Misdiagnosis of mycorrhizas and inappropriate recycling of data can lead to false conclusions.
Identifieur interne : 000752 ( Main/Corpus ); précédent : 000751; suivant : 000753Misdiagnosis of mycorrhizas and inappropriate recycling of data can lead to false conclusions.
Auteurs : Mark Brundrett ; Leho TedersooSource :
- The New phytologist [ 1469-8137 ] ; 2019.
English descriptors
- KwdEn :
- MESH :
- classification : Mycorrhizae.
- microbiology : Plants.
- physiology : Mycorrhizae.
- Data Accuracy, Databases, Factual.
Abstract
We draw attention to a worrying trend for the uncritical use of 'recycled' mycorrhizal data to compile host species lists that include obvious errors or undertake risky analyses that correlate mycorrhizal colonisation levels with environmental or physiological factors despite inherent limitations in datasets. We are not suggesting that all meta-studies are wrong, only that more care should be taken to resolve what can safely be done with recycled mycorrhizal data in the future. We also recommend that mycorrhizal species lists should be checked against standard references since the majority of EM hosts and NM plant belong to families that are well resolved. However, additional research is required in cases where plant families have multiple root types within genera or occur in habitats where mycorrhizal associations are often suppressed (see Brundrett & Tedersoo, 2018). We hope that the mycorrhizal science community will work together more closely in the future to develop and enforce standards for mycorrhizal diagnosis and to share carefully corrected datasets for realistic meta-studies.
DOI: 10.1111/nph.15440
PubMed: 30191568
Links to Exploration step
pubmed:30191568Le document en format XML
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<term>Plants (microbiology)</term>
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<front><div type="abstract" xml:lang="en">We draw attention to a worrying trend for the uncritical use of 'recycled' mycorrhizal data to compile host species lists that include obvious errors or undertake risky analyses that correlate mycorrhizal colonisation levels with environmental or physiological factors despite inherent limitations in datasets. We are not suggesting that all meta-studies are wrong, only that more care should be taken to resolve what can safely be done with recycled mycorrhizal data in the future. We also recommend that mycorrhizal species lists should be checked against standard references since the majority of EM hosts and NM plant belong to families that are well resolved. However, additional research is required in cases where plant families have multiple root types within genera or occur in habitats where mycorrhizal associations are often suppressed (see Brundrett & Tedersoo, 2018). We hope that the mycorrhizal science community will work together more closely in the future to develop and enforce standards for mycorrhizal diagnosis and to share carefully corrected datasets for realistic meta-studies.</div>
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<Abstract><AbstractText>We draw attention to a worrying trend for the uncritical use of 'recycled' mycorrhizal data to compile host species lists that include obvious errors or undertake risky analyses that correlate mycorrhizal colonisation levels with environmental or physiological factors despite inherent limitations in datasets. We are not suggesting that all meta-studies are wrong, only that more care should be taken to resolve what can safely be done with recycled mycorrhizal data in the future. We also recommend that mycorrhizal species lists should be checked against standard references since the majority of EM hosts and NM plant belong to families that are well resolved. However, additional research is required in cases where plant families have multiple root types within genera or occur in habitats where mycorrhizal associations are often suppressed (see Brundrett & Tedersoo, 2018). We hope that the mycorrhizal science community will work together more closely in the future to develop and enforce standards for mycorrhizal diagnosis and to share carefully corrected datasets for realistic meta-studies.</AbstractText>
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<Keyword MajorTopicYN="Y">diagnosis errors</Keyword>
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