Species-Area Relationships Indicate Large-Scale Data Gaps in Herbarium Collections

Abstract

Species-area relationships (SAR) are useful in predicting species richness for a given geographical area. Using SAR and the state of Texas as a case study, we present a model that provides a quantifiable and objective approach for identifying large scale data gaps in species inventories and museum collections by comparing documented species richness (determined by herbarium records) to predicted species richness. For Texas our results indicate that 88% of the counties have documented species richness values that are below predicted values based upon our results from the proposed model. Many biological survey and inventory programs are funded to document species occurrence and richness. Such studies help identify species of concern and enhance species conservation efforts. Future species inventories may benefit from such predictive models in identifying regions of large scale data gaps.