Snow dynamics influence tree growth by controlling soil temperature in mountain pine forests

Sanmiguel‐Vallelado, Alba; Camarero, J. Julio; Morán-Tejéda, Enrique; Gazol, Antonio; Colangelo, Michele; Alonso‐González, Esteban; López‐Moreno, Juan I.

doi:10.1016/j.agrformet.2020.108205

Cited by 27 publications

(8 citation statements)

References 64 publications

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“…Additionally, the pine in the Minusinsk forest was able to draw some moisture from deeper soil layers due to the flat terrain and proximity to a watercourse, whereas the slope location of the forest stands at the BID site prevented this from happening. Conifer growth can be influenced not only by air temperature, but also by soil warming at the start of the vegetative season [55,72]. As higher direct surface insolation and faster snowmelt on the sunlit slope can enhance soil warming in spring in the BID site, thawing of the root-inhabited soil layer at lower air temperature can possibly explain the lower minimum air temperature for tree growth obtained by VS-model parameterization for this site despite other temperature boundaries being identical.…”

Section: Process-based Tree Growth Simulation Model and Its Applicati...mentioning

confidence: 88%

Seasonal Growth of Pine Tree Rings: Comparison of Direct Observations and Simulation

Babushkina

Sitnikov

Upadhyay

et al. 2022

Forests

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Repetitive observations (direct measurements) of seasonal kinetics of xylogenesis and simulations (proxy data) with tree growth models are the two main approaches available to assess tree-ring growth and development. Both have drawbacks: short cover period for observations; limited accuracy of simulations depending on input data for models. We proposed an implementation of both approaches on the same trees to find ways for compensation. Cell numbers at subsequent xylogenesis stages were observed for Pinus sylvestris L. over five seasons in moisture-deficient habitats of Southern Siberia. The Vaganov–Shashkin model was parameterized for species and soil-landscape conditions to fit local tree-ring width chronologies (R = 0.56–0.73). Seasonal kinetics variables were then compared among themselves and with the simulated environmentally driven growth rate. The number of cells in the cambial and cell enlargement zone closely followed the curve of the 15-day moving average of the simulated growth rate (R = 0.56–0.87 at one site and R = 0.78–0.89 after shifting rate curve forward by 17–20 days at another site). The maximum number of cambium cells, which occurred within three weeks of the summer solstice, was found to be positively related with the number of tracheids in the complete tree ring (R2 = 0.12–0.75 for individual seasons and 0.49 for total dataset), making it a promising short-term forecast variable for tree radial growth and productivity.

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Section: Process-based Tree Growth Simulation Model and Its Applicati...mentioning

confidence: 88%

Seasonal Growth of Pine Tree Rings: Comparison of Direct Observations and Simulation

Babushkina

Sitnikov

Upadhyay

et al. 2022

Forests

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“…From the perspective of sensitivity, ASD in the Kaidu River and the Aksu River is more sensitive to SCAP in winter and in autumn, respectively (Table 4). A recent study suggests that heavy snow accumulation led to later snow loss, and thus delayed the onset of soil warming [31]. For example, in the Kaidu River, there is a significant negative correlation between SCAP in autumn and winter, and air temperature in autumn, with correlation coefficients of −0.51 (p < 0.05) (Table 5).…”

Section: Effects Of Scap In Four Seasons and Other Factors On Asdmentioning

confidence: 94%

Research on Sediment Discharge Variations and Driving Factors in the Tarim River Basin

Chen

Zhang

et al. 2022

Remote Sensing

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Sediment discharge is widely regarded as a critical indicator of soil and water loss. The Mann–Kendall (M-K) test was applied to analyze the trends of temperature, precipitation, annual runoff, annual sediment discharge (ASD), and snow cover area proportion (SCAP). Sensitivity coefficient and contribution rate were adopted to assess the sensitivity of ASD to driving factors, and the contribution of driving factors to ASD. The results showed: (1) ASD of the Kaidu River and the Aksu River originating from Tien Shan decreased at rates of 3.8503 × 107 kg per year (p < 0.01) and 47.198 × 107 kg per year, respectively, from 2001 to 2019. The ASD there was also found to be more sensitive to SCAP changes in autumn and winter, respectively. (2) ASD of the Yarkand River and the Yulong Kashgar River originating from the Karakoram Mountains increased at rates of 21.807 × 107 kg per year and 27.774 × 107 kg per year, respectively, during 2001–2019. The ASD there was determined to be more sensitive to annual runoff. (3) In terms of contribution rate, except for the Kaidu River, annual runoff of the other three rivers made the largest contribution. (4) In addition, the proportion of glacial-melt water, slope, glacierization and human activities are also possible factors affecting sediment discharge.

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“…At our experimental site, where the ground temperature remained near 0°C due to the thick snow cover and its insulation, the well-developed pioneer roots were observed (Appendix 3). It is thus possible that changes in the physical environment other than soil temperature, such as soil moisture conditions associated with snowmelt (Sanmiguel-Vallelado et al 2021), and finer-scale nutrient conditions (Pregitzer et al 2000) are relevant to spring root dynamics.…”

Section: Spring Dynamics Of Pioneer Rootsmentioning

confidence: 99%

“…The pattern of intra-species variation in phenology provides cues for predicting how organisms seasonally react to climate changes (Franks et al 2014). In trees, the intra-species variation in the development of above-ground phenotypes has been elucidated (Mediavilla & Escudero 2009, De Kort et al 2016, Noordermeer et al 2021), particularly under seasonal changes of environmental conditions (Fréchette et al 2020, Sanmiguel-Vallelado et al 2021). However, the body of studies on the intra-species variation in the below-ground dynamics is still growing yet (Wang et al 2018, Ma et al 2022), and little information is available regarding the root phenology (McCormack et al 2015, Liu et al 2022).…”

Section: Introductionmentioning

confidence: 99%

Spring growth variation in pioneer and fibrous roots inAbies sachalinensisseedlings from provenances with contrasting snow cover environments

Sugai

Ishizuka

Masumoto

et al. 2022

Preprint

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Root development of evergreen conifer trees shows the specific patterns under spring soil conditions and its patterns further varied between the early developing pioneer roots and the subsequently developing fibrous roots. However, few empirical studies have verified the intra-species variation in developmental patterns of these two root types. To elucidate the regional variation in morpho-anatomical development of these roots, we conducted a common garden trial of Abies sachalinensis, a representative boreal conifer species with local adaptation. Six-year-old seedlings derived from an eastern region (ER) with less snowfall and a northern region (NR) with abundant snowfall were grown in a common garden with snowfall equivalent to NR. Seedlings were directly dug up and root phenotypes were evaluated in both early spring immediately after snowmelt and late spring after one month has passed since the snow was melted. Principal component analysis with 32 phenotypes showed that the differences in provenance regions and sampling months were associated with the morphological traits of pioneer roots and anatomical traits of fibrous roots, respectively. Seedlings derived from NR demonstrated pioneer roots with relatively higher specific root length and specific root area but lower average diameter and fibrous roots with lower size of a parenchymal cell after snowmelt. Meanwhile, non-significant variations in seedlings derived from ER denoted a relatively stable root dynamics, which may be associated with the plastic responses to abundant snowfall. These regional intra-species variations of A. sachalinensis may be linked to provenance soil environments with contrasting snowfall conditions.

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Snow dynamics influence tree growth by controlling soil temperature in mountain pine forests

Cited by 27 publications

References 64 publications

Seasonal Growth of Pine Tree Rings: Comparison of Direct Observations and Simulation

Seasonal Growth of Pine Tree Rings: Comparison of Direct Observations and Simulation

Research on Sediment Discharge Variations and Driving Factors in the Tarim River Basin

Spring growth variation in pioneer and fibrous roots inAbies sachalinensisseedlings from provenances with contrasting snow cover environments

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