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Diel and seasonal stem growth responses to climatic variation are consistent across species in a subtropical tree community

2023/09/22 by Bo Zhou, Frank J. Sterck, Frank Sterck +3 · 25 citations
Earth and Planetary Sciences · Environmental Science · #Biology #Botany #Diel vertical migration #Ecology #Environmental science #Forest ecology and management #Montane ecology #Plant Water Relations and Carbon Dynamics #Productivity #Subtropics #Tree-ring climate responses #Tropical and subtropical moist broadleaf forests #Vapour Pressure Deficit

paper · pdf · doi:10.1111/nph.19275

published in New Phytologist 240(6), 2253-2264 (Wiley)

openalex publication_date 2023/09/22 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01

Abstract

Understanding how intra-annual stem growth responds to atmospheric and soil conditions is essential for assessing the effects of climate extremes on forest productivity. In species-poor forests, such understanding can be obtained by studying stem growth of the dominant species. Yet, in species-rich (sub-)tropical forests, it is unclear whether these responses are consistent among species. We monitored intra-annual stem growth with high-resolution dendrometers for 27 trees belonging to 14 species over 5 yr in a montane subtropical forest. We quantified diel and seasonal stem growth patterns, verified to what extent observed growth patterns coincide across species and analysed their main climatic drivers. We found very consistent intra-annual growth patterns across species. Species varied in the rate but little in the timing of growth. Diel growth patterns revealed that - across species - trees mainly grew before dawn when vapour pressure deficit (VPD) was low. Within the year, trees mainly grew between May and August driven by temperature and VPD, but not by soil moisture. Our study reveals highly consistent stem growth patterns and climatic drivers at community level. Further studies are needed to verify whether these results hold across climates and forests, and whether they can be scaled up to estimate forest productivity.

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