Elevational differences in the net primary productivity response to climate constraints in a dryland mountain ecosystem of northwestern China

Xu, Haojie; Wang, Xinping

doi:10.1002/ldr.3587

Cited by 39 publications

(13 citation statements)

References 75 publications

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“…We also found that an increase to decrease trend of NPP occurred in the southern part of Qinghai Province (Figure 2c), which is different with the monotonic increase trend reported by Peng, Liu, Liu, Wu, and Han (2012). The trend reversal from increase to decrease in the southern part of Qinghai Province was related to the transition of climate conditions from warm–wet to warm–dry and the heavy grazing (Jiang, Li, Shen, & Chen, 2012; Wang, 2003; Xu, Zhao, & Wang, 2020). These results indicated that the shifted trends, including decrease to increase and increase to decrease, were widely distributed in arid and semiarid areas, which was rarely reported by previous studies (He et al, 2015; Huang & Kong, 2016; Wu et al, 2018).…”

Section: Discussionmentioning

confidence: 99%

Effects of land use changes on the nonlinear trends of net primary productivity in arid and semiarid areas, China

et al. 2021

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Monitoring the nonlinear trend of net primary productivity (NPP) is essential for assessing the changes of ecosystems quality. Land use change caused by human activities is considered to be a key factor leading to vegetation changes. However, how land use change impacts the nonlinear trend of NPP has not yet been determined. This article analyzed the nonlinear trend of NPP in arid and semiarid areas of China during in the period 1982-2015 based on the ensemble empirical mode decomposition (EEMD) method and elucidated the effects of land use changes on the nonlinear trends of NPP. The results revealed that: (a) With the EEMD method, although monotonic increase was the main type of the trend of NPP (28.40 %), trend reversals from increase to decrease and from decrease to increase accounted for 13.52 and 20.90 % of the study area, respectively. (b) Although vegetation in most types of land use has been improved a lot, it has not been improved significantly in forest areas and changed from improvement to degradation in some forest and urban land areas. (c) Urbanization limited vegetation recovery but other land use changes generally favoured vegetation improvement. Although afforestation improved vegetation, there was a considerable area of the forest converted from nonforest threatened by the changes from improvement to degradation due to water limitation.Overall, nonlinear trend analysis can reveal the hidden trend reversals to prevent the overestimation or underestimation of the risk of vegetation degradation and is conducive to accurate assessment of the effects of land use changes on vegetation trends. K E Y W O R D Sarid and semiarid areas, ensemble empirical mode decomposition (EEMD) method, land use change, net primary productivity, nonlinear trend analysis

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Section: Discussionmentioning

confidence: 99%

Effects of land use changes on the nonlinear trends of net primary productivity in arid and semiarid areas, China

et al. 2021

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“…The CASA model is a remote sensing-based process model. It performs well in longterm series and large-scale estimation of NPP [31,32]. The two indispensable components in the CASA model are absorbed photosynthetically active radiation (APAR) (MJ•m −2 ) and light use efficiency (LUE) factor ε (gC•MJ −1 ) [33][34][35].…”

Section: Net Primary Production (Npp) Estimation Modelmentioning

confidence: 99%

Large-Scale Analysis of the Spatiotemporal Changes of Net Ecosystem Production in Hindu Kush Himalayan Region

Guo

Song

et al. 2021

Remote Sensing

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The Hindu Kush Himalayan (HKH) region is one of the most ecologically vulnerable regions in the world. Several studies have been conducted on the dynamic changes of grassland in the HKH region, but few have considered grassland net ecosystem productivity (NEP). In this study, we quantitatively analyzed the temporal and spatial changes of NEP magnitude and the influence of climate factors on the HKH region from 2001 to 2018. The NEP magnitude was obtained by calculating the difference between the net primary production (NPP) estimated by the Carnegie–Ames Stanford Approach (CASA) model and the heterotrophic respiration (Rh) estimated by the geostatistical model. The results showed that the grassland ecosystem in the HKH region exhibited weak net carbon uptake with NEP values of 42.03 gC∙m−2∙yr−1, and the total net carbon sequestration was 0.077 Pg C. The distribution of NEP gradually increased from west to east, and in the Qinghai–Tibet Plateau, it gradually increased from northwest to southeast. The grassland carbon sources and sinks differed at different altitudes. The grassland was a carbon sink at 3000–5000 m, while grasslands below 3000 m and above 5000 m were carbon sources. Grassland NEP exhibited the strongest correlation with precipitation, and it had a lagging effect on precipitation. The correlation between NEP and the precipitation of the previous year was stronger than that of the current year. NEP was negatively correlated with temperature but not with solar radiation. The study of the temporal and spatial dynamics of NEP in the HKH region can provide a theoretical basis to help herders balance grazing and forage.

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“…Light-use efficiency (ε), which is the efficiency of vegetation to convert absorbed photosynthetic effective solar radiation into organic carbon, is a key parameter for calculating NPP [20]. It can be affected by various environmental conditions (e.g., temperature and moisture).…”

Section: Modeling 231 Casa Modelmentioning

confidence: 99%

“…where T ε1 (x, t) and T ε2 (x, t) are temperature stress coefficients, which indicate the reduction in light-use efficiency caused by temperature; W ε (x, t) is the moisture stress coefficient, which reflects the reduction in light-use efficiency caused by moisture; and ε max is the maximum light-use efficiency and is determined by the empirical method [20]. For details of the above parameters, see Table S2.…”

Section: Modeling 231 Casa Modelmentioning

confidence: 99%

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Decoupling the Effect of Climate and Land-Use Changes on Carbon Sequestration of Vegetation in Mideast Hunan Province, China

Liu

Xie

et al. 2021

Forests

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Urbanization and global climate change are two important global environmental phenomena in the 21st century. Human activities and climate changes usually increase the uncertainties of the ecosystem functions and structures and can greatly affect regional landscape patterns and the carbon cycle. Consequently, it is critical to understand how various climate and land-use changes influence the carbon dynamics at a regional scale. In this study, we quantitatively analyzed the spatial and temporal changes of net primary productivity (NPP) and the effects of climate factors and human disturbance factors (i.e., land-use changes) on the “Chang–Zhu–Tan” (CZT) urban agglomeration region from 2000 to 2015. The Carnegie–Ames–Stanford Approach (CASA) model was combined with spatially explicit land-use maps, monthly climate data, and MODIS NDVI images to simulate the carbon dynamics in the CZT area. Based on our six different scenarios, we also analyzed the relative roles of climate change and land-use change in total production. Our results indicated that the annual NPP of the study area maintained an upward trend by 7.31 gC•m−2•yr−1 between 2000 and 2015. At the same time, the average annual NPP was 628.99 gC•m−2 in the CZT area. We also found that the NPP was lower in the middle of the north region than in others. In addition, land-use changes could contribute to a positive effect on the total production in the study area by 3.42 T gC. Meanwhile, the effect of climate changes on the total production amounted to −1.44 T gC in the same region and period. Temperature and precipitation had negative effects on carbon sequestration from 2000 to 2015. As forest land constituted over 62.60% of the total land use from 2000 to 2015, the negative effect of carbon sequestration caused by urbanization could be ignored in the CZT area. Although climate and land-use changes had simultaneously positive and negative effects during the period 2000–2015, prioritizing the protection of existing forest land could contribute to increasing carbon sequestration and storage at the regional scale. Our study assists in understanding the impact of climate changes and land-use changes on carbon sequestration while providing a scientific basis for the rational and effective protection of the ecological environment in mid-east Hunan Province, China.

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Elevational differences in the net primary productivity response to climate constraints in a dryland mountain ecosystem of northwestern China

Cited by 39 publications

References 75 publications

Effects of land use changes on the nonlinear trends of net primary productivity in arid and semiarid areas, China

Effects of land use changes on the nonlinear trends of net primary productivity in arid and semiarid areas, China

Large-Scale Analysis of the Spatiotemporal Changes of Net Ecosystem Production in Hindu Kush Himalayan Region

Decoupling the Effect of Climate and Land-Use Changes on Carbon Sequestration of Vegetation in Mideast Hunan Province, China

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