Monitoring and mapping species diversity through the use of indicators can allow detecting changes in communities. Conclusions regarding these changes greatly depend upon which indicator is used. Here we propose a new metric, the distance biochange index (DBCI), which enables the characterization and quantification of the level and direction of change in biological communities relative to a given reference state. The proposed metric assesses the probability of observing a complete change in a given community and can be decomposed into 4 conditional probabilities of change: no change, complete change in species composition only, complete change in species richness only and complete change in both species composition and richness. In this study, we compared the properties of our metric with those of other widely used indices using numerical examples and partial derivatives. We also extended its application to a simulated case study of the predicted evolution of suitable habitats under climate change. The simulated case study was used to assess the ability of DBCI and other widely used indices to detect and assess the effect of changing environmental gradients on the structure and diversity of biological communities.
Results/Conclusions
The results from simulation and case studies demonstrated how DBCI captured the effect of ecological gradients on species composition and richness in biological communities and compared favorably with commonly used similarity indices to monitor both the level and the direction of changes in biological communities. Most of the studied indices were insensitive or provided an incomplete assessment of change under the specific conditions of our scenarios. Therefore, it is important to account for the limits of similarity indices when evaluating the effects of global change on biological communities.
The DBCI represents a significant improvement over other similarity indices in that DBCI1) explicitly accounts for differences in species richness and species composition among communities when assessing similarity, 2) simultaneously quantifies directional (e.g., gains or losses) changes in species richness and composition among biological communities, and 3) provides a probability of change of the ecosystem relative to a reference state. The combination of these attributes in a metric, represents a step forward to study changes in biological communities, especially in the context of global change. The quantitative assessment derived from this index provides useful insights, since it can be interpreted as conditional probabilities of change in species composition and richness.