DOI: 10.5061/dryad.31zcrjdtf
title: Hotter drought and trade-off between fast and slow growth strategies as major drivers of tree-ring growth variability of global conifers

description: We found: a) growth variability was mainly affected by warm-induced
 drought and increased at lower latitudes. Climate warming in winter could
 decrease growth variability, but this effect is by far not enough to
 offset the threat of hotter drought; b) there existed a trade-off between
 fast- and slow-growing (drought tolerance) strategies for global conifer
 species, and abiotic and stand factors affected growth variability via
 functional traits. Contrary to common conjecture, species with higher
 drought tolerance revealed higher growth variability due to their
 occupation of more xeric sites, and may also because higher investment in
 drought tolerance leads to less investment remaining for growth; c) older
 trees revealed higher growth variability due to their more conservative
 growth strategy, while at large scales taller trees showed lower growth
 variability due to occupying more productive sites; and d) moderate N
 deposition could reduce growth variability by leading conifers to adopt a
 more fast-growing strategy (e.g., in Asia), but long-term and excessive N
 deposition led to increased growth variability (e.g., in North America and
 Europe). Our results suggest that coniferous forests in water-limited
 regions should be more vulnerable to hotter drought, and the ‘fast-slow’
 growth strategies may be key in regulating the effects of various abiotic
 and stand factors on ecosystem stability. Moreover, future hotter drought
 and N deposition will severely threaten conifer growth, especially for old
 trees and conifers at lower latitudes.
description: Raw tree-ring widths data were extracted from the International
 Tree-Ring Data Bank (ITRDB) V.7.23
 (https://www1.ncdc.noaa.gov/pub/data/paleo/treering/) in October
 2021.  The monthly temperature, precipitation, and
 potential evapotranspiration during 1970-2010 were extracted for each
 tree-ring site based on its latitude and longitude, from the Climatic
 Research Unit (CRU) database (https://crudata.uea.ac.uk/cru/data/hrg/). N deposition data were obtained from the N Deposition Database (Ackerman<em> et al.</em> 2019; https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2018GB005990), which used the GEOS-Chem Chemical Transport Model to estimate total (wet and dry) inorganic N deposition globally at a spatial resolution of 2°×2.5°. For stand factors, the stand age of each chronology was calculated as the mean age for all tree rings used to build the chronology. This global canopy height map was estimated with new satellite LiDAR (light detecting and ranging) data, with a high accuracy and a very high spatial resolution of 10×10 m (Lang<em> et al.</em> 2022; arXiv:2204.08322).
description: ## GENERAL INFORMATION **1. Title of Dataset:** Hotter drought and
 trade-off between fast and slow growth strategies as major drivers of
 tree-ring growth variability of global conifers
 [https://doi.org/10.5061/dryad.31zcrjdt](https://doi.org/10.5061/dryad.31zcrjdt) **2. Author information:** First author: Xuemei Wang, Beijing Forestry University, China; [wxmbju@163.com;](mailto:wxmbju@163.c) Corresponding author: Xiangping Wang, Beijing Forestry University, China; [wangxiangpingbjfu@edu.cn;](mailto:wangxiangpingbjfu@edu.c) **3. Summary of the dataset:** We used global conifer (mainly from North America, Asia, and Europe) tree-ring records (123 species from 1,780 sites) from 1970–2010 to calculate growth variability and assess how climate factors and stand factors affect growth variability (coefficient of variation) ## Description of the data and file structure DATA-SPECIFIC INFORMATION FOR: database.xls 1\. Number of variables: 25 2\. Number of cases/rows: 2023 3\. Variable List: * ITRDB Code: abbreviation for plot from International Tree-Ring Data Bank (ITRDB) * Site: The country where the growth rings come from * Latitude: latitude of tree ring plot * Longitude: Longitude of tree ring plot * Elevation: Elevation of tree ring plot (m) * FirstYear: Start year of tree-ring chronology * LastYear: End year of tree-ring chronology * Famlity: family of species from tree-ring sites * Genus: genus of species from tree-ring sites * Species: species from tree-ring sites * P/PET: the ratio of precipitation to potential evapotranspiration * TMAX: maximum temperature (℃) * TMIN, minimum temperature (℃) * S_P/PET: the slope (annual changing rate) of P/PET * S_TMAX: the slope (annual changing rate) of TMAX (℃/yr) * S_TMIN: the slope (annual changing rate) of TMIN (℃/yr) * CV_P/PET: coefficient of variability for P/PET * CV_TMAX: coefficient of variability for TMAX * CV_TMIN: coefficient of variability for TMIN * N deposition, mean annual inorganic nitrogen deposition rate (Tg N/yr) * Stand age: mean age of tree-ting chronogy (yr) * Canopy height: height in tree-ring site (m) * MS: mean sensitivity * SD: standard deviation * CV: coefficient of variation 4\. Missing data codes: NA 5\. Specialized formats or other abbreviations used: None ## SHARING/ACCESS INFORMATION 1. Raw tree-ring widths data were extracted from the International Tree-Ring Data Bank (ITRDB) V.7.23 ([https://www1.ncdc.noaa.gov/pub/data/paleo/treering/)](https://www1.ncdc.noaa.gov/pub/data/paleo/treering/\)) 2. The monthly temperature, precipitation, and potential evapotranspiration during 1970-2010 were extracted from the Climatic Research Unit (CRU) database ([https://crudata.uea.ac.uk/cru/data/hrg/)](https://crudata.uea.ac.uk/cru/data/hrg/\)) 3. N deposition data were obtained from the N Deposition Database (Ackerman et al. 2019; [https://doi.org/10.1029/2018GB005990)](https://doi.org/10.1029/2018GB005990\)) which used the GEOS-Chem Chemical Transport Model to estimate total (wet and dry) inorganic N deposition globally at a spatial resolution of 2°×2.5°. 4. Canopy height maps are freely available from Lang et al. 2022 ([arXiv:2204.08322](https://arxiv.org/abs/2204.08322))