The importance of di ff erent spatial scales in determining structure and function of deep-sea infauna communities

Introduction Conclusions References


Introduction
The great variability displayed by natural communities have continuously instigated ecologists to develop and test conceptual models that explain patterns at various temporal and spatial scales based on biological interactions and/or abiotic processes (e.g. Connell, 1978;Hubbell, 2001;Levin et al., 2001b;Volkov et al., 2003;Svensson et al., 5 2007). In applying these models to the deep-sea benthic environment, the evidence to date suggests that small-scale habitat variability and patchy disturbance, as well as global and regional variability, may play roles in maintaining deep-sea diversity (Snelgrove and Smith, 2002;Rex and Etter, 2010;Vanreusel et al., 2010;e.g. McClain et al., 2011). It is generally accepted that benthic distribution and diversity patterns can be related to local and regional-scale phenomena such as geographical barriers, productivity gradients, sediment grain size diversity, and current regimes, amongst others. In turn, environmental drivers, such as the changes in sedimentary trophic parameters and physical disturbances may regulate deterministic biotic processes including colonisation, competition for food resources, predation, etc., leading to the large and 15 small-scale patterns in benthic fauna, but available data seem to suggest that particular attention should be paid to the scale relevant to the organism and their interactions when investigating such processes (Jumars, 1976). In marine biodiversity and ecosystem functioning studies, much attention is drawn to the processes themselves and the role played by single species or limited species groups (in an autecological approach), m) habitat variability and patchiness in this context has been demonstrated for only a small subset of species or taxa and for a limited number of habitats (Snelgrove and Smith, 2002). Traditionally, deep-sea studies are performed along a single spatial scale, thereby renouncing the variable importance of different scales; from micro-scale (mmcm) variability up to the larger geographic scale (100s km). Whilst it is critical to choose the appropriate scale in investigating diversity patterns (Huston, 1999) studies seeking to document the most important patterns and underlying processes for deep-sea benthic diversity and ecosystem functioning should consider the inherent scalability of patterns and processes and cover the whole spatial range.
For the benthic meiofauna (32-1000 µm, most abundant group of metazoans on 15 Earth) in the deep sea, it has long been shown that smaller spatial scales (cm) are particularly important to detect diversity and distribution patterns (Thistle, 1978;Eckman and Thistle, 1988) and micro-scale variability of biogeochemical conditions and biotic interactions along the vertical sediment profile has been used to explain the structure of meiobenthic assemblages (Thiel, 1983;Jorissen et al., 1995; a powerful influence on biotic diversity (Levin et al., 2010). At the same time, each canyon is considered unique in its environmental settings, implying great variability between canyon systems and adding to the heterogeneity observed on across-canyon scales. These canyon characteristics give support for their use in the present study to investigate the variable effects of scale in structuring deep-sea benthic assemblages.

10
The aim of this study was to address the question "what is the most determinant scale for processes that regulate structure, diversity and function of marine meiofauna in the deep sea?". A combination of four different datasets from deep-sea submarine canyon/slope ecosystems at six different geographic areas in the Northeast (NE) Atlantic were analysed in terms of community standing stocks, diversity, functional 15 characteristics and structure on different spatial scales, using Nematoda as the most representative benthic component. The different spatial scales were: Irish Margin and Western Iberian Margin (ca. 1500 km apart), distance between adjacent canyon/slope areas (50-200 km), water depth (ca. 700, 1000, 3400 and 4300 m, representing different sampling locations within a canyon, 5-50 km apart), distance between cores from 20 independent deployments (1-200 m), and vertical sediment depth differences (1-5 cm) (Fig. 1). Given the supposition that the size-scale of a group of organisms is important in identifying their communities' structure and function, we hypothesise that the sediment-dwelling meiofauna will be largely controlled by small-scale, local environmental conditions rather than large-scale differences between canyons, water depths where sediment organic loads are higher (Lampitt and Antia, 1997). At the Porcupine Seabight and further south along the Meriadzek Terrace, the margin is incised by numerous canyons and channels, which provide conduits for the transport of sediment from the shelf to the abyssal plain and over-bank turbidity currents, which deposit on the intervening terraces and spurs (Cunningham et al., 2005), but they also accumu-15 late high amounts of sediments and organic matter. In addition, at the IM cascading of dense water masses down the slope is likely to occur (Ivanov et al., 2004) and may entrain fresh chlorophyll material rapidly down slope, as reported by Hill et al. (1998). Two different systems were investigated for this study, the Gollum Channel System and the Whittard Canyon. The Gollum Channel System is a tributary channel system incis- 20 ing the upper slope of the south-eastern Porcupine Seabight, and converging into one main channel that opens into the Porcupine Abyssal Plain. Samples were taken in the most northerly channel, the Bilbo channel, at ca. 700 m and 1000 m water depth (Ingels et al., 2011c). The upper 1000 m of the water column in this channel system is dominated by the Eastern North Atlantic Water and Mediterranean Outflow Water, resulting 25 in relatively warm (8-10 • C) and saline water (ca. 35.5) between 700 and 1000 m water depth (White, 2006 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | significant turbidity. The Whittard Canyon comprises several deeply incised branches, extending from the shelf break south of the Goban Spur. Sampling locations at ca. 700 and 1000 m water depth were situated on the interfluvial area in between two upper NE branches (Ingels et al., 2006(Ingels et al., , 2011c. Down-slope sediment transport is dominated by turbidity currents in the head of the canyon, causing mud-flows to overspill the canyon 5 walls and lead to deposition of mainly fine sediments in the adjacent areas. The WIM comprises a narrow shelf and steep irregular slope, which is cut by various canyons. Hydrodynamic patterns in this area are mainly seasonal and are driven by seasonally varying winds which regulate the down-and upwelling regimes in winter and summer, respectively (Vitorino et al., 2002;Quaresma et al., 2007). The largest 10 canyon, The Nazaré canyon, intersects the entire continental shelf and acts as a temporary sediment trap with intermittent transport of sediments and organic matter to the abyssal plain (de Stigter et al., 2007;Masson et al., 2011). Samples were taken at ca. 3400 and 4300 m water depth in the canyon (sediment-laden terrace, and canyon floor, respectively), and at similar depths along the adjacent slope to the north of the 15 canyon . The relatively short Cascais Canyon begins at the shelf edge southwest of the mouth of the Tagus Estuary and extends to the Tagus Abyssal Plain. The Setúbal Canyon cuts the continental shelf close to the Sado River Estuary, and also leads to the Tagus Abyssal Plain. Comparable sedimentation regimes have been observed for both the Cascais and Setúbal canyons, with accumulation of sed-20 iment in the upper parts and limited down-canyon transport (de Stigter et al., 2011). Current regimes seem variable in both canyons. Samples in both canyons were taken at ca. 3400 and 4300 m water depth, and more or less along the axes of the canyons (Ingels et al., 2011a) 2.2 Sampling design and sample processing 25 Data from four different deep-sea canyon studies (Ingels et al., , 2011a were merged (totalling 17 273 nematode individuals belonging to 248 different genera) to investigate the most important scale of variability in structure, diversity and function of 201 A total of 162 samples were used for this study. Nematoda, the most abundant metazoan phylum in the marine environment, was used as a model taxon for the small benthic fauna. Borax-buffered formalin (4 %) sediment samples were used to extract the meiofauna using standard procedures (Heip et al., 1985; 32-1000 µm sieves, LUDOX HS as centrifugation medium) to sep- 15 arate the organisms from the sediment particles. All nematodes were counted and between 100 and 150 individuals were picked out randomly from each 1-cm sample, transferred to glycerine (Seinhorst, 1959) and mounted on slides. All nematodes were identified under a compound microscope (100× magnification) to genus level using Platt and Warwick (1988), taxonomic literature of the Nematode Library at Ghent University, and the NeMys nematode database and identification keys (Deprez et al., 2005; http://nemys.ugent.be/). Specimens that could not be identified to the genus level were assigned to the appropriate higher taxon level. All individuals were grouped into four feeding types based on buccal morphology and teeth composition sensu Wieser (1953): selective deposit feeders (1A), non-selective deposit feeders (1B), epistratum 25 feeders (2A), and predators/scavengers or omnivores (2B). This classification was amended with one extra group to account for "chemosynthetic" nematodes that lack a mouth and buccal cavity, have a degenerated alimentary canal and live in association with symbiotic micro-organisms (Ingels et al., 2011c) individual was assigned a c-p score (score from 1 to 5 reflecting life history with 1 = colonizer and 5 = persister; in this context colonizers are regarded as r-strategists, and persisters are regarded to be k-strategists; cf. Bongers (1990) and Bongers et al., 1991). Length (excluding filiform tails) and maximum width were measured using a Leica DMR compound microscope and Leica LAS 3.3 imaging software.

Data treatment and analysis
Various descriptors for nematode structure, diversity and function were used to test the importance of different scales in determining community patterns (Table 2). Community structure was determined by using the relative abundances of genera in the sample assemblage. Diversity descriptors used were the four Hill numbers (Hill, 1973) and 10 expected number of genera for a normalised sample size of 51 individuals (EG(51)), based on the formula by Sanders (1968) which was later corrected by Hurlbert (1971). Hill numbers were used because they give a measure of both richness, as well as equitability (evenness) of the communities studied (Heip et al., 1998). As functional descriptors, we used Trophic Diversity (TD) and the Maturity Index (MI). We used the 15 reciprocal value of TD as defined by Heip et al. (1998), so that higher values correspond with higher trophic complexity, and it was modified for use with the four Wieser (1953) feeding groups and the extra "chemosynthetic" guild (Ingels et al., 2011c). The MI was originally defined by Bongers (1990) for soil nematodes, but has been applied to marine nematode communities (Bongers et al., 1991). The MI is a useful descriptor in that it 20 characterises the community in terms of life-history and -strategies of its members and has been successfully used to infer various types of disturbance and subsequent recolonisation processes. Similarly to TD, MI is based on autecological information, but it is based on a broader character complex. To distinguish the significance of different scale effects in determining deep-sea 25 meiofauna communities four different sets of community descriptors were analysed (  Anderson et al., 2008). Genera relative abundance data were standardised for sample size, square-root transformed, and Bray-Curtis was used as a similarity measure. The diversity descriptor data (Hill numbers,EG(51)) were normalised sensu Clarke and Gorley (2006) and Euclidean distance was used to construct the resemblance matrix. The same diversity data treatment was applied to the sets of standing stock (total 5 abundance, total biomass) and functional descriptors (TD, MI). For the PERMANOVA tests, we used a mixed-model hierarchical design (Table 3) with four factors: Area (Ar, fixed, with levels "Whittard", "Gollum", "Nazaré", "Setúbal", "Cascais", "Slope"), Water Depth (WD, fixed, with levels "700 m", "1000 m", "3400 m", "4300 m"), Core (Co, random, identifying each core in the dataset to account for repli-10 cate variability at the station level and adding an extra spatial scale to the model), and Sediment Depth (SD, fixed, with levels "0-1", "1-2", "2-3", "3-4", "4-5", identifying each sediment layer). Because the different levels of WD were not represented at each margin, the dataset was split into two groups, one for each margin.
The non-replicated nature of the vertical sediment layers within each core warranted 15 a split plot design with Co nested in Ar and WD, leading to a repeated measures analysis, whereby the main-factor test was followed by a pairwise comparison test within each significant double or triple factor interaction term to investigate significant effects in the full-model test. The nesting of Co in Ar and WD had as a consequence that the variability contained in the term Co (Ar × WD) × SD, indicative of the variability of each 20 layer within each core, is included in the residual term, leading to a more conservative test. Because of the unbalanced design (not all sediment layers are fully replicated for each Ar × WD combination) in the PERMANOVA model we used type III sums of squares (partial) leading to a conservative test while maintaining independence between terms. To assess the magnitude of the spatial variation at each spatial scale 25 we used the estimated components of variation (ECV) as a percentage of the total variation. When negative variance components were encountered, these were set to zero in the assumption that they were sample underestimates of small or zero variances (Benedetti-Cecchi, 2001;Fletcher and Underwood, 2002 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | multidimensional scaling plots (MDS) were used to illustrate the variability contained within each descriptor set and visualise the main-factor and interaction effects.

Results
The community structure was significantly different for all factors and interaction terms (except for WD × SD at the WIM, Table 3), with greatest variability found at the station 5 level (Ar × WD) for both IM and WIM margins as indicated by ECV values (Fig. 2a). Relative effect sizes were larger for the IM, except for the factor Ar. Community effects of WD, Core (Co) and three-way interaction terms were lower than those of Ar, SD and Ar × WD (station scale) at both margins ( Fig. 2a). The effect size of sediment depth (SD) occupied third place at the WIM and was placed second at the IM, imply-10 ing important variability occurring at the sediment micro-scale. The SD effect is clearly illustrated in Bray-Curtis space in Fig. 3a, showing the increasing variability contained within deeper SD layers. The 0-1 cm layers group tightly (smallest grey area), while with increasing SD the resemblance between samples gradually increases, with maximum variability exhibited for the 4-5 cm layer.
15 Figure 3c, d shows the different community variability contained within each area, and within each water depth, respectively as attested by the ECV values in Fig. 2a. Area differences, as evidenced by ECV values (Fig. 2a), are larger at the WIM than at the IM, which is also illustrated by the differential size of overlap between the greyshaded areas in Fig. 3c for each margin. Water-depth differences are smaller at the 20 WIM compared to the IM, as attested by the smaller overlap of grey-shaded areas in Fig. 3d and the WD ECV values (Fig. 2a) at the IM compared to those of the WIM.
Several double interaction terms were significant (Table 3; Fig. 2a) prompting us to investigate pairwise comparisons within each significant term (Supplement, Appendix A, Table A1). For the IM, these show that differences between the surface layers and the 25 deepest sediment layers are more pronounced, and that these differences are variable between different areas and water depths. Similar patterns are observed for the WIM.

205
BGD 10,2013 The importance of spatial scales in the deep sea To investigate the significant three-way interaction factor (Ar × WD × SD), subsequent pairwise comparisons were performed within the three-way term for both margins (Table A1), and the reasons for the three-way interaction can be seen in Bray-Curtis space in Fig. 3b-d. For the IM, area differences are clear for nearly all WD × SD combinations (Table A1). WD differences on the other hand were only significant for each of 5 the Whittard Canyon Ar × SD combinations. Pairwise SD comparisons for each station (Ar × WD) indicate that SD variability is a general phenomenon at the IM, with hardly any significant differences between stations. The SD gradient that can be seen for the IM in Fig. 3b is indeed similar for all stations, whilst the differences between WDs are more pronounced for the Whittard Canyon compared to the Gollum Channels.

10
At the WIM, there are three distinct groups of stations, visible in Fig. 3b. At each station (Ar × WD, exhibiting the largest effect scale), the variability contained along the vertical sediment depth differs considerably, with for instance smallest SD variation observed for the Nazaré 3400 m station and greatest SD variation at the Nazaré 4300 m station (Fig. 3b). 15 Core effects were significant for both margins (PERMANOVA; p < 0.01), but were small compared to Ar, SD and station (Ar × WD) effects (Fig. 2a). Sediment depth variability within each core was high as illustrated by the spatial coverage in the MDS plots ( Fig. 3e, f), but was variable depending on the Ar, WD or Ar × WD considered.
The PERMANOVA results for the diversity descriptors (Table 3) at the IM indicate that 20 SD is the main factor causing most variability (SD differences are greater when comparing surface layers with the deepest layers, cf. pairwise comparisons), and Ar × SD the most important interaction term. Area, WD and Ar × WD, although significant, constitute only minor sources of variability. The reason behind the significant Ar × SD interaction lies in the fact that SD diversity differences are differently expressed in the Gollum and 25 Whittard areas (Figs. 2b,4a), and this is confirmed by pairwise comparison tests (Supplement, Appendix A, Table A2). Together with the significant double interaction terms, the significant three-way interaction term Ar × WD × SD suggests that SD variability is also differently expressed within each level of WD and Ar × WD at the IM (Table 2b; 206 BGD 10,2013 The importance of spatial scales in the deep sea  Fig. 4b). The case for the WIM is different; SD and Ar are the most important in terms of effect size (Fig. 2b). Similar to the IM, however, SD diversity differences vary according to which level of Ar × WD is considered. These interactions are visible in the MDS plot of Fig. 4b. The factor Co was not significant, indicating no differences between cores from different deployments at each station. Overall, diversity patterns between 5 margins differed with a partial separation of samples from different margins based on Euclidean distance values (Fig. 5a), but this may have been caused by the WD differences between margins inherent to our sampling design since a very similar separation is visible for the factor WD (Fig. 5b).
The PERMANOVA results for the functional descriptors can be interpreted in the 10 same way as the diversity results. For the IM, SD is the main factor with the highest effect size (Fig. 2d). The IM Ar × SD significant interaction term signifies the differential SD diversity in different areas (Fig. 4c). The main factors Ar and WD only cause minor variability based on function descriptors. For the WIM, SD is again the most important main factor for which variability is significant (Fig. 2d), with differences between different 15 areas and stations (Fig. 4d) and see pairwise comparisons in Table A3 (Supplement, Appendix A), causing the interaction terms Ar × WD, Ar × SD, and Ar × WD × SD to be significant as well. The factor Co was not significant, indicating no differences between different deployments at each station. No clear margin or water depth separation was observed based on Euclidean distance measures of sample diversity (Fig. 5c, d), but 20 variability between samples was greater at the WIM than at the IM as illustrated by the spatial coverage of the sample clouds in Fig. 5c, d. The variability observed for standing stocks is mainly caused by differences at the scale of sediment layers. This is particularly the case at the IM, where ECV for the factor SD explains 55 % of the total variation; at the WIM, this is only 21.3 %. At the IM, 25 the SD differences are variable between different levels of Ar and WD effects, resulting in significant interactions (Ar × SD, WD × SD, Ar × WD × SD; Fig. 2c, Supplement, Appendix A, Table A4), which are clearly discernible in Bray-Curtis space as illustrated in Fig. 4e. Overall, no clear standing stock patterns arose in the MDS plot of Fig. 5e, f BGD 10,2013 The importance of spatial scales in the deep sea due to margin or WD differences, but the WD × SD effect at the IM is visible in that the 1000 m sample points are more dispersed compared to the 700 m sample points.

Discussion
The aim of this study was to analyse and assess the importance of different spatial scales in structuring deep-sea meiofaunal communities. To achieve this, a large set 5 of sediment samples from different submarine canyons along the European margins in the northeast Atlantic, encompassing spatial scales ranging centimetres to 100s of kilometres, were analysed for nematode community patterns, using different sets of descriptors to describe community structure, diversity, function and standing stocks. This study is the first to include functional parameters as descriptors of meiofauna communities to reveal the importance of different spatial scales and discuss associated processes on deep-sea benthic communities. In support of using nematodes as representative taxon, we note here that they comprise 90 % or more of the metazoan organisms in the deep sea, they exhibit very high species and genus richness, are sensitive to environmental perturbations and have well established functional traits which have 15 been used successfully in biodiversity and ecosystem functioning studies (Danovaro, 2012). By using submarine canyons -assumed to be the most heterogeneous environments in the deep marine realm -to test the importance of different spatial scales, we perhaps reduce the possibility that larger scale gradients, such as latitudinal and 20 bathymetrical, attain an important status in driving benthic assemblages because localscale heterogeneity can be the paramount effect in structuring the resident fauna (Rex et al., 1993(Rex et al., , 2006Rex and Etter, 2010). Yet, considering the pervasiveness of canyons along the world's continental margins (De Leo et al., 2010;Harris and Whiteway, 2011), an important source of heterogeneity may be omitted in studies that exclude canyon

Margins, water depth and inter-canyon comparisons: the large spatial patterns and processes
Latitudinal and bathymetrical gradients in benthic assemblages have been widely recognised in the deep sea (Rex et al., 1993(Rex et al., , 2006Rex and Etter, 2010), including for meiofaunal organisms (Rex et al., 2001;Lambshead et al., 2002;Mokievsky and 5 Azovsky, 2002;Mokievsky et al., 2007). These large geographical gradients may represent environmental gradients or contrasts that drive the faunal assemblages. We noticed clear differences in community structure -and to some extent diversity -between the IM and WIM, but we cannot rule out that these are the result of bathymetric variability since water-depth comparisons were not the same at each investigated margin.
Water depth and latitude (or margin differences) may be inextricably linked because of ocean basin topography, water-mass characteristics, oceanographic currents and fronts, and sampling design, and the role of depth needs to be accounted for when analysing latitudinal patterns to avoid confounding the role of the most important scale (Lambshead et al., 2001;Rex et al., 2001). In doing so, Rex et al. (2001) suggested that 15 nematode patterns are predominantly shaped by bathymetrical changes rather than latitudinal differences when comparing only those two variables. Within each margin, our analyses showed that WD affected community structure and diversity, but not biomass, whilst nematode function only differed with WD at the Irish Margin. The benthic environment at different margins can be typified by different euphotic productivity regimes, 20 and consequently variable phytodetrital influx and quality. Water depth differences may add to the gradient created by variable surface production through the degradation processes that ensue; deeper stations may receive more degraded organic matter compared to shallower locations, resulting in benthic structure and diversity differences.
The contrast between 700 m and 1000 m stations at the IM in terms of phytodetrital 25 influx and presence of organic matter may be greater than is the case when comparing 3400 and 4300 m depth stations (WIM), because of the higher down-canyon transport, more rugged topography, and greater accumulation rates in the upper regions of the canyon/channel systems compared to the deeper parts. The nematode functional differences between water depths at the IM, and the lack of them at the WIM, may be representative for such contrasts -nematode trophic diversity (function) may have complied with the differences in food arrival. Exacerbating the effect of the here observed WD-contrast between margins could be the underlying regional differences 5 in euphotic production. The North Atlantic is a particularly productive area with high deep-sea fluxes because of inadequate zooplankton grazing in the upper water column (Longhurst et al., 1995;Longhurst, 2007). This is particularly the case for the Porcupine Abyssal Plain and adjacent margin where the Gollum Channels are situated and further south along the Goban Spur, below which the Whittard Canyon is located varied substantially with water depth (Ingels et al., 2011c, Tchesunov et al., 2012, possibly explaining the WD differences observed for community structure, diversity and function. These community differences may also contribute to the higher WD effectsizes observed for the IM compared to the WIM, since chemotrophic nematode genera are absent from the WIM in the here analysed dataset. Water depth differences may 5 also bear a relation to grain size differences, particularly in canyons where hydrodynamic flow is able to sort sediment particles efficiently along a WD gradient. Grain size is known to regulate benthic diversity (Etter and Grassle, 1992) beyond the effects of water depth and food input (Leduc et al., 2012), and a WD effect on community structure and diversity is evident here. Significant community descriptor differences between 10 WD levels hence suggest the existence of regulating mechanisms on the associated spatial scale, but differences were not clear for standing stock descriptors, suggesting biomass and abundance patterns are likely driven by patchiness and processes on smaller spatial scales within each investigated canyon system. Turning to the regional spatial scales within each margin separately, we have to 15 appreciate the contrasts posed between different areas, represented by the different canyon systems. It was clearly shown that the canyon communities differed between different margins, but variability is also high within each margin. Area differences were significant for the community structure and the diversity and functional descriptors (Table 2a-c), albeit with several significant interactions with WD and SD, implying levels of 20 variability being expressed differently within different factor combinations. Submarine canyons are arguably the most heterogeneous habitats in the deep sea, displaying high diversity in terms of morphology, topography, sediment transport processes, hydrodynamic activity, geological structure, size, sinuosity, substratum types, position and distance from land and river systems; all characteristics that may be determinative for Introduction

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Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | slope samples in the canyon dataset at the WIM, and the fact that not all WIM canyons are connected to river systems may be the reason for the higher Ar effect size at the WIM. This highlights the importance of inter-canyon differences (i.e. Ar differences) and processes that act on this scale and their role in regulating benthic communities, which seems superimposed on the effects associated with continental margin and WD 5 differences.

Stations, replicates and sediment depth comparisons: the small spatial scales and processes
The heterogeneity observed between canyons extends to the within-canyon comparison between subhabitats or stations (Ar × WD, 5-50 km apart), and between the lo-10 cations of replicated samples at each station (Co (Ar × WD), 1-200 m). Highest effect sizes on community descriptors occurred at the level of stations (Ar × WD) and vertical sediment depth, implying that processes that act on these spatial scales are determinative for structure, diversity, function and standing stocks of the resident communities. Differences between replicate locations (Co(Ar × WD)) were minor compared to SD 15 and station differences, suggesting the distances between replicate samples hosted no great faunal variability. Only for the community structure, significant differences were observed between replicates, with similar effect sizes as Ar and WD differences. Community structure differences between adjacent patches of seafloor indicate that smallscale heterogeneity may be at the basis of niche separation for different genera in 20 this case, with different genera benefiting from different environmental conditions over small (1-200 m) distances. Diversity, function and standing stocks, on the other hand are more uniform over these distances, and seem more susceptible to differences over cm scales. Submarine canyons offer a highly heterogeneous habitat relative to similar depths 25 on slopes (Levin and Gooday, 2003), which translates into numerous available subhabitats within these systems (flanks, walls, overhangs, thalweg, sedimented terraces and slopes, etc. canyon systems, increased heterogeneity also applies for these subhabitats as indicated by the high Ar × WD (station) interaction effect sizes. Processes acting on the station scale, such as hydrodynamic activity and frequency and intensity of sediment disturbance events may be superimposed on the patterns caused by larger spatial scale processes such as regional or water depth-dependent phytodetrital input, and 5 this seems particularly the case for submarine canyon systems. Environmental variables such as oxygen, temperature, resource availability, and grain size may vary with within-canyon morphology and associated flow dynamics, including enhanced currents and detrital flows, exerting control on the faunal communities present (Vetter and Dayton, 1999). Topographical effects on the within-canyon scale have also been observed 10 to drive the quantity and availability of food resourcesleading to different faunal communities at short distances from each other (McClain and Barry, 2010). The aggregation of organisms at locations with enhanced food availability within a canyon may augment the effects of biotic interactions between different faunal groups and species, leading to further fluctuations of community characteristics over small to medium distances (Gal-15 lucci et al., 2008a;McClain and Barry, 2010). The within-canyon processes relevant for the km-scale mentioned here are likely more important than the larger-scale processes in this study judging by the high Ar × WD variance components, particularly for community structure (Fig. 2a). Community structure differs between stations, and hence the processes associated 20 with that scale, but the sediment depth effect is here considered as the most important factor affecting community diversity, function and standing stocks and may be related to numerous processes, environmental and biological, acting on the cm scale. The implications of this are not limited to the vertical gradients per se, but may be seen as representative for small horizontal variations along the deep-sea floor. Environmen- 25 tal gradients on the cm scale are imperative in driving benthic assemblages because they define the suitability of the niches that are exploited by different small-sized benthic taxa, and are influenced by the activities of the taxa themselves (e.g. bioturbation and nutrient flux generation). Previous studies suggest that the spatial dynamics of  Gallucci et al., 2008b;Fonseca et al., 2010;Guilini et al., 2011), but small-scale patterns of deep-sea meiofauna are still poorly understood (Snelgrove and Smith, 2002). It is believed that like macrofauna organisms, meiofauna species are patchily distributed with patch sizes ranging a few centimetres to meters (Gallucci et al., 2009) which accords with our results. Nema-5 todes, for instance, are attracted to patches with high levels of food, but the scale on which food input drives nematode communities varies from local scale patches to regional scale phytodetrital input. Fonseca et al. (2010) reported that chloroplastic pigments, as an indicator of food availability, may vary most on very small scales (cm), implying that these are the results of local variability. In the same study, however, sedi-10 ment depth was not the most important scale of variability and hence stands in contrast with our results. The distances between cores was one of the moret important scales in the Arctic deep-sea study, possibly related to the distribution patterns of chloroplastic pigment content of the sediments, but the authors also suggested that other (unmeasured) environmental variables are likely the main cause of small-scale fauna 15 variability. The contrast between Arctic deep-sea sediments (Fonseca et al., 2010) and the canyon sediments in the present study may explain the difference in importance of vertical scale in driving communities; whilst Arctic deep-sea sediments are characterised by a surficial layer of phytodetrital food over larger areas, regulated by strong seasonality, canyon sediments are characterised by different levels of disturbance and 20 temporal dynamics allowing the burial of organic matter in deeper sediment layers and enhancement of microhabitat variability. The strong heterogeneity on small spatial and short temporal (disturbance-related) scales in canyon sediments may hence add to the contrasting observations. It is on the small cm scale that also the sediment grain size should be considered 25 as a direct regulating factor for benthic communities. Particle-size diversity is known to positively influence meiofaunal diversity through increased partitioning of food resources based on particle size, and/or greater habitat heterogeneity (Leduc et al., 2012 and references therein), which would also result in higher functional complexity of the  (Ingels et al., , 2011c. In the case of canyons, grain size composition can vary greatly between locations because of variable sediment deposition and hydrodynamic sorting. Disturbance events such as gravity flows and slumps, add to this variability by redistributing the sediments, as does the feeding and burrowing activity of benthic organisms. These processes cause granulometric differences predominantly 5 on very small scales, supporting their importance in regulating benthic patterns along the vertical sediment depth and horizontal cm scale. Both food availability and strength and frequency of disturbance events can be considered in the patch mosaic model, whereby the spatio-temporal mosaic of sedimentdwelling communities is driven by highly localised processes, such as colonisation fol-10 lowing disturbance events. This supposition is not limited to the meiofauna, macrofauna also exhibits spatial dispersion patterns driven by the presence of a mosaic of microhabitats in canyon sediments (Lamont et al., 1995). Further evidence for this can be found in the association of meiofauna with biogenic structures, such as foraminifera and sponges (Levin et al., 1986;Hasemann and Soltwedel, 2011) which may provide pro-15 tection against small disturbance events and may indirectly increase food-availability thereby attracting a suite of prokaryotic and metazoan organisms (Levin and Gooday, 1992) or providing a more complex habitat structure (Hasemann and Soltwedel, 2011). In addition, the physically controlled sedimentary environment is modified at the mm to cm scale by bioturbation, a common feature in many canyons. 20 Considering the biochemistry of sediments, we have to appreciate the role of oxygen and other chemical gradients along the vertical scale, since it has been shown that such variables affect the meiobenthic communities greatly (Vanreusel et al., 1995;Soetaert et al., 1997Soetaert et al., , 2009Cook et al., 2000;Gooday et al., 2000;Moodley et al., 2000;Braeckman et al., 2011). Moreover, the interaction between oxygen and food has been found 25 to affect meiofauna assemblages via mechanics explained by the TROX model (Jorissen et al., 1995). In organically enriched canyon sediment patches, the ecosystem is no longer food-controlled, but instead oxygen takes over and drives the structure and diversity of benthic fauna (Jorissen et al., 1995). This is exemplified here at the IM, with higher structural and functional diversity compared to the WIM, partly because of the presence of chemotrophic nematode genera in response to reduced micro-patches, and a redox layer appearing closer to the sediment surface (Ingels et al., 2011c). Hence, the role of sediment depth is more important at the IM for different community descriptors (Fig. 2a-d). In recent years, evidence has emerged that oxygen could 5 be a particularly powerful mediator in creating patches (anoxic micro-environments) and/or small-scale reduced environments, in areas that are not truly chemosynthetic (e.g. Van Gaever et al., 2004;Ingels et al., 2011c) with effects on meiobenthic diversity and function as a result.
The results of the present study suggest that differences on small spatial scales 10 are more important than larger spatial scales in identifying benthic patterns. If we are to improve our understanding of these patterns and underlying processes that drive sediment-dwelling faunal communities, their structure, diversity and functioning, we need to focus on the small scales in deep-sea environments, particularly for canyons. Patchy input and local reworking of phytodetritus and sediments, seafloor microtopog-15 raphy, sediment biogeochemistry as well as benthic biogenic processes in the sediment (e.g. bioturbation, biogeochemical processes mediated by fauna and chemical interactions), and disturbance events, are likely the cause of the high variability observed along the vertical sediment scale in the present study and further investigations into the causal mechanisms are warranted. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Gallucci, F., Moens, T., Vanreusel, A., and Fonseca, G.: Active colonisation of disturbed sediments by deep-sea nematodes: evidence for the patch mosaic model, Mar. Ecol.-Prog. Ser., 367, 173-183, 2008b. Gooday, A. J., Bernhard, J. M., Levin, L. A., and Suhr, S. B Ingels, J., Kiriakoulakis, K., Wolff, G. A., and Vanreusel, A.: Nematode diversity and its relation to quantity and quality of sedimentary organic matter in the Nazaré Canyon, Western Iberian Margin, Deep-Sea Res. Pt. I, 56, 1521-1539, 2009 functional diversity of Nematoda in relation with environmental variables in the Setúbal and 5 Cascais canyons, Western Iberian Margin, Deep-Sea Res. Pt. II, 58, 2354-2368, 2011a An insight into the feeding ecology of deepsea canyon nematodes -results from field observations and the first in-situ 13 C feeding experiment in the Nazaré Canyon, J. Exp. Mar. Biol. Ecol., 396, 185-193, 2011b. Ingels, J., Tchesunov, A., and Vanreusel, A.: Meiofauna in the Gollum Channels and the Whit-   (Hurlbert, 1971;Heip et al., 1998) Adapted for normalized sample size of 51 individuals • q i = proportion of feeding type i in the assemblage • n = number of feeding types (5) MI (maturity index) (Bongers, 1990;Bongers et al., 1991) n i =1 v i * p i • p i = relative proportion of genus i in sample • v i = c-p score Standing stock Total nematode abundance (ind./10 cm 2 ) ---Biomass (µg dry weight/10 cm 2 ) Based on Andrassy (