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Global warming alters Himalayan hemlock’s climate sensitivity and growth dynamics

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Abstract

Global warming may lead to increased tree growth but also reduced tree performance due to increased moisture stress. Under what conditions these conflicting responses occur remains uncertain, especially when growth is controlled by different climatic factors throughout the year. Here, we investigate the growth response of Tsuga dumosa, a Himalayan endemic tree species, to global climate change in unique old-growth forests that persist at around 3000 m elevation near Kanchenjunga, Nepal. Specifically, we are examining various growth parameters, including earlywood, adjusted latewood, maximum latewood density, and total basal area increment, to determine how different climatic factors influence growth dynamics during the year. First, we found that the response to climate change varied by season. Climate warming had contrasting effects on different components of tree growth. Higher temperatures during previous October and previous December and warming-induced moisture stress in April reduce earlywood and total annual increment. On the other hand, higher rainfall during June and July limits total tree ring width and adjusted latewood width, respectively. Second, warming is changing the sensitivity of tree growth to various climatic factors. Growth in the past two decades became more dependent on autumn conditions than on spring and summer conditions. Warming alleviates the cold limitation during the cool monsoon summer but reinforces the water deficit during autumn, winter, and pre-monsoon dry spring. Third, analysis of basal area increments, an indicator of aboveground biomass production, showed that accelerated warming in summer contributes to increased annual productivity. However, the growth reduction observed during warming spring and autumn months counteracts this effect. In conclusion, this study highlights the contrasting responses of Tsuga dumosa to climate warming in Himalayan montane forests. While accelerated warming makes the trees less sensitive to summer temperature limitations, warm autumns, dry springs, and less snowy winters become the main limiting factors for their growth. Understanding these complex and contrasting responses, as well as the sensitivity of different growth parameters, is essential for predicting the long-term impacts of climate change on mountain ecosystems.

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Data availability

The datasets generated from lab measurements can be provided in the future upon reasonable request to the corresponding author. CHELSAcruts temperature and precipitation time-series were retrieved from its official website (https://chelsa-climate.org/chelsacruts/).

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Acknowledgements

We thank Eva Návratová for tree ring measurement.

Funding

The study was financially supported by the Czech Science Foundation, Czech Republic (21–26883S), MSMT INTER-EXCELLENCE project, Czech Republic (LTAUSA18007), and the long-term research development project of the Czech Academy of Sciences, Czech Republic (RVO 67985939).

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Authors and Affiliations

  1. Institute of Botany of the Czech Academy of Sciences, Zámek 1, CZ-252 43, Průhonice, Czech Republic

    Samresh Rai, Jan Altman, Martin Kopecký, Vít Pejcha & Jiří Doležal

  2. Faculty of Science, University of South Bohemia, Branišovská 1645/31a, CZ-370 05, České Budějovice, Czech Republic

    Samresh Rai & Jiří Doležal

  3. Faculty of Forestry and Wood Sciences, Czech University of Life Sciences Prague, Kamýcká 129, CZ-165 21, Prague 6 - Suchdol, Czech Republic

    Jan Altman, Martin Kopecký & Miroslav Svoboda

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  1. Samresh Rai
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Contributions

JD, MK and MS designed the research and collected the field data. SR, JA and VP performed the lab measurements and statistical analyses. SR wrote the original draft. All authors contributed to the discussion and writing of the paper.

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Correspondence to Samresh Rai.

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Appendix

Appendix

See Figs. 6, 7, 8 and Table 2.

Fig. 6
figure 6

SSS and sample depth for T. dumosa RW, EW, LW, BAI, and MXD standard chronologies. SD1—sample depth for RW, EW, and LW; SD2—sample depth for BAI; SD3—sample depth for MXD

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Fig. 7
figure 7

Lead-lag (1-year) correlation coefficients between a TRW, b EW, c LWadj, and d MXD indices with CHELSAcruts monthly temperature and precipitation from previous year’s March to September

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Fig. 8
figure 8

Pearson’s correlation between MXD and 3-month averages of CHELSAcruts climate data. Correlations at 95% significance level are shaded dark

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Table 2 Pointers years of all chronologies
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Rai, S., Altman, J., Kopecký, M. et al. Global warming alters Himalayan hemlock’s climate sensitivity and growth dynamics. Clim Dyn 62, 2333–2347 (2024). https://doi.org/10.1007/s00382-023-07026-9

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