Evaluating functional diversity: Missing trait data and the importance of species abundance structure and data transformation

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985939%3A_____%2F16%3A00456840" target="_blank" >RIV/67985939:_____/16:00456840 - isvavai.cz</a>

Alternative codes found

RIV/60077344:_____/16:00456840 RIV/60076658:12310/16:43890829

Result on the web

<a href="http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0149270" target="_blank" >http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0149270</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1371/journal.pone.0149270" target="_blank" >10.1371/journal.pone.0149270</a>

Result language

angličtina

Original language name

Evaluating functional diversity: Missing trait data and the importance of species abundance structure and data transformation

Original language description

Functional diversity is a very important component of biodiversity that quantifies the difference in functional traits between organisms. However, functional diversity studies are often limited by the availability of trait data and functional diversity indices are very sensitive to missing data. The distribution of species abundance and trait data, and its transformation, may thus affect the accuracy of indices when data is incomplete. The transformation of the data used to calculate functional diversity indices was very often neglected by authors. Here we show how important the completeness and transformation of the data are. Using an existing approach, we simulated the effects of missing trait data by gradually removing data from a plant, an ant and a bird community dataset. We worked with datasets originating from completely surveyed 12, 59, and 8 plots and containing plant 62, and 297 and bird 238 species respectively. We ranked plots by functional diversity values calculated from full datasets and then from our increasingly incomplete datasets. We compared the ranking between the original and virtually reduced datasets to assess the accuracy of functional diversity indices when used on datasets with increasingly missing data. Finally, we tested the accuracy of functional diversity indices with and without data transformation, and the effect of missing trait data per plot or per the whole pool of species. Functional diversity indices became less accurate as the amount of missing data increased, with the loss of accuracy depending on the index. But, where transformation improved the normality of the trait data, functional diversity values from incomplete datasets were more accurate than before transformation. The distribution of data and its transformation are therefore as important as data completeness and can even mitigate the effect of missing data.

Czech name

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Czech description

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Type

J_x - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

CEP classification

EH - Ecology - communities

OECD FORD branch

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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

2016

Confidentiality

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

Name of the periodical

PLoS ONE

ISSN

1932-6203

e-ISSN

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Volume of the periodical

11

Issue of the periodical within the volume

2

Country of publishing house

US - UNITED STATES

Number of pages

17

Pages from-to

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UT code for WoS article

000371219000066

EID of the result in the Scopus database

2-s2.0-84960510984