DOI: 10.5061/dryad.np5hqc05j
title: Seasonal climate variations drive decoupling between the duration and amount of xylem growth along a hydrothermal gradient in the southern Altai Mountains

description: Arid and semiarid forests are vulnerable to climate change. Whether rising
 temperatures would increase wood production by extending the growing
 season in these relatively dry forests remains unclear.  Here, we
 document a decoupling of duration versus the amount of wood production.
 Despite the prolonged duration of xylem cell production induced by
 warming, we did not observe a consistent increase in the amount of xylem
 growth, based on a two-year (2018-2019) monitoring of wood formation in
 Siberian spruce (Picea obovata Ledeb.) along a natural hydrothermal
 gradient in the southern Altai Mountains of central Asia.  The
 duration of cell production ranged from 43 to 93 days, with the total
 number of xylem cells between 37 and 185. Notably, the warmest Altai
 low-altitude site (AL) had the longest duration (82.6 ± 13.3 days) but the
 lowest number of xylem cells (63.88 ± 15.6 cells) in 2018, indicating a
 decoupling between growing season length and xylem growth. However, this
 decoupling weakened in 2019 when spring temperatures were cooler and
 summer precipitation was higher than in 2018.  Warmer spring
 temperatures can extend the duration of wood cell production by triggering
 an earlier onset of cambium activity. Additionally, sufficient summer
 precipitation provides the water necessary for turgor-driven cell division
 and expansion, enhancing the cell production rate, which plays a dominant
 role in determining wood growth in arid and semiarid forests. Thus, warmer
 spring temperatures may amplify the observed decoupling, whereas
 sufficient summer precipitation may narrow it.  Synthesis. This
 decoupling highlights the critical role of seasonal climates in regulating
 wood formation dynamics in arid and semiarid forests. With ongoing climate
 change, longer and warmer growing seasons may amplify the importance of
 water availability, further constraining forest growth and carbon
 sequestration when growing-season water conditions are unfavourable.
description: # Seasonal climate variations drive decoupling between the duration and
 amount of xylem growth along a hydrothermal gradient in the southern Altai
 Mountains Dataset DOI: [10.5061/dryad.np5hqc05j](10.5061/dryad.np5hqc05j)
 ## Description of the data and file structure ### Files and variables ####
 File: growth\_seasonal\_climate.csv **Description:** seasonal climates and
 xylem cell production ##### Variables * site: site code * year: study year
 * Tree: Tree ID * RCN.mean: the final total number of xylem cells produced
 by the end of the growing season (dimensionless count) * bE: beginning
 timing of cell enlargement (expressed as the day of the year) * cE:
 cessation timing of cell enlargement (expressed as the day of the year) *
 dE: duration of cell enlargement (days) * r90: mean cell production rate
 (cells/day) * Tmean_spring: spring temperature (degree Celsius) *
 P_spring: spring precipitation (mm) * Tmean_summer: summer
 temperature (degree Celsius) * P_summer: summer precipitation (mm) *
 Tmean_autumn: autumn temperature  (degree Celsius) * P_autumn: autumn
 precipitation (mm) * Tmean_winter: winter temperature (degree Celsius) *
 P_winter: winter precipitation (mm) #### File: Rcode.R
 **Description:** all statistical analyses presented in the main text ####
 File: seasonal\_climates.csv **Description:**  seasonal climate  #####
 Variables * site: site code * year: study year * season: four seasons *
 Tmean: mean temperature (degree Celsius) * Tmax: maximum
 temperature (degree Celsius) * Tmin: minimum temperature (degree Celsius)
 * P: precipitation (mm) #### File: weekly\_growth.csv
 **Description:** weekly cell increment and corresponding climates  #####
 Variables * Year: study year * Site: site code * DY: the day of the year *
 nT: the total number of xylem cells  (dimensionless count) * Week_Growth:
 weekly cell production  (dimensionless count) * Tmean_p7: average 7-day
 temperature prior to each sampling date (degree Celsius) * Psum_p7: summed
 7-day precipitation prior to each sampling date (mm) ## Code/software R
 programming *version 4.4.1 (2024-06-14)* ## Access information Other
 publicly accessible locations of the data: * n/a Data was derived from the
 following sources: * n/a