Comprehensive analysis of the impact of climatic changes on Chinese terrestrial net primary productivity

An integrated approach to prioritizing ecological restoration of abandoned mine lands based on cost-benefit analysis

How to increase the usable land area by adhering to environmentally friendly ecological restoration of mines with limited funds is a challenge that many cities are currently facing. Cost-benefit analysis (CBA) can provide efficient and effective restoration decisions for abandoned mine land (AML) ecological restoration with limited financial resources. Thus, this study proposes an integrated approach for coupling ecological benefits and restoration costs, including hotspots/coldspots analysis based on five ecosystem services (ESs), landscape connectivity analysis based on graph theory model, hidden costs, and project implementation costs to prioritize AML restoration. The study was conducted on 54 abandoned mine lands (AMLs) in Chaoyang city, the ecological security barrier of China's northern sand prevention belt (NSPB). The comprehensive analysis prioritized the restoration of AMLs into four levels, of which 9 mines were in priority I, where restoration was recommended as a priority, and 22 mines were in priority II, where restoration could be carried out within the affordability of funds. In addition, our model indicates areas with high ecological benefits, in which the ecological source area (7423.66 km2) and the ecosystem service hotspots area (2028.44 km2) are mostly distributed in the southwestern part of Chaoyang city, the two mountain ranges of Songling mountain and Nuruerhu mountain. This study provides scientific spatial guidance to ensure that the AMLs realizes effective restoration and management.

The Different Impacts of Climate Variability and Human Activities on NPP in the Guangdong–Hong Kong–Macao Greater Bay Area

As two main drivers of vegetation dynamics, climate variability and human activities greatly influence net primary productivity (NPP) variability by altering the hydrothermal conditions and biogeochemical cycles. Therefore, studying NPP variability and its drivers is crucial to understanding the patterns and mechanisms that sustain regional ecosystem structures and functions under ongoing climate variability and human activities. In this study, three indexes, namely the potential NPP (NPPp), actual NPP (NPPa), and human-induced NPP (NPPh), and their variability from 2000 to 2020 in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) were estimated and analyzed. Six main scenarios were generated based on change trends in the three indexes over the past 21 years, and the different relative impacts of climate variability and human activities on NPPa variability were quantitatively analyzed and identified. The results showed that the NPPp, NPPa, and NPPh had heterogeneous spatial distributions, and the average NPPp and NPPa values over the whole study area increased at rates of 3.63 and 6.94 gC·m−2·yr−1 from 2000 to 2020, respectively, while the NPPh decreased at a rate of −4.43 gC·m−2·yr−1. Climate variability and the combined effects of climate variability and human activities were the major driving factors of the NPPa increases, accounting for more than 72% of the total pixels, while the combined effects of the two factors caused the NPPa values to increase by 32–54% of the area in all cities expect Macao and across all vegetation ecosystems. Human activities often led to decreases in NPPa over more than 16% of the total pixels, and were mainly concentrated in the central cities of the GBA. The results can provide a reference for understanding NPP changes and can offer a theoretical basis for implementing ecosystem restoration, ecological construction, and conservation practices in the GBA.

Three Decades of Gross Primary Production (GPP) in China: Variations, Trends, Attributions, and Prediction Inferred from Multiple Datasets and Time Series Modeling

The accurate estimation of gross primary production (GPP) is crucial to understanding plant carbon sequestration and grasping the quality of the ecological environment. Nevertheless, due to the inconsistencies of current GPP products, the variations, trends and short-term predictions of GPP have not been sufficiently well studied. In this study, we explore the spatiotemporal variability and trends of GPP and its associated climatic and anthropogenic factors in China from 1982 to 2015, mainly based on the optimum light use efficiency (LUEopt) product. We also employ an autoregressive integrated moving average (ARIMA) model to forecast the monthly GPP for a one-year lead time. The results show that GPP experienced an upward trend of 2.268 g C/m2 per year during the studied period, that is, an increasing rate of 3.9% per decade since 1982. However, these trend changes revealed distinct heterogeneity across space and time. The positive trends were mainly distributed in the Yellow River and Huaihe River out of the nine major river basins in China. We found that the dynamics of GPP were concurrently affected by climate factors and human activities. While air temperature and leaf area index (LAI) played dominant roles at a national level, the effects of precipitation, downward shortwave radiation (SRAD), carbon dioxide (CO2) and aerosol optical depth (AOD) exhibited discrepancies in terms of degree and scope. The ARIMA model achieved satisfactory prediction performance in most areas, though the accuracy was influenced by both data values and data quality. The model can potentially be generalized for other biophysical parameters with distinct seasonality. Our findings are further verified and corroborated by four widely used GPP products, demonstrating a good consistency of GPP trends and prediction. Our analysis provides a robust framework for characterizing long-term GPP dynamics that shed light on the improved assessment of the environmental quality of terrestrial ecosystems.

Change Trend and Restoration Potential of Vegetation Net Primary Productivity in China over the Past 20 Years

As an important vegetation parameter and ecological index, vegetation net primary productivity (NPP) can intuitively reflect changes in the ecological environment and the level of the carbon budget. However, the change trend of NPP and its recovery potential in China over the past 20 years remain unclear. Here, we used trend analysis, multiple regression analysis and residual analysis methods to analyse the change trend in the NPP of China’s terrestrial ecosystems from 2000 to 2019, as well as the climax background, restoration status and restoration potential of the NPP of forest, grassland and desert ecosystems. The results showed that (1) the change in vegetation NPP in China from 2000 to 2019 showed a continuous upward trend, with a change slope of 2.39 gC/m2/a2, and the area with a positive slope of change accounted for 68.10% of the country’s land area. The contribution rates of meteorological conditions and human activities to vegetation NPP changes were 85.41% and 14.59%, respectively. (2) The results obtained by the regression analysis method of meteorological conditions based on nature reserves could reflect the zonal climax vegetation status to a large extent, and the obtained values had a smooth transition within each ecogeographical division and between each ecogeographical division, which truly reflected the law of gradual change in climate, vegetation and natural conditions. The annual total NPP of the climax background vegetation in China’s forest, grassland and desert ecosystems was approximately 2.76 ± 0.28 PgC, and the annual total NPP of the three ecosystems was 1.90 ± 0.2 PgC, 0.80 ± 0.07 PgC and 0.009 ± 0.0005 PgC, respectively. (3) The annual total vegetation NPP of the restoration status of China’s forest, grassland and desert ecosystems was 2.24 PgC, and the annual total vegetation NPP of the three was 1.54 PgC, 0.65 PgC and 0.007 PgC, respectively. Benefiting from the effective implementation of climate warming and humidification and ecological engineering, the agro-pastoral zone, the Loess Plateau, the eastern Sichuan Basin and the Greater Khingan Range had the most significant increases in the past 20 years. (4) The annual total vegetation NPP of China’s forest, grassland and desert ecosystem restoration potential was approximately 0.52 ± 0.28 PgC, which accounted for approximately 19.05% of the annual total NPP of the climax background vegetation. The annual total vegetation NPP of forest, grassland and desert ecosystems restoration status was 0.36 ± 0.2 PgC, 0.16 ± 0.07 PgC and 0.002 ± 0.0005 PgC, respectively; the restoration potential accounted for 18.80%, 9.67% and 23.95% of the climax background vegetation NPP, respectively. The deployment of ecological projects should fully consider the restrictive climate conditions for decision makers and ecological scholars, and the benefits and costs of the projects should be considered comprehensively.

Spatial relationships between ecosystem services and socioecological drivers across a large-scale region: A case study in the Yellow River Basin

Understanding the relationships between ecosystem services (ES) and their underlying socioecological drivers is essential for forming the efficient management decisions of ecosystems. We use a large watershed area as a case-study to analyze trade-offs/synergies and bundles of ESs and identify the associated socioecological variables (SEVs). This study assessed the supply of 7 ES indicators, namely, three provisioning services (crop production, livestock production, and industrial production), three regulating services (water conservation, soil conservation, and carbon sequestration), and one cultural service (recreation), across 65 municipalities in the Yellow River Basin (YRB) in China. We analyzed the paired trade-offs/synergies using Spearman's coefficient and identified the ES bundles (ESBs) by applying principal component analysis and K-means clustering. Subsequently, we detected the SEVs that affect the ES supply using the geo-detector model and characterized the associations between ESBs and socioecological clusters according to the spatial overlap. The results demonstrated that the synergies between ESs substantially exceeded the trade-offs, among which the strongest synergies were between the crop production and the livestock production, and both responded strongly to the cropland and the population density. Trade-offs were identified between provisioning services and soil conservation. Municipalities were grouped into three ESBs in the YRB. The ESB, which was dominated by provisioning ESs, was associated with areas where cropland, precipitation and socioeconomic conditions were all important, and the regulation of ESB was linked to regions with distinct ecological characteristics. We also identified an ESB that was dominated by carbon sequestration, as determined by extensive grassland and bare land. The land use/land cover strongly affected the characteristics of the ESBs. The findings can be used by land managers to identify areas in which ESs are dominant, to determine the associations of these compositions of the ESs with SEVs, and to support the formulation of optimal ES management in large-scale basins.

Multifunctional landscapes identification and associated development zoning in mountainous area

Multifunctional landscape has become a new discipline growth point in landscape ecology. Globally mountainous areas occupy about one fifth of Earth's surface. However, few studies focused on landscape multifunctionality in mountainous areas. Taking Dali Bai Autonomous Prefecture, China, as a case study area, five typical landscape functions (net primary productivity, soil retention, water yield, crop production, and residential support) were quantified and mapped. Hotspots of multiple landscape functions were identified using spatial overlap tools, interaction between each landscape function pair was discussed through Spearman's rank correlation analysis, and development zoning was conducted based on landscape function bundle. The results showed that, about 61% of the study area had at least one kind of landscape function hotspot, with only 2.7% covering three or more kinds of landscape function hotspots. Significant trade-offs or synergies existed between all pairs of landscape functions, except the pair of net primary productivity and residential support. With the application of Self-Organizing Feature Maps (SOFM) method, the study area was divided into four types of development zones (i.e. ecological shelter area, ecological transition area, suburban development area, and urban agglomeration area) which were all corresponding to different landscape function bundles. This study could provide spatial guidance for differentiated sustainable developing in mountainous areas according to local conditions of landscape multifunctionality.

A framework for assessing the effects of afforestation and South-to-North Water Transfer on nitrogen and phosphorus uptake by plants in a critical riparian zone

The uptake of nitrogen (N) and phosphorus (P) by plants in riparian zones can significantly decrease the water pollution risk. Moreover, the vegetation area in riparian zone can be impacted by raising of water level and afforestation. As the largest reservoir in North China, the Miyun Reservoir is affected by the South-to-North Water Transfer (SNWT) and large-scale afforestation. However, few efficient technology frameworks that can be used to assess the effects of similar anthropogenic projections on N and P uptake by plants at riparian zone catchment scale have been reported. Therefore, this study proposed a framework including an ecological simulation tool coupled with multi-source data and scenario setting methods to identify the effects of these two projects on the uptake of N and P by plants in Miyun Reservoir riparian zone from April to September in 2015. The results show that the total N and P uptake by plants in Miyun Reservoir riparian zone are 1214.18 t and 148.66 t in growing seasons. After afforestation, the N (P) removal will increase by 2.56 (2.17) times in the impacted area (below 160 m in elevation). When the water level rises to 150 m in elevation, the joint effects of afforestation and SNWT will increase the total N and P removals by 851.18 t and 83.33 t. This implies that the afforestation can offset the negative effect on N (P) removal caused by SNWT. Overall, this study can provide useful scientific reference for the design and effective management of the riparian zone.

Influence of the geographic proximity of city features on the spatial variation of urban carbon sinks: A case study on the Pearl River Delta

Locations of city features, e.g., city centers, roads, railways, and rivers, may impact urban carbon sinks. Therefore, the effects of city features on spatial variations of urban carbon sinks were investigated using geographic proximity data. The main results were as follows. (1) Carbon sink function varied in a complex manner with distance from the city center and with city size. The carbon sink per unit area increased with distance from the prefecture-level city center (0-30 km), with the dominant influence occurring within a 9 km radius. The lowest carbon sink per unit area was observed at a distance of 12 km from the city center of the provincial capital city (Guangzhou) and special economic zone (Shenzhen), which may be suburban industrial zones. (2) Carbon sinks decreased with increases in road grades as a result of the different functions and traffic flow, and carbon sinks were lowest near city express ways. For highways, carbon sinks were lower near highway entrances and exits. Carbon sinks around ordinary railways were higher than those around subways and light rail, but carbon sink characteristics grew more complex with increasing distances from subways and light rail. (3) Rivers were closely related to the urban layout. Grade I (i.e., larger) rivers were associated with lower carbon sinks, and carbon sink characteristics became increasingly complex around larger rivers. Within a 0-1000 m distance of all rivers, the carbon sink per unit area increased rapidly, but carbon sink characteristics differed slightly for grade I rivers. This study implies that it is important to take urbanization spatial position effects into account while assessing regional carbon sinks during urbanization and development.

Influence of land urbanization on carbon sequestration of urban vegetation: A temporal cooperativity analysis in Guangzhou as an example

Land urbanization can affect carbon sequestration. In this study, the relationships between land urbanization and carbon sequestration of urban vegetation were studied for Guangzhou, China. The methodology was based on land use data from Thematic Mapper (TM) imagery, MODIS13Q1 data, and climate data, and the improved Carnegie-Ames-Stanford approach (CASA) model and linear system models were employed. Characteristics such as the amount of expansion, spatial agglomeration, spatial expansion intensity, and spatial growth of built-up land were analyzed, and the influence of land urbanization (built-up land expansion) on carbon sequestration of urban vegetation was elucidated by a temporal sequential cooperativity analysis. The main results were as follows. (1) Land urbanization had a clear influence on carbon sequestration of urban vegetation in Guangzhou, and the proportion and spatial agglomeration of built-up land showed significant negative correlations with this carbon sequestration; the correlation coefficients were -0.443 and -0.537, respectively, in 2014. (2) The spatial expansion intensity and spatial growth of built-up land showed small correlations with carbon sequestration, and the correlations from 2000 to 2005 were relatively larger than those at other times; this was because the built-up land expansion speed was the fastest during this period. (3) The temporal sequential cooperativity analysis revealed that carbon was lost as natural surfaces were transformed to artificial surfaces, and land urbanization effects on carbon sequestration showed no significant temporal lag. Carbon sequestration of urban vegetation in the city could be improved by adding urban green spaces; however, this would likely take some time as the system recovers.

Determining the contributions of urbanisation and climate change to NPP variations over the last decade in the Yangtze River Delta, China

Terrestrial net primary production (NPP) is an important measure of global change, and identifying the relative contributions of urbanisation and climate change to NPP is important for understanding the impact of human and natural influences on terrestrial systems and the carbon cycle. The objective of this study was to reveal how urbanisation and climate drive changes in NPP. Satellite-based estimates of NPP collected over a 12-year period (1999-2010) were analysed to identify NPP variations in the Yangtze River Delta. Temporal and spatial analysis methods were used to identify the relationships among NPP, nighttime light urbanisation index values, and climatic factors from pixel to regional scales. The NPP of the entire Yangtze River Delta decreased slightly at a rate of -0.5 g C m(-2)a(-1) from 1999 to 2010, but this change was not significant. However, in the urban region, NPP decreased significantly (p<0.05) at a rate of -4.7 g C m(-2)a(-1) due to urbanisation processes. A spatially explicit method was proposed to partition the relative contributions of urbanisation and climate change to NPP variation. The results revealed that the urbanisation factor is the main driving force for NPP change in high-speed urbanisation areas, and the factor accounted for 47% of the variations. However, in the forest and farm regions, the NPP variation was mainly controlled by climate change and residual factors.

Variations of NPP and Carbon Stock Benefits before and after the Grain for Green Project in Northern Shaanxi

Northern Shaanxi is one of the pilot zones for implementating of Grain for Green Project. Monitoring the net primary production (NPP) change before and after the project would help understand the spatial patterns and the accomplishment of the Grain for Green project, and also be propitious to calibrate the projects benefits. Using the improved Carnegie-Ames-Stanford Approach (CASA) modeling, the terrestrial NPP was estimated. Meanwhile, the carbon (C) stock benefits of Grain for Green Project were analyzed through the different land cover types and slope gradients. The results are as follows: (1) There was an apparently increase of average NPP in Northern Shaanxi from 2000 to 2007. Based on the trend analysis, the areas with high NPP growth rate (more than 20%) account for about 75% area of the whole Northern Shaanxi. (2) The C stock increased significantly from 2000 to 2007 in Northern Shaanxi. The total C stock of vegetation was 7169.4 t and the C stock per unit area was 121.2 t Ckm-2a-1. The total C stock of sloping farmland was more than 2000 t, which account for 31.3% of the whole C stock in Northern Shaanxi. (3) The main districts of the Grain for Green Project, such as the sloping farmland, open forest and lands with slope 15° to 35°, gained better C stock benefits than other areas. The results in this study indicated that the Grain for Green project resulted in good C stock benefits.

Evaluating nitrogen removal by vegetation uptake using satellite image time series in riparian catchments

Nitrogen (N) removal by vegetation uptake is one of the most important functions of riparian buffer zones in preventing non-point source pollution (NSP), and many studies about N uptake at the river reach scale have proven the effectiveness of plants in controlling nutrient pollution. However, at the watershed level, the riparian zones form dendritic networks and, as such, may be the predominant spatially structured feature in catchments and landscapes. Thus, assessing the functions of riparian system at the basin scale is important. In this study, a new method coupling remote sensing and ecological models was used to assess the N removal by riparian vegetation on a large spatial scale. The study site is located around the Guanting reservoir in Beijing, China, which was abandoned as the source water system for Beijing due to serious NSP in 1997. SPOT 5 data was used to map the land cover, and Landsat-5 TM time series images were used to retrieve land surface parameters. A modified forest nutrient cycling and biomass model (ForNBM) was used to simulate N removal, and the modified net primary productivity (NPP) module was driven by remote sensing image time series. Besides the remote sensing data, the necessary database included meteorological data, soil chemical and physical data and plant nutrient data. Pot and plot experiments were used to calibrate and validate the simulations. Our study has proven that, by coupling remote sensing data and parameters retrieval techniques to plant growth process models, catchment scale estimations of nitrogen uptake rates can be improved by spatial pixel-based modelling.