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

Kód výsledku v 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>

Nalezeny alternativní kódy

RIV/60077344:_____/20:00533773

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10618 - Ecology

Projekt

<a href="/cs/project/GA20-02901S" target="_blank" >GA20-02901S: Diverzita společenstva jako odpověď a jako determinant. Využití dlouhodobých experimentů k objasnění funkční role diverzity</a><br>

Návaznosti

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

Rok uplatnění

2020

Kód důvěrnosti údajů

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

Název periodika

Acta Oecologica

ISSN

1146-609X

e-ISSN

—

Svazek periodika

109

Číslo periodika v rámci svazku

NOV 2020

Stát vydavatele periodika

FR - Francouzská republika

Počet stran výsledku

10

Strana od-do

—

Kód UT WoS článku

000592556800013

EID výsledku v databázi Scopus

2-s2.0-85094194120