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Comparison of three biodiversity metrics to evaluate corporate no net loss achievement under spatial constraints
Margaux Durand1, Leon Bennun2, Joshua Berger3
1Université Paris-Saclay, INRAE, AgroParisTech, Paris-Saclay Applied Economics, 91120, Palaiseau, France; CDC Biodiversité, 75017, Paris, France.
Abstract:
Business and finance sector actors have the potential to contribute substantially to bending the curve of biodiversity loss, in the context of a global nature positive agenda. The scope of application of the mitigation hierarchy - avoiding and reducing negative impacts on nature, and compensating for the residual ones - is being extended, from localised impacts to potentially diffuse ones at the level of corporate value-chains, to achieve at least no net loss (NNL) of biodiversity. This poses a need to define and quantify the equivalence of biodiversity losses and gains, which may depend on the metric(s) used to measure them. Here we evaluate and compare three biodiversity metrics in a global NNL context, using an optimisation approach to identify the minimum area to be restored in order to compensate for biodiversity losses from corporate activities. The three metrics are Mean Species Abundance (MSA), the Land-cover Change Impacts on Future Extinctions (LIFE) score and the Species Threat Abatement and Restoration (STAR) metric. We also investigate how spatial scale constraints imposed on restoration affect the achievement of NNL across metrics. We observe cases for all metrics where NNL cannot be achieved within strict spatial scale constraints. We also find that NNL for one metric does not guarantee NNL for the others, and that differences in the nature of the metrics (MSA, compared to LIFE/STAR) influences the overall area restored to achieve NNL. The results highlight how outcomes for biodiversity will be more satisfactory if using two or more complementary metrics for value-chain level NNL assessments, and how avoiding and minimising losses is key, as compensation within certain spatial constraints is not always possible.
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