Global root traits (GRooT) database

Abstract

Motivation Trait data are fundamental to the quantitative description of plant form and function. Although root traits capture key dimensions related to plant responses to changing environmental conditions and effects on ecosystem processes, they have rarely been included in large‐scale comparative studies and global models. For instance, root traits remain absent from nearly all studies that define the global spectrum of plant form and function. Thus, to overcome conceptual and methodological roadblocks preventing a widespread integration of root trait data into large‐scale analyses we created the Global Root Trait (GRooT) Database. GRooT provides ready‐to‐use data by combining the expertise of root ecologists with data mobilization and curation. Specifically, we (a) determined a set of core root traits relevant to the description of plant form and function based on an assessment by experts, (b) maximized species coverage through data standardization within and among traits, and (c) implemented data quality checks. Main types of variables contained GRooT contains 114,222 trait records on 38 continuous root traits. Spatial location and grain Global coverage with data from arid, continental, polar, temperate and tropical biomes. Data on root traits were derived from experimental studies and field studies. Time period and grain Data were recorded between 1911 and 2019. Major taxa and level of measurement GRooT includes root trait data for which taxonomic information is available. Trait records vary in their taxonomic resolution, with subspecies or varieties being the highest and genera the lowest taxonomic resolution available. It contains information for 184 subspecies or varieties, 6,214 species, 1,967 genera and 254 families. Owing to variation in data sources, trait records in the database include both individual observations and mean values. Software format GRooT includes two csv files. A GitHub repository contains the csv files and a script in R to query the database.

Root trait variation of seed plants from China and the primary drivers

“…Our study presented an in-depth analysis of the variability and influencing factors of six traits of first-order roots based on the largest sample size of seed plant species in China to date. The mean and SD values of RD were lower in the present study than in global patterns (Guerrero-Ramírez et al, 2021;Iversen et al, 2017) (Figure 6a).…”

RhizoVision Explorer: open-source software for root image analysis and measurement standardization

“…Volume is an important measurement, typically used as a proxy for root mass and also for the calculation of root tissue density. These measures relying on volume that exist in the literature and in public root databases like FRED ( Iversen et al 2017 ) or GRoot ( Guerrero-Ramírez et al 2021 ) should be carefully evaluated before use.…”

Crop Domestication, Root Trait Syndromes, and Soil Nutrient Acquisition in Organic Agroecosystems: A Systematic Review

“…Older crop varietals may be more able to form these symbiotic relationships regardless of nutrient availability, while modern varietals only benefit FIGURE 2 | Bivariate relationships among root traits [root diameter and specific root length (A) and root N and specific root length (B)] of crops. In order to visualize the extent of root trait trade-offs, crops and their wild relatives are included, as well as trait relationships observed across the whole GRooT dataset (Guerrero-Ramirez et al, 2021).…”