Terrestrial Ecosystems In China Research Articles

Spatio-Temporal Evolution of Ecological Environment Quality Based on High-Quality Time-Series Data Reconstruction: A Case Study in the Sanjiangyuan Nature Reserve of China

The Sanjiangyuan Nature Reserve of China (SNRC) is recognized as one of the most fragile and sensitive terrestrial ecosystems in China, posing challenges for obtaining reliable and complete Moderate Resolution Imaging Spectro Radiometer (MODIS) data for ecological environment quality (EEQ) monitoring due to adverse factors like clouds and snow. In this study, a complete high-quality framework for MODIS time-series data reconstruction was constructed utilizing the Google Earth Engine (GEE) cloud platform. The reconstructed images were used to compute the Remote Sensing based Ecological Index (RSEI) on a monthly scale in the SNRC from 2001 to 2020. The results were as follows: The EEQ of the study area exhibited a “first fluctuating decline, then significant improvement” trend, with the RSEI values increasing at a rate of 0.84%/a. The spatial pattern of the EEQ displayed significant spatial heterogeneity, characterized by a “low in the west and high in the east” distribution. The spatial distribution pattern of the RSEI exhibited significant clustering characteristics. From 2001 to 2020, the proportion of “high–high” clustering areas exceeded 35%, and the proportion of “low–low” clustering areas exceeded 30%. Poor ecological conditions are mainly associated with population agglomerations, cultivated land, unutilized land, and bare ground, while grasslands and forests have higher RSEI values. The result of the trend analysis revealed a significant trend in RSEI change, with 62.96% of the area significantly improved and 6.31% significantly degraded. The Hurst Index (HI) results indicated that the future trend of the RSEI is predominantly anti-persistence. The proportion of areas where the EEQ is expected to continue improving in the future is 33.74%, whereas 21.21% of the area is forecasted to transition from improvement to degradation. The results showed that the high-quality framework for MODIS time-series data reconstruction enables the effective continuous monitoring of EEQ over long periods and large areas, providing robust scientific support for long time-series data reconstruction research.

Increased harvested carbon of cropland in China

Crop harvested carbon (HC) is one of the most important components of the carbon cycle in cropland ecosystems, with a significant impact on the carbon budget of croplands. China is one of the most important crop producers, however, it is still unknown on the spatial and temporal variations of HC. This study collected statistical data on crop production at the province and county levels in China for all ten crop types from 1981 to 2020 and analyzed the magnitude and long-term trend of harvested crop carbon. Our results found a substantial increase of HC in cropland from 0.185 Gt C yr−1 in 1981 to 0.423 Gt C yr−1 in 2020 at a rate of 0.006 Gt C yr−1. The results also highlighted that the average annual carbon sink removal from crop harvesting in China from 1981 to 2020 was 0.32 Gt C yr−1, which was comparable to the net carbon sink of the entire terrestrial ecosystems in China. This study further generated a gridded dataset of HC from 2001 to 2019 in China by using jointly the statistical crop production and distribution maps of cropland. In addition, a model-data comparison was carried out using the dataset and results from seven state-of-the-art terrestrial ecosystem models, revealing substantial disparities in HC simulations in China compared to the dataset generated in the study. This study emphasized the increased importance of HC for estimating cropland carbon budget, and the produced dataset is expected to contribute to carbon budget estimation for cropland ecosystems and the entire China.

Elevation-dependent pattern of net CO2 uptake across China

The elevation gradient has long been known to be vital in shaping the structure and function of terrestrial ecosystems, but little is known about the elevation-dependent pattern of net CO2 uptake, denoted by net ecosystem productivity (NEP). Here, by analyzing data from 203 eddy covariance sites across China, we report a negative linear elevation-dependent pattern of NEP, collectively shaped by varying hydrothermal factors, nutrient supply, and ecosystem types. Furthermore, the NEP shows a higher temperature sensitivity in high-elevation environments (3000–5000 m) compared with the lower-elevation environments (<3000 m). Model ensemble and satellite-based observations consistently reveal more rapid relative changes in NEP in high-elevation environments during the last four decades. Machine learning also predicts a stronger relative increase in high-elevation environments, whereas less change is expected at lower elevations. We therefore conclude a varying elevation-dependent pattern of the NEP of terrestrial ecosystems in China, although there is significant uncertainty involved.

Evolutionary characteristics of carbon sources/sinks in Chinese terrestrial ecosystems regarding to temporal effects and geographical partitioning

Whereas the current complex diversity in Chinese terrestrial ecosystems and the significant differences in net ecosystem productivity (NEP) among various regions, as well as the temporal effect between vegetation and climate factors, the NEP in Chinese terrestrial ecosystems was estimated between 2001 and 2020, and characterized the spatiotemporal dynamics of NEP and its driving mechanisms, taking into account geographic subdivisions. The results demonstrated that the multiannual mean of NEP in Chinese terrestrial ecosystems ranged from 42.79 to 61.91 g C/m2a over the past two decades, indicating a volatile upward trend. Spatially, the NEP of Chinese terrestrial ecosystems indicated significant spatial differentiation, with carbon sinks encompassing 68.83 %, primarily focused in Northeast Region (DB), East China (HD), South China (HN), and Central China (HZ). Moving forward, Chinese terrestrial ecosystems will be predominantly restored, with 40.88 % of the area going from degradation to improvement, and 14.17 % of the area undergoing sustained improvement. There were geographic differences in the temporal effects between NEP and climate elements (precipitation and temperature). Precipitation was identified as the dominant factor affecting the variation of NEP in DB, HB, HZ, XB, and XN. While solar radiation was the major factor influencing the variation of NEP in HD (51.72 %) and HN (76.07 %). Compared with human activities, climate change emerged as the primary driver impacting the spatiotemporal evolution of NEP in Chinese terrestrial ecosystems, with 61.40 % of the area of NEP increasing due to climate change, while 58.42 % increased due to human activities. Additionally, changes in land use/land cover played a crucial role in altering NEP of terrestrial ecosystems in China.

Carbon storage in mollusk shells: An overlooked yet significant carbon sink in terrestrial ecosystems

Mollusks, the second largest animal family, are found in a variety of ecosystems. As they grow, their shells absorb carbon and form calcium carbonate, making them an important storage place for carbon. However, the amount of carbon deposited in the carbonate shells of terrestrial mollusks throughout modern and geological history has not been quantified. In this study, we first conducted an investigation of carbon deposits in shells from various mollusk species at 470 modern surface soil sample sites across diverse terrestrial ecosystems in China. The deciduous broadleaf forest and shrublands exhibited a higher carbon deposition rate of ∼1.37 ± 2.15 and ∼1.56 ± 2.92 g C m−2/yr−1, while croplands and grasslands displayed a rate of ∼1.11 ± 1.95 and 1.07 ± 1.78 g C m−2/yr−1, respectively. Using geostatistical methods, we estimated the total shell carbon deposition of grassland, forest, shrublands, and croplands in China to be ∼3.39–5.45 × 106 t C yr−1, constituting ∼1.68–2.71 % of China's terrestrial carbon sink, an overlooked portion in previous studies. Additionally, we provided quantitative data on shell carbon fluxes spanning a remarkable 20,000-year period through over ten fossil sequences from loess deposits. The results underscore the continuous and abundant carbon deposition in mollusk shells across various locations for at least 20,000 years, highlighting the persistence and substantial accumulation of shell carbon deposits over time. Remarkably, we estimated that the total shell carbon deposition of loess sediments in China and the world over the past 20,000 years may reach 1.10 × 108 t C and 1.29 × 109 t C, roughly equivalent to an afforestation area of 2.32 × 106 km2 and 2.72 × 107 km2, respectively.

Pervasive soil phosphorus losses in terrestrial ecosystems in China

AbstractFuture phosphorus (P) shortages could seriously affect terrestrial productivity and food security. We investigated the changes in topsoil available P (AP) and total P (TP) in China's forests, grasslands, paddy fields, and upland croplands during the 1980s–2010s based on substantial repeated soil P measurements (63,220 samples in the 1980s, 2000s, and 2010s) and machine learning techniques. Between the 1980s and 2010s, total soil AP stock increased with a small but significant rate of 0.13 kg P ha−1 year−1, but total soil TP stock declined substantially (4.5 kg P ha−1 year−1) in the four ecosystems. We quantified the P budgets of soil–plant systems by harmonizing P fluxes from various sources for this period. Matching trends of soil contents over the decades with P budgets and fluxes, we found that the P‐surplus in cultivated soils (especially in upland croplands) might be overestimated due to the great soil TP pool compared to fertilization and the substantial soil P losses through plant uptake and water erosion that offset the P additions. Our findings of P‐deficit in China raise the alarm on the sustainability of future biomass production (especially in forests), highlight the urgency of P recycling in croplands, and emphasize the critical role of country‐level basic data in guiding sound policies to tackle the global P crises.

Biological nitrogen fixation and the role of soil diazotroph niche breadth in representative terrestrial ecosystems

Biological nitrogen fixation (BNF) driven by diazotrophs is a fundamental process underpinning the primary productivity of terrestrial ecosystems and plays a pivotal role in the global nitrogen cycle. However, the relationships between BNF function and soil diazotroph taxa with different niche breadths remain unclear. This study investigated the N2 fixation rate and community structure of diazotrophs in soils collected from representative terrestrial ecosystems in China—agricultural, desert, forest, grassland and wetland—and explored the specific contributions of groups of diazotrophs with different niche breadths to the N2 fixation rate. Among all the ecosystems, the N2 fixation rate, nifH gene abundance and diazotroph diversity were highest in the wetland ecosystems. The N2 fixation rate was significantly (P < 0.05) positively correlated with diazotroph diversity, indicating a relationship between microbial community diversity and ecosystem functionality. Furthermore, the N2 fixation rate and Shannon index were significantly (P < 0.05) positively correlated with the abundances of diazotrophs classified as specialists and opportunists. Structural equation modeling indicated that geographical factors and climatic factors affected the abundance of specialists and opportunists directly or indirectly through soil physicochemical properties, which in turn affected N2 fixation rates. Collectively, these valuable insights into the intrinsic relationship between nitrogen-fixing function and groups of soil diazotroph taxa with different niche breadths advance our understanding of BNF across terrestrial ecosystems.

Climate-shaped vegetation dominated the spatial pattern of the Bowen ratio over terrestrial ecosystems in China

The Bowen ratio (β), which is the ratio of sensible heat (H) to latent heat (LE), reflects the energy balance and partitioning processes among soil, vegetation, and the atmosphere. Although the spatial patterns of β have been clearly delineated, the importance of vegetation in the spatial variation of β is frequently underestimated. Revealing the spatial patterns of β would improve the understanding of the variation in energy partitioning in terrestrial ecosystems and its reciprocal relationship with environmental change. Here, we calculated β by integrating H and LE flux values from 80 flux observation sites based on the eddy-covariance method in ChinaFLUX to analyze the spatial pattern and mechanism of β in China. Terrestrial ecosystems in China had an average β of 0.64 ± 0.47. β varied significantly among ecosystem types. Deserts had the highest β (2.08 ± 0.17), while wetlands had the lowest β (0.37 ± 0.11). The β values of terrestrial ecosystems exhibited a significant latitudinal pattern, increasing linearly with latitude. This pattern also existed in forest and cropland ecosystems. The spatial pattern of β was dominated by climate-shaped vegetation factors, including leaf area index (LAI) and fractional vegetation cover (FVC). Nevertheless, as water and thermal conditions decline, the contribution of vegetation factors gradually wanes. These findings demonstrated the spatial variations and driving mechanisms of terrestrial ecosystem β and provided insights into the mitigation of future climate change by vegetation.

Ecosystem responses dominate the trends of annual gross primary productivity over terrestrial ecosystems of China during 2000–2020

The annual gross primary productivity (AGPP) forms the foundation for terrestrial carbon sink. AGPP trends stem from the combined impacts of environmental factors and ecosystem responses to those factors. These responses include model structure modifications altering both the structural properties (represented by leaf area index) and the functional properties (represented by per leaf AGPP). Understanding the contributions of ecosystem responses to AGPP trends is crucial for accurately assessing spatiotemporal variations in AGPP, which aids in effective carbon management. Based on eddy covariance measurements of AGPP in China, we generated AGPP during 2000–2020 by constructing yearly AGPP mapping schemes from site measurements and analyzed AGPP trends. The roles of ecosystem responses and their pathways were further elucidated by employing analysis of variance. Results showed that the total AGPP in China was 7.39 ± 0.62 PgC yr−1, with an increasing trend of 0.095 PgC yr−2. This increase primarily sourced from the total AGPP in Subtropical Evergreen Needleleaf Forest. AGPP trends spatially decreased from east to west, with most regions showing positive values. Structural and functional properties contributed similarly to AGPP trends, with varying regional contributions. The structural properties played a dominant role in north regions while the functional properties were more important in south and west regions. Ecosystem responses similarly determined the trends of ecosystem properties, which decreased from west to east. Ecosystem responses thus dominated AGPP trends through the structural properties in north regions but through the functional properties in south and west regions. Therefore, Chinese AGPP exhibited a spatially varied increasing trend during 2000–2020. Ecosystem responses dominated AGPP trends through divergent properties across regions. Our results highlight the significanc of ecosystem responses in AGPP trends and their divergent pathways across regions. This also provides independent data support for quantifying regional carbon budgets.

Spatial variation of sulfur in terrestrial ecosystems in China: Content, density, and storage

Sulfur (S) is an important macronutrient that is widely distributed in nature. Understanding the patterns and mechanisms of S dynamics is of great significance for accurately predicting the geophysical and chemical cycles of S and formulating policies for S emission and management. We systematically investigated and integrated 17,618 natural plots in China's terrestrial ecosystems and built a S density database of vegetation (including leaves, branches, stems, and roots) and surface soil (0–30 cm depth). The biogeographic patterns and environmental drivers of the S content, density, and storage in the vegetation and soil of terrestrial ecosystems were explored. Vegetation and soil were the major components of terrestrial ecosystems, storing a total of 2228.77 ± 121.72 Tg S, with mean S densities of 4.32 ± 0.04 × 10−2, and 267.93 ± 14.94 × 10−2 t hm−2, respectively. The forest was the most important vegetation S pool and their S storage accounted for about 55.28 % of the total vegetation S storage, whereas soil S pools of croplands and other vegetation types (e.g., deserts and wetlands) accounted for about 63.18 % of the total soil S storage. The mean S density (2.18 ± 0.02 × 10−2 t hm−2) and S storage (12.45 ± 0.31 Tg) of plant roots were significantly higher than those of other organs. The spatial variation in the S density was mainly regulated by climate and soil properties, reflecting the physiological adaptation mechanisms of plants by adjusting the S uptake and distribution to cope with climate change. In this study, the spatial patterns of S density and storage in vegetation and soil in terrestrial ecosystems of China and their response to environmental factors on a national scale were systematically studied. The results provide insights into the biological functions of S and its role in plant–environment interactions.

Synergistic changes in precipitation and soil water use efficiency and their driving mechanisms of terrestrial ecosystems in China

Soil water use efficiency (SWUE) and precipitation use efficiency (PUE) are paramount indicators in examining the coupling mechanism of carbon and water cycles in terrestrial vegetation ecosystems. However, the mechanisms influencing variations in PUE and SWUE warrant further investigation due to existing research gaps. The gross primary productivity (GPP) and net primary productivity (NPP) in China were simulated using the TL-LUE model and improved CASA model, respectively. PUE and SWUE were then calculated in conjunction with precipitation and soil water data. A further investigation was conducted on the joint evolutionary patterns of PUE and SWUE. The impact of factors such as climate change, vegetation variation, carbon dioxide emission, and human activities on PUE and SWUE was separately identified using partial derivatives and elasticity coefficients. The results suggest an insignificant downward in PUE and a significant upward trend in SWUE in China from the period of 2000–2018. Notably, drought mitigation in the arid zone led to a steeper decrease in PUE compared to humid, sub-humid and semi-arid zones. Drought mitigation resulted in a decrease of SWUE in arid zones, yet an increase in humid, sub-humid and semi-arid zones. The correlations between vegetation change and precipitation and PUE or SWUE, respectively, were predominantly influenced by changes in drought conditions. NPP and precipitation collectively dominated the alterations in PUE, contributing 41.55% and −58.45%, respectively. However, GPP exerted a more substantial influence on SWUE compared to precipitation, with notable contributions of 93.93% and −6.07%, respectively. The contributions to PUE from climate variation, human activities, vegetation change and carbon dioxide were −57%, 30%, 12% and −1%, respectively. Simultaneously, the contributions to SWUE from these same factors appeared as 20%, 63%, 16% and 1%, respectively. This study intends to augment the comprehension of the influence exerted by global climate change and human activities on the correlation between carbon and water in terrestrial vegetation ecosystems.

A dataset of ecological quality indexes of terrestrial ecosystems in China from 2000 to 2018

The deteriorating ecological conditions have attracted widespread attention, spurring the development of quantitative analysis methods for ecological quality, improving the concept of ecological quality, and thus facilitating the formulation of future ecological environmental protection policies. Using satellite remote sensing and ecosystem process model data, we constructed a conceptual framework for ecological quality based on a pixel-level historical baseline of current ecosystem functions and biodiversity habitats through data quality control in forward normalization, correlation analysis, and projection pursuit algorithm based on particle swarm optimization, resulting in dataset of ecological quality indexes of terrestrial ecosystems in China from 2000 to 2018 with a spatial resolution of 1 km. By sharing this dataset, we aim to provide a data foundation for the advancement of ecological assessment theories and methods, as well as the management and decision-making of macro ecosystems.

A dataset of carbon and water fluxes observed in Xishuangbanna tropical seasonal rain forest from 2011 to 2015

The proposal for China's dual-carbon target is based on the foundation of addressing climate change. It is imperative to enhance carbon sinks and reduce carbon sources to implement climate governance. The terrestrial ecosystem is an important atmospheric carbon sink, while the tropical seasonal rain forest, as a component of the terrestrial ecosystem in China characterized by rich biomass, and strong productivity, plays an essential role in carbon sequestration. As one of the basic observation and research stations of China Flux Research Network (ChinaFLUX), the Xishuangbanna Tropical Seasonal Rainforest Ecological Station built in 2002 has accumulated 20 years of carbon and water flux observation data. Based on the ChinaFLUX data processing system, this dataset processes and collates the tropical seasonal rain forest flux and conventional meteorological data of Xishuangbanna from January 2011 to December 2015. The result is a collection of data products at half-hourly, daily, monthly, and yearly intervals. This dataset can be applied to research fields such as the analysis of the carbon cycle response mechanism of ecosystems and the assessment of carbon sequestration benefits under climate change, and it can also serve as a valuable reference for the optimization of ecosystem model parameters and the verification of results. Through multi-platform architecture, multi-scale integration, and multi-method coupling, the dataset is expected to further provide basic support for analyzing the mechanisms of regional and even global carbon-water-heat cycles in ecosystems, spatiotemporal dynamics and predicting future carbon sink potential, thus providing the scientific basis for achieving China's carbon neutrality goal.

Rapid Vegetation Growth due to Shifts in Climate from Slow to Sustained Warming over Terrestrial Ecosystems in China from 1980 to 2018

The fraction of absorbed photosynthetically active radiation (FPAR) is a key biophysiological parameter of terrestrial ecosystems. However, due to a lack of data with adequate spatial resolution and in long enough time series, there have been limitations in exploring the spatiotemporal changes of vegetation and response to climate change. In this study, a 1 km spatial resolution and 8-day period length dataset (FPARANN) was developed covering the years 1980 to 2018 and evaluated on spatiotemporal change consistency by validating with Gross Primary Production (GPP) observations from the Chinese Flux Observation and Research Network (ChinaFLUX), and comparison with other FPAR products. FPARANN provided a comparable performance in capturing seasonal change observed through GPP, according to the coefficient of determination (R2): 0.50, 0.51, 0.70 and 0.74 averaged for all sites, forest sites, grassland sites and cropland flux sites, respectively. The new data had more spatial similarity to the MODIS FPAR product (FPARMCD15A2) with a greater R2 (0.77) and a lower RMSE (0.12) than other products. With a newly developed dataset, combined with FPARANN (1980–2003) and FPARMCD15A2 (2004–2018), an overall increasing trend in FPAR was found for over 81% of the vegetated area of China from 1980 to 2018. FPAR increased more rapidly for over 83.7% of the area in the 2010s, and at a slower pace for over 62.1% of the area in the early 2000s, which was attributed to a decadal shifting of climate change. This study implies the new dataset is useful in quantifying vegetation changes and would be an important data source for future study of the carbon cycle, soil erosion, or evapotranspiration, with great application potential.

Net Primary Productivity Estimation of Terrestrial Ecosystems in China with Regard to Saturation Effects and Its Spatiotemporal Evolutionary Impact Factors

The net primary productivity (NPP) of vegetation holds a pivotal character for the global carbon balance as a key parameter for characterizing terrestrial ecological processes. The most commonly used indices for estimating vegetation NPP, for instance, the normalized difference vegetation index (NDVI), often suffer from saturation issues that can compromise the accuracy of NPP estimation. This research utilizes a new vegetation index based on the radial basis function (RBF) to estimate vegetation NPP in Chinese terrestrial ecosystems over the past two decades (2001–2020) and investigates the spatiotemporal variation characteristics of NPP and the driving mechanisms. The results indicate that the kernel vegetation index (kNDVI) can effectively alleviate the saturation problem and significantly improve the accuracy of NPP estimation compared to NDVI. Over the past two decades, the NPP of Chinese terrestrial vegetation ranged from 64.13 to 79.72 g C/m2, with a mean value of 72.75 g C/m2, showing a fluctuating upward trend. Changes in the NPP of terrestrial ecosystems in China are mainly affected by precipitation. The dominant factors influencing NPP changes varied over time and had different impacts. For instance, in the period of 2001–2005 the climate had a positive effect on NPP changes, with the dominant factors being evaporation and precipitation. However, in the period of 2010–2015 the dominant climate factors shifted to evaporation and temperature, and their effect on NPP changes became negative. The outcomes of this research aim to serve as a foundation for carbon cycle research and ecosystem environment construction in China.

Response of Plant and Soil N, P, and N:P Stoichiometry to N Addition in China: A Meta-Analysis.

Nitrogen (N) and phosphorus (P) are key elements essential for plant growth and development. Due to fertilizer application, rapid urbanization, and fossil fuel combustion, nitrogen deposition has reached relatively high levels in China. However, there is still uncertainty regarding the response of N:P stoichiometry in plants and soil to N deposition across different ecosystems. Therefore, a meta-analysis was conducted using 845 observations from 75 studies to evaluate the response of plant and soil N and P concentrations and N to P ratios across various ecosystems to N addition. The analysis revealed that N concentration and N:P stoichiometry in plants and soil increased under N addition, while P concentration in plants and soil decreased on average. Furthermore, the magnitude of these responses was related to the N input rate and experimental duration. Finally, the effects of N addition on N concentration, P concentration, and N:P in terrestrial ecosystems would alter their allocation patterns, depending on relevant climate factors such as mean annual temperature and mean annual precipitation. This study highlights the ecological impact of N addition on the biogeochemical cycling of major elements (N and P) in terrestrial ecosystems in China. These findings are necessary for improving our understanding of the characteristics of plant ecological stoichiometry and helping to plan measures for increasing N deposition.

Advances in Meta-Analysis of the Effects of Grazing on Grassland Ecosystems in China

Grassland ecosystems are among the largest terrestrial ecosystems in China, and grazing, as an important grassland management method, has direct and indirect impacts on grassland ecosystems. Meta-analyses can be used to systematically evaluate and summarize multiple findings from existing studies, but there have been few comparisons of meta-analysis methods. In this review, we summarize the effects of grazing on grassland plants and soil in the existing meta-analysis studies in China from 38 meta-analysis papers. The results show that they have consistent conclusions, such as grazing reduces the aboveground biomass by approximately half, increases the soil pH, decreases the C:N:P ratio, and reduces the number of topsoil microorganisms, but the conclusions of light and moderate grazing index changes vary greatly from study to study. The belowground biomass was generally found to increase, but it slightly decreased in some cases, and the total biomass generally decreased, but it slightly increased in other cases. Vegetation coverage increased during moderate grazing; the soil moisture content was highest for light grazing, and microbial diversity increased at light to moderate levels of grazing. There are also very inconsistent conclusions due to the different datasets and quantities of samples used in meta-analysis studies, as well as variations in the types and scales of grassland areas. The ranges of changes in other indicators were large, especially for the root-shoot ratio and soil carbon. However, changes in the aboveground biomass were generally stable. We suggest subsequent meta-analyses of grazing should further clarify the classification of grassland types and compare conclusions at different scales. Additionally, standardized network analyses are recommended for field manipulation experiments to further improve the accuracy of meta-analysis and reduce the temporal and spatial limitations of existing data.

A remote sensing based method for assessing the impact of O3 on the net primary productivity of terrestrial ecosystems in China

O3 pollution in China has been increasing in recent years, but the process of O3 impact on net primary productivity of terrestrial ecosystems remains unclear. We attempts to explore a remote sensing-based method to assess the impact of O3 on NPP of China’s terrestrial ecosystems by combining MODIS NPP and the latest ground observation data of O3 concentration. By comparing the NPP data of MODIS image pixels with the 6-year average AOT40 data of corresponding pixels, we extracted the signal data that highlighted the effects of O3 on NPP and established the response relationships between AOT40 and NPP. It was found that NPP was significantly negatively correlated with AOT40 in farmland and grassland ecosystems in China (farmland: r = 0.8674, p &amp;lt; 0.003, grassland: r = 0.7181, p &amp;lt; 0.03). Then the response relationships were adopted to evaluate the effect in China in 2014. The results showed that the estimated percentage of O3-induced NPP decline was in the range of 5%–35%. Among them, the most significant declines were found in farmland ecosystems, with the vast majority of declines in 10%–35%. The decrease rate of evergreen coniferous forests ranked second, mostly in the range of 15%–20%. The grassland ecosystems declined at a lower rate, almost between 5% and 15%. And the evergreen broad-leaved forests has the lowest decline rate, most distributed in 0%–5%. The highest percentage decreases were mainly found in the Beijing-Tianjin-Hebei region and Shandong Province. And the decline rate of farmland ecosystems was significantly higher than other ecosystem types.

Variation in Vegetation Quality of Terrestrial Ecosystems in China: Coupling Analysis Based on Remote Sensing and Typical Stations Monitoring Data

Vegetation is the most important component of the terrestrial ecosystem. Scientific and quantitative analysis of changes in vegetation quality is of great significance to the realization of ecosystem sustainability. Based on data of remote sensing and typical station monitoring, we examined dynamic NDVI (Normalized Difference Vegetation Index) changes in typical ecosystems from 1998 to 2020. We found that about 1/3 of China’s regions had significantly improved vegetation quality in the past 22 years, and 10% of the region had decreased, which indicated that China’s ecological situation is continuously improving. There is a large spatial heterogeneity in the trend of NDVI changes. The NDVI of agricultural and forest stations in the north of China rose relatively slowly. The NDVI of desert stations has a significant upward trend. The large-scale implementation of ecological restoration projects had improved vegetation conditions. The NDVI of forest stations and agricultural stations in the south of China still showed growth, which already has better vegetation conditions. This research can provide theoretical support for the long-term monitoring of different ecosystem types and ecological protection in China.

Soil moisture content-based analysis of terrestrial ecosystems in China: Water use efficiency of vegetation systems

Water is a prerequisite for the formation of earth-biochemical-ecological systems. Differences in the spatial and temporal distribution of water resources are important factors in the formation of differences in the distribution of vegetation in terrestrial ecosystems and are key to the differences in vegetation productivity. Vegetation water use efficiency is calculated by the total amount of fixed biogenic carbon per unit mass of water consumed in photosynthesis and can be used to assess the intensity and capacity of an ecosystem to use water biomass. Based on remote satellite sensing data, this study proposes a new water use efficiency assessment model. The model was validated using flux site data, and we analyzed the relative contribution of climate factors to soil moisture use efficiency using a first-difference method. The results revealed the following: (1) The soil moisture use efficiencies (SUE) of remote sensing data inversions that were evaluated using flux site data based on correlation coefficients and Nash coefficients showed high reliability, and only the NMG (Inner Mongolia) station showed low correlation among the nine sites. (2) Among the nine agricultural sub-regions in China, only the SUE of the Qinghai-Tibet Plateau region showed a decreasing trend (−1.08 g C/m−2 kg H2O yr), while all other regions showed an increasing trend. (3) The highest vegetation soil moisture use efficiency (1.83 g C/m−2 kg H2O) was found in ferralisols, while the lowest vegetation SUE (0.17 g C/m−2 kg H2O) was found in arid soils. The SUE of different vegetation types showed the characteristics of forest > scrub > cultivated vegetation > wetland > grassland. (4) The relative contribution of gross primary productivity (GPP) to the change in SUE was 37.53%, while the relative contribution of soil moisture content to the change in SUE was −26.71%. Among the five climatic factors, temperature was the most dominant factor affecting the change in SUE, followed by precipitation, net radiation, leaf area index, and potential evapotranspiration. Revealing the relationship between terrestrial ecosystem GPP, soil moisture content, and their responses to climate factors is a prerequisite for understanding the adaptation strategies of regional terrestrial ecosystems to global climate change, which can help to inform decision-making for the sustainable development of ecosystems.