Ecological Uniqueness: New Measures to Reconcile Method With Concept

Abstract

Aim

Ecological uniqueness quantifies how different a community is relative to all other communities within the study. This broad-sense definition of uniqueness makes it dependent on the choice of the dissimilarity metric used to quantify differences between communities. Moreover, under a narrow-sense definition of the concept, a uniqueness metric should indicate the proportion of species in the community that are unique to that community, i.e., absent from other communities. Here we develop and assess the key properties of a reliable metric for the quantification of uniqueness and compare the behaviour of two widely used approaches: (i) average pairwise dissimilarity between the focal community and all others and (ii) Local Contribution to Beta Diversity (LCBD).

Innovation

We introduce two new metrics to compute ecological uniqueness using presence/absence (U_rlb) and abundance data (U_rlb.ab), based on asymmetric Ruggiero dissimilarity (β_rlb) and a new abundance-based asymmetric dissimilarity index (β_rlb.ab), respectively. We also identify two key properties for the quantification of uniqueness under a narrow definition of the concept: pairwise index asymmetry and independence from the number of non-focal sites included in the study. Pairwise asymmetry refers to the possibility that the dissimilarity between community A and B differs from the dissimilarity between B and A. To show this, we provide conceptual and simulated examples assessing the behaviour of uniqueness when quantified as LCBD (Hellinger and Sørensen), as average symmetric dissimilarity (Sørensen and Simpson) and as average asymmetric dissimilarity (Ruggiero) using presence/absence data. We also include a case study using real data on European longhorn beetles. We show that both approaches (average dissimilarity and LCBD) are conceptually and mathematically equivalent, but only average dissimilarity can be interpreted in absolute terms as it accounts for the overall beta diversity (i.e., community differentiation) within the region and does not depend on the number of non-focal communities.

Conclusion

Our results show that only average dissimilarity values based on an asymmetric index allow the quantification of uniqueness that is consistent with its ecological narrow-sense concept. Uniqueness thus emerges as an important ecological attribute that, if properly quantified, can be used to identify highly valuable communities, containing many species exclusive to them. Consequently, by focusing on uniqueness, conservation efforts can target large-scale conservation goals with a site-focused perspective.