Limited sampling hampers "big data" estimation of species richness in a tropical biodiversity hotspot.

ABSTRACT: Macro-scale species richness studies often use museum specimens as their main source of information. However, such datasets are often strongly biased due to variation in sampling effort in space and time. These biases may strongly affect diversity estimates and may, thereby, obstruct solid inference on the underlying diversity drivers, as well as mislead conservation prioritization. In recent years, this has resulted in an increased focus on developing methods to correct for sampling bias. In this study, we use sample-size-correcting methods to examine patterns of tropical plant diversity in Ecuador, one of the most species-rich and climatically heterogeneous biodiversity hotspots. Species richness estimates were calculated based on 205,735 georeferenced specimens of 15,788 species using t

SUBMITTER: Engemann K 

PROVIDER: S-EPMC4328781 | biostudies-literature | 2015 Feb

REPOSITORIES: biostudies-literature