Minimum temperature during the growing season limits the radial growth of timberline Schrenk spruce (P. schrenkiana)

Qin, Li; Liu, Kexiang; Shang, Huaming; Zhang, Tongwen; Yu, Shulong; Zhang, Ruibo

doi:10.1016/j.agrformet.2022.109004

Cited by 13 publications

(4 citation statements)

References 54 publications

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“…Temperature controls the allocation of biomass to individual trees by influencing the respiration rate and nutrient accumulation, as well as the length of the growing season [62,63]. With global warming, drought stress caused by increased temperatures hinders tree growth, an argument that has been confirmed in spruce forests [60,64]. Comparing the effects of both temperature and precipitation on AGB, various studies have indicated that moisture is a critical factor limiting the growth of spruce forests [65][66][67].…”

Section: Accuracy and Uncertainty Analysis Of Agb Estimationmentioning

confidence: 99%

“…The third AGB class is much more tolerant to altitude than the first and second AGB classes. At high altitudes, the environmental tolerance of plants is mainly manifested in tolerance to minimum temperatures during the growing season, whereas at lower altitudes plants are mainly affected by drought stress, which is more pronounced under global warming; therefore, mid-altitude areas are more suitable for spruce stands with high biomass, as Figure 3 clearly shows [59,60].…”

Section: Accuracy and Uncertainty Analysis Of Agb Estimationmentioning

confidence: 99%

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Application of MaxEnt Model in Biomass Estimation: An Example of Spruce Forest in the Tianshan Mountains of the Central-Western Part of Xinjiang, China

Xue

Wang

2023

Forests

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Accurately estimating the above-ground biomass (AGB) of spruce forests and analyzing their spatial patterns are critical for quantifying forest carbon stocks and assessing regional climate conditions in China’s drylands, with significant implications for the sustainable management and conservation of forest ecosystems in the Tianshan Mountains. The K-Means clustering algorithm was used to divide 144 measured AGB samples into four AGB classes, combined with remote sensing data from Landsat products, 19 bioclimatic variables, 3 topographical variables, and 3 soil variables to generate probability distributions of four AGB classes using the MaxEnt model. Finally, the spatial distribution of AGB was mapped using the mathematical formulae available in the GIS software. Results indicate that (1) the area under the receiver operating characteristic curve (AUC-ROC) of the AGB models for all classes exceeded 0.8, indicating satisfactory model accuracy; (2) the dominant factors affecting the distribution of different AGB classes varied. The primary dominant factors for the first–fourth AGB classes model were altitude (20.4%), precipitation of warmest quarter (Bio18, 15.7%), annual mean temperature (Bio1, 50.5%), and red band (Band4, 26.7%), respectively, and the response curves indicated that the third AGB model was more tolerant of elevation than the first and second AGB classes; (3) the AGB has a spatial distribution pattern of being higher in the west and low in the east, with a “single-peaked” pattern in terms of latitude, and the average AGB of pixels was 680.92 t·hm−2; (4) the correlation coefficient between measured and predicted AGB is 0.613 (p < 0.05), with the average uncertainty of AGB estimation at 39.32%. This study provides valuable insights into the spatial patterns and drivers of AGB in spruce forests in the Tianshan Mountains, which can inform effective forest management and conservation strategies.

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Section: Accuracy and Uncertainty Analysis Of Agb Estimationmentioning

confidence: 99%

Section: Accuracy and Uncertainty Analysis Of Agb Estimationmentioning

confidence: 99%

Application of MaxEnt Model in Biomass Estimation: An Example of Spruce Forest in the Tianshan Mountains of the Central-Western Part of Xinjiang, China

Xue

Wang

2023

Forests

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“…In the southern Canadian Rockies, research on Picea engelmanni Parry and Abies lasiocarpa (Hook.) identified non-monotonic relationships between radial growth and climate predictors that may be indicators of ecological thresholds [61]. A study of arid Central Asia found that temperature had a stable limiting effect on radial growth at the treeline over 60 years, but that the effect of precipitation on tree growth has increased due to rapid warming [62].…”

Section: Characterization Of the Temporal And Spatial Gradient Of Lar...mentioning

confidence: 99%

Expansion of Treeline in North China and Its Relationship with Altitude Sensitivity Gradient of Larix gmelinii

Li,

Liu,

Henderson

et al. 2023

Forests

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As the climate has warmed, alpine treelines have moved to higher altitudes and the responses of tree growth to different climate factors have changed. We collected dendrochronologies of Larix gmelinii at different elevations on the Dabai Mountain, the highest peak in northeastern China’s Greater Khingan range, to measure the sensitivity and stability of radial growth over time. We found that the treeline has moved upslope since 1970. From the mid-1980s, radial growth increased in the treeline ecotone but decreased in the subtimberline forest, an example of “growth divergence” under warming conditions: increases in the previous October’s maximum temperatures promoted growth at higher altitudes but inhibited it at lower altitudes. The treeline ecotone appears to be more sensitive to climate change, with the effects on tree growth of different climate indicators varying by altitude in linear or U-shaped relationships. As warming continues, the management of boreal forests needs to consider the changing potential for tree growth and carbon sequestration capacity in relation to changing site conditions.

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“…Such asymmetrical warming affects the carbon assimilation and energy consumption of vegetation (Peng et al, 2013; Xia et al, 2018). The mean minimum temperature is a key factor affecting the plant biochemical processes and physiological activities that are important for tree growth (Korner, 2003; Qin et al, 2022). Therefore, it is important to study the minimum temperature in the Changbai Mountains.…”

Section: Introductionmentioning

confidence: 99%

A 219‐year reconstruction of April–June mean minimum temperature from the tree‐ring earlywood density on the Changbai Mountains, China

Abudureheman,

Zhang,

Wang

et al. 2023

Intl Journal of Climatology

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Using mean earlywood density data from Pinus koraiensis cores, we reconstructed the April–June mean minimum temperature from 1797 to 2015 for the Changbai Mountains. The reconstruction explained 52.6% of the actual mean minimum temperature variance during 1901–2015. After smoothing with an 11‐year moving average, we identified three major cold periods (1797–1875, 1881–1899, and 1903–1946) and three major warm periods (1876–1880, 1900–1902, and 1947–2015) in the reconstructed series. Spatial correlation showed that the reconstruction contained climatic signals for a large area including most of northeast China, especially the Bohai Rim region and the eastern side of the Mongolian Plateau. A comparison between the newly reconstructed temperature series for the surrounding areas reveals similar variations, particularly in the warming trend during the second half of the 20th century. The driving factors of the mean minimum temperature were influenced mainly by the interaction of solar activity and large‐scale atmospheric‐oceanic variability. The reconstructed series provides a basis for understanding past climate change in the Changbai Mountains and for predicting future climate change trends in Northeast China.

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Minimum temperature during the growing season limits the radial growth of timberline Schrenk spruce (P. schrenkiana)

Cited by 13 publications

References 54 publications

Application of MaxEnt Model in Biomass Estimation: An Example of Spruce Forest in the Tianshan Mountains of the Central-Western Part of Xinjiang, China

Application of MaxEnt Model in Biomass Estimation: An Example of Spruce Forest in the Tianshan Mountains of the Central-Western Part of Xinjiang, China

Expansion of Treeline in North China and Its Relationship with Altitude Sensitivity Gradient of Larix gmelinii

A 219‐year reconstruction of April–June mean minimum temperature from the tree‐ring earlywood density on the Changbai Mountains, China

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