MycoDB, a global database of plant response to mycorrhizal fungi

V. Bala Chaudhary, Megan A. Rúa, Anita Antoninka, James D. Bever, Jeffery Cannon, Ashley Craig, Jessica Duchicela, Alicia Frame, Monique Gardes, Catherine Gehring, Michelle Ha, Miranda Hart, Jacob Hopkins, Baoming Ji, Nancy Collins Johnson, Wittaya Kaonongbua, Justine Karst, Roger T. Koide, Louis J. Lamit, James MeadowBrook G. Milligan, John C. Moore, Thomas H. Pendergast Iv, Bridget Piculell, Blake Ramsby, Suzanne Simard, Shubha Shrestha, James Umbanhowar, Wolfgang Viechtbauer, Lawrence Walters, Gail W.T. Wilson, Peter C. Zee, Jason D. Hoeksema

Research output: Contribution to journalArticlepeer-review

78 Scopus citations

Abstract

Plants form belowground associations with mycorrhizal fungi in one of the most common symbioses on Earth. However, few large-scale generalizations exist for the structure and function of mycorrhizal symbioses, as the nature of this relationship varies from mutualistic to parasitic and is largely context-dependent. We announce the public release of MycoDB, a database of 4,010 studies (from 438 unique publications) to aid in multi-factor meta-analyses elucidating the ecological and evolutionary context in which mycorrhizal fungi alter plant productivity. Over 10 years with nearly 80 collaborators, we compiled data on the response of plant biomass to mycorrhizal fungal inoculation, including meta-analysis metrics and 24 additional explanatory variables that describe the biotic and abiotic context of each study. We also include phylogenetic trees for all plants and fungi in the database. To our knowledge, MycoDB is the largest ecological meta-analysis database. We aim to share these data to highlight significant gaps in mycorrhizal research and encourage synthesis to explore the ecological and evolutionary generalities that govern mycorrhizal functioning in ecosystems.

Original languageEnglish (US)
Article number160028
JournalScientific data
Volume3
DOIs
StatePublished - May 10 2016
Externally publishedYes

ASJC Scopus subject areas

  • Statistics and Probability
  • Information Systems
  • Education
  • Computer Science Applications
  • Statistics, Probability and Uncertainty
  • Library and Information Sciences

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