Marine renewable energy and aquaculture

Modeling the effect of the installation of marine renewable energy devices (MREDs) and aquaculture sites on the surrounding ecosystem is challenging. Deployment of structures for offshore renewable energy (ORE) and farming (e.g., cages) can lead to exclusion zones, limiting the access to the area for users such as shipping, fishing and tourism[1] [2] [3][4]  as well as ‘artificial reefs’ effect with the presence of new structures that can supply nursery areas and feeding grounds for fish species (Petersen and Malm, 2006; Wilhelmsson et al., 2006). Larvae and juveniles can disperse from these sites to the surrounding area leading to a ‘spill-over effect’, enhancing local production[5].

MREDs can negatively impact species indirectly, by changing habitat properties, as well as directly, by causing collision risks with moving turbine components[6] [7]. For diving species, there is also the risk of collision with static underwater structures[8]. Moreover, these devices can also produce continuous low frequency noise that propagates in the air as well as underwater causing dislocations of acoustically-sensitive species[9] [10] [11] [12] (Bailey et al., 2010; Brandt et al., 2011; Madsen et al., 2006; Tougaard et al., 2020, 2009).

Serpetti et al.[13] evaluated the impact of wind farms as a MRED on the West Coast of Scotland by assessing the impact of the low frequency noise produced by the operational wind turbine (see section 6.8 below) and by assessing the seabird spatial dislocation caused by the presence of the offshore wind turbines (OWTs). Three species within the seabird functional group (representing 45% of the total biomass) of the previously published West Coast of Scotland model[14], were assumed to show significant spatial dislocation caused by the wind turbines[15] The Ecospace results estimated a significant decrease in seabird biomass of 8% within an 8 km2 region set around the OWTs site (Table 1). In the same study, the impact of salmon farming was also tested. The attraction of predators by the farms and the organic enrichment of detritus by deposition of wasted feed and feces on the seabed below and surrounding the fish farms was simulated (Table 1). The spatial distribution of top predators (large fish and seabirds) affected the marine ecosystem through top-down control pathways causing the decline of their prey within the area. Similarly, changes in bottom-up controls were included through detritus enrichment and cascaded through the food web causing the increases of infauna, epifauna and other benthic species (Fig. 14). The spatial distributions of infauna and epifauna also showed larger diffused footprints in relation to the detritus enrichment footprint proportional to their dispersal rates (30 km/year for epifauna, and 3 km/year for infauna)

Table 1. Mean relative annual biomasses changes of selected functional group for different selected scenarios (modified from Serpetti et al.[16])

Functional group

A: Operational wind farm

B: Predator attraction by fish farm

B+: Detritus organic enrichment

Seabirds

-8.1%

3.6%

3.6%

Cod

-0.7%

10.1%

11.1%

Haddock

-0.9%

5.9%

7.1%

Whiting

-5.0%

5.4%

5.7%

Saithe

0.0%

20.8%

20.9%

Flatfish

0.0%

-0.1%

0.0%

Herring

0.0%

-0.1%

-0.1%

Poor_cod

0.0%

0.0%

-1.2%

Sandeel

0.2%

-0.4%

-0.1%

Sprat

0.1%

-0.3%

-0.2%

Nephrops

0.0%

-0.1%

-1.5%

Lobster

0.1%

-0.4%

-3.1%

Velvet_crab

0.0%

0.0%

1.8%

Infauna

0.0%

0.0%

2.2%

Epifauna

0.0%

-0.2%

10.3%

Detritus

0.0%

0.0%

3.3%

image

Figure 1. Relative biomasses spatial distribution of detritus, infauna and epifauna showing the relative foot-print increases of detritus, infauna and epifauna (modified from Serpetti et al.[17])

 

Attribution

This chapter is based on de Mutsert K, Marta Coll, Jeroen Steenbeek, Cameron Ainsworth, Joe Buszowski, David Chagaris, Villy Christensen, Sheila J.J. Heymans, Kristy A. Lewis, Simone Libralato, Greig Oldford, Chiara Piroddi, Giovanni Romagnoni, Natalia Serpetti, Michael Spence, Carl Walters. 2023. Advances in spatial-temporal coastal and marine ecosystem modeling using Ecopath with Ecosim and Ecospace. Treatise on Estuarine and Coastal Science, 2nd Edition. Elsevier. https://doi.org/10.1016/B978-0-323-90798-9.00035-4, adapted with permission, License Number 5651431253138.

Rather than citing this chapter, please cite the source.


  1. Alexander, K.A., Potts, T., Wilding, T.A., 2013. Marine renewable energy and Scottish west coast fishers: Exploring impacts, opportunities and potential mitigation. Ocean & Coastal Management 75, 1–10. https://doi.org/10.1016/j.ocecoaman.2013.01.005
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