Tender Summary

Defining the geographic scale of fish species populations, for impact assessments of low carbon energy projects an

Buying Organisation

Defra Network eTendering Portal

Contract Value

Unknown

Suitable for SMEs

Yes

Suitable for VCSEs

Yes

Tender Description

The Government's commitment to Carbon Net Zero targets1 is driving the rapid expansion of the UK renewable energy sector. The Government Ten Point Plan for a Green Industrial Revolution2 outlines further commitments to low-carbon energy technologies, including nuclear power. Renewable energy, nuclear power station developments, and other Nationally Significant Infrastructure Projects are all required to conduct Environmental Impact Assessments (EIA), as well as other statutory assessments, to fulfil environmental regulations and support the consenting process for the projects.
There is currently a lack of guidance on the process to define the geographic scales of populations of fish species in the marine environment, as required for use in EIA, Habitats Regulations Assessments (HRA), and Marine Conservation Zone assessments (MCZa). Establishing standardised process will ensure consistency in approach between projects, robustness for consenting processes, and has the potential to de-risk and streamline the consenting process for developments and regulators.
EIA has traditionally taken an approach of assessing losses of fish in a solely anthropogenic context, comparing losses to fishery management stock units, or fishery landings data. This approach however, is not considered relevant when assessing fish populations as features of MPAs, Estuarine N2K sites (SAC/RAMSAR), or as prey species for protected marine mammals and seabirds. High-quality, standardised assessments will contribute to delivering the 25 Year Environment Plan and achieving Good Environmental Status under the UK Marine Strategy.

Tender categories (products & services required)

Research and experimental development services (CPV 73100000)

Region

London (UKI)

Buyer Information

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