Upscaling biodiversity: estimating the species-area relationship from small samples

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11310%2F18%3A10385363" target="_blank" >RIV/00216208:11310/18:10385363 - isvavai.cz</a>

Alternative codes found

RIV/00216208:11620/18:10385363

Result on the web

<a href="https://doi.org/10.1002/ecm.1284" target="_blank" >https://doi.org/10.1002/ecm.1284</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1002/ecm.1284" target="_blank" >10.1002/ecm.1284</a>

Result language

angličtina

Original language name

Upscaling biodiversity: estimating the species-area relationship from small samples

Original language description

The challenge of biodiversity upscaling, estimating the species richness of a large area from scattered local surveys within it, has attracted increasing interest in recent years, producing a wide range of competing approaches. Such methods, if successful, could have important applications to multi-scale biodiversity estimation and monitoring. Here we test 19 techniques using a high quality plant data set: the GB Countryside Survey 1999, detailed surveys of a stratified random sample of British landscapes. In addition to the full data set, a set of geographical and statistical subsets was created, allowing each method to be tested on multiple data sets with different characteristics. The predictions of the models were tested against the &quot;true&quot; species-area relationship for British plants, derived from contemporaneously surveyed national atlas data. This represents a far more ambitious test than is usually employed, requiring 5-10 orders of magnitude in upscaling. The methods differed greatly in their performance; while there are 2,326 focal plant taxa recorded in the focal region, up-scaled species richness estimates ranged from 62 to 11,593. Several models provided reasonably reliable results across the 16 test data sets: the Shen and He and the Ulrich and Ollik models provided the most robust estimates of total species richness, with the former generally providing estimates within 10% of the true value. The methods tested proved less accurate at estimating the shape of the species-area relationship (SAR) as a whole; the best single method was Hui&apos;s Occupancy Rank Curve approach, which erred on average by &lt;20%. A hybrid method combining a total species richness estimate (from the Shen and He model) with a downscaling approach (the Sizling model) proved more accurate in predicting the SAR (mean relative error 15.5%) than any of the pure upscaling approaches tested. There remains substantial room for improvement in upscaling methods, but our results suggest that several existing methods have a high potential for practical application to estimating species richness at coarse spatial scales. The methods should greatly facilitate biodiversity estimation in poorly studied taxa and regions, and the monitoring of biodiversity change at multiple spatial scales.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

10618 - Ecology

Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2018

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Ecological Monographs

ISSN

0012-9615

e-ISSN

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Volume of the periodical

88

Issue of the periodical within the volume

2

Country of publishing house

US - UNITED STATES

Number of pages

18

Pages from-to

170-187

UT code for WoS article

000431631400002

EID of the result in the Scopus database

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