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Hydrokinetic Energy As an Ecological Factor – How Might Wave and Tidal Energy Extraction Affect the Distribution of Marine Organisms?

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Hydrokinetic Energy As an Ecological Factor – How Might Wave and Tidal Energy Extraction Affect the Distribution of Marine Organisms? NOT TO BE CITED WITHOUT PRIOR REFERENCE TO THE AUTHORS ICES Annual Science Conference 2011 ICES CM 2011 / S:14 Theme Session S: Extracting energy from waves and tides – what are the consequences for ecosystems, physical processes and other sea users? Hydrokinetic energy as an ecological factor – how might wave and tidal energy extraction affect the distribution of marine organisms? Michael C. Bell1, Eric P. M. Grist2, Susana Baston1, Sally Rouse3,4, Mary Spencer Jones3, Joanne S. Porter4, Andrew Want1, Robert E. Harris1, and Jonathan C. Side1 1 International Centre for Island Technology, Institute of Petroleum Engineering, Heriot‐Watt University, Old Academy, Back Road, Stromness, Orkney, KW16 3AW, United Kingdom. Tel. +44 (0)1856 850605, Fax +44 (0)1856 851349, Web www.icit.hw.ac.uk, Email [email protected] 2 WCA Environment Ltd, Brunel House, Faringdon, Oxfordshire, SN7 7YR, United Kingdom. 3 Department of Zoology, Natural History Museum, Cromwell Road, London, SW7 5DB, United Kingdom. 4 Centre for Marine Biodiversity and Biotechnology, School of Life Sciences, Heriot‐Watt University, John Muir Building, Gait 1, Edinburgh, EH14 4AS, United Kingdom. ABSTRACT Water movements define some of the most important ecological factors determining the distribution of organisms in marine environments. This is true both at large spatial scales, where ecological connectivity and trophic coupling are defined by circulation patterns and vertical mixing structure, and at the much smaller scales at which individual organisms experience flow, turbulence and shear forces. Moving water possesses energy, and this is increasingly regarded as a resource for power generation, potentially meeting 15% of energy demands at a European level by the middle of this century. Conversion of hydrokinetic energy into other forms of energy that are useful for human purposes inevitably involves diversion of physical processes from their ‘natural’ pathways, with possible consequences also for ecological processes. In simple terms, extraction of energy from water flow involves reducing the average velocity of flow and hence changing the conditions experienced by an organism living in the flowing water. In reality, the hydrodynamic consequences of extracting energy are likely to be complex and site‐specific, with changes in turbulence as well as both increases and decreases in local flow velocities. We use statistical models applied to incidence records for marine bryozoan species in Scottish waters to examine the extent to which their distribution may be governed by the same wave and tidal energy variables that influence the location of marine renewable energy developments, and address the question of whether it is possible to predict what might be the consequences of energy extraction for species distribution. KEYWORDS: wave energy, tidal energy, marine biogeography, ecological impacts 1 INTRODUCTION The wave and tidal energy industry is emerging as an important new user of space and resources in the marine environment and must co‐exist with a complex and dynamic mix of environmental and ecological features and other maritime activities and values. Extraction of energy from waves and tides involves the interception of hydrokinetic energy that would otherwise be expended elsewhere in the marine environment. In simple terms, extraction of energy will result in reductions in the velocity of water flow (Bryden et al., 2004; Bryden & Couch, 2006), although in practice the effects are likely to be complex involving turbulence, wave‐current interactions and boundary‐layer effects dependent upon seabed characteristics (see review by Bell & Side, 2011). Hydrodynamic features are defining environmental factors of the ecological niches of many if not all marine species (e.g. see review by Shields at al., 2011). It is thus pertinent to ask: what are the likely consequences for marine organisms of hydrodynamic changes resulting from energy extraction? A number of recent reviews have drawn together much relevant information for a qualitative appreciation of the likely potential for environmental and ecological interactions involving marine renewable energy developments (e.g. Gill, 2005; Inger et al., 2009; ICES, 2010a, 2010b; Shields et al., 2011), but little direct research attention has so far been paid to the potential for alteration of hydrodynamic processes by energy extraction to have ecological consequences at systemic or local scales. Recent research, driven by the immediate needs of regulators to address statutory requirements in relation to protected species and habitats, has tended to focus on the potential for direct effects of energy extraction devices on marine wildlife, such as noise impacts and collisions (e.g. Wilson et al., 2007; OSPAR Commission, 2009). Some commentators have suggested more serious systemic consequences of energy extraction (van Haren, 2010). Whilst not all scientists would agree about the seriousness of such concerns, this does highlight the need for research to improve our understanding at a whole system level of the role of hydrodynamics in marine ecology and the consequences of disrupting hydrodynamic processes by energy extraction. This paper uses an example data set on the incidence of marine bryozoan species in Scottish waters (Rouse, 2010) to examine the extent to which hydrodynamic variables relating to the resource targeted by wave and tidal energy developers are also ecological factors determining the distribution of marine organisms. Realistic scenarios for hydrodynamic changes consequent on energy extraction are not yet available (and are an urgent research need), but we use our models of species incidence to consider how sensitive the distribution of selected bryozoan species might be to changes in hydrokinetic energy. We also highlight the need to judge any responses against a background of concurrent climate change. MATERIALS AND METHODS Sources of species distribution data As an example data set for examining the extent to which hydrokinetic energy is an ecological factor determining the geographical incidence of marine species we used records for Bryozoa in Scottish waters collated by Rouse (2010). Ecological niches occupied by marine bryozoan species are known to encompass a range of conditions with respect to current velocities and exposure to wave energy. The likelihood of different species showing differential responses, coupled with the existence of extensive records for Scottish waters, 2 makes this group particularly suitable for providing examples of species sensitive to changes in hydrodynamic conditions. Scottish waters were defined for this collation as lying between 54°38’2” N – 60°51’38” N and 0°46’50” W – 13°40’13” W. Historical records were obtained from the Bryozoa collection at the Natural History Museum, London. Contemporary records were sourced primarily from the reports of the Marine Nature Conservation Review (MNCR), which sampled the marine fauna of the UK between 1987 and 1998 (Hiscock, 1998). Additional records were sourced from selected literature, a field survey conducted in Orkney during 26‐30 June 2010 and the National Biodiversity Network gateway (http://data.nbn.org.uk/, which includes data collected by the Joint Nature Conservancy Council (JNCC), Scottish Natural Heritage (SNH), MarLin (http://www.marlin.ac.uk/); Seasearch (http://www.seasearch.co.uk/) and private contract surveys). Records from north Liverpool Bay were included owing to their proximity to the Scottish border. Full details of data sources, sampling methods, taxonomy and data quality criteria are given by Rouse (2010). A total of 22,376 records were collated for 249 taxa in Scottish waters (Figure . 1) There were 508 records for 49 taxa within the spatial domain considered for the Pentland Firth and Scapa Flow (see below). Sources of environmental data An implementation of the SUNTANS hydrodynamic model (Fringer et al., 2006) for the Pentland Firth and Scapa Flow (hereinafter referred to as Pentland Firth)s wa used to generate information on tidal flow conditions in these waters over a 10‐day period including spring tides (see Baston & Harris, in press, for further information on this implementation). SUNTANS is a 3‐D model running on an unstructured grid, and was run for the Pentland Firth using 20 depth bands at a resolution of 4.9 m (Figure 2). We used maximum velocities for the deepest band at each grid node to represent near‐bed peak current flow, and for the purposes of modelling species distributions we calculated averages of these peak values for a regular grid of 0.01° latitude by 0.01° longitude over the spatial domain of the model. Following Gross et al. (2011) we then calculated bed shear stress (τ in units of Pa) as: 2 ρτ uC bd ‐3 where ρ is average water density (1025 kg.m ), Cd is the drag coefficient and ub is the near‐ ‐1 bed velocity (in m.s ). A drag coefficient of Cd = 0.005 (dimensionless) was used, determined by Baston & Harris (in press) to be the most appropriate value for the Pentland Firth based on validation of the SUNTANS model. A wave model for the Pentland Firth is not yet available, so we used large‐scale modelled data on annual mean significant wave heights in UK waters obtained from the UK Department of Trade and Industry (DTI, 2004) interpolated onto the same 0.01° grid as for tidal current data. We used the same wave data for UK waters as a whole, interpolated onto a 0.05° grid. The same source was used for average tidal velocity data for spring tides, again interpolated onto a 0.05° grid for UK waters. Shear stress was calculated as for the Pentland Firth data. In principle, Cd is likely to vary between areas according to seabed type, but in the absence of better information no attempt was made to adjust for different Cd values at different locations. Also, given that these tidal velocity data stemmed from a 2‐D hydrodynamic model, no adjustment was made for depth to derive near‐bed values. As a 3 matter of convenience, the DTI data sets were also used as the main source of bathymetry data.
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