Compensation effect of winter snow on larch growth in Northeast China

Li, Yuanqiao; Wu, Xiuchen; Huang, Yongmei; Li, Xiaoyan; Shi, Fangzhong; Zhao, Shoudong; Yang, Yuting; Tian, Yongchao; Wang, Pei; Zhang, Shulei; Zhang, Cicheng; Wang, Yang; Xu, Chongyang; Zhao, Ping

doi:10.1007/s10584-021-02998-1

Cited by 22 publications

(5 citation statements)

References 81 publications

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“…Wu et al [27] suggested that snow is an important driver of tree growth in regions where growing-season precipitation is limited. Li et al [34] also found that winter snow plays a crucial role in regulating tree growth during the subsequent growing season in regions that experience seasonal or even annual drought stress. These studies and our results show that winter snow has an important impact on the radial growth of trees in precipitation-limited regions.…”

Section: Discussionmentioning

confidence: 99%

The Spatially Inhomogeneous Influence of Snow on the Radial Growth of Schrenk Spruce (Picea schrenkiana Fisch. et Mey.) in the Ili-Balkhash Basin, Central Asia

Qin

Bolatov

Yuan

et al. 2022

Forests

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Snow has an important impact on forest ecosystems in mountainous areas. In this study, we developed 14 tree-ring-width chronologies of Schrenk spruce (Picea schrenkiana Fisch. et Mey.) for the Ili-Balkhash Basin (IBB), Central Asia. We analyzed the response of radial growth to temperature, precipitation and snow parameters. The results show that previous winter and current summer precipitation have an important influence on the radial growth of P. schrenkiana. Further, we find spatially inhomogeneous effects of snow on subsequent growing-season tree growth in IBB. The radial growth response of P. schrenkiana to snow shows a weak–strong–weak trend from west to east across the Ili-Balkhash Basin. This spatial difference is mainly related to precipitation, as snow has little effect on tree growth in regions that receive more precipitation. Thus, winter snow has an important influence on the radial growth of trees in regions that receive limited amounts of precipitation.

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Section: Discussionmentioning

confidence: 99%

The Spatially Inhomogeneous Influence of Snow on the Radial Growth of Schrenk Spruce (Picea schrenkiana Fisch. et Mey.) in the Ili-Balkhash Basin, Central Asia

Qin

Bolatov

Yuan

et al. 2022

Forests

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“…Studies also suggest that the climatic response of trees varies regionally, possibly reflecting different climatic limitations on tree growth across study areas [55]. Areas with less summer precipitation rely on winter precipitation for replenishment [57], while the negative response to winter precipitation in regions with abundant rainfall may reflect the indirect impact of excessive snow harming tree growth [58]. Additionally, snowfall is associated with a delayed onset of the growing season and reduced radial growth [59].…”

Section: Discussionmentioning

confidence: 99%

Improving the Site Index and Stand Basal Area Model of Picea asperata Mast. by Considering Climate Effects

Wang,

Feng,

Wang

et al. 2024

Forests

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The stand basal area, closely related to age, site quality, and stand density, is an important factor for predicting forest growth and yield. The accurate estimation of site quality is especially a key component in the stand basal area model. We utilized sample plots with Picea asperata Mast. as the dominant species in the multi-period National Forest Inventory (NFI) dataset to establish a site index (SI) model including climate effects through the difference form of theoretical growth equations and mixed-effects models. We combined the SI calculated from the SI model, stand age, and stand density index to construct a basal area growth model for Picea asperata Mast. stands. The results show that the Korf model is the best SI base model for Picea asperata Mast. The mean temperatures in summer and winter precipitation were used as the fixed parameters to construct a nonlinear model. Ultimately, elevation, origin, and region, as random effects, were incorporated into the mixed-effects model. The coefficients (R2) of determination of the base model, the nonlinear model including climate, and the nonlinear mixed-effects model are 0.869, 0.899, and 0.921, with root-mean-square errors (RMSEs) of 1.320, 1.315, and 1.301, respectively. Among the basal area models, the Richards model has higher precision. And the basal area model including an SI incorporating climatic factors had a higher determination coefficient (R2) of 0.918 than that of the model including an SI without considering climatic effects. The mixed-effects model incorporating climatic and topographic factors shows a better fitting performance of SI, resulting in a higher precision of the basal area model. This indicates that in the development of forest growth models, both biophysical and climatic factors should be comprehensively considered.

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“…Therefore, once the ecosystem warms up in spring, snowmelt water can infiltrate into soils, directly increasing plant growth by improving water availability and indirectly by enhancing microbial activity [78,81]. Secondly, extended snow cover can protect soils from extremely low temperatures and strong winds [82][83][84]. In our study area, the average temperature in winter (late October to March of the following year) is approximately −14 • C. Therefore, the thermal insulation function of snow is important, particularly early in the growing season.…”

Section: Snow Cover Duration Legacy On Vegetation Growthmentioning

confidence: 99%

Distance to a River Modifies Climate Legacy on Vegetation Growth in a Boreal Riparian Forest

Li,

Sun,

Zou

et al. 2023

Remote Sensing

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Inter-annual variability in growing season temperature and precipitation, together with snow coverage duration, determine vegetation growth in boreal ecosystems. However, little is known about the impact of concurrent and antecedent climate, particularly snow cover duration, on vegetation growth in a boreal riparian forest. Additionally, significant uncertainty exists regarding whether the distance to a river (as a proxy of groundwater availability) further modifies these climatic legacy effects on vegetation growth. To fill this knowledge gap, we quantified the responses of different vegetation types (shrub, deciduous coniferous and broadleaf forests) to concurrent and antecedent climate variables in a boreal riparian forest, and further determined the magnitude and duration of climate legacies in relation to distance to a river, using MODIS-derived NDVI time series with gridded climate data from 2001 to 2020. Results showed that higher temperature and precipitation and longer snow cover duration increased vegetation growth. For deciduous coniferous forests and broadleaf forests, the duration of temperature legacy was about one year, precipitation legacy about two years and snow cover duration legacy was 3 to 4 years. Further, distance to a river modified the concurrent and antecedent temperature and snow cover duration legacy effects on vegetation growth, but not that of precipitation. Specifically, temperature and snow cover duration legacies were shorter at the sites near a river compared to sites at greater distance to a river. Our research highlights the importance of snow cover duration on vegetation growth and that closeness to a river can buffer adverse climate impacts by shortening the strength and duration of climate legacies in a boreal riparian forest.

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Compensation effect of winter snow on larch growth in Northeast China

Cited by 22 publications

References 81 publications

The Spatially Inhomogeneous Influence of Snow on the Radial Growth of Schrenk Spruce (Picea schrenkiana Fisch. et Mey.) in the Ili-Balkhash Basin, Central Asia

The Spatially Inhomogeneous Influence of Snow on the Radial Growth of Schrenk Spruce (Picea schrenkiana Fisch. et Mey.) in the Ili-Balkhash Basin, Central Asia

Improving the Site Index and Stand Basal Area Model of Picea asperata Mast. by Considering Climate Effects

Distance to a River Modifies Climate Legacy on Vegetation Growth in a Boreal Riparian Forest

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