10.5061/DRYAD.KH0QH06
Zhao, Shoudong
Beijing Normal University
Pederson, Neil
Harvard University
D'Orangeville, Loïc
University of New Brunswick
Harvard University
HilleRisLambers, Janneke
University of Washington
Boose, Emery
Harvard University
Penone, Caterina
University of Bern
Bauer, Bruce
National Centers for Environmental Information
Jiang, Yuan
Beijing Normal University
Manzanedo, Rubén D.
Harvard University
University of Washington
Data from: The International Tree-Ring Data Bank (ITRDB) revisited: data
availability and global ecological representativity
Dryad
dataset
2018
Bias Analysis
Tree Ring Research
Data Accessibility
Big Data
ITRDB
Dendroecology
1000-2016 AD
2018-12-06T14:10:02Z
2018-12-06T14:10:02Z
en
https://doi.org/10.1111/jbi.13488
89735144 bytes
1
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
Aim: The International Tree-Ring Data Bank (ITRDB) is the most
comprehensive database of tree growth. To evaluate its usefulness and
improve its accessibility to the broad scientific community, we aimed to:
i) quantify its biases, ii) assess how well it represents global forests,
iii) develop tools to identify priority areas to improve its
representativity, and iv) make available the corrected database. Location:
Worldwide. Time period: Contributed datasets between 1974 and 2017. Major
taxa studied: Trees. Methods: We identified and corrected formatting
issues in all individual datasets of the ITRDB. We then calculated the
representativity of the ITRDB with respect to species, spatial coverage,
climatic regions, elevations, need for data update, climatic limitations
on growth, vascular plant diversity, and associated animal diversity. We
combined these metrics into a global Priority Sampling Index (PSI) to
highlight ways to improve ITRDB representativity. Results: Our refined
dataset provides access to a network of >52 million growth data
points worldwide. We found, however, that the database is dominated by
trees from forests with low diversity, in semi-arid climates, coniferous
species, and in western North America. Conifers represented 81% of the
ITRDB and even in well sampled areas, broadleaves were poorly represented.
Our PSI stressed the need to increase the database diversity in terms of
broadleaf species and identified poorly represented regions that require
scientific attention. Great gains will be made by increasing research and
data sharing in African, Asian, and South American forests. Main
conclusions: The extensive data and coverage of the ITRDB shows great
promise to address macroecological questions. To achieve this, however, we
have to overcome the significant gaps in the representativity of the
ITRDB. A strategic and organized group effort is required, and we hope the
tools and data provided here can guide the efforts to improve this
invaluable database.
Appendix S1: Corrected and harmonized datasetContent: - Cleaned datasets -
Conflictive dataset - Duplicated (removed) datasets - Sampling coordinates
- Error correction log - .rwl files metadataAppendix S1.zipITRDB-RscriptR
code used for analysis and PSI generation
Global