Abstract
Abstract The recent adoption of Bayesian networks (BNs) in ecology provides an opportunity to make advances because complex interactions can be recovered from field data and then used to predict the environmental response to changes in climate and biodiversity. In this study, we use a dynamic BN model with a hidden variable and spatial autocorrelation to explore the future of different fish and zooplankton species, given alternate scenarios, and across spatial scales within the North Sea. For most fish species, we were able to predict a trend of increase or decline in response to change in fisheries catch; however, this varied across the different areas, outlining the importance of trophic interactions and the spatial relationship between neighbouring areas. We were able to predict trends in zooplankton biomass in response to temperature change, with the spatial patterns of these effects varying by species. In contrast, there was high variability in terms of response to productivity changes and consequently knock-on effects on higher level trophic species. Finally, we were able to provide a new data-driven modelling approach that accounts for multispecies associations and interactions and their changes over space and time, which might be beneficial to give strategic advice on potential response of the system to pressure.
Highlights
The North Sea is a dynamic system, heavily modified by humans and climate
We describe the outputs from the modelled fisheries catch, temperature and net primary production (Net PP) scenarios by examining future trends of individual fish and zooplankton species at spatial and temporal scales
Our results demonstrate some variability in the future trends of different species, which we explain through the use of “what if” type descriptions of the model structures in response to predicted changes in the other variables
Summary
The North Sea is a dynamic system, heavily modified by humans and climate. There is an increasing demand for tools with which to explore alternative hypotheses about ecosystem response to change in pressures (Mackinson and Daskalov, 2007). We present an approach to explore how species and trophic groups respond to change in human and climate pressures and understand potential trade-offs between such ecosystem components, given a set of alternate scenarios. Fishing pressure can change the structure of marine populations and influence the nature of their responses to climate (Planque et al, 2010). The ecosystem-based approach to fisheries management acknowledges that fisheries are part of the environment and cannot be managed in isolation (Cury et al, 2005) and requires recognition of the ecosystem dynamics and structure
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