Not to be cited without prior reference to the author ICES CM 2010/H:19 Development of a combined indicator of bioturbation and redox, a proxy for seabed function? S.N.R. Birchenough

1*, Parker, R.E.

1, Brooks, L.

2, M

cManus, E

1.,Barry, J

1.

1The Centre for Environment, Fisheries and Aquaculture Science, Lowestoft Laboratory,

Pakefield Road, Lowestoft, Suffolk, NR 33 0HT, United Kingdom.

2 Norwegian Institute for water research, Head Office, Gaustadalléen 21, NO-0349 Oslo,

Norway.

*Corresponding author. Tel.: +441502-527786; fax: +441502-513865; e-mail address: silvana.birchenough@cefas.co.uk

Abstract

Marine systems are represented by a wide range of habitats. These systems are dynamic entities which have a high degree of complexity and may harbour high levels of biodiversity. Human-induced pressures (i.e. dredging, fishing, construction, pollution and others) often produce additional disturbance to these marine systems with repercussions for biodiversity. Current national (e.g. UK Marine and Coastal Access Act, Charting Progress 2) and international (e.g. Water Framework Directive, Habitats and Bird Directives, European Marine Strategy Framework Directive) legislation are focused on the quality and status of the marine environment. To this end, the UK has continued to work on the need to develop indicators which can assist with this process. This work has helped to identify the natural processes and man-made activities that are affecting marine systems. One of the marine descriptors within the EMSFD is ‘seabed integrity’. This descriptor asks member states to ensure that the structure and function of ecosystems are safeguarded and benthic systems are not adversely affected. To date, we have furthered our understanding of the seabed by, for example, studying benthic systems. For this purpose indicator tools, such as a suite of benthic indices, have been employed as measurers of ‘the health of benthic systems’. In most cases this information mainly relates to the structure of benthic populations. However, there is a gap in terms of what we can measure with regards to the function of the ecosystem and how individual benthic animals perform their roles within specific ecosystems. There is also a lack of data to assess if the functions of the seafloor are safeguarded. This work has defined sediment function as an indicator to measure both carbon and nutrient cycling. These two processes are largely driven by the organisms controlling the redox potential of the sediments via bioturbation activities.

Keywords: redox, bioturbation, indicators, EMSD, ecosystem function, seabed

integrity.

1876 (ICES ref.)

1.Introduction: Marine ecosystems are under constant human pressures (e.g. the effects of organic enrichment, dredged material disposal, construction, climate change, etc.) (Birchenough et al., 2009; Birchenough et al., 2010; Borja, 2006). These activities present a continuous challenge for scientists as the pressures they exert and the resulting wider effects on marine communities needs to be quantified and regulated. To date, significant effort has been made to develop indicators of ecosystem health. These can be used as tools to support various European legislative and policy frameworks in relation to the management of human activities. Central to legislative and policy goals, especially under the European Marine Strategy Directive 2007 (EMSFD, thereafter) is the maintenance of ecosystem biodiversity, goods and services by focusing on structure and function when undertaking the assessment and management of impacts. For the sediment system, this involves the development of indicators looking at the sediment state, the role organisms play in maintaining ecosystem function and how this is affected by human impacts. Collectively, under the EMSFD this is described as ‘seabed integrity’. A key function of which is carbon and nutrient cycling. However, linking observations of biogeochemical rates which are often measured at specific sites to more regional scale approaches for indicator monitoring and management provides challenges of linking scales and complexity of measurements. The aims of this work were to test and integrate two candidate functional indicators relevant to sediment carbon and nutrient cycling, an indicator of community bioturbation potential (BPc) (Solan et al., 2004). The BPc describes the benthic faunal function (based on bioturbation) and an indicator of sediment redox (aRPD - apparent Redox Potential Discontinuity) as derived from Sediment Profile Images. The aRPD describes the key sediment redox boundary between faster and slower carbon recycling, oxidised and reduced sediments (OS and RS in Figure 1).Therefore, aims of this work were: to test the performance of these candidate indicators with respect to: i) temporal and spatial variability and; ii) in response to human impacts (e.g. a dredged material disposal site and areas with trawling influence). 1.1. Bioturbation calculations This index accounts for three biological traits know to influence sediment bioturbation: (i) mean body size (Bi, biomass in grams); (ii) propensity to move through the sedimentary matrix (mobility, Mi) and; (iii) method of reworking the sediments (reworking mode, Ri). The abundance Ai of individual species is also included in the calculations. Overall calculations were conducted for individual species (BP) and for the whole community (BPc). This index is an indicator of bioturbation on the functional role of benthic infauna in relation to sediment turnover. 1.2 Sediment Profile Images (SPI): apparent Redox Potential Discontinuity (aRPD) as

an indicator of sediment redox. The Sediment Profile Imagery (SPI thereafter) is a well-known technique which allows the operator to take rapid, in-situ vertical profile pictures of the upper 20cm of the sediment system. The SPI camera works “like an inverted periscope”. The camera possesses a wedge-shaped prism with a plexiglass faceplate and an internal light provided by a flash strobe. The back of the prism has a mirror mounted at a 45° angle which reflects the image of the sediment-water interface at the faceplate up to the camera. The camera is supported by an inner frame and prism assembly, which is controlled by a ‘passive’ hydraulic piston. The wedge-shaped prism enters the bottom and is driven into the sediment by its weight. The piston ensures that the prism enters the bottom slowly and does not disturb the sediment-water interface. On impact with the bottom, a trigger activates a time delay on the camera shutter release and a photograph is taken when the prism comes to rest. SPI images can provide clear insight into the relationship between benthic communities and the sediment. The uses of SPI imagery have been widely employed to study benthic systems following hypoxia (Shumchenia & King, 2010), for habitat quality assessments (Nilsson and Rosenberg, 2000; Nilsson and Rosenberg, 1997), to quantify bioturbation (Solan et al., 2004)

and for monitoring dredged material disposal sites (Birchenough et al., 2006; Birchenough et al., 2007; Valente et al., 1992) among some applications. The SPI technology can also act as a complementary tool for to study in situ seafloor organisms and processes that cannot be directly observed via other equipment (i.e. grabs, corers or trawls) (Birchenough et al., 2006). The benthic animal activity can alter the physical and chemical conditions of the sedimentary environment. Additionally, process such as bioturbation, bioirrigation and biodeposition can influence the conditions of life in the sediment and the vertical distribution of organisms and the sediment redox conditions (Rhoads, 1974). An important community attribute such as species diversity can directly affect the functioning of the marine ecosystem. An example of this, are large and deep-burrowing species which are important for ecosystem processes in the sediment (Norling et al., 2007). The sedimentary environment mirrors the functional biodiversity and activity pattern of the macrofauna. Burrows, infaunal tubes, feeding voids, pits and mounds are examples of structures in the sediment that relate to animal activities (Rhoads and Germano, 1982; Schaffner, 1990). These biogenic activities could also be related to the vertical distribution of the apparent redox potential discontinuity (aRPD) layer. The aRPD and species’ composition can be used to distinguish late successional stages with a high functional biodiversity and associated deep vertical distribution of the RPD, whereas the shallower aRPD and reduced species compositions can be used to characterise early successional stages (Pearson and Rosenberg, 1978; Rhoads and Germano, 1986). Using the qualitative Pearson and Rosenberg model (1978) the SPI images can then be placed on a continuum of sediment and biological structure in relation to potential impacts. Figure 1 illustrates this conceptual model. The left hand panel represents the highest successional stage – reference type conditions. Moving to the right side of the diagram, driven by disturbance illustrates the combined changes between the sediment community and redox state. Associated with this change is impact on sediment functions such as bioturbation, carbon cycling or benthic-pelagic coupling. For this purpose the aRPD is used which delineates the boundary between oxic sediment (OS) and reduced sediment (RS) on Figure 1. Figure 1. Conceptual model (adapted from Pearson and Rosenberg, 1978) of benthic fauna and sediment redox changes along a gradient. The arrow sizes describe the predicted rates and significance of remineralisation routes.

At present, discrimination of the aRPD from a SPI image uses the difference in reflectance values caused by the presence/absence of ferric hydroxide particles or coatings in oxidised/anoxic sediment regions. The oxidised form of Fe, FeOOH, is highly insoluble and gives the sediment an olive-brown colouration (Bull and Williamson, 2001; Lyle, 1983. It can also be linked to the zone where all nitrate in porewaters has been reduced (Lyle, 1983). This ‘apparent’ depth may not be equivalent to the actual RPD (where Eh =0) due to the kinetic rates of processes related to iron oxidation/reduction and the presence of bioturbating infauna

(Bull and Taillefert, 2001; Diaz and Cutter, 2001). The thickness of a measured and also ‘apparent’ RPD will reflect the particle bioturbation depth and mode over various timescales and hence is linked to the infaunal community (Solan et al., 2004). 2. Methods: 2.1 Study sites A variety of study sites with a combination of infauna data and SPI images were available for this work, these were chosen to cover 3 shelf areas in the North Sea and a costal dredged material disposal site with some legacy from capping contaminated material (Table 1). The bioturbation (BPc’s) were calculated for a range of faunal datasets to give an idea of spatial variability (such as: Oyster Ground, North Dogger and Southern Bight) and sites with a distinct human impact (e.g. Tyne dredged material disposal and Oyster Ground with fishing activity). Principal Component analysis (PCA) of the abiotic information was also analysed in relation to the BPc’s to enable an assessment of individual and between sites in relation to biological information to elucidate physical variables influencing the infaunal communities. Table 1: A summary of study sites characteristics and data available. 2.2 Bioturbation potential calculations

This metric was calculated from infaunal benthic data (i.e. abundance, biomass and biological traits information of individual species) collected with 0.1 m

2 grabs and corers (for details on

methodology see Birchenough et al., 2006). The calculation of the bioturbation potential (BPc’s thereafter) was based on the methodology proposed by Solan et al. (2004). Where individual species were coded based on the type of activity (M, e.g. fixed in a tube, limited movement, slow movement through the sediment and free movement via burrow system) and their relative position on the seabed (R, e.g. epifauna, surficial modifiers, head down/head up feeders, biodiffusers and regenerators). The bioturbation formula is represented below:

BPi = Σ (Bi/Ai)0.5

x Mi x Ri 2.3 Sediment redox boundary – aRPD from Sediment Profile Camera (SPI) The oxidised sediment, also known as mixing depth (MD), is influenced by a combination of biotic and physical forces and it is often used as a direct parameter to quantify net benthic functioning (Solan et al., 2004). The aRPD (measured in cm) has been derived using image

Site type Region Scale Dates BPc’s aRPD

North sea

North Dogger North Sea – deep (80m), stratified, muddy sand

Regional 2007 - seasonal

X X

Oyster Ground North Sea – shallow stratified (40m), muddy sand

Regional, Local 2007 – seasonal

X X

Sean Gas Field

North Sea – Shallow (25m), well mixed, sandy/mobile

Regional 2007 - seasonal

X X

North sea-coastal

Tyne – Souter Point disposal

Coastal-dispersive area, mixed site (~15-20m), muddy area

Local 2007 summer

X X

analysis software (Image –J) which allows a consistent threshold to be set to calculate the average aRPD across a 15-18cm wide image. Image analysis with the Image J software allows you to draw in the sediment surface and consistently set threshold (see example in Figure 2). This methodology allows calculating the total area above threshold and average depth (Godbold and Solan, 2009). Alternatives methodologies to enable aRPD calculation can also be conducted using the software Adobe Photoshop ® to identify the aRPD by colour changes (Shumchenia & King, 2010; Cicchetti et al., 2006; Nilsson & Rosenberg, 2000; Nilsson & Rosenberg, 1997 and others) and trace and measure the area delineated. In this work we have adopted the aRPD calculation with Image J to increase the quantities of processed images at a given time and providing an unbiased approach whilst delineating aRPD. The aRPD calculation was performed on all of the SPI images collected at the Tyne dredged material disposal=TD, North Dogger Bank =ND, Sean Gas Field =SGF and Oyster Ground=OG). Figure 2. Sediment Profile Camera, resulting image from North Dogger and Image J analysis determination of the aRPD.

2.4 Analysis: 2.4.1 Combined indicators: The calculation of both metrics was conducted independently for BPc’s (calculated from infauna data) and aRPD (derived from SPI images) for all of the sites. After individual calculations were made both the indicator metrics were combined for the different sites to assess and describe their condition. This approach has been based on the classic Pearson and Rosenberg (1978) paradigm. The advantage of combining these two metrics allowed greater discrimination between habitat features, variability and impacts across a wide range of scenarios. 3. Results: 3.1 Environmental characterisation of the sites: Data collected during 2007 showed the sediments present at North Dogger Bank and Oyster Grounds to be a mixture of muddy sands. In contrast, sediments at Sean Gas Fieldwere dominated by sands (Figure 3). Overall, % gravel content at the three sites was always below 1%, with the exception of the Tyne disposal site, with up to 17.39% and 12.5% of gravel at stations Cap1 and Cap5 respectively. PCA of the abiotic data showed the %mud and mean to be highly correlated with PC 1, accounting for 44.9% of the variation. Furthermore, PC axis 2 was also correlated with %OC, accounting for an additional 24 % of the variation (Table 2).

Table 2.Principal components analysis (PCA) of physical variables (C:N, %OC, Mean (mm), % gravel, % sand and % silt & clay) conducted at North Dogger Bank, Oyster Grounds, Sean Gas Field and Tyne dredged material disposal site. PC1 accounted for 44.9% of the variation in the original data and PC2 for a further 24%.

Scores

Variable PC1 PC2

Bpc's 0.224 -0.209

C:N 0.361 0.443

%OC 0.21 0.69

Mean 0.511 -0.228

%GRAVEL -0.227 0.461

%SAND -0.449 -0.061

%MUD 0.512 -0.125

Eigenvalues 3.14 1.68

Percentage of variance 44.9 24

Cumulative percentage 44.9 68.9

The environmental samples plotted in a PCA space (Figure 3) showed 3 distinct groups. These clusters also provided clear indication of seasonal variability within individual sites (for SB, OG and DB) and between sites over time. In contrast, the Tyne dredged samples clustered together on the ordination but still there was some degree of separation which indicated differences observed among stations. The reference sites (e.g. TC4, TC2 and Cap4) grouped together. There was also some separation over the samples collected at the dredged sites (Cap2 and Cap5) and subjected to capping activity (Cap1). Finally, at Sean Gas Field samples showed a distinct cluster with some degree of seasonal variability between samples mainly driven by mean (Figure 3). Figure3. PCA based on %gravel, %sand, % mud, mean, C:N, %OC and Bpc’s in PC space. PC1 accounted for 44.9% of the variation in the original data and PC2 for a further 24%.

3.2 Bioturbation potential (BPc’s) BPc’s calculations were conducted at all individual sites, the values ranged from 0.89 to 6.74. At Sean Gas Field the highest BPc’s values were observed in October and the highest BPc’s values were noted in February and May (Figure3-a). The community at this site was mainly dominated by motile deep burrowing carnivore polychaetes such as Nepthys hombergii and Goniada maculata. At Oyster Ground the highest BPc’s values were observed in September and similar BPc’s values were observed during remainder of the sampling periods (Figure3-a). The main bioturbators were observed to be a combination of echinoderms (heart urchin and brittlestars) and deep burrowing shrimps (Callianasa subterranea). In contrast, at North Dogger Bank, the

Cap1

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Cap7

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SGFSGF

OG

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OGOG

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DBDB

DBDB

lowest values were observed during April and October (Figure 3-a). The community was structured by the filter feeding echinoderms (mainly the brittlestar Amphiura filiformis). At the Tyne dredged material disposal stations, the BPc’s values ranged between 2.4 to 3.8. It was clearly that the areas disturbed from dredged material disposal had lowest BPc’s values (2.4 and 3.1, mainly Cap1 and Cap4 respectively, see Figure3-b). The main bioturbators were the polychaetes Mediomastus fragilis and Nepthys hombergii and also the juvenile bivalve Nuculoma tenuis. The stations which were less disturbed by dredged material disposal also showed higher BPc’s when compared with the directly impacted disposal stations. Finally, the reference sites (Cap4, Cap 9, TC2 and TC4) showed the highest bioturbation values along the entire transect (Figure3-b). The main species present at these sites were the Golfingia elongata, Chaetozone setosa, Amphiura filiformis and Ampelisca tenuicornis. Figure 4. Bioturbation potential (BPc’s) values (log transformed) calculated per 0.1 m

2 for

benthic infauna (n=4 +/- SE), the following sites have been used: a) North Sea sites (OG, NB and SGF) and b) Tyne dredged material disposal site (red=capping material, amber=dredged material impacted and green reference stations). Note different scales for both figures.

3.3 Sediment profile images and aRPD values Over 90 SPI images were analysed to characterise the physical and biological status of all of the study sites. For simplicity only a sub-set of SPI images are presented in this paper to provide characterisation and information on the aRPD values, biological information and sediment of the sites (Figure 6). The Sean Gas Field was sandy, with an apparent aRPD of >10cm in some of the SPI images. The determination of aRPD at Sean Gas Field was limited by a lack of fines to give colour change, this was only visible in September (Figure 5-a). The North Dogger Bank was characterised by muddy sand and an aRPD of ~2-3cm. The overall aRPD calculation ranged from 1.5 to 2.5 cm over the sampling time (Figure5-a). Analysis of SPI images showed burrows and small feeding voids, but over overall there was a reduced amount of benthic infauna present at the site (Figure 6-b) over time.

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pc’s

)

The Oyster Ground was characterised by muddy sands, there is clear variability through the seasons. The aRPD values ranged from 2 to 6cm over time (Figure 5-a). The presence of deep aRPD can be liked to the presence of bioturbating species observed at the site. There was also clear presence of burrowing infauna, surface fauna and feeding voids observed on the SPI images (Figure 6-c). Analysis from SPI images showed added clean sand (see Cap1, Cap2 and Cap5) which did not enable the calculation of a ‘true aRPD’ (Figure 5-b and Figure 6D-F). For the reminder of stations the aRPD calculations varied from 1.7 to 5.1. At stations with a degree of disturbance resulting from the disposal activity, there was some indication of low aRPD (1.7 at station Cap7). In contrast, at stations located further away from the disposal activity the aRPD were 2.5, 2.3 and 5.1 (stations Cap9, TC2, and TC4 respectively). The SPI images also indicated that these stations were predominately dominated by muddy sands and with moderate biological activity, mainly by surface fauna, burrowing infauna and presence of feeding voids (Figure 6 G-H). Figure 5. Examples of SPI images from study sites collected at: A) Sean Gas Field, B) Oyster Ground and C) North Dogger Bank, and Tyne Dredged material disposal site: D) Cap5, E) Cap2, F) Cap1, G) TC4, H) Cap9 and I)Cap7. SWI=sediment water interface, DM= dredged material, I=infaunal polychaete, SF=surface fauna, v=void and B= burrows.

A) B) C)

D) E) F)

G) H) I)

2cm

SWI SWISWI

Bv

IB

DMDM

DM

SF

Iv

II

SWISWI

SWI

SWISWISWI

SF

Figure 6. aRPD measurements (n=5, +/- SE) conducted at: a) Sean Gas Field, Oyster Ground and North Dogger Bank and b) Tyne dredged material disposal site (red=capping material, amber=dredged material impacted and green reference stations) in 2007. The aRPD at the Sean Gas Field is a minimum estimate determined from oxygen penetration from microelectrodes. The true aRPD/redoxcline is likely to be deeper. There is not true aRPD present at Cap1,Cap2 and Cap5 due to the addition of material.

3.4 Combined metrics: Plotting a proxy of sediment redox (aRPD) and a proxy of benthic function (BPc’s) determined by bioturbation activity allowed a distinctive characterisation of different regions (Figure7). It is clear that there are deep (e.g. Southern Bight/SGF and Oyster Ground) and shallow (Tyne dredged site and Oyster Ground) aRPD and the same principle applies for the BPc’s calculations. The areas where the BPc’s is high (Oyster Ground) and low (Southern Bight/SGF, North Dogger and Tyne disposal site).Considering all this combined information, we can then classified onto 4 different regions, based on the C cycling Regions (Figure 7) as follows:

A Deep aRPD, Low BPc’s, Physically controlled, Fast coupling (natural) B Deep aRPD, high BPc’s, Biologically controlled, Healthy shelf – fast biological coupling C Shallow aRPD, low BPc’s, Coastal sites or impacted shelf D Shallow aRPD, high BPc’s, potentially low carbon areas

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Figure 7. Combined aRPD/BPc’s values for the study sites. Classified areas (A-D), these are as follows: A Deep aRPD, Low BPc’s, Physically controlled, Fast coupling (natural), B Deep aRPD, high BPc’s, Biologically controlled, Healthy shelf – fast biological coupling, C Shallow aRPD, low BPc’s, Coastal sites or impacted shelf and D Shallow aRPD, high BPc’s, potentially low carbon areas.

4.0 Discussion: Current national (e.g. UK Marine and Coastal Access Act, Charting Progress 2) and international (e.g. Water Framework Directive [WFD; EU 2000], Habitats and Bird Directives, European Marine Strategy Framework Directive (MSFD)[EUMSFD, COM 2005]) legislation are focused on the quality and status of the marine environment. Whilst these initiatives have clear aims and strategies, there implementation presents great challenges for managers, scientists and policy makers (Rees et al., 2003). In a regulatory context, a powerful tool to underpin environmental management is the use of environmental indicators. Indicators have been described by generic definition as ‘a measure, index or model used to estimate the current state and future trends in physical, chemical, biological or socio-economic conditions of the environment, along with thresholds for management action to achieve desired ecosystem goals’ (Fisher, 2001 and Rees et al., 2003). This definition incorporates the human dimension in combination with other parameters identifying the regulatory action of setting indicators with associated thresholds. In reality the development of these thresholds is often more demanding than the development of the indicators themselves. Recently, the adoption of an ecosystem-based approach to management has been pursued via selection of desired states of the physical and biological components of the ecosystem and the close management action which is set up to achieve the required status. Examples

based on the use of ecosystem indicators has became a fundamental pillar of management systems in UK waters to ensure sustainable development of the marine waters (Rogers & Greenaway, 2005). The UK has been proactive in the development of many indicators for the UK marine environment which have been adopted as part of a sustainable development indicators strategy, covering ecological and socio-economic aspects (Defra, 2004). Clearly, all of these policies have a common desire for the protection of the marine environment and its sustainable use by improving marine environmental quality (Rogers & Greenaway, 2005). In the UK there have been specific indicators of ecosystem components developed through time for phytoplankton (Beaugrand and Reid, 2003), benthic invertebrates (Rees et al., 2003; Bustos-Baez and Frid, 2003), fish populations (Greenstreet et al., 2006; Jennings et al., 2002), marine mammals (Defra, 2004), etc. Additionally, the UK is also committed to direct scientific efforts in support of the MSFD. The MSFD aims to protect and/or restore the European seas ensuring that human activities are conducted in a sustainable manner (Fleischer & Zettler et al., 2009; Borja, 2006) by targeting good environmental status (GES) by 2021. GES is defined as the environmental status of marine waters where these provide ecologically diverse and dynamic oceans and seas which are clean, healthy and productive within their intrinsic conditions and through its sustainable use for current and future generations (Van Hoey et al, in press). There are a series of GES descriptors which directly relate to benthic systems (e.g. biological diversity, non-indigenous species, marine food webs and seafloor integrity). Seafloor integrity is defined at a level that ensures that the structure and functions of the ecosystems are safeguarded and benthic ecosystems, in particular, are not adversely affected. The definition considers both the physical and biotic composition of the benthic community and integrity, including the characteristics and functioning of the natural ecosystem processes and spatial connectedness (Rice et al., 2010). To define the structure and function of benthic systems as highlighted in ‘Seafloor integrity’ are not trivial tasks, this needs sounds tools to provide an accurate assessment of these benthic ecosystems. In this work we have tested functional indicators relevant to sediment carbon and nutrient cycling with an indicator of community bioturbation potential (BPc), which can be considered as proxy for seabed function. Our aim was to assess the performance of these candidate indicators with respect to their: i) temporal and spatial variability and; ii) response to human impacts (e.g. a dredged material disposal site and an area of trawling activity). The four study sites were chosen due to their physical characteristics and the biological communities inhabiting these sites. The Oyster Ground and Dogger Bank have a stratified water column during summer months with limited water exchange in the bottom mixed layer (Greenwood et al., 2010). In addition, the dissolved oxygen concentration in bottom water at the Oyster Grounds is strongly influenced by short term (e.g. storms and particulate organic matter pulses). On the contrary, the North of the Dogger Bank, the dissolved oxygen concentration in bottom water is a longer seasonal process (Greenwood et al., 2010). Trawling intensity is patchy in the North Sea (Trimmer et al., 2005 and Jennings et al., 1999). Recent evidence (Greenwood et al., 2010) has shown that both areas (OG and DB) are subject to trawling creating an effect on the oxygen demand as sediment is mixed in the overlaying water with repercussions for sediment biogeochemistry and ecosystems (Trimmer et al., 2005). The Sean Gas Field is well-mixed throughout the year, due to a combination of shallow water, strong tides and wave activity. The rate of exchange between the water column and the seabed (i.e. benthic-pelagic coupling) at the Sean Gas Field is relatively high and mainly dominated by physical variables (permeability, bottom water currents, tidal forces) with seasonal changes likely mediated by temperature increase through the year (Neubacher unpublished data). Finally, the Tyne dredged material receives maintenance dredged material from the Tyne Estuary sometimes exceeding 150,000 tonnes per annum. The nature of the material disposed off is mainly sand, silt, with a legacy of elevated levels of heavy metals and hydrocarbons, mainly from the mining industry (especially from colliery waste and fly ash) (Birchenough et al., 2006; Birchenough et al., 2007). PCA analysis showed the distinctive nature of the sites, with an indication of the sediment types (e.g. mud) and the organic carbon content influencing the sites.

The information tested in this approach can be a valid way to assess seabed integrity on benthic systems. The aRPD values (or oxidised layer of surface sediment) to characterise sediment redox and biological activity (or lack of benthic infauna present on specific sites) has enabled us to assess in situ the status of these systems. This information has merit in that there is a direct observation, which reflects animal vertical distribution and activity on the biogeochemical processes and the aRPD (Nilsson and Rosenberg, 2000). The brown colour of the sediment surface is indicative of the presence of Fe

+III and below is the sulphidic

reduced area (Lyle 1983). Dissolved oxygen usually penetrates only few millimetres into muddy sediment and in the sub-oxic zone NO

-III, Mn

+IV and Fe

+III act as oxidising agents (Aller

& Aller, 1998). Different burrowing, irrigation and feeding processes conducted by animals are an important pathway for the nitrification-denitrification processes in sediments. The aRPD clearly showed shallow and deeper values at the different study sites, likewise, the BPc’s calculations at also identified areas where there influence of deep burrowing polychaetes (e.g. Sean Gas Field) and their burrowing behaviour, which allows for them to mix some of the top 10 cm of the sediment column (D’Andrea & Lopez, 1997). The aRPD results were absent from Sean gas Field due to the lack of fines, with no results on the detection of the colour changes on the sediment layers. Although further work conducted at the site has indicated the clear influence of physical processes (Neubacher unpublished data). In contrast at Dogger Bank, bioturbation values were mainly driven by the brittlestar Amphiura filiformis, which has free movement through a burrow system. The effects of A.Filiformis on sediments as a result of bioturbation are well documented on the literature (Solan et al., 2002; Solan et al., 2004), the RPD measurements also showed shallow aRPD layers which concord with limited bioturbation activity. The higher Bpc’s were observed at the Oyster Grounds, with the echinoderms Amphiura filiformis and Brissopsis lyrifera and the mud burrowing shrimp Callianassa subterranea. These bioturbators contribute by moving sediment fast and deeper down via upward or downward conveyor or regenetator properties in this area, this process helps to mediate the fast fresh carbon re-mineralisation via oxygen by working on the oxygenated layer of the sediment hence the deepest aRPD. The disposal site had addition of clean sand (as capping strategy at three stations) hence there was not possible to delineate aRPD but the bioturbation activity was also low in relation to the reference sites. The faunal composition at the disturbed stations was mainly composed by polychaete and juvenile bivalves. At the reference sites the community was characterised by a combination of species (e.g. echinoderms, polychaetes and crustaceans). This overall information on sediment redox and bioturbation calculations as a proxy for benthic function has enabled us to relate in situ observations with quantitative data. This approach has clear advantages over traditional benthic sampling techniques, where sieving sediment to retain animals lacks information on animal burrow structure and sediment redox conditions (Rosenberg et al., 2003). Nilsson and Rosenberg (2000) conducted a similar assessment using SPI images for assessing Benthic Quality Status for the WFD (Rosenberg et al., 2009). Their approach mainly used aRPD measurements and biological information to calculate a Benthic Habitat Quality Index (BHQ). The assessment used in this work is based on similar principles but also incorporates the benthic bioturbation (BPc’s calculations) and combines both metrics to develop a classification of regions from the study sites data to highlight C cycling areas distilled from BPc’s and aRPD information. The complementary information from SPI and quantitative benthic information (used to estimate bioturbation) provided further information on the biodiversity of these systems, infaunal processes in the sediments and characteristic of in situ sediment redox state (Rosenberg et at., 2003). The overall evaluation of these metrics in relation to benthic changes and sediment redox state are based on the classic Person & Rosenberg (1978) model which describes benthic succession responses to a gradient of disturbances. The approach presented here is straightforward but it provides the necessary information to measure the redox in sediments and quantify the benthic function via bioturbation activities which can be adopted when assessing the integrity of benthic systems and seafloor function. The combined indicator for benthic function developed in this paper will require further testing on additional study sites over wider scales and other human activities. But the results are

promising and they seem to fulfil a number of ideal indicator properties (ICES 2001), in that it is:

i) capable to convey information that is responsive and meaningful to decision-making process;

ii) easily communicated/understand by scientists and managers; iii) applicable to a wider range of spatial scales; and iv) scientifically and legally defensible and highly sensitive and anticipatory for a

potential problem.

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