Temporal-spatial variations of net ecosystem productivity in alpine area of southwestern China

Rui, 庞瑞 Pang; Fengxue, 顾峰雪 Gu; Yuandong, 张远东 Zhang; Zhenhong, 侯振宏 Hou; Shirong, 刘世荣 Liu

doi:10.5846/stxb201204090496

Cited by 7 publications

(3 citation statements)

References 4 publications

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“…However, precipitation promoted an increase in NEP in Anhui, and air temperature had no significant effect on it. The results are consistent with the results of some other scholars [15,40,41], namely that the NEP of vegetation is negatively correlated with annual mean temperature in a small region, especially in a region with little human disturbance. This data indirectly indicates that the vegetation ecosystem in the Yangtze River Delta region was also developing healthily while the cities were developing rapidly in the past 20 years.…”

Section: Discussionsupporting

confidence: 92%

Spatial-Temporal Changes of Carbon Source/Sink in Terrestrial Vegetation Ecosystem and Response to Meteorological Factors in Yangtze River Delta Region (China)

Zou

Chen

et al. 2022

Sustainability

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As an important part and the core link of a terrestrial ecosystem, terrestrial vegetation is the main means for human to regulate climate and mitigate the increase in atmospheric CO2 concentration. The Yangtze River Delta (YRD) region is an urban agglomeration with the strongest comprehensive strength among developing countries (China). In the context of global climate change, a rapid, comprehensive, and detailed understanding of the spatio-temporal characteristics and variation tendency of the net ecosystem productivity (NEP) of vegetation and its response to climate during the rapid development of the YRD region is important for protecting ecological land, strengthening land management, and optimizing urban planning. The monthly mean temperature and rainfall data from 63 meteorological stations, the MODIS net primary productivity product, and a land cover product in the YRD region were used to estimate the NEP from 2000 to 2019 based on the soil respiration model, and the correlation between NEP and meteorological factors (such as temperature and rainfall) was analyzed. The results showed that: (1) From 2000 to 2019, the carbon sink area was much larger than the carbon source area in terrestrial vegetation in the Yangtze River Delta, the mean NEP of the vegetation ecosystem in the past 20 years was 253.2 g C·m−2·a−1, and the spatial distribution presented a trend that was higher in the south and lower in the north, higher in the east and lower in the west, and that gradually increased from northwest to southeast; moreover, the NEP of mountain areas was generally higher than that of river courses and urban surroundings. The interannual fluctuation of NEP was small, but presented a slightly increasing trend, and the interannual variation of NEP was significantly correlated with the maximum NEP in this region. (2) The carbon sink capacity of different vegetation cover types was (from strong to weak): forestlands > grasslands > wetlands ≈ croplands. (3) The area with the NEP change rate (θslope) > 0 accounted for 69.0%; however, there was certain spatial difference, the proportions of the areas with θslope < 0 were (from large to small) 14.50% (Zhejiang Province, China), 9.10% (Anhui Province, China), 6.65% (Jiangsu Province, China), and 0.79% (Shanghai, China). In terms of the individual changes of these provinces and municipalities, Shanghai > Zhejiang Province > Jiangsu Province ≈ Anhui Province. (4) There was a correlation between NEP and the annual mean temperature and annual precipitation in some regions.

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Section: Discussionsupporting

confidence: 92%

Spatial-Temporal Changes of Carbon Source/Sink in Terrestrial Vegetation Ecosystem and Response to Meteorological Factors in Yangtze River Delta Region (China)

Zou

Chen

et al. 2022

Sustainability

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“…The strong carbon sink function of broadleaf forest is also suggested by existing literature [63]. In addition, the amount of carbon sink of forest is much higher than agricultural crops and grassland [64,65]. The NEP is an important indicator of carbon sequestration by a region's vegetation.…”

Section: Comparative Analysis Of the Yrb's Diurnal Asymmetric Warmingmentioning

confidence: 80%

Spatial Responses of Net Ecosystem Productivity of the Yellow River Basin under Diurnal Asymmetric Warming

Zhang

Jing

et al. 2018

Sustainability

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The net ecosystem productivity (NEP) of drainage basins plays an important role in maintaining the carbon balance of those ecosystems. In this study, the modified CASA (Carnegie Ames Stanford Approach) model and a soil microbial respiration model were used to estimate net primary productivity (NPP) and NEP of the Yellow River Basin’s (YRB) vegetation in the terrestrial ecosystem (excluding rivers, floodplain lakes and other freshwater ecosystems) from 1982 to 2015. After analyzing the spatiotemporal variations in the NEP using slope analysis, the coefficient of variation, and the Hurst exponent, precipitation was identified as the main factor limiting vegetation growth in the YRB. Hence, precipitation was treated as the control variable and a second-order partial correlation method was used to determine the correlation between diurnal asymmetric warming and the YRB’s NEP. The results indicate that: (i) diurnal asymmetric warming occurred in the YRB from 1982 to 2015, with nighttime warming (Tmin) being 1.50 times that of daytime warming (Tmax). There is a significant correlation between variations in NPP and diurnal warming; (ii) the YRB’s NEP are characterized by upward fluctuations in terms of temporal variations, large differences between the various vegetation types, high values in the western and southeastern regions but low values in the northern region in terms of spatial distribution, overall relative stability in the YRB’s vegetation cover, and changes in the same direction being more dominant than those in the opposite direction (although the former is not sustained); and (iii) positive correlations between the NEP and nighttime and daytime warming are approximately 48.37% and 67.51% for the YRB, respectively, with variations in nighttime temperatures having more extensive impacts on vegetation cover.

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“…Theoretical studies of NPP have mainly focused on the improvement of estimation methods [4,5,6,7]. On the other hand, empirical studies have primarily focused on the spatial and temporal patterns and changes in NPP [8,9,10,11], the factors that affect these changes [12,13,14,15,16], the responses to climate change [14,17], and predictions of future trends [18]. Wang et al [19] studied the spatial–temporal variations and factors that affect the NPP of vegetation and concluded that NPP is significantly affected by rainfall and the increase in urbanization.…”

Section: Introductionmentioning

confidence: 99%

The Response of Net Primary Production to Climate Change: A Case Study in the 400 mm Annual Precipitation Fluctuation Zone in China

Qin

2019

IJERPH

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The regions in China that intersect the 400 mm annual precipitation line are especially ecologically sensitive and extremely vulnerable to anthropogenic activities. However, in the context of climate change, the response of vegetation Net Primary Production (NPP) in this region has not been scientifically studied in depth. NPP suffers from the comprehensive effect of multiple climatic factors, and how to eliminate the effect of interfering variables in the correlation analysis of NPP and target variables (temperature or precipitation) is the major challenge in the study of NPP influencing factors. The correlation coefficient between NPP and target variable was calculated by ignoring other variables that also had a large impact on NPP. This increased the uncertainty of research results. Therefore, in this study, the second-order partial correlation analysis method was used to analyze the correlation between NPP and target variables by controlling other variables. This can effectively decrease the uncertainty of analysis results. In this paper, the univariate linear regression, coefficient of variation, and Hurst index estimation were used to study the spatial and temporal variations in NPP and analyze whether the NPP seasonal and annual variability will persist into the future. The results show the following: (i) The spatial distribution of NPP correlated with precipitation and had a gradually decreasing trend from southeast to northwest. From 2000 to 2015, the NPP in the study area had a general upward trend, with a small variation in its range. (ii) Areas with negative partial correlation coefficients between NPP and precipitation are consistent with the areas with more abundant water resources. The partial correlation coefficient between the NPP and the Land Surface Temperature (LST) was positive for 52.64% of the total study area. Finally, the prediction of the persistence of NPP variation into the future showed significant differences on varying time scales. On an annual scale, NPP was predicted to persist for 46% of the study area. On a seasonal scale, NPP in autumn was predicted to account for 49.92%, followed by spring (25.67%), summer (13.40%), and winter (6.75%).

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Temporal-spatial variations of net ecosystem productivity in alpine area of southwestern China

Cited by 7 publications

References 4 publications

Spatial-Temporal Changes of Carbon Source/Sink in Terrestrial Vegetation Ecosystem and Response to Meteorological Factors in Yangtze River Delta Region (China)

Spatial-Temporal Changes of Carbon Source/Sink in Terrestrial Vegetation Ecosystem and Response to Meteorological Factors in Yangtze River Delta Region (China)

Spatial Responses of Net Ecosystem Productivity of the Yellow River Basin under Diurnal Asymmetric Warming

The Response of Net Primary Production to Climate Change: A Case Study in the 400 mm Annual Precipitation Fluctuation Zone in China

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