Article

CAPOT: A flexible rapid assessment model to estimate local deposition of fish cage farm wastes

Details

Citation

Telfer TC, Bostock J, Oliver RLA, Corner RA & Falconer L (2022) CAPOT: A flexible rapid assessment model to estimate local deposition of fish cage farm wastes. Marine Environmental Research, 182, Art. No.: 105788. https://doi.org/10.1016/j.marenvres.2022.105788

Abstract
The Cage Aquaculture Particulate Output and Transport (CAPOT) model is an easy to use and flexible farm-scale model that can rapidly estimate particulate waste deposition from fish cage production. This paper describes and tests the model and demonstrates its use for Atlantic salmon (Salmo salar) and Atlantic cod (Gadus morhua). The spreadsheet-based model gives outputs for waste distribution in a variety of spatial modelling software formats, used for further analysis. The model was tested at a commercial Atlantic cod farm and commercial Atlantic salmon farm under full production conditions. Sediment trap data showed predictions, using actual recorded feed and biomass data, to be 96% (±36%) similar for Atlantic cod beyond 5 m from the cage edge, giving a satisfactory estimate of local benthic impact in the vicinity of the farm. For Atlantic salmon, using estimated production biomass and FCR (Feed Conversion Ratio) to calculate feed input, the model overestimated wastes directly beneath the cages (120% ± 148%) and underestimated beyond 5 m from the cage edge, being 48% (±42%) similar to sediment trap data. CAPOT is a suitable initial, rapid assessment model to give an overview of potential impact of particulate waste from new or expanded fish cage farms, with little operator expertise by a wide range of stakeholders.

Keywords
Pollution; Aquatic Science; General Medicine; Oceanography

Journal
Marine Environmental Research: Volume 182

StatusPublished
FundersEuropean Commission (Horizon 2020), NERC Natural Environment Research Council, Seafish UK and Highlands and Islands Enterprise
Publication date31/12/2022
Publication date online27/10/2022
Date accepted by journal22/10/2022
URLhttp://hdl.handle.net/1893/34676
PublisherElsevier BV
ISSN0141-1136

People (2)

Dr Lynne Falconer

Dr Lynne Falconer

Research Fellow, Institute of Aquaculture

Professor Trevor Telfer

Professor Trevor Telfer

Professor, Institute of Aquaculture

Projects (1)

Files (1)