Search Results (134)

The introduction of the ”dual carbon” target has increased the need for products that can accurately measure carbon dioxide levels, reflecting the rising demand. Due to challenges in achieving the required spatiotemporal resolution, accuracy, and spatial continuity with current carbon dioxide concentration products, it is essential to explore methods for obtaining carbon dioxide concentration products with completeness in space and time. Based on the 2018 OCO-2 carbon dioxide products and environmental variables such as vegetation coverage (FVC, LAI), net primary productivity (NPP), relative humidity (RH), evapotranspiration (ET), temperature (T) and wind (U, V), this study constructed a multiple regression model to obtain the spatial continuous carbon dioxide concentration products in the provinces of Huai River Basin. Using indicators such as correlation coefficient, root mean square error (RMSE), local variance, and percentage of valid pixels, the performance of model was validated. The validation results are shown as follows: (1) Among the selected environmental variables, the primary factors affecting the spatiotemporal distribution of carbon dioxide concentration are ET, LAI, FVC, NPP, T, U, and RH. (2) Compared with the OCO-2 carbon dioxide products, the percentage of valid pixels of the reconstructed carbon dioxide concentration data increased from less than 1% to over 90%. (3) The local variance in reconstructed data was significantly larger than that of original OCO-2 ${\mathrm{C}\mathrm{O}}_2$ products. (4) The average monthly RMSE is 2.69. Therefore, according to the model developed in this study, we can obtain a carbon dioxide concentration dataset that is spatially complete, meets precision requirements, and is rich in local detail information, which can better reflect the spatial pattern of carbon dioxide concentration and can be used to examine the carbon cycle between the terrestrial environment, biosphere, and atmosphere. Full article

This study quantitatively evaluates the effects of human activities (HAs) and climate change (CC) on the terrestrial ecosystem carbon cycle, providing a scientific basis for ecosystem management and the formulation of sustainable development policies in urban agglomerations located in arid and ecotone regions. Using the LanXi urban agglomeration in China as a case study, we simulated the spatiotemporal variation of vegetation net primary productivity (NPP) from 2000 to 2023 based on MODIS remote sensing data and the CASA model. Trend analysis and the Hurst index were employed to identify the dynamic trends and persistence of NPP. Furthermore, the Geographical Detector model with optimized parameters, along with nonlinear residual analysis, was employed to investigate the driving mechanisms and relative contributions of HAs and CC to NPP variation. The results indicate that NPP in the LanXi urban agglomeration exhibited a fluctuating upward trend, with an average annual increase of 4.26 gC/m² per year. Spatially, this trend followed a pattern of “higher in the center, lower in the east and west,” with more than 95% of the region showing an increase in NPP. Precipitation, mean annual temperature, evapotranspiration, and land use types were identified as the primary driving factors of NPP change. The interaction among these factors demonstrated a stronger explanatory power through factor coupling. Compared with linear residual analysis, the nonlinear model showed clear advantages, indicating that vegetation NPP in the LanXi urban agglomeration was jointly influenced by HAs and CC. These findings can further act as a basis for resource and environmental research in similar ecotone regions globally, such as Central Asia, the Mediterranean Basin, the southwestern United States, and North Africa. Full article

As a critical region for ecological construction in China, the upper Yellow River is still relatively short of research on the time-lag and cumulative effects of regional-scale drought on vegetation growth. Therefore, based on net primary productivity (NPP) estimated by the improved CASA (Carnegie–Ames–Stanford approach) model and multi-time scale SPEI, trend analysis, significance test and partial correlation analysis were employed to explore the spatial and temporal patterns of NPP and quantitatively evaluate its response to drought. The results showed that (1) From 2001 to 2022, NPP was higher in the south and lower in the north, decreasing from southwest to northeast, and annual NPP was increasing in 87.9% of the regions. NPP in spring, summer and autumn has been significantly improved. (2) In terms of interannual and spatial distribution, except for spring and winter, annual, summer and autumn all showed an insignificant trend of humidification. (3) The lag and cumulative effects of drought on vegetation in most areas are positively correlated. About 82.58% of NPP in the growing season has a time-lag effect with drought, which mainly focuses on 1–2 months. The average lag time was 3.6 months, indicating that NPP had the strongest correlation with the meteorological drought index of the previous 3.6 months. For cumulative effect, about 66.14% of NPP had a cumulative effect on drought, and the cumulative time scales were mainly March, April, November and December. With the worsening of drought conditions, the effect of drought on NPP is enhanced. These findings enhance the understanding of the long-term consequences of drought on terrestrial ecosystems and provide a basis for the development of mitigation and adaptation strategies aimed at alleviating the adverse effects of drought on agriculture and ecosystems. Full article

Vegetation plays an important role in carbon sequestration in terrestrial ecosystems and is affected by climate change and human activities. As a major factor affecting vegetation growth, the role of soil moisture in the impacts of climate change on vegetation is not well understood. Therefore, the effects of climate change on net primary productivity (NPP) may be underestimated. In this study, we analyzed the spatial distribution of NPP and land use degree comprehensive index (LDCI) in China from 2001 to 2020. The actual and relative contributions of climate change and human activities to NPP variation were explored. The findings indicated that NPP trended upward in 73.12%, 66.78%, and 81.34% of woodland, grassland, and cropland areas, respectively. Most of the woodland and grassland showed a decreasing trend in LDCI, while 48.63% of the cropland showed an increasing trend. The positive joint effects of climate change and human activities increased the NPP of woodlands, grasslands, and croplands by 42.83%, 53.49%, and 45.22%, respectively. Human activities (55.04%) contributed more to NPP than did climate change (44.96%). Analyzing the response of NPP (woodlands, grasslands, and croplands) to climate change and human activities in China is conducive to taking more targeted measures for different land use types to increase carbon sinks in terrestrial ecosystems. Full article

Plantation forests (PFs) play a crucial role in China’s climate change mitigation strategy due to their significant capacity to sequestrate carbon (C). Understanding the long-term trend in PFs’ C uptake capacity and the key drivers influencing it is crucial for optimizing PF management and planning for climate mitigation. In this study, we quantified the long-term (1981–2019) C sequestration of PFs in Jiangsu Province, where PFs have expanded considerably in recent decades, particularly since 2015. Seasonal and interannual variations in gross primary productivity (GPP), net primary productivity (NPP), and net ecosystem productivity (NEP) were assessed using the boreal ecosystem productivity simulator (BEPS), a process-based terrestrial biogeochemical model. The model integrates multiple sources of remote-sensing datasets, such as leaf area index and land cover data, to simulate the critical biogeochemical processes governing land surface dynamics, enabling the quantification of vegetation and soil C stocks and nutrient cycling patterns. The results indicated a significant increasing trend in GPP, NPP, and NEP over the past four decades, suggesting enhanced C sequestration by PFs across the study region. The interannual variability in these indicators was associated with that of nitrogen (N) deposition in recent years, implying that nutrient availability could be a limiting factor for plantation productivity. Seasonal GPP and NPP exhibited peak values in spring (April to May) or late summer (August to September), with increases in growing season productivity in recent years. In contrast, NEP peaked in spring (April to May) but declined to negative values in early summer (July to August), indicating a seasonal C source–sink transition. All three indicators showed a general negative correlation with late-growing-season temperature (August to September), suggesting that summer droughts probably highly constrained the C sequestration of the existing PFs. These findings provide insights for the strategic implementation and management of PFs, particularly in regions with a warm temperate climate undergoing afforestation expansion. Full article

The carbon cycle of forest ecosystems is a component of the global terrestrial ecosystem carbon cycle, and the productivity of forest ecosystems is significantly influenced by vegetation phenology. In this investigation, we simulated the spatiotemporal trends of the carbon cycle in forest ecosystems in Hangzhou between 2001 and 2020 by means of the phenology-driven InTEC model and analyzed the mechanisms of carbon cycle changes in response to phenological changes. The results of this study suggested that the gross primary productivity (GPP), the net primary production (NPP), and the net ecosystem productivity (NEP) have obvious heterogeneity in spatiotemporal distribution, and the tendency of the start of the growing season (SOS) advancement, the end of the growing season (EOS) postponement, and the length of the growing season (LOS) lengthening is significant for a GPP increase with positive effects. Both phenology and climate have direct impacts on carbon cycle changes, while climate change indirectly affects carbon cycle changes through phenology changes. Full article

Water use efficiency (WUE) connects two key processes in terrestrial ecosystems: the carbon and water cycles. Thus, it is important to evaluate temporal and spatial changes in WUE over a prolonged period. The spatiotemporal variation characteristics of the WUE in the Mongolian Plateau from 1982 to 2018 were analyzed based on the net primary productivity (NPP), evapotranspiration (ET), temperature, precipitation, and soil moisture. In this study, we used remote sensing data and various statistical methods to evaluate the spatiotemporal patterns of water use efficiency and their potential influencing factors on the Mongolian Plateau from 1982 to 2018. In total, 27.02% of the region witnessed a significant decline in the annual WUE over the 37 years. Two abnormal surges in the WUE_Season (April–October) were detected, from 1997 to 1998 and from 2007 to 2009. The trend in the annual WUE in some broadleaf forest areas in the middle and northeast of the Mongolian Plateau reversed from the original decreasing trend to an increasing trend. WUE has shown strong resilience in previous analytical studies, whereas the WUE in the artificial vegetation area in the middle of the Mongolian Plateau showed weak resilience. WUE had a significant positive correlation with precipitation, soil moisture, and the drought severity index (DSI) but a weak correlation with temperature. WUE had strong resistance to abnormal water disturbances; however, its resistance to the effects of temperature and DSI anomalies was weak. The degree of interpretation of vegetation changes for WUE was higher than that for meteorological factors, and WUE showed weak resistance to normalized difference vegetation index (NDVI) disturbances. Delaying the start of the vegetation growing season had an increasing effect on WUE, and the interaction between phenological and meteorological vegetation factors had a non-linear enhancing effect on WUE. Human activities have contributed significantly to the increase in WUE in the eastern, central, and southern regions of the Mongolian Plateau. These results provide a reference for the study of the carbon–water cycle in the Mongolian Plateau. Full article

The carbon cycle in terrestrial ecosystems is a crucial component of the global carbon cycle, and drought is increasingly recognized as a significant stressor impacting their carbon sink function. Net ecosystem productivity (NEP), which is a key indicator of carbon sink capacity, is closely related to vegetation Net Primary Productivity (NPP), derived using the Carnegie-Ames-Stanford Approach (CASA) model. However, there is limited research on desert grassland ecosystems, which offer unique insights due to their long-term data series. The relationship between NEP and drought is complex and can vary depending on the intensity, duration, and frequency of drought events. NEP is an indicator of carbon exchange between ecosystems and the atmosphere, and it is closely related to vegetation productivity and soil respiration. Drought is known to negatively affect vegetation growth, reducing its ability to sequester carbon, thus decreasing NEP. Prolonged drought conditions can lead to a decrease in vegetation NPP, which in turn affects the overall carbon balance of ecosystems. This study employs the improved CASA model, using remote sensing, climate, and land use data to estimate vegetation NPP in desert grasslands and then calculate NEP. The Standardized Precipitation Evapotranspiration Index (SPEI), based on precipitation and evapotranspiration data, was used to assess the wetness and dryness of the desert grassland ecosystem, allowing for an investigation of the relationship between vegetation productivity and drought. The results show that (1) from 1982 to 2022, the distribution pattern of NEP in the Inner Mongolia desert grassland ecosystem showed a gradual increase from southwest to northeast, with a multi-year average value of 29.41 gCm⁻². The carbon sink area (NEP > 0) accounted for 67.99%, and the overall regional growth rate was 0.2364 gcm⁻²yr⁻¹, In addition, the area with increasing NEP accounted for 35.40% of the total area (p < 0.05); (2) using the SPEI to characterize drought changes in the Inner Mongolia desert grassland ecosystems, the region as a whole was mainly affected by light drought. Spatially, the cumulative effect was primarily driven by short-term drought (1–2 months), covering 54.5% of the total area, with a relatively fast response rate; (3) analyzing the driving factors of NEP using the Geographical detector, the results showed that annual average precipitation had the greatest influence on NEP in the Inner Mongolian desert grassland ecosystem. Interaction analysis revealed that the combined effect of most factors was stronger than the effect of a single factor, and the interaction of two factors had a higher explanatory power for NEP. This study demonstrates that NEP in the desert grassland ecosystem has increased significantly from 1982 to 2022, and that drought, as characterized by the SPEI, has a clear influence on vegetation productivity, particularly in areas experiencing short-term drought. Future research could focus on extending this analysis to other desert ecosystems and incorporating additional environmental variables to further refine the understanding of carbon dynamics under drought conditions. This research is significant for improving our understanding of carbon cycling in desert grasslands, which are sensitive to climate variability and drought. The insights gained can help inform strategies for mitigating climate change and enhancing carbon sequestration in arid regions. Full article

A comprehensive evaluation of the variations in carbon use efficiency (CUE) and water use efficiency (WUE) in the Nanling Mountains Region (NMR) is crucial for gaining insights into the intricate relationships between climate change and ecosystem processes. This study evaluates the spatiotemporal rates of dynamics in CUE, WUE, gross primary productivity (GPP), net primary productivity (NPP), and evapotranspiration (ET) over the period from 2001 to 2023, using remote sensing data and linear regression analysis. Trend analysis, Hurst exponent analysis, and stability analysis were applied to examine the long-term patterns of CUE and WUE, while partial correlation analysis was employed to explore the spatial relationships between these efficiencies and climatic factors. The main findings of the study are as follows: (1) The CUE and WUE of the NMR decreased geographically from 2001 to 2023, and both the CUE and WUE of NMR showed a significant declining trend (p < 0.05) with the CUE decreasing at a rate of 0.0014/a (a: year) and the WUE falling at a rate of 0.0022/a. (2) The average values of the CUE and WUE of the NMR from 2001 to 2023 were 0.47 and 0.82 g C·m⁻²·mm⁻¹, respectively, with a clear geographical difference. (3) The CUE and WUE in the NMR showed widespread degradation trends with some localized improvements, yet sustainability analysis indicates a likely continued decline across most areas, particularly for forests, while grasslands exhibit the greatest resilience. (4) Precipitation had a significantly stronger impact on WUE, while temperature appeared to exert a more substantial effect on CUE, with vegetation types responding differently; notably, shrubland displayed a direct association between CUE and temperature. In summary, multi-source data were employed to comprehensively analyze the spatiotemporal dynamics of CUE and WUE in the NMR over the past 23 years. We also examined the features of their responses to global warming, offering valuable theoretical insights into the carbon and water dynamics within the terrestrial ecosystems of the NMR. Full article

To assess the carbon balance of terrestrial ecosystems, it is crucial to consider the net primary productivity (NPP) of vegetation. Understanding the response of NPP in Xinjiang’s vegetation to climate factors and human activities is essential for ecosystem management, the Belt and Road Initiative, and achieving carbon neutrality goals. Based on the CASA model, this study uses meteorological data, DEM data, and land cover data, employing trend analysis and partial derivative analysis methods to investigate the temporal trends and spatial distribution of NPP in Xinjiang from 2000 to 2020. Additionally, it quantifies the contributions of climate factors and human activities to NPP fluctuations. The key findings are: (1) The average annual NPP is 101.52 gC/m², with an upward trend, showing an overall growth rate of 0.447 gC/m²/yr. Spatially, NPP is higher in northern Xinjiang than in the south, and in mountainous areas compared to basins. (2) Over 21 years, climate factors contributed an average of 1.054 gC/m²/yr, while human activities contributed 0.239 gC/m²/yr to NPP changes. Among climate factors, temperature, precipitation, and sunshine duration contributed 0.003, 0.169, and 0.588 gC/m²/yr, respectively, all showing positive effects on NPP. (3) Forests have the highest average NPP at 443.96 gC/m², with an annual growth rate of 2.69 gC/m²/yr. When forest is converted to cropland, the net loss in NPP is −1.94 gC/m², and the loss is even greater in conversion to grassland, reaching −17.33 gC/m². (4) The changes in NPP are driven by both climate factors and human activities. NPP increased in 77.25% of the area, while it decreased in 22.69%. Climate factors have a greater positive impact than human activities. Full article

Net primary productivity (NPP) is a core ecological indicator within terrestrial ecosystems, representing the potential of vegetation growth to offset anthropogenic carbon emissions. Thus, assessing NPP in a given region is crucial for promoting regional ecological restoration and sustainable development. This study utilized the CASA model and GEE to calculate the annual average NPP in Shandong Province (2001–2020). Through trend analysis, Moran’s Index, and PLS−SEM, the spatiotemporal evolution and driving factors of NPP were explored. The results show that: (1) From 2001 to 2020, NPP in Shandong showed an overall increasing trend, rising from 254.96 to 322.49 g C·m⁻²/year. This shift was accompanied by a gradual eastward movement of the NPP centroid, indicating significant spatial changes in vegetation productivity. (2) Regionally, 47.9% of Shandong experienced significant NPP improvement, 27.6% saw slight improvement, and 20.1% exhibited slight degradation, highlighting notable spatial heterogeneity. (3) Driver analysis showed that climatic factors positively influenced NPP across all four periods (2005, 2010, 2015, 2020), with the strongest impact in 2015 (coefficient = 0.643). Topographic factors such as elevation and slope also had positive effects, peaking at 0.304 in 2015. In contrast, human activities, especially GDP and nighttime light intensity, negatively impacted NPP, with the strongest negative effect in 2010 (coefficient = −0.567). These findings provide valuable scientific evidence for ecosystem management in Shandong Province and offer key insights for ecological restoration and sustainable development strategies at the national level. Full article

The processes of urbanization and climate change have exerted a marked influence on net primary productivity (NPP). However, the underlying mechanisms that drive these effects remain intricate and insufficiently understood. The processes of urbanization and climate change both have an adverse effect on habitat quality (HQ) and biodiversity loss. The HQ has a direct influence on the health and stability of ecosystems, which regulate the level of NPP. A higher HQ is associated with stronger NPP. Now, the quantification and assessment of the impacts of climate change and urbanization on NPP are still challenging because of the various driving factors and the intricate mechanisms influencing the production of terrestrial vegetation. Therefore, a new perspective was adopted to study the effects of urbanization and climate change on NPP in the Qinghai–Tibet Plateau in China during 2000–2020. The spatiotemporal analysis method was employed to investigate the impact of the night light urbanization index and climate factors on NPP in different HQ regions (the HQ is divided into five levels, with each area type corresponding to a specific HQ level). Then, the coupled coordination model (CCD) was used to analyze the coupling coordination relationship between NPP and HQ. Finally, the relative contribution of urbanization and climate change to NPP was studied using scenario simulation. The results showed that (1) NPP in the whole Tibetan Plateau increased very little, with an average growth rate of 0.42 g C m⁻² per year. (2) It was surprising to find that NPP in urban areas did not decline significantly as a result of urbanization. However, there was a notable decline in NPP in higher HQ areas. (3) The mean contribution of urbanization to NPP change was found to be 17%, while the mean contribution of climate change and other factors to NPP change was 69% and 14%, respectively. These findings provide valuable insights into the interactions between human development and environmental factors, enhancing our comprehension of their role in the Tibetan Plateau’s carbon cycle. Full article

Diverse exogenous nitrogen (N) sources have a considerable impact on microbial community structure in terrestrial ecosystems. Legume plants and N deposition can relieve N limitations and increase net primary productivity. However, the differences in their effects on soil microbial communities remain unclear. Here, the responses of the soil microbial community to a legume-planting system and simulated N deposition were examined in karst grasslands in Southwest China over five years by analyzing soil microbial phospholipid fatty acids (PLFAs). The experiment included three treatments—legume plant introduction (N_L, Indigofera atropurpurea), N deposition (N_D, NH₄NO₃:10 g N m⁻² yr⁻¹), and a control with no treatment. The effects of N_L and N_D on soil microbial community composition differed significantly. N_D significantly reduced the biomass of bacteria, actinobacteria, and arbuscular mycorrhizal fungi. N_L insignificantly increased the biomass of all microbial groups. However, the total amounts of PLFAs and fungal biomass were significantly higher in N_L than in N_D. The effect of legume plant introduction on soil microbial community composition was more powerful than that of N_D. Overall, the introduction of legume plants is beneficial in terms of increasing the biomass of the soil microbial community and stabilizing the soil microbial community structure in karst grassland ecosystems. Full article

Net primary production (NPP) serves as a critical proxy for monitoring changes in the global capacity for vegetation carbon sequestration. The assessment of the factors (i.e., human activities and climate changes) influencing NPP is of great value for the study of terrestrial systems. To investigate the influence of factors on grassland NPP, the ecologically vulnerable Qinghai–Tibet Plateau region was considered an appropriate study area for the period from 2000 to 2020. We innovated the use of the RICI index to quantitatively represent human activities and analyzed the effects of RICI and climatic factors on grassland NPP using the geographical detector. In addition, the future NPP was predicted through the integration of two modeling approaches: The Patch-Generating Land Use Simulation (PLUS) model and the Carnegie–Ames–Stanford Approach (CASA) model. The assessment revealed that the expanded grassland contributed 7.55 × 10⁴ Gg C (Gg = 10⁹ g) to the total NPP, whereas the deterioration of grassland resulted in a decline of 1.06 × 10⁵ Gg C. The climatic factor was identified as the dominant factor in grassland restoration, representing 70.85% of the total NPP, as well as the dominant factor in grassland degradation, representing 92.54% of the total NPP. By subdividing the climate change and human activity factors into sub-factors and detecting them with a geographical detector, the results show that climate change and anthropogenic factors have significant ability to explain geographic variation in NPP to a considerable extent, and the effect on NPP is greater when the factors interact. The q-values of the Relative Impact Contribution Index (RICI) and the RICI of the land use change NPP are consistently greater than 0.6, with the RICI of the human management practices NPP and the evapotranspiration remaining at approximately 0.5. The analysis of the interaction between climate and human activity factors reveals an average impact of greater than 0.8. By 2030, the NPP of the natural development scenario, economic development scenario (ED), and ecological protection scenario (EP) show a decreasing trend due to climate change, the dominant factor, causing them to decrease. Human activities play a role in the improvement. The EP indicates a positive expansion in the growth rate of forests, water, and wetlands, while the ED reveals rapid urbanization. It is notable that this is accompanied by a temporary suspension of urban greening. Full article