Estimating conservation value and natural capital value of land cover classes in the Irish National Land Cover Map and application to a case study area
Citation
S. Ruas, J.A. Finn and D. Ó hUallacháin et al. Estimating conservation value and natural capital value of land cover classes in the Irish National Land Cover Map and application to a case study area. Irish Journal of Agricultural and Food Research. 2024. Vol. 63(1):27-42. DOI: https://doi.org/10.15212/ijafr-2023-0111Abstract
Conservation science and planning, by measuring proxies of biodiversity and ecosystem services provision, aim to identify priority areas for nature conservation and ecosystem services. In Ireland, fine-scale data on ecosystems functioning and biodiversity are limited, making it challenging to map conservation value (CV) and natural capital value (NCV) accurately. We elicited expert knowledge to rank habitat classes mapped in the recently published National Land Cover Map (NLCM) (EPA and Tailte Éireann, 2023). A scoring system from 0 to 10 was used to score habitats based on their estimated provision of biodiversity (CV) and ecosystem services (NCV). As a case study, we applied this scoring system to a catchment in the south-east of Ireland (>2,000 km2) with land cover information available from the draft NLCM. The expert elicitation showed little overall difference between the scores assigned by the team and the experts invited to validate the CV and NCV scores. However, some scores were revised based on experts’ contributions. Results of the mapping exercise indicated a high correlation between monads with high CV and high NCV scores. Future work should focus on differentiating the weighting assigned to each ecosystem service associated with each land cover class. This could result in changes in the overall NCV scores assigned to each habitat (and monads). Nevertheless, the approach developed here has the potential to identify areas in the landscape that should be targeted for conservation. For reproducibility, we provide the R code for analysis at polygon scale.Funder
Department of Agriculture, Food and the MarineGrant Number
2019R425ae974a485f413a2113503eed53cd6c53
10.15212/ijafr-2023-0111
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