harmonised methods and tools used for sampling and analysis of soft-sediment macrozoobenthos along the European coastline, as well as the results of the first surveys on the geographic patterns of diversity. For the Geographic patterns of benthic diversity in Europe soft-sediment benthos the adopted hypothesis was that the diversity for all taxonomic groups would decrease with increasing latitude (see reviews on patterns and causes of the Latitudinal Diversity Gradient (LDG) in Stehli et al., 1967; Schopf et al., 1978; Rohde, 1992; Roy et al., 1998; Gaston, 2000; Willig et al., 2003; Hillebrand, 2004). The results of the surveys carried out in 2014 were used to examine whether this LDG could be found also from our results. Hillebrand (2004) indicated that most studies on LDG comprise only few organism types and are often restricted to certain regions. Because of the harmonised set-up of the EMBOS Pilots we can address these problems and compare data on a wide range of organisms from a wide latitudinal range. Moreover, since we also included environmental data (temperature, salinity, wave height, organic and mud content of the sediment) in our analyses we can elucidate whether the trends in diversity might be explained by these factors regardless of latitude. The results for the hard bottom benthic communities along the European coastline are reported in Kotta et al. (2016, same volume) focussing on relationships between cover, diversity and environmental factors, in Dal Bello et al. (2016, same volume) with regard to scale-specific variability in community diversity and abundance, and in Puente et al. (2016, same volume) focussing on the role of physical variables in biodiversity patterns of intertidal macroalgae. The results for the functional diversity of the soft bottom benthic communities are reported in Pavloudi et al. (2016, same volume). MATERIAL AND METHODS Sampling procedure To assess the trends in diversity in soft-sediment benthic communities along the European coastline, the individual densities of macrozoobenthos species was determined at 28 stations through field surveys from the south to the north of Europe (Figure 1; Table 1). The sampling stations covered a latitudinal cline extending from the Mediterranean, through the Eastern Atlantic and the North Sea to the Baltic (Figure 1). Sampling procedures and treatment and analyses of samples were harmonised for all participants as follows. Sampling was conducted in early spring, given that by being early into, or just before, the reproduction season, then only low numbers of juveniles, if any, are present. Most samples were therefore taken in April, except for those from Crete and one location in Cyprus where samples were taken in May (Table 1). In intertidal areas, sampling was done at low tide, during the day, preferably at noon. In regions without tidal variation, samples were taken at the waterline during calm weather. When multiple stations within a region were sampled, the stations had a distance of at least two kilometres from each other (Figure 2). At each station, samples were taken at the lower intertidal (i.e. just above Low Water Level = LWL) and/or upper subtidal (UST) level at a maximum depth of two metres. At each level, three plots were chosen parallel to the LWL line, with a distance between plots of 100-200 m. At each plot, three replicate sediment samples with a depth of 30 cm, each at a distance of about two meters, were taken Geographic patterns of benthic diversity in Europe with a hand-corer with a diameter of 13 cm (Figure 3) and sieved over a 0.5 mm mesh. The residues of the sieved samples were stained with Rose Bengal and preserved in 96% ethanol or 4% formaldehyde solution buffered with borax or hexamethylene tetramine. Thus, at each station a total of nine replicates per level were taken. Replicates at the three plots were taken in sediment of comparable granulometry, whereby the median grain size was in between 0.06 and 0.2 mm (sandy silt). The metadata describing the sampling campaign can be accessed at http://lifewww-00.her.hcmr.gr:8080/medobis/resource.do?r=embos_2014. Taxonomic analysis The residues were sorted in the laboratory under a magnification lamp or stereomicroscope. The macrofauna taxa (>0.5 mm) were determined to the species level, when possible, according to up-to-date taxonomic literature, and their abundance recorded. The most optimal mesh-size for obtaining most macrofaunal species, and to have more realistic abundance values, while comparing different regions, is 0.5 mm (Rees, 1984; Bishop & Hartley, 1986; Bachelet, 1990; Ferraro & Cole, 2004; Couto et al., 2010). Species nomenclature followed the World Register of Marine Species (WoRMS) (Costello et al., 2013). Oligochaetes, turbellarians, sponges, nemerteans, insect larvae, and meiofaunal taxa (mainly nematodes and copepods) were not identified to the species level but at the overarching group levels. Incomplete specimens were counted as single individuals if containing the head, whereas other body parts assigned to a given taxon were collectively counted as “1” (one). Analysed samples were kept at the individual laboratories for (re)analyses, if needed, at a later stage. Environmental factors In order to analyse species diversity in relation to the main environmental factors, salinity was measured in the surrounding water with a CTD, and sediment temperature with the tip of a thermometer 1 cm below the surface. Moreover, additional sediment samples were taken for grain size and organic carbon content analyses. For this, two cores per plot were taken from the upper 5 cm top layer of the sediment with a 3 cm diameter corer. Samples were pooled per plot and mixed, resulting in three sediment samples per station. The samples were preserved at room temperature in aluminium foil or plastic bottles, after drying at 60 ºC for at least 24 – 48 h. Shell remains, which were abundant, were removed from the dried sediments with pincers before further sample processing. The sediment samples were centrally analysed by the Institute for Coastal Marine Environment in Torregrande, Oristano, Italy. Sediment samples (ca. 4 g) were pre-treated with H2O2 (20% volume) to eliminate organic material, washed with bi-distilled water to eliminate chlorides and then oven-dried at 40 °C for 12 h. They were subsequently wet sieved in order to obtain the sand fraction (>63 µm). Samples were then pre-treated with Na- Geographic patterns of benthic diversity in Europe Hexametaphosphate 0.6% to avoid particle flocculation for 24 h and sonicated for 5 min before analysis. The analysis of mud content (<63 µm) was performed using a Galai CIS 1 laser instrument, with specific analytical size intervals of 0.5 m (De Falco et al., 2004). The organic matter (OM) content in the sediments was determined from a subsample (ca. 1 g) by loss on ignition (LOI) at 500 °C for 3 h (Dean, 1974). An overview of the stations and the environmental factors used in the analysis is given in Table 1. To estimate the variations of sea surface temperature (SST) and significant wave height (Hs), data from 1985 to 2013 were acquired by the Instituto de Hidráulica Ambiental de la Universidad de Cantabria (Fundación IH, Santander, Spain) from reanalysis sources at the nearest coastal point with information to the reference points. SST values were supplied, with daily temporal resolution, by the Operational Sea surface Temperature and sea-Ice concentration Analysis (OSTIA) dataset, which is under MyOcean2 project by UK- Met Office (NASA) (Stark et al., 2007). Specifically, the Group for High Resolution Sea Surface Temperature (GHRSST) L4 Gap-free gridded products have been used, with a spatial resolution of 0.05º. The wave data used in this work come from the Global Ocean Wave reanalysis database (GOW), reflecting wave height in the open coastal zone (Reguero et al., 2012). Hourly significant wave height data were extracted with a spatial resolution of 0.125º for all sites. Salinity was obtained from in situ measurements provided by the World Ocean Database (WOD) of the National Oceanic and Atmospheric Administration (NOAA)-NESDIS National Oceanographic Data Centre (NODC) (Levitus et al., 2013). The salinity profiles used in this study were acquired between 1985 and 2014, and due to the sparse available data, for each station the salinity value was calculated as the average of all data points within a circle of 0.4º radius in the first 40 m around the reference points. Statistical analysis Differences in macrozoobenthic assemblages between regions and/or subregions were analyzed using a non-metric multidimensional-scaling (nmMDS) ordination model based on the Bray-Curtis dissimilarity matrix (Clarke & Warwick, 2001) calculated on the mean values among the three replicate samples within each plot. A one-way ANOSIM randomization/permutation test was used to check for the significance of differences among regions (i.e. Baltic, Atlantic and Mediterranean regions) in the ordination model (Clarke & Warwick, 2001). A one-way ANOSIM was also used to check for the significance of differences among subregions (see Tables 2a and 2b for respectively the identification of the regions and the sub-regions). All data were square-root transformed prior to the analyses, to minimise the effect of dominant species (Clarke & Warwick, 2001). One of the plots from Cyprus (Softades-Larnaca1) was excluded from the analyses as no fauna was found in each of the three replicates. MDS 2D representations were considered acceptable when Geographic patterns of benthic diversity in Europe the stress factor did not transgress the value of 0.2 (Clarke & Warwick, 2001). nmMDS and ANOSIM were conducted with the PRIMER v6.1.12 package (Clarke & Gorley, 2006). Hierarchical clustering and ordination methods were performed to identify, analyse, and compare the multivariate pattern of soft sediment macrozoobenthic assemblages based on diversity and density descriptors (number of species (S), total density (n), Margalef species richness (d = (S-1)/ln(n)), Shannon diversity (H’ = -∑pi(ln(pi)) and Pielou evenness (J’ = (H’/ln(S)) per sample with pi being the proportion of species i in the sample) and environmental and geographic location characteristics. Multivariate analyses based on community descriptors were used as an initial analysis solely based on densities for each of the species resulted in poor relations with environmental descriptors because the locations to compare at European scale each had a rather unique species composition with few species in common. A Principal Component Analysis (PCA), an indirect gradient analysis (i.e. ordination with optimal gradient distribution solely based on ‘species’ data, with plotting of environmental and location specific characteristics afterwards to identify potential relations), was performed on ‘ln(x+1)’-transformed data, using the CANOCO for Windows version 4.5 software package (Ter Braak & Smilauer, 1998). A Detrended Correspondence Analysis (DCA) showed that the data had a short gradient length, which allowed the use of a linear ordination method. In the PCA analysis, environmental and location-specific characteristics with little explanatory power towards the observed patterns in species compositions, or highly co-varying with other characteristics, are not shown in the PCA results, as omitting (or adding) potential explanatory parameters does not have an influence on the ordination results in an indirect analysis. The total macrozoobenthic densities (subdivided in abundances for larger taxonomical groups) were plotted in bar-graphs against the environmental factors that showed the best explanatory power in the PCA analysis (subdivided into classes from low to high values). Significant differences in total densities between identified classes were tested by using 2-side t-tests after testing for similarity of variances (F-tests) in Microsoft Excel 2010. Additional graphs were plotted identifying relations of Shannon diversity (H’ log e) and total macrozoobenthos densities (the average of 3 replicates per sampling plot) with the environmental parameters. Because diversity indicators such as S, d, J’ and H’ are highly correlated, as can be expected since they are calculated on the basis of the same elements, the focus was on Shannon diversity (H’) as community descriptor. Best fitting regressions were calculated starting from linear regression through a quadratic and cubic, to maximally a quartic (polynomial) regression, assuming that r2 should increase at least 10% in order to adopt a higher polynomial level as being better fitting (r2 will always increase at a higherorder term, but it is hard to imagine a biological meaning for exponents greater than 3) (McDonald, 2014). Geographic patterns of benthic diversity in Europe RESULTS Relations of major taxonomic groups with latitude and region Multivariate analyses (MDS and ANOSIM) revealed differences in the densities-based species composition of macrozoobenthic assemblages among the Baltic, Atlantic and Mediterranean regions (Figure 4a; Table 2a). We also found a significant differentiation between most sub-regions as indicated by the pairwise test (Figure 4b; Table 2b). In particular, all Mediterranean sub-regions (i.e. Eastern Mediterranean, Sea of Crete, Ionian Sea and Western Mediterranean) were significantly different from each other (Table 2b), with the highest R value when comparing the Eastern with the Western sub-region (R= 0.879, P<0.001; Table 2b). In contrast, most Atlantic sub-regions (i.e. Atlantic Ocean, English Channel and North Sea) did not significantly differ (p>0.10; Table 2b), except for the Bay of Biscay which is different from all other subregions. The distribution of the mean densities of the major taxonomic groups (expressed in absolute and relative terms) varied with latitude (Figure 5), reflecting the major differentiation among regions and sub-regions as revealed by multivariate analyses. The following major trends were found: 1) at low latitudes (= Eastern Mediterranean at 32-36 °N): very low densities of all groups, 2) at somewhat higher latitudes (= Western Mediterranean >36 °N): high densities of mainly Malacostraca (crustaceans), 3) middle latitudes (= Atlantic and North Sea): intermediate densities, with a dominance of Polychaetes, 4) high latitudes (= Baltic): intermediate densities with mainly insects. Relations of major taxonomic groups with environmental factors and location characteristics The densities of all major taxonomic groups together (i.e. total densities) did not show a consistent pattern in relation to salinity (Figure 6a). Yet, for each separate taxonomic group a specific relation with salinity was found (Figure 6b). Both in absolute as well as in relative terms, insects were mainly found at low salinities, and crustaceans (Malacostraca) at higher salinities. Polychaetes were found equally at all salinities, whereas bivalves and gastropods were not present at the lowest salinities. These results corroborate the abovedescribed results on the distribution of taxa by region, as low salinities occur in the Baltic, where mainly insects were found, and high salinities are found in the Mediterranean favouring the crustaceans. Densities of major taxonomic groups were higher at higher temperatures (Figure 7A). The insects, mainly occurring in the Baltic (Figure 7B), were found at low temperatures (as do occur in the Baltic in early spring). The crustaceans (Malacostraca), and especially the bivalves, were found mainly at higher temperatures, while polychaetes were found equally at all temperatures. 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(2014) Biodiversity gradient in the Baltic Sea: a comprehensive inventory of macrozoobenthos data. Helgoland Marine Research, 68, 1, 49-57. Geographic patterns of benthic diversity in Europe Table 1. Characteristics of the EMBOS soft substrate sample locations. Values of the Mud (% DW; <63 µm), Organic matter (%) content of sediment, and Salinity are averages of measurements at each site according to the EMBOS protocol. Values for wave height (m) and sea surface temperature (SST; °C) are the resultant of long-term Remote Sensing data interpretations for the coastal zone as specified in the Material & Methods. Location Region Subregion (Med. = Mediterranean) System type Sample date (2014) Stratum sampled Sampling depth (m, relative to LWL ) Latitude Longitude Avg. Sea Surface Temperature (°C) Salinity Mud content (%) Organic matter content (%) Avg. wave height (m) EE-Väike Väin Strait Baltic Baltic Sea Open coast 9 Apr Subtidal -0.6 58.511 23.200 6.45 4.61 0.24 EE-Gulf of Riga Baltic Baltic Sea Open coast 9 Apr Subtidal -0.6 58.371 22.982 7.67 5.04 0.64 LT-Curonian lagoon Baltic Baltic Sea Lagoon 20 Apr Subtidal -0.8 55.373 21.213 8.96 0.20 2.88 0.84 0.63 PL-Puck bay Baltic Baltic Sea Open coast 7 Apr Subtidal -0.5 54.454 18.566 7.74 8.00 0.19 0.14 0.38 PL-Vistula lagoon 1 Baltic Baltic Sea Lagoon 30 Apr Subtidal -1.0 54.331 19.542 8.96 2.19 1.36 0.35 0.43 PL-Vistula lagoon 2 Baltic Baltic Sea Lagoon 30 Apr Subtidal -1.0 54.331 19.470 8.92 2.07 2.12 0.39 0.43 NL-Oosterschelde Atlantic North Sea Lagoon 3 Apr Intertidal +0.05 51.518 4.063 11.57 29.33 2.14 0.57 0.54 GB-Salcombe estuary Atlantic English Chan. Estuary 30 Apr Intertidal +2.0 50.237 -3.760 12.52 34.41 7.08 1.73 1.25 FR-Pertuis Charentais Atlantic Bay of Biscay Open coast 29 Apr Intertidal +0.95 46.123 -1.146 14.48 32.10 8.17 1.44 0.68 FR-Arcachon bay 1 Atlantic Bay of Biscay Lagoon 2 Apr Intertidal +0.1 44.690 -1.081 15.56 17.00 37.34 2.47 0.97 FR-Arcachon bay 2 Atlantic Bay of Biscay Lagoon 2 Apr Subtidal -1.0 44.690 -1.081 15.56 17.00 56.80 4.99 0.97 FR-Arcachon bay 3 Atlantic Bay of Biscay Lagoon 1 Apr Intertidal +0.1 44.674 -1.209 15.61 27.10 8.73 1.60 1.43 FR-Arcachon bay 4 Atlantic Bay of Biscay Lagoon 1 Apr Subtidal -1.0 44.674 -1.209 15.61 27.10 38.26 4.04 1.43 ES-Bay of Santander 1 Atlantic Bay of Biscay Estuary 15 Apr Intertidal +0.5 43.438 -3.788 15.99 34.00 10.37 1.45 1.30 ES-Bay of Santander 2 Atlantic Bay of Biscay Estuary 16 Apr Intertidal +0.5 43.424 -3.803 15.99 34.00 34.11 3.60 1.30 ES-Ria Vigo Atlantic Atlantic Ocean Lagoon 1 Apr Intertidal +1.3 42.324 -8.615 15.08 21.16 4.10 2.89 0.79 PT-Ria de Aveiro Atlantic Atlantic Ocean Open coast 25 Apr Intertidal +1.0 40.860 -8.656 15.63 12.58 4.05 1.07 1.27 PT-Sines beach Atlantic Atlantic Ocean Open coast 14 Apr Intertidal +0.8 37.954 -8.866 16.91 34.40 0.90 0.49 1.64 ES-Mar Menor - Encañizadas Med. Western Med. Lagoon 2 Apr Subtidal -0.8 37.796 -0.762 19.22 43.51 9.30 2.50 0.62 ES-Mar Menor – Los Urrutias Med. Western Med. Lagoon 2 Apr Subtidal -1.0 37.687 -0.831 19.21 44.77 3.46 1.14 0.61 IT-Oristano gulf – Marceddi Med. Western Med. Open coast 10 Apr Subtidal -0.6 39.724 8.507 18.47 39.67 7.39 1.01 0.85 IT-Oristano gulf – Mistras Med. Western Med. Lagoon 14 Apr Subtidal -0.6 39.892 8.449 18.43 41.63 7.39 1.01 0.85 GR-Amvrakikos Gulf 1 Med. Ionian Sea Lagoon 7 Apr Subtidal -0.7 39.041 20.914 19.79 20.50 48.97 9.61 0.20 GR-Amvrakikos Gulf 2 Med. Ionian Sea Lagoon 7 Apr Subtidal -1.0 39.036 20.879 19.78 22.80 24.37 2.89 0.20 GR-Crete - Balos 1 Med. Sea of Crete Open coast 28 May Intertidal +0.1 35.582 23.588 19.90 38.67 0.54 1.96 0.98 GR-Crete - Balos 2 Med. Sea of Crete Open coast 28 May Subtidal -0.3 35.583 23.591 19.90 39.17 0.96 1.78 0.98 CY-Softades - Larnaca 1 Med. Eastern Med. Open coast 8 Apr Subtidal -1.0 34.813 33.541 21.46 39.26 1.93 1.35 0.35 CY-Softades - Larnaca 2 Med. Eastern Med. Open coast 1 May Subtidal -0.5 34.813 33.541 21.46 39.26 2.25 1.04 0.35 Geographic patterns of benthic diversity in Europe Table 2: ANOSIM pairwise global tests on the differentiation between regions on basis of macrozoobenthic species and densities (2a – for the regions: global R = 0.439, significance level of sample statistic 0.1%; 2b – for the subregions: global R = 0.619, significance level of sample statistic 0.1%; n.s. = not significant) Table 2a. R Significance Possible Actual Number >= Regions compared statistic level % permutations permutations observed Mediterranean, Baltic 0.54 0.1 Very large 999 0 Mediterranean, Atlantic 0.322 0.1 Very large 999 0 Baltic, Atlantic 0.522 0.1 Very large 999 0 Table 2b. R Significance Possible Actual Number >= Groups statistic level % permutations permutations observed Eastern Mediterranean, Baltic Sea 0.63 0.2 33649 999 1 Eastern Mediterranean, Bay of Biscay 0.909 0.1 65780 999 0 Eastern Mediterranean, Western Mediterranean 0.879 0.1 6188 999 0 Eastern Mediterranean, Atlantic Ocean 0.384 0.9 2002 999 8 Eastern Mediterranean, English Channel 0.487 3.6 56 56 2 Eastern Mediterranean, Ionian Sea 0.753 0.2 462 462 1 Eastern Mediterranean, Sea of Crete 0.628 0.2 462 462 1 Eastern Mediterranean, North Sea 0.615 1.8 56 56 1 Baltic Sea, Bay of Biscay 0.734 0.1 very large 999 0 Baltic Sea, Western Mediterranean 0.659 0.1 86493225 999 0 Baltic Sea, Atlantic Ocean 0.378 0.1 4686825 999 0 Baltic Sea, English Channel 0.555 0.7 1330 999 6 Baltic Sea, Ionian Sea 0.607 0.1 134596 999 0 Baltic Sea, Sea of Crete 0.595 0.1 134596 999 0 Baltic Sea, North Sea 0.341 4.3 1330 999 42 Bay of Biscay, Western Mediterranean 0.61 0.1 354817320 999 0 Bay of Biscay, Atlantic Ocean 0.595 0.1 14307150 999 0 Bay of Biscay, English Channel 0.626 0.4 2024 999 3 Bay of Biscay, Ionian Sea 0.638 0.1 296010 999 0 Bay of Biscay, Sea of Crete 0.802 0.1 296010 999 0 Bay of Biscay, North Sea 0.492 1.1 2024 999 10 Western Mediterranean, Atlantic Ocean 0.523 0.1 293930 999 0 Western Mediterranean, English Channel 0.827 0.2 455 455 1 Western Mediterranean, Ionian Sea 0.405 0.4 18564 999 3 Western Mediterranean, Sea of Crete 0.686 0.1 18564 999 0 Western Mediterranean, North Sea 0.816 0.2 455 455 1 Atlantic Ocean, English Channel 0.067 26.8 (n.s) 220 220 59 Atlantic Ocean, Ionian Sea 0.361 0.5 5005 999 4 Atlantic Ocean, Sea of Crete 0.373 0.6 5005 999 5 Atlantic Ocean, North Sea 0.056 32.7 (n.s) 220 220 72 English Channel, Ionian Sea 1 1.2 84 84 1 English Channel, Sea of Crete 0.691 1.2 84 84 1 English Channel, North Sea 0.926 10.0 (n.s) 10 10 1 Ionian Sea, Sea of Crete 0.756 0.2 462 462 1 Ionian Sea, North Sea 1 1.2 84 84 1 Sea of Crete, North Sea 0.66 1.2 84 84 1 Geographic patterns of benthic diversity in Europe Table 3. Results of Principal Component Analysis (PCA) between the diversity and density based macrozoobenthic community descriptors (number of species (S), total density (n), Margalef species richness (d), Pielou evenness (J’) and Shannon diversity (H’) per sample) and environmental and geographic location characteristics (characteristics with little explanatory power towards the observed patterns in species compositions are not indicated; to these belong the environmental variables ‘CaCO3 content’ and ‘sampling depth’). Axis 1 Axis 2 Summary statistics of first two canonical axes Eigenvalues 0.908 0.082 Species-environment correlations 0.842 0.839 Cumulative percentage variance of species data 90.8 99.0 of species-environment relation 91.4 99.6 Correlation of geographic variables with canonical axes Baltic 0.0188 0.6670 Atlantic -0.1883 -0.4315 Latitude -0.1273 0.4246 Longitude 0.3837 0.3715 Correlation of environmental variables and location characteristics with canonical axes Salinity -0.0314 -0.6280 Temperature 0.0988 -0.4795 Wave height -0.1934 -0.4638 Mud content (%) -0.3194 -0.3436 Organic matter content (%) -0.3341 -0.3063 Lagoon -0.4449 -0.0325 Open coast 0.5080 0.2662 Estuary -0.0913 -0.3611 Intertidal 0.0023 -0.3658 Geographic patterns of benthic diversity in Europe Fig. 1. EMBOS soft substrate sampling locations Geographic patterns of benthic diversity in Europe Station Y 1 series of 3 plots above LWL 1 series of 3 plots in upper subtidal At least 2 km Station X 1 series of 3 plots above LWL 1 series of 3 plots in upper subtidal 2 meter Sampling Plot Y.1 3 replicates core ø 13 cm 0.5 mm sieve 100 to 200 meter 2 meter Sampling Plot Y.2 3 replicates core ø 13 cm 0.5 mm sieve 2 meter Sampling Plot Y.3 3 replicates core ø 13 cm 0.5 mm sieve 2 meter Sampling Plot X.1 3 replicates core ø 13 cm 0.5 mm sieve 100 to 200 meter 2 meter Sampling Plot X.2 3 replicates core ø 13 cm 0.5 mm sieve 2 meter Sampling Plot X.3 3 replicates core ø 13 cm 0.5 mm sieve Fig. 2. Harmonised EMBOS sampling scheme Corer for EMBOS pilot study Inner diameter 13 cm Mark to indicate 30 cm depth Cork PVC thickness about 3 mm 125 cm Fig. 3. Standard EMBOS sampling corer for soft sediments Geographic patterns of benthic diversity in Europe 0 0,7 1,4 2,1 2,8 3,5 020 40 60 80 Shannon diversity H' Mud content (%) 0 5000 10000 15000 20000 25000 020 40 60 80 Densities (n/m2) Mud content (%) Fig. 17. Diversity (a; Shannon H’; 2nd order polynomial, r2=0.32, p<0.001) and density (b; total number per m2, 2nd order polynomial. r2=0.20, p<0.001) of macrozoobenthos with mud content (%DW). 0 0,7 1,4 2,1 2,8 3,5 0 2 4 6 8 10 Shannon diversity H' Organic matter content (%) 0 5000 10000 15000 20000 25000 0 2 4 6 8 10 Densities (n/m2) Organic matter content (%) Fig. 18. Diversity (a; Shannon H’; 2nd order polynomial, r2=0.26, p<0.001) and density (b; total number per m2, 3rd order polynomial. r2=0.21, p<0.001) of macrozoobenthos with organic matter content (%DW). 0 0,7 1,4 2,1 2,8 3,5 0 0,4 0,8 1,2 1,6 2 Shannon diversity H' Average wave height (m) 0 5000 10000 15000 20000 25000 00,4 0,8 1,2 1,6 2 Densities (n/m2) Average wave height (m) Total macrofauna Fig. 19. Diversity (a; Shannon H’; 3rd order polynomial, r2=0.41, p<0.001) and density (b; total number per m2, 4th order polynomial. r2=0.37, p<0.001) of macrozoobenthos with average wave height (%DW).