Modelling the biomass of functional groups of fish in an archipelago bay of the Baltic Sea

Andreas C. Bryhn, Henrik Ragnarsson Stabo and Jens Olsson

Ecological Modelling, 2013, vol. 269, issue C, 86-97

Abstract: Fish biomass estimates in European coastal waters are necessary for several reasons, e.g., for meeting requirements in legislation and international agreements, for establishing sustainable outtakes of the resources, for developing management plans and for assessing the ecological and environmental status of coastal waters. This study estimated piscivorous and non-piscivorous fish biomass as well as total fish biomass in Kvädöfjärden Bay on the Swedish Baltic Sea coast using dynamic foodweb modelling. Weight-per-unit-effort data from the coastal fish monitoring program in the area together with a range of abiotic variables (including salinity and total phosphorus) were used as drivers for the CoastWeb model. To further refine the estimates of fish biomass, we complemented the model by using data from nearby areas on the ratio of piscivorous to non-piscivorous fish for those size classes not representatively sampled by the monitoring gear (fish<12cm). Piscivorous fish biomass in the area was estimated at 10–14 tonnes (4.6–6.5kg/ha), non-piscivorous fish biomass at 105–139 tonnes (47–62kg/ha) and the subsequent total fish biomass was estimated at 115–154 tonnes (52–69kg/ha). The estimated range of total fish biomass was comparable with findings from other investigations on the Swedish Baltic Sea coast which used a coarser methodology. The method presented in this paper can be used for making biomass estimates in other coastal waters where passive gears are used to monitor the local fish communities, and could thus serve a range of purposes for assessing the production and status of fish in coastal waters.

Keywords: Coastal fish; Piscivores; Non-piscivores; Biomass; Food-web modelling (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:269:y:2013:i:c:p:86-97

DOI: 10.1016/j.ecolmodel.2013.08.015

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