Dataset Information

DAR (diversity-area relationship): Extending classic SAR (species-area relationship) for biodiversity and biogeography analyses.

ABSTRACT: I extend the classic SAR, which has achieved status of ecological law and plays a critical role in global biodiversity and biogeography analyses, to general DAR (diversity-area relationship). The extension was aimed to remedy a serious application limitation of the traditional SAR that only addressed one aspect of biodiversity scaling-species richness scaling over space, but ignoring species abundance information. The extension was further inspired by a recent consensus that Hill numbers offer the most appropriate measures for alpha-diversity and multiplicative beta-diversity. In particular, Hill numbers are essentially a series of Renyi's entropy values weighted differently along the rare-common-dominant spectrum of species abundance distribution and are in the units of effective number of species (or species equivalents such as OTUs). I therefore postulate that Hill numbers should follow the same or similar law of the traditional SAR. I test the postulation with the American gut microbiome project (AGP) dataset of 1,473 healthy North American individuals. I further propose three new concepts and develop their statistical estimation formulae based on the new DAR extension, including: (i) DAR profile-z-q relationship (DAR scaling parameter z at different diversity order q), (ii) PDO (pair-wise diversity overlap) profile-g-q relationship (PDO parameter g at order q, and (iii) MAD (maximal accrual diversity: D _max) profile-D _max-q. While the classic SAR is a special case of our new DAR profile, the PDO and MAD profiles offer novel tools for analyzing biodiversity (including alpha-diversity and beta-diversity) and biogeography over space.

SUBMITTER: Ma ZS

PROVIDER: S-EPMC6206192 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

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DAR (diversity-area relationship): Extending classic SAR (species-area relationship) for biodiversity and biogeography analyses.

Ma Zhanshan Sam ZS

Ecology and evolution 20180925 20

I extend the classic SAR, which has achieved status of ecological law and plays a critical role in global biodiversity and biogeography analyses, to general DAR (diversity-area relationship). The extension was aimed to remedy a serious application limitation of the traditional SAR that only addressed one aspect of biodiversity scaling-species richness scaling over space, but ignoring species abundance information. The extension was further inspired by a recent consensus that Hill numbers offer t ...[more]

PMID: 30397444

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Project description:Understanding the patterns and processes underlying the uneven distribution of biodiversity across space constitutes a major scientific challenge in systematic biology and biogeography, which largely relies on effectively mapping and making sense of rapidly increasing species occurrence data. There is thus an urgent need for making the process of coding species into spatial units faster, automated, transparent, and reproducible. Here we present SpeciesGeoCoder, an open-source software package written in Python and R, that allows for easy coding of species into user-defined operational units. These units may be of any size and be purely spatial (i.e., polygons) such as countries and states, conservation areas, biomes, islands, biodiversity hotspots, and areas of endemism, but may also include elevation ranges. This flexibility allows scoring species into complex categories, such as those encountered in topographically and ecologically heterogeneous landscapes. In addition, SpeciesGeoCoder can be used to facilitate sorting and cleaning of occurrence data obtained from online databases, and for testing the impact of incorrect identification of specimens on the spatial coding of species. The various outputs of SpeciesGeoCoder include quantitative biodiversity statistics, global and local distribution maps, and files that can be used directly in many phylogeny-based applications for ancestral range reconstruction, investigations of biome evolution, and other comparative methods. Our simulations indicate that even datasets containing hundreds of millions of records can be analyzed in relatively short time using a standard computer. We exemplify the use of SpeciesGeoCoder by inferring the historical dispersal of birds across the Isthmus of Panama, showing that lowland species crossed the Isthmus about twice as frequently as montane species with a marked increase in the number of dispersals during the last 10 million years. [ancestral area reconstruction; biodiversity patterns; ecology; evolution; point in polygon; species distribution data.].

Dataset Information

DAR (diversity-area relationship): Extending classic SAR (species-area relationship) for biodiversity and biogeography analyses.

Publications

DAR (diversity-area relationship): Extending classic SAR (species-area relationship) for biodiversity and biogeography analyses.

Similar Datasets

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