Estimating the Number of Species: A Review

Bunge, John; Fitzpatrick, Matthew C.

doi:10.2307/2290733

Cited by 330 publications

(234 citation statements)

References 52 publications

(75 reference statements)

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“…Means and standard deviations of richness estimates were calculated from 10,000 bootstrap replicates of the dataset. Because our data represents a limited sampling of individuals from each accession, with varying numbers of sampled individuals per accession, we estimated the total number of expected amplified fragments had each accession been sampled with a uniform number of individuals per, using n = 3 (Bunge and Fitzpatrick 1993). For each individual, we also computed the number of unique amplified fragments across all primer pairs.…”

Section: Estimates Of Genetic Parametersmentioning

confidence: 99%

Post-glacial evolution of Panicum virgatum: centers of diversity and gene pools revealed by SSR markers and cpDNA sequences

et al. 2011

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Switchgrass (Panicum virgatum), a central and Eastern USA native, is highly valued as a component in tallgrass prairie and savanna restoration and conservation projects and a potential bioenergy feedstock. The purpose of this study was to identify regional diversity, gene pools, and centers-of-diversity of switchgrass to gain an understanding of its post-glacial evolution and to identify both the geographic range and potential overlap between functional gene pools. We sampled a total of 384 genotypes from 49 accessions that included the three main taxonomic groups of switchgrass (lowland 4x, upland 4x, and upland 8x) along with one accession possessing an intermediate phenotype. We identified primary centers of diversity for switchgrass in the eastern and western Gulf Coast regions. Migration, drift, and selection have led to adaptive radiation in switchgrass, creating regional gene pools within each of the main taxa. We estimate that both upland-lowland divergence and 4x-to-8x polyploidization within switchgrass began approximately 1.5-1 M ybp and that subsequent ice age cycles have resulted in gene flow between ecotype lineages and between ploidy levels. Gene flow has resulted in ''hot spots'' of genetic diversity in the southeastern USA and along the Atlantic Seaboard.

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Section: Estimates Of Genetic Parametersmentioning

confidence: 99%

Post-glacial evolution of Panicum virgatum: centers of diversity and gene pools revealed by SSR markers and cpDNA sequences

et al. 2011

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“…Historically first was the idea to use parametric distributions to approximate the frequency distribution of captured species, and to project the given distribution so as to estimate how many more species must be present in the community to account for the empirically collected data (8). This powerful tool has often not been used to its potential.…”

mentioning

confidence: 99%

Predicting microbial species richness

Hong

Bunge

Jeon

et al. 2005

Proc. Natl. Acad. Sci. U.S.A.

191

165

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Microorganisms are spectacularly diverse phylogenetically, but available estimates of their species richness are vague and problematic. For example, for comparable environments, the estimated numbers of species range from a few dozen or hundreds to tens of thousands and even half a million. Such estimates provide no baseline information on either local or global microbial species richness. We argue that this uncertainty is due in large part to the way statistical tools are used, if not indeed misused, in biodiversity research. Here we develop a powerful synthetic statistical approach to quantify biodiversity. It provides statistically sound estimates of microbial richness at any level of taxonomic hierarchy. We apply this approach to a large original 16S rRNA dataset on marine bacterial diversity and show that the number of bacterial species in a sample from marine sediments is (2.4 ؎ 0.5 SE) ؋ 10 3 . We argue that our methodology provides estimates of microbial richness that are reliable and general, have biologically meaningful SEs, and meet other fundamental statistical standards. This approach can be an essential tool in biodiversity research, and the estimates of microbial richness presented here can serve as a baseline in microbial diversity studies.global biodiversity ͉ microorganisms ͉ number of species

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“…After extensive trials it was decided to use Chao's estimator of sample coverage as the correction factor (C = one minus the relative frequency of species found in just one plot) (Bunge & Fitzpatrick, 1993) (Chao & Lee, 1992 (Magnussen & McRoberts, 2011). The variance of ,h est S was estimated as detailed in the source document for each estimator (c.f.…”

Section: Estimation Of Regional Forest Tree Species Richnessmentioning

confidence: 99%

Sample-based Estimation of Regional Forest Tree Species Richness

Magnussen¹

2011

ENRR

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Sample-based estimates of species richness for large heterogeneous regions may be affected by interactions between the sampling design and sub-regional heterogeneity in species richness and diversity. To investigate this issue a Monte Carlo simulation study was conducted with actual forest inventory tree species incidence data from two large regions, four estimators of species richness, three sampling designs, two sampling units (fixed area plots and tree nearest to plot center), and five sample sizes. The regions represent forested areas in central and eastern Canada and three states in the USA. Design effects in estimates of regional species richness were generally weak, of little practical import, and limited to settings with the smallest sample sizes. The study shows that accurate regional estimates of richness can be obtained by pooling sub-regional species incidence data. Sampling with fixed area plots was, with few estimator-dependent exceptions, considerably more efficient than sampling with one tree per sample location. A proposed ratio-based procedure for combining sub-regional estimates of richness broadens the options for regional estimation.

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Estimating the Number of Species: A Review

Cited by 330 publications

References 52 publications

Post-glacial evolution of Panicum virgatum: centers of diversity and gene pools revealed by SSR markers and cpDNA sequences

Post-glacial evolution of Panicum virgatum: centers of diversity and gene pools revealed by SSR markers and cpDNA sequences

Predicting microbial species richness

Sample-based Estimation of Regional Forest Tree Species Richness

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