“Not to be cited without prior reference to the author” ICES CM 2010 / Q:12
Identification of sensitive benthic habitats in the Eastern English Channel based on functional traits and the Kostylev approach Aurélie Foveau*, Sandrine Vaz*, Vladimir E. Kostylev+ * IFREMER - Centre Manche - Mer du Nord, Département Halieutique Manche - Mer du Nord, 150, Quai Gambetta, BP 699, F- 62321 Boulogne/mer, France [emails :
[email protected];
[email protected]] + Natural Resources Canada, 1 Challenger Drive (P.O. Box 1006), Dartmouth, NS, Canada B2Y 4A2 [email :
[email protected]] Keywords: epibenthic invertebrate communities, trawling impact, sensitivity, habitat template, functional traits ABSTRACT Mesoscale information on offshore benthic species and assemblages is often lacking and the use of fish assessment research surveys enables the observation of the macro-epifauna and megafauna over large geographic areas. The species sampled by trawling represent mainly the sessile part of the macro-invertebrate fauna which is the part of benthos most susceptible to be adversely affected by certain fishing activities. Therefore, these species may serve as accurate indicators of benthic habitat sensitivity to bottom trawling. The aim of the present study was to determine the distribution of the main epibenthic habitats and their sensitivity to fishing effort in the Eastern English Channel and southern North Sea. The Kostylev habitat template mapping approach was adapted to predict the sensitivity of benthic habitats. Moreover, a functional approach (study of the species biological traits) was applied to complete and validate this habitat sensitivity modelling. This kind of information may be very relevant to plan future human activities in the area and to mitigate potential impacts of fishery active trawling. It may also be useful to better understand the factors affecting the distribution of fish. INTRODUCTION The English Channel is a biogeographical crossroad between the Atlantic Ocean and the North Sea waters. The Channel’s configuration (bathymetry and coastal arrangement) contributes to create specific structures (fronts and gyres), which control advection processes, the dispersion of living organisms but also pollutants, etc. But, this area is also one of the world’s busiest areas in terms of anthropogenic activities (maritime traffic, gravel extraction, offshore windfarm…). And it supports key fishing grounds as a result of the presence of numerous commercial fish species, nursery and spawning areas, migration routes, all related to specific environmental characteristics. In this area, some rich benthic communities can also be found, which, because of their constraint mobility, may integrate local conditions and be good indicators of long-term environmental changes. In this context, the CHARM III project is an ecosystem-based approach of marine resources management, which requires the synthesis of existing scientific knowledge and its integration to new research. Such an approach will help improving the quality of management and planning advice given to decision-makers.
One of the actions of this project is linked to the description of the structure, composition and distribution of benthic invertebrates in the Eastern English Channel and southern North Sea, based on samples collected with a bottom trawl. The information on offshore species and assemblages at mesoscale often lacks and the use of fish assessment research survey enables the observation of the macro-epifauna and megafauna on large geographic areas. Moreover, because of the large area covered during trawling, these observations represent a habitat on a larger scale than that usually studied using grab. The species observed by trawling are essentially represented by the sessile part of the macroinvertebrate fauna, the most susceptible to be affected by trawling from fishery activities. In order to determine the sensitive benthic habitat in the Eastern English Channel and south of the North Sea, it has been chosen to use the method now known as the Kostylev method (figure 1; Kostylev, 2004, 2005, 2007), which is based on the principles used in others publications (Grime, 1977, Huston, 1994, Southwood, 1977, 1988). This method presents the different benthic habitat in terms of “scope for growth” (sometimes named “adversity”, which represents the unfavorableness of habitat and factors that pose a cost for the physiological functioning of species) and “disturbance” (which reflects the intensity of habitat destruction or alteration, or durational stability of habitat).
Figure 1: Schematic representation of the concept of habitat template.
Moreover, Kostylev (2005, 2007) highlights that the habitat template created must be correlated to the distribution of species and could be validated as a predictor of the communities’ distribution. This kind of information may be very relevant to plan future human activities in the area and to mitigate potential impacts of bottom fishing. It may also be useful to investigate the factors affecting the distribution of marine species.
METHODS In this part, we describe first the different data and sources used to create the habitat template. Then, the analyses used to validate the habitat template were presented.
Depth Depth is presented as bathymetry plus mean sea level (figure 2). From an ecological point of view, the notion of depth was considered more pertinent than bathymetry alone. The depth raster layer was created (using ArcMap, © ESRI) by adding the bathymetric raster to that of mean sea level. These two rasters were created as follows. Bathymetric data (or zero level, or low tide, i.e. corresponding to a tidal coefficient of 120) were derived from SHOM (Service Hydrographique et Océanographique de la Marine) navigation charts. Starting with a regular grid of 1.8 km resolution (referenced in WGS 1984 datum), a continuous raster of 1 km² resolution was created by simple interpolation. Mean sea level was estimated using IFREMER’s MARS 3D hydrodynamic model (Le Roy & Simon, 2003). This level corresponds to mid-tide, i.e. to a tidal coefficient of 70. The model is built on the basis of a regular square grid (of 4 km cell size) using sigma coordinates (with the same number of layers across the study area) and is applicable to an area extending from the Lizard Point (United Kingdom) to the north of the River Rhine on the continent. The calculation grid is nested in a series of grids of greater spatial extent providing required values at the marine boundaries of the hydrodynamic model. This grid of points (referenced in datum WGS 1984) was then interpolated to create a continuous raster of 1 km² resolution.
Figure 2: Depth in the Eastern English Channel and the south of the North Sea (deeper blue represents the higher depths).
Temperature Sea surface temperature (SST) is here estimated using satellite imagery (figure 3). The first step consists in assessing the physical value of interest by applying geometric and atmospheric corrections onto the measurements taken by the sensor on-board the satellite, for instance the sea brightness temperature (thermal infra-red, AVRHH sensor on-board NOAA satellites) to estimate sea surface temperature. Then, climatologies, which study weather conditions averaged over a period of time (e.g. monthly maps), can be produced using the data.
Sea Surface Temperature (SST, in °C) is calculated using the infra-red channels of the AVHRR (Advanced Very High Resolution Radiometer) sensor on-board NOAA satellite platforms. Since 1986, NOAA polar-orbiting satellites series (NOAA 9, 11, 14, 16, 17 …) have provided data to build twice-daily temporal series for SST. The SST calculation algorithm is described in Walton et al. (1998), and it uses measurements from the sensor’s channels 4 and 5. The coefficients are calculated by regression using in situ data. For Climatologies per month (January-December) of STT, the maps cover the period 1986-2006 (AVHRR sensor). Images (provided as rasters, 1.2 km cell size, referenced in WGS 1984) were obtained from IFREMER’s CERSAT (located in Plouzané, France) from databases generated for European projects (e.g. MARCOAST, ECOOP). Original data come from the AVHRR/Pathfinder centre (AVHRR sensor) and from NASA (SeaWiFS and MODIS). The best images, i.e. those where the percentage of cloud-free pixels was above a threshold of 25%, were used to calculate monthly averages. The mean was calculated on a Mercator grid (733 columns by 657 lines) with a pixel size of 1.2 km. For each pixel of the grid, the mean value is simply the arithmetic mean of all the satellite-derived SST recorded during the month considered.
Figure 3: Mean sea surface temperature in the Eastern English Channel and south of the North Sea (in blue: low values, in red: high values).
Sediment type The map of seabed sediment types presented is derived from the so-called "Larsonneur map" (Larsonneur et al., 1979). This map of superficial sediments in the English Channel was created using data available in 1977 (around 12,000 samples, plus additional information derived from British publications, navigation charts, rock coring and seismic profiles necessary to determine the occurrence and the spatial extent of rock outcrops). Each sampled station was assigned a sediment type based on its granulometry and its calcium carbonate content, resulting in 48 possible seabed types, though three were not found in the English Channel. Seabed sediment types could also be classified into four main categories (pebble, gravel, sand and mud) based on their granulometry. These criteria enhanced the importance of
smaller particles on one hand, and of coarse particles on the other, which both determine the physical and chemical properties of the deposits and hence the biotopic characteristics. The Larsonneur paper chart was digitised and it was decided to use only five main categories of sediment (pebble, gravel, coarse sand, fine sand and mud). Then, a mean grain size value was assigned for each sediment type polygon so as to calculate the disturbance axis (figure 4).
Figure 4:Distribution of the sediments types in the Eastern English Channel and south of the North Sea, weighted by the values of the mean grain size (in red, the polygons with the more important mean grain size, in blue, the polygons with the lower mean grain size).
Habitat template Disturbance axis The disturbance axis, which reflects the intensity of habitat alteration or destruction, is a function of the physical regime at the sea floor (representing by the median grain size, the current speed and the waves) and is proportional to the probability of suspension of sediment particles. This axis is defined as the ratio of the characteristic friction velocity to the critical shear stress. This last parameter is a function of grain size (X, mm), derived from the Hjulstrom diagram (1935), which is approximated empirically by the following equation: Y = −0.0272 × X 4 − 0.0905 × X 3 + 0.2411 × X 2 + 0.4691 × X + 1.8761 This ratio was then rescaled from 0 to 1, using the minimum and maximum values over the area.
Scope for Growth The scope for growth considers the environmental stressors that pose a cost for species functioning, e.g. that it represents the unfavorableness of the benthic environment to species growth and need data layers indicative of an important bioenergetic process. This axis is normally calculated using five data layers: food availability index, annual bottom temperature, annual and inter-annual temperature variability and oxygen saturation. Here, only food availability index (Fa), defined as the ratio between chlorophyll-a concentration and water depth, and global sea surface temperature (SST, as a proxy of the bottom sea temperature) have been used. For calculation, each data layer was rescaled
between 0 to 1, based on the minima and maxima. The equation for the scope for growth is here defined as: F + SST Sfg = a 2 This axis was then rescaled from 0 to 1, using the minimum and maximum values over the area. The habitat template results in a combination of these two layers. For a better interpretation of the result (figure 5), a calculation of risk is done: Risk = (1 − Sfg )² − (1 − Dist )²
Figure 5: Schematic representation of the risk against the “disturbance” and “scope for growth” axis.
Test of the habitat template In order to develop the habitat template, the data coming from two annual surveys done each year in the IFREMER (CGFS and IBTS surveys) were used. The benthic data was collected with a Very High Vertical Opening (VHVO) bottom trawl (or "GOV”), well adapted for catching demersal species, with a 10 mm mesh size for catching juveniles. One or two 30 minutes hauls are performed within each division of the 'CGFS grid' or within each ‘ICES squares’ for the IBTS. At each sampling station, benthic species are sorted, weighed and counted.
BIOENV procedure To determine which subset of “environmental” variables explain the best the benthic communities’ distribution, we used the BIOENV procedure (Clarke & Ainsworth, 1993) in the PRIMER computer package (Clarke & Gorley, 2006). The BIOENV procedure consists in calculate the Spearman’s rank correlation coefficient (ρ) between two distance matrices. The values of ρ are obtained by using all the possible combination of predictor variables in order to define the best fit: for that, a number of
iterations and the number of variables to take into account can be defined. The result of this procedure is the variables that better distinguish communities. Note that the BIOENV procedure is an explanatory one. Species distribution against habitat template Distributions of some species or groups of species (depending on some functional traits) were made and compared to the three layers described above.
FINDINGS AND DISCUSSION Disturbance axis The result for the disturbance axis is presented in figure 6.
Figure 6: Disturbance in the Eastern English Channel and south of the North Sea (in blue the lower values of disturbance, in red, the higher ones).
The main areas where disturbance is biggest are near the coasts and in the areas where the depth is lower. Grime (1977) defined that disturbance is a factor that limit the biomass of species and Kostylev defined it in terms of temporal persistence of habitat structure. So the areas in which the disturbance is biggest are the one which are the most impacted by environmental factors influencing the stability of the seabed and modifying the grain size, the morphology of the seabed… In our case, these factors could be currents, waves or storms.
Scope for growth The result for the Scope for growth axis is presented in figure 7.
Figure 7: Scope for growth in the Eastern English Channel and south of the North Sea (in blue the lower values of scope for growth, in red, the higher ones).
The scope for growth in our area is highly linked to the food availability and the areas with favourable temperature. The areas of high scope for growth are along the different coasts of France, south and south-east of England, Belgium and the Netherlands. These observations are well correlated with the fact that if these factors are not stressing, they are favourable for the growth of species.
Habitat template and risk maps The combination of the disturbance axis and the scope for growth axis gives the representation presented in the figure 8 for the habitat template. A RGB map was used to represent the habitat template, where the disturbance is in green and the scope for growth is in red. There are four main areas in this habitat template: -
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“High disturbance and high scope for growth” areas are in orange in this map and are located in the south of the North Sea, especially along the Netherlands and German coasts; “High disturbance and low scope for growth” areas are in red in this map and located near the eastern coasts of England; “Low disturbance and high scope for growth” areas (in yellow) are located in the English Channel, in the neighbours of the Wight Island and the Pays de Caux. “Low disturbance and low scope for growth” areas (in green) are located in the centre of the English Channel.
These last two groups of areas are the one which characterise the most sensitive benthic habitat.
Figure 8: Habitat template in the Eastern English Channel and south of the North Sea.
The same observations could be done with the risk map (figure 9), which is another expression of the disturbance and scope for growth. But this map highlights some sensitive areas in the south of the North Sea, near the English coasts.
Figure 9: Risk map in the Eastern English Channel and south of the North Sea (in blue the lower risk values, in red, the higher ones).
BIOENV Procedure Table 1. Results of the BIOENV procedure, showing the best results obtained for different predictor variable subsets. Best results No of variables Spearman's rho Variables chosen 3 0,286 Food availability; Mean sea temperature 2 0,279 Food availability; Disturbance; Mean sea temperature 4 0,278 Scope for growth; Food availability; Disturbance; Mean sea temperature 2 0,271 Disturbance; Mean sea temperature 3 0,268 Scope for growth; Disturbance; Mean sea temperature
Analyses performed on the available biological dataset indicated that some environmental parameters such as mean sea surface temperature, food availability could explain the communities’ distributions (Table 1). But so did the newly created parameters too (Disturbance and Scope for growth). The fact that the new created parameters could explain the distribution of the benthic communities allows to take into account the risk map to highlight the sensitive areas. Groups of species distribution against habitat template The distributions of some groups of species are here represented to illustrate the correlation with the habitat template and the habitat sensitivity. The first group chosen belong to the sessile epifauna (Porifera), for which their immobility could be a disadvantage in the case of habitat disturbance. The maps, presented in figure 10, showed that this group is correlated with the areas of low disturbance and intermediate to high scope for growth. Against the risk (i.e. the areas where any impacts could be the more prejudicial), this group is found in the areas of relatively high risk.
Figure 10: Distribution of the group Porifera (+) against the disturbance (A), the scope for growth (B) and the risk (C).
The second group chosen belong to the crustacean, a group of species more or less mobile that could escape disturbances. For this group (figure 11), we found that its distribution is not well associated with particular values of disturbance, scope for growth or risk.
Figure 11: Distribution of the group Crustacea (+) against the disturbance (A), the scope for growth (B) and the risk (C).
All these results highlight the fact that the areas cover by coarser sediments (pebbles and/or gravels) are the more sensitive benthic habitats. In these kind of sediments, rich benthic communities are found as, for example, the sessile epifauna communities (Cabioch, 1968, Davoult, 1988, Foveau, 2009). The analysis of their functional traits reveals that these species have low growth and little flexibility and are sensitive to anthropogenic disturbances. On the other hand, species occurring in sand communities have often rapid growth and a reproductive strategy that allows a fast recovery if they are disturbed. This work is a first approach for the definition of sensitive benthic habitats in the Eastern English Channel and south of the North Sea. However, this habitat template must be refined with some other environmental maps (e.g. salinity, waves …. ) at a better resolution than those used so far (if they can be found). Moreover, a comparison of the areas of highest sensitivity with the areas of high level of fishing effort could also be done.
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