Integrating perspectives in developing mycorrhizal trait databases: a call for inclusive and collaborative...

Area of Science:

• Ecology
• Mycology
• Biodiversity Research

Background:

• Global mycorrhizal symbiosis assessments suffer from significant sampling biases in high-biodiversity regions.
• Underrepresented areas like Africa, Asia, and South America lack sufficient data on mycorrhizal fungi, hindering comprehensive analysis.
• High biodiversity and endemism in these regions underscore the need for focused research on understudied organisms, especially mycorrhizal fungi.

Purpose of the Study:

• To highlight the necessity of filling sampling gaps in mycorrhizal research for unbiased, large-scale databases.
• To propose a conceptual framework for building comprehensive mycorrhizal trait databases in underrepresented regions.
• To address challenges in constructing large mycorrhizal datasets using the four Vs of big data: volume, variety, veracity, and velocity.

Main Methods:

• Adopting a collaborative, continental-scale approach to integrate diverse perspectives.
• Utilizing open calls and working groups to engage regional mycorrhizal researchers.
• Developing a South American Mycorrhizal Database as a model for data collection.

Main Results:

• Identified key challenges in constructing large mycorrhizal datasets based on big data principles.
• Proposed actionable solutions to overcome data collection and integration hurdles.
• Demonstrated a collaborative methodology for building regional mycorrhizal databases.

Conclusions:

• Inclusive, collaborative continental efforts are essential for creating robust mycorrhizal trait databases.
• Addressing geographical biases in ecological studies requires comprehensive data from underrepresented regions.
• Enhanced mycorrhizal databases will provide critical insights into the evolution, ecology, and functioning of these vital symbioses.