Linking natural capital to maritime activities: operationalizing the ecosystem service cascade framework along the Basque coast (SE Bay of Biscay).

Supervisors: Ibon Galparsoro, Arantza Murillas (AZTI).
The development and economic performance of maritime sectors are reliant on natural capital (NC), accessed in part through ‘Ecosystem Services’ (ES). In understanding both concepts within the spatial domain, management plans may better incorporate the capacity of the environment to develop novel sectors, in order to efficiently allocate resource use and avoid environmental degradation. This is especially relevant to the increasing development of ‘Blue Growth’ sectors, which rely on varying NC, in addition to technical, and economic considerations. Therefore, we propose linking maritime activities to NC, directly or through ES, in order to understand where activities can develop and the inadvertent socio-economic and environmental consequences that may arise from such development. To model relationships from NC to maritime activities, we present a spatially-explicit Bayesian Belief Network (BBN), using the Basque coast (SE Bay of Biscay) as a case study. The model links economic performance of relevant marine activities (including aquaculture, marine tourism, benthic and artisanal fisheries) with the ES provided by benthic habitats and ecosystem components, incorporating empirical and published ES indicators. The study identifies the specific interaction of NC with activities, where aquaculture and marine tourism are highly dependent on NC adjacent to the coast, although to different ES and ecosystem components. Furthermore, when NC dependencies are combined with economic and legislative factors, the current spatial distribution of the activity can be explained and the impacts of management decisions could be determined. The model provides a ‘first-pass’ overview of the NC dependency of the maritime economy, especially Blue Growth sectors on NC and is therefore highly relevant towards achieving ecosystem-based marine spatial planning.