Climate change is currently one of the main forces behind the changes in the distribution of species which affects the suitability of a species habitat both in terms of the environment (temperature) and available food. To enable better predictions of the likely changes in spatial dynamics, it is necessary to establish mechanistic links between changes in primary production and higher trophic levels.
This requires a combination of data from different trophic levels, an understanding of species physiological requirements, and specific modelling exercises to establish the links. A vast amount of acoustic data are being collected every year during statutory surveys. These data are notoriously under-utilised and serve primarily to deliver an index of biomass of a specific “target” fish species. Over the last 10 years, some of these surveys have collected acoustic data synoptically at several frequencies. This delivers more information about encountered organisms, allowing for a better classification and identification of them.
Layers of planktonic organisms usually feature prominently on echograms which are recorded during surveys -e.g. in the North Sea. If these layers can be appropriately classified, acoustic multifrequency data may be used to produce high-resolution distribution maps and abundance estimates of lower secondary production. Recent work in the Bay of Biscay has demonstrated easy ways to extract abundance and distribution of macrozooplankton from acoustic multifrequency data. Such information is vital for the development of ecosystem models which can be used to describe habitat quality and energy sources of organisms at higher trophic levels – e.g. forage fish.
In order to infer abundance of planktonic organisms from acoustic multifrequency data, plankton production in combination with a physiological model (DEB) is used to model habitat quality of organisms at higher trophic level. When the link between annual variability in production, habitat quality (based on DEB) and realised spatial dynamics of forage fish (acoustic data) will be investigated, Herring will be used as an example forage fish species.
In the first phase, the organizational phase, the algorithm of multifrequency “plankton extraction” will be developed. Backscatter models will be developed in order to deliver a species-specific frequency response used in the algorithm. In the second phase, plankton extraction from acoustics will be compared with satellite data and ERSEM model based on statistical analyses (e.g. GAM). In phase three, the DEB model with temperature data and high-resolution plankton data from acoustics are used as input to map changes in herring habitat quality (growth potential) in the northern North Sea between 2002-2010 and these are compared to actual herring abundance recorded during the acoustic survey.
The project will enhance data usage from (existing) survey data and thereby improving their potential use for ecosystem modelling. The findings will contribute towards the broad concept of the ecosystem approach to fisheries management by producing answers to ecosystem functioning. Habitat quality descriptors resulting from the project are key to the MSFD and definition of GES.