Abstract

PurposeThe focus of land use modeling in life cycle impact assessment has been mainly on taxonomic measures of biodiversity, namely species richness (SR). However, increasing availability of trait data for species has led to the use of functional diversity (FD) as a promising metric to reflect the distinctiveness of species; this paper proposes the use of an FD index to calculate characterization factors (CFs) for land use impacts. Furthermore, we compare the results of the CFs to current practice and assess the increase in complexity introduced by the use of the new indicator.MethodsThe model proposed is based on data compiled by previous regional meta-analysis on SR and FD, in different land use types in the Americas. The taxonomic groups included were mammals, birds, and plants. Within each study, calculated values for FD for different land use types were compared with the natural or close-to-natural state, taken as the reference situation. FD values among different land uses were standardized, and CFs were calculated. The final results were then analyzed and compared by analysis of variance and post hoc tests. A sensitivity analysis was also applied to verify the influence on the choice of the reference state.Results and discussionThe results show that significant differences exist between CFs for SR and FD metrics. Across all taxa, CFs differ significantly between land use types. The results support the use of CF for FD, as a complement to current practice. Distinct CFs should be applied for at least six groups of land use categories. The choice of reference land use type did not significantly alter the results but can be a source of variability. A sensitivity analysis evaluating the impact of alternate land use types as reference types found only few significant changes on the results.Conclusions and recommendationsGiven the results, we believe the use of CFs based on FD can help on the establishment of possible links between species loss and key ecosystem functions, i.e., on the association between the midpoint indicator (e.g., biodiversity loss) and the damage caused to ecosystem quality, in terms of functions lost. Basing CFs on FD is not without challenges. Such indices are data hungry (requiring species composition and traits) require more complex calculations than current common practice, including decisions on the choice of a method to calculate FD and the selection of traits.

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