Turning off the DRIP (‘Data-rich, information-poor’) – rationalising monitoring with a focus on marine renewable energy developments and the benthos

Date published

2017-03-04

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Elsevier

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Article

ISSN

1364-0321

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Citation

Thomas A. Wilding, Andrew B. Gill, Arjen Boon, Emma Sheehan, Jean–Claude Dauvin, Jean-Philippe Pezy, Francis O’Beirn, Urszula Janas, Liis Rostin, Ilse De Mesel, Turning off the DRIP (‘Data-rich, information-poor’) – rationalising monitoring with a focus on marine renewable energy developments and the benthos, Renewable and Sustainable Energy Reviews, Volume 74, July 2017, pp848-859

Abstract

Marine renewable energy developments (MREDs) are rapidly expanding in size and number as society strives to maintain electricity generation whilst simultaneously reducing climate-change linked CO2 emissions. MREDs are part of an ongoing large-scale modification of coastal waters that also includes activities such as commercial fishing, shipping, aggregate extraction, aquaculture, dredging, spoil-dumping and oil and gas exploitation. It is increasingly accepted that developments, of any kind, should only proceed if they are ecologically sustainable and will not reduce current or future delivery of ecosystem services. The benthos underpins crucial marine ecosystem services yet, in relation to MREDs, is currently poorly monitored: current monitoring programmes are extensive and costly yet provide little useful data in relation to ecosystem-scale-related changes, a situation called ‘data-rich, information-poor’ (DRIP). MRED –benthic interactions may cause changes that are of a sufficient scale to change ecosystem services provision, particularly in terms of fisheries and biodiversity and, via trophic linkages, change the distribution of fish, birds and mammals. The production of DRIPy data should be eliminated and the resources used instead to address relevant questions that are logically bounded in time and space. Efforts should target identifying metrics of change that can be linked to ecosystem function or service provision, particularly where those metrics show strongly non-linear effects in relation to the stressor. Future monitoring should also be designed to contribute towards predictive ecosystem models and be sufficiently robust and understandable to facilitate transparent, auditable and timely decision-making.

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Github

Keywords

Benthos, Biodiversity, Confidence and risk, Environmental impact assessment, Monitoring, Spatial and temporal scales, Study design, Offshore, Tidal- and wave-power, Wind-turbines

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