Assessing natural capital value in the network of Italian marine protected areas: a comparative approach
DOI:
https://doi.org/10.12775/EQ.2020.029Keywords
environmental accounting, natural capital, marine ecosystems, marine protected areasAbstract
Marine and coastal natural capital stocks provide a bundle of ecosystem services vital for human well-being. The biophysical and economic assessment of the value of natural capital stocks is much needed for achieving nature conservation goals, while ensuring the sustainable exploitation of marine resources. Marine Protected Areas (MPAs) are increasingly being established worldwide to protect and conserve natural capital stocks from anthropogenic threats. In this study, a biophysical and trophodynamic model based on the emergy accounting method was used to assess the value of natural capital for a set of Italian MPAs. In particular, the assessment focused on four main macro-habitats: 1) sciaphilic hard bottom (SHB), 2) photophilic hard bottom (PHB), 3) soft bottom (SB), and 4) Posidonia oceanica seagrass beds (PSB). The emergy method allowed the assessment of natural capital stocks in terms of direct and indirect solar energy flows invested by nature for their generation. The SHB habitat showed the highest emergy density value in most of the investigated MPAs, confirming the high convergence of input resource flows in the formation of this habitat. When considering extensive indicators, the contribution of the PSB habitat to the total value of natural capital was higher than other habitats in most MPAs. In addition, to facilitate the understanding of the results in socio-economic contexts, the biophysical values of natural capital stocks were converted into monetary units. The total value of natural capital in the investigated MPAs ranged from about 8 to 1163 M€. In conclusion, assessing the value of natural capital can support local managers and policy makers in charge for achieving nature conservation targets while ensuring the sustainable exploitation of natural resources.References
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