Everyone makes mistakes: Sampling errors in vegetation analysis - The effect of different sampling methods, abundance estimates, experimental manipulations, and data transformation

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60076658%3A12310%2F20%3A43901304" target="_blank" >RIV/60076658:12310/20:43901304 - isvavai.cz</a>

Alternative codes found

RIV/60077344:_____/20:00533773

Result on the web

<a href="https://www.sciencedirect.com/science/article/pii/S1146609X20301594?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S1146609X20301594?via%3Dihub</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.actao.2020.103667" target="_blank" >10.1016/j.actao.2020.103667</a>

Result language

angličtina

Original language name

Everyone makes mistakes: Sampling errors in vegetation analysis - The effect of different sampling methods, abundance estimates, experimental manipulations, and data transformation

Original language description

Understanding of causes for recent changes in vegetation structure and species richness of natural habitats is crucial for their maintaining for future generations. However, to avoid misinterpretation of vegetation changes in time, we should be aware of limits and errors of methods used for vegetation sampling. In a specific vegetation type, i.e. species rich wet meadow, we quantified sampling error in vegetation sampling at four different sampling levels (visual cover estimation, detailed recording in a grid of small cells, detailed assessment during clipping for biomass, biomass sorting), compared differences among three abundance estimates (frequency, cover and biomass), and assessed the effect of data transformation, and rapid change in vegetation structure caused by experimental species removal. At the 1 m(2) scale the captured proportion of species missed by classical releve sampling was on average 16%. Subsequent detailed subquadrat sampling captured the majority of previously overlooked species. The chance of a species being overlooked increased both with rarity, and the species richness of the area sampled. Where abundance was measured using metrics of cover and biomass, common species were overvalued, but when abundance was measured using frequency, common species were undervalued. In this study, logarithmic transformation of values provided a more reliable characterization of vegetation, than binarized or untransformed values. With the exception of species abundance, the number of species overlooked, quadrat species richness, and vegetation characterization were all affected by the experimental treatment. Our findings highlight the potential effects of error when conducting vegetation sampling and analyses of community dynamics. Due to these effects, we need to consider the reliability of conclusions drawn when assessing temporal changes in plant dynamics. Data transformation modifies the effect of sampling error in analyses of vegetation data.

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

<a href="/en/project/GA20-02901S" target="_blank" >GA20-02901S: Community diversity as a response and as a driver: Exploiting long-term experiments to address functional roles of diversity</a><br>

Continuities

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

Publication year

2020

Confidentiality

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

Name of the periodical

Acta Oecologica

ISSN

1146-609X

e-ISSN

—

Volume of the periodical

109

Issue of the periodical within the volume

NOV 2020

Country of publishing house

FR - FRANCE

Number of pages

10

Pages from-to

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UT code for WoS article

000592556800013

EID of the result in the Scopus database

2-s2.0-85094194120