Carbon exchanges and their responses to temperature and precipitation in forest ecosystems in Yunnan, Southwest China

Fei, Xuehai; Song, Qinghai; Zhang, Yiping; Liu, Yuntong; Sha, Liqing; Yu, Guirui; Zhang, Leiming; Duan, Changqun; Deng, Yun; Wu, Chuansheng; Lü, Zifeng; Luo, Kang; Chen, Aiguo; Xu, Kun; Liu, Weiwei; Huang, Hua; Jin, Yang; Zhou, Ruiwu; Li, Jing; Lin, Yiming; Zhou, Liguo; Fu, Yane; Bai, Xiaolong; Tang, Xianhui; Gao, Jinbo; Zhou, Wenjun; Grace, John

doi:10.1016/j.scitotenv.2017.10.239

Cited by 62 publications

(45 citation statements)

References 125 publications

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“…The precipitation showed a significant increasing trend in NWC and the TP (Table ), which will decrease drought in those regions. In NC and western SC, the precipitation showed a decreasing trend (Fei et al, ), which may aggravate drought. Larger sensitive coefficients for drought were observed in NWC, the TP and NC for temperature, and stations in SC show small coefficients (Figure b).…”

Section: Resultsmentioning

confidence: 99%

Assessment of candidate distributions for SPI/SPEI and sensitivity of drought to climatic variables in China

Wang

Chen

Pan

et al. 2019

Intl Journal of Climatology

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Drought occurs more frequently in the context of climate change and threatens water security worldwide. An appropriate fitting distribution is crucial for accurately identifying drought using drought indices. Here, seven two-parameter distributions (Gamma, Gumbel, Logistic, Log-Logistic, Log-normal, Normal, and Weibull) and four distributions (general logistic, generalized extreme value, Normal, and Pearson Type III) are applied to calculate the standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI), respectively, to choose the most appropriate fit for the 541 stations in China. The results show that, in most cases, Gamma and general logistic were the best distributions for SPI and SPEI, respectively. Nevertheless, we noted that Pearson Type III and generalized extreme value also fit the SPEI series well, indicating the importance of distribution fitting assessment for various regions. The annual and seasonal drought evolutions across China were clarified, with drought decreasing significantly in western Northwest China (annually and each season), northern North China (spring and winter), the Tibetan Plateau (spring), and the lower reaches of the Yangtze River (winter) and increasing mainly in South China (spring) and western South China (summer and autumn). The intensity, duration and severity of light, moderate, and severe drought were also detected; the results suggest that drought in China is mainly concentrated around the changes in light and moderate drought. Additionally, we assessed the sensitivity of drought evolution to various meteorological variables. The most sensitive variable in South China, North China and the Tibetan Plateau is precipitation, followed by wind speed, temperature, relative humidity, and sunshine duration; in Northwest China, the order is wind speed, precipitation, temperature, relative humidity, and sunshine duration. Furthermore, the correlation results also indicate that the drought evolution is affected by the multivariate ENSO index, while the influencing characteristics are different in various seasons and regions. The results in this paper contribute to drought mitigation and the effective utilization of water resources in China.

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Section: Resultsmentioning

confidence: 99%

Assessment of candidate distributions for SPI/SPEI and sensitivity of drought to climatic variables in China

Wang

Chen

Pan

et al. 2019

Intl Journal of Climatology

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“…According to the SPEI ranking criteria , three classifications are defined: (1) SPEI < 0 (mild drought), (2) SPEI < −1 (moderate drought), and (3) SPEI < −1.5 (severe drought). In this study, our drought frequency has been defined as the ratio between the total month of drought's occurrences (Fei et al, 2018). The carbon flux stations are plotted in Figure 1 as green triangles.…”

Section: The Characteristics Of Droughts In Chinamentioning

confidence: 99%

“…Furthermore, Zhao and Running (2010) have reported that a total loss of 0.55 PgC/yr global NPP between 2000 and 2009 could be explained by droughts, occurred in the Southern Hemisphere. Compared with forest ecosystems, grass ecosystems are more sensitive to droughts (e.g., Lei et al, 2015;Fei et al, 2018). In addition, long-lasting and severe droughts can also significantly lower the regional NPP in semi-humid and humid areas (Vicente−Serrano et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Responses of the Terrestrial Ecosystem Productivity to Droughts in China

Wang

Liu

2020

Front. Earth Sci.

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“…Продуктивність деревних рослин істотно залежить від ступеня функціонування їх структурних частин та від багатьох геофізичних факторів (Castañeda-Moya et al, 2013;Ding et al, 2016;Ellison et al, 2017;Fei et al, 2018;Lu et al, 2018).…”

Section: вступunclassified

Estimation of the leaf area index of the pine forest stands within Northern Steppe of Ukraine conditions

Lovynska¹,

Agrarian²,

Lakyda³

2018

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Assimilation part of forest ecosystems play an important role in the global carbon cycle and forming net-primary productivity. However, knowledge on leaf area index (LAI), that affect carbon fluxes is lacking, especially within territory of Steppe zone of Ukraine. We studied twenty Scots pine (Pinus sylvestris L.) plantations different age in pure and mixed stands to examine the changes in LAI. The method for determining samples mass and volume was to random select of needles from green fraction from different crown parts. The next step was in weighing and the volume determination of the samples by the xylometric method. Pine stands within temporary sample plots represent different age structure and function in the following types of forest condition: very dry (A 0) and dry (A 1) bir, dry (B 1), fresh (B 2) and moist (B 3) subir, dry (C 1), fresh (C 2) and moist (C 3) suhrud, rarely-in the hrud condition. The obtained results of model trees biometric parameters show their approximate values to the average indexes of the temporal sample plots on which they were selected. The variation of the weight of needle samples in fresh and completely dry states depending on the age of the model trees is analyzed. Parameters of the needle area and ratio of fresh and dry weight to the total surface area of needle samples is calculated. The average value of needle biomass in completely dry states and the needles surface area of the of needles on the study plots is defined. The calculated LAI of pine stands varies from 1.1 to 3.36 m²/m². The dependence of LAI on the model tree age is established. There is the increase of the trend line for young trees, stabilization and then decrease this parameter up to 90 years old is defined. The maximum LAI index is characterized for a pure 83-year-old pine plantation of pine, with I class bonitat, that grows under dry suhrud conditions. The minimum LAI is recorded for the mixed pine stand in age of 9 years, with III class bonitat, which function in dry hrud conditions. Calculation of LAI of Scots pine stands showed that it depends on the type of site conditions and stand age.

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Carbon exchanges and their responses to temperature and precipitation in forest ecosystems in Yunnan, Southwest China

Cited by 62 publications

References 125 publications

Assessment of candidate distributions for SPI/SPEI and sensitivity of drought to climatic variables in China

Assessment of candidate distributions for SPI/SPEI and sensitivity of drought to climatic variables in China

Responses of the Terrestrial Ecosystem Productivity to Droughts in China

Estimation of the leaf area index of the pine forest stands within Northern Steppe of Ukraine conditions

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