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240410s2024 xx |||||o 00| ||eng c |
| 024 |
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|a 10.1111/nph.19754
|2 doi
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|a pubmed24n1390.xml
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|e rakwb
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|a eng
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| 100 |
1 |
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|a Mujica, María Isabel
|e verfasserin
|4 aut
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| 245 |
1 |
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|a Integrating perspectives in developing mycorrhizal trait databases
|b a call for inclusive and collaborative continental efforts
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|c 2024
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| 336 |
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
|b c
|2 rdamedia
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|a ƒa Online-Ressource
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|2 rdacarrier
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|a Date Completed 25.04.2024
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|a Date Revised 26.04.2024
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|a published: Print-Electronic
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|a Citation Status MEDLINE
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|a © 2024 The Authors. New Phytologist © 2024 New Phytologist Foundation.
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|a Global assessments of mycorrhizal symbiosis present large sampling gaps in rich biodiversity regions. Filling these gaps is necessary to build large-scale, unbiased mycorrhizal databases to obtain reliable analyses and prevent misleading generalizations. Underrepresented regions in mycorrhizal research are mainly in Africa, Asia, and South America. Despite the high biodiversity and endemism in these regions, many groups of organisms remain understudied, especially mycorrhizal fungi. In this Viewpoint, we emphasize the importance of inclusive and collaborative continental efforts in integrating perspectives for comprehensive trait database development and propose a conceptual framework that can help build large mycorrhizal databases in underrepresented regions. Based on the four Vs of big data (volume, variety, veracity, and velocity), we identify the main challenges of constructing a large mycorrhizal dataset and propose solutions for each challenge. We share our collaborative methodology, which involves employing open calls and working groups to engage all mycorrhizal researchers in the region to build a South American Mycorrhizal Database. By fostering interdisciplinary collaborations and embracing a continental-scale approach, we can create robust mycorrhizal trait databases that provide valuable insights into the evolution, ecology, and functioning of mycorrhizal associations, reducing the geographical biases that are so common in large-scale ecological studies
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|a Journal Article
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| 650 |
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|a Research Support, Non-U.S. Gov't
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| 650 |
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|a Research Support, U.S. Gov't, Non-P.H.S.
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| 650 |
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4 |
|a South America
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| 650 |
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|a big data
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| 650 |
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|a collaborative database
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| 650 |
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|a four Vs
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| 650 |
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|a geographical biases
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| 650 |
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4 |
|a global south
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| 650 |
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4 |
|a mycorrhiza database
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| 700 |
1 |
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|a Silva-Flores, Patricia
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Bueno, C Guillermo
|e verfasserin
|4 aut
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| 700 |
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|a Duchicela, Jessica
|e verfasserin
|4 aut
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| 773 |
0 |
8 |
|i Enthalten in
|t The New phytologist
|d 1979
|g 242(2024), 4 vom: 23. Apr., Seite 1436-1440
|w (DE-627)NLM09818248X
|x 1469-8137
|7 nnns
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| 773 |
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|g volume:242
|g year:2024
|g number:4
|g day:23
|g month:04
|g pages:1436-1440
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| 856 |
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|u http://dx.doi.org/10.1111/nph.19754
|3 Volltext
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