CEFAS24-41 Contract to provide analysis and data to support development and validation of a model of macroalgal, seagrass and saltmarsh growth
Buyers
Value
£54,000
Suppliers
Classifications
- Analysis services
Tags
- award
Submission Deadline
7 months ago
Published
6 months ago
Description
Background: The Marine Natural Capital and Ecosystem Assessment (mNCEA) programme is a flagship science innovation programme that is addressing integrating natural capital and ecosystem assessment approaches into policy and decision making for marine and coastal environments. Ecosystem assessment tells us about the health of our natural environment and how this is changing over time, whereas natural capital describes the economic, social and environmental value our natural assets hold for people, from food to carbon storage to health and wellbeing. The mNCEA programme is funded by Defra and delivered by its partners (The Arm's Length Bodies - ALBs) Phase I of the Macroalgae Seagrass Model Development project, for the Land-sea Interface work in the mNCEA programme, was completed during October 2023 - March 2024. This phase provided analysis and data on seagrass occurrence within Langstone harbour (Ward and Preston, 2024) that informed development and calibration of the seagrass component within the extended CPM mode being developed under mNCEA (LSI) WP3. Based on the recommendations in the technical report submitted to Cefas (Ward and Preston, 2024), and directly shaped by explicit data needs communicated by Cefas staff, Cefas require the supplier to provide the below services. Requirement: Cefas require the supplier; 1. To provide feedback on the underlying principles, and utility of the Cefas CPM model. 2. To provide an updated seagrass coverage spatial map for Langstone Harbour. 3. To provide data on seasonal cycles of seagrass coverage at selected sites in Langstone harbour. 4. To provide spatial estimates of seagrass above and below ground biomass. 5. To collate suite of abiotic data to further characterise environmental conditions in relation to seagrass presence. 6. To analyse which ranges of potentially predictive environmental variables, including depth, tidal inundation, bathymetric slope and current speed, correlate with known seagrass extent.
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