On stability measures and effects of data structure in the recognition of areas of endemism

CASAGRANDA, M DOLORES; GOLOBOFF, PABLO A

BIOLOGICAL JOURNAL OF THE LINNEAN SOCIETY

WILEY-BLACKWELL PUBLISHING, INC

Año: 2019 vol. 127 p. 143 - 155

0024-4066

Incomplete data sampling, bias, and like properties of distribution datasets that potentially introduce uncertainty inbiogeographical analyses and blur biogeographical patterns; therefore, it is important to understand their influence.Despite their relevance, these problems have been largely overlooked in biogeography, where concepts such asambiguity, stability or support have not even been defined. Here, we propose two stability measures for hypothesesof areas of endemism (AEs) and use them to explore the degree to which different structural qualities of data affectthe results of analyses of endemism. Our findings suggest that different types of data incompleteness have differenteffects on the recovery of the species composition and the geographical or spatial structure of AEs, showing thatdistinct levels of sampling coverage affect the stability of results in different ways. We show that a small proportionof poorly sampled species may have a stronger impact on AEs stability than many species with medium samplingand that excluding poorly sampled species from the analyses does not guarantee more stable results. These resultshighlight the importance of planning data collection and indicate that, in order to obtain more stable results, focusingon completing the distribution of strongly undersampled species might be preferable to adding records of any speciesrandomly.