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

Assessment of vegetation net primary productivity variation and influencing factors in the Beijing-Tianjin-Hebei region

Exploring the spatiotemporal variations of vegetation net primary productivity (NPP) and analyzing the relationships between NPP and its influencing factors are vital for ecological protection in the Beijing-Tianjin-Hebei (BTH) region. In this study, we employed the CASA model in conjunction with spatiotemporal analysis techniques to estimate and analyze the spatiotemporal variations of NPP in BTH and different ecological function sub-regions over the past two decades. Subsequently, we established three scenarios (actual, climate-driven and land cover-driven) to assess the influencing factors and quantify their relative contributions. The results indicated that the overall NPP in BTH exhibited a discernible upward trend from 2000 to 2020, with a growth rate of 3.83 gC·m-2a-1. Furthermore, all six sub-regions exhibited an increase. The Bashang Plateau Ecological Protection Zone (BP) exhibited the highest growth rate (5.03 gC·m-2a-1), while the Low Plains Ecological Restoration Zone (LP) exhibited the lowest (2.07 gC·m-2a-1). Geographically, the stability of NPP exhibited a spatial pattern of gradual increase from west to east. Climate and land cover changes collectively increased NPP by 0.04 TgC·a-1 and 0.07 TgC·a-1, respectively, in the BTH region. Climate factors were found to have the greatest influence on NPP variations, contributing 40.49% across the BTH region. This influence exhibited a decreasing trend from northwest to southeast, with precipitation identified as the most influential climatic factor compared to temperature and solar radiation. Land cover change has profound effects on ecosystems, which is an important factor on NPP. From 2000 to 2020, 15.45% area of the BTH region underwent land cover type change, resulting in a total increase in NPP of 1.33 TgC. The conversion of grass into forest brought about the 0.89 TgC increase in NPP, which is the largest of all change types. In the area where land cover had undergone change, the land cover factor has been found to be the dominant factor influencing variations in NPP, with an average contribution of 49.37%. In contrast, in the south-central area where there has been no change in land cover, the residual factor has been identified as the most influential factor influencing variations in NPP. Our study highlights the important role of land cover change in influencing NPP variations in BTH. It also offers a novel approach to elucidating the influences of diverse factors on NPP, which is crucial for the scientific assessment of vegetation productivity and carbon sequestration capacity.

Spatiotemporal patterns of net regional productivity and its causes throughout Ordos, China

A comprehensive understanding of the terrestrial carbon sink is essential for proficient regional carbon management. However, previous studies predominantly relied on net ecosystem productivity (NEP) as an indicator of regional carbon sink, overlooking the impacts of carbon emissions from physical processes and carbon leakage associated with anthropogenic activities. In this study, net region productivity (NRP), a vital metric representing carbon sink dynamics in regional multi-landscape ecosystems, was employed to systematically analyze the patterns, trends, and causes of carbon sink in Ordos. The results revealed that spatially averaged NRP in Ordos was 70.334 g·m-2·a-1, indicating a carbon sink effect. The coefficient of variation of NRP was 68.035%, with a higher NRP in the southern region. Normalized difference vegetation index (NDVI) predominantly controlled the spatial heterogeneity of NRP in Ordos, while precipitation emerged as the primary climatic factor influencing spatial differences in NRP. Regional variations in the impact of environmental factors on NRP were evident. In most areas, NRP showed a notable increasing trend influenced by various factors. Specifically, the simultaneous rise in NDVI and improvements in hydrothermal conditions contributed to the gradual elevation of NRP, each with varying degrees of influence across Ordos and its sub-regions.

Unraveling the enigma of NPP variation in Chinese vegetation ecosystems: The interplay of climate change and land use change

Global carbon emissions have exacerbated the greenhouse effect, exerting a profound impact on ecosystems worldwide. Gaining an understanding of the fluctuations in vegetation net primary productivity (NPP) is pivotal in the assessment of environmental quality, estimation of carbon source/sink potential, and facilitation of ecological restoration. Employing MODIS and meteorological data, we conducted a comprehensive analysis of NPP evolution in Chinese vegetation ecosystems (VESs), employing Theil-Sen median trend analysis and the Mann-Kendall test. Furthermore, utilizing scenario-based analysis, we quantitatively determined the respective contributions of climate change and land use change to NPP variations across various scales. The overall NPP exhibited a discernible upward trend from 2000 to 2020, with a growth rate of 5.83 gC·m-2·year-1. Forestland ecosystem (FES) displayed the highest rate of increase (9.40 gC·m-2·year-1), followed by cropland ecosystem (CES) (4.00 gC·m-2·year-1) and grassland ecosystem (GES) (3.40 gC·m-2·year-1). Geographically, NPP exhibited a spatial pattern characterized by elevated values in the southeast and diminished values in the northwest. In addition, climate change had elevated 76.39 % of CES NPP, 90.62 % of FES NPP, and 71.78 % of GES NPP. At the national level, climate change accounted for 83.14 % of the NPP changes, while land use change contributed 14.14 %. Notably, climate change emerged as the primary driving force behind NPP variations across all VEGs, with land use change exerting the most pronounced influence on CES. At the grid scale (2 km × 2 km), land use change played a substantial role in all VEGs, contributing 60.01 % in CES, 54.20 % in FES, and 55.61 % in GES of the NPP variations.

Refined assessment of space-time changes, influencing factors and socio-economic impacts of the terrestrial ecosystem quality: A case study of the GBA

The terrestrial ecosystem is the cradle of energy and material basis for human survival and development. However, there are large research deficits in accurately and finely depicting the quality of the terrestrial ecosystem (QTE) and assessing its changing triggers' contribution. Here, we summarized three major principles for selecting image sources in remote sensing data fusion. A continuous 30-m net vegetation productivity (NPP) dataset during 2000-2019 for the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) was derived by using the Carnegie-Ames-Stanford approach model and pre-fused normalized difference vegetation index. The factors' contributions to the QTE changes were quantitatively assessed. The role of the QTE in affecting the socio-economic and its behind mechanisms was quantitatively investigated. The results showed that: (1) High-quality images sources are the preference for spatio-temporal fusion of remote sensing data. Images with close month, the same season and year, and sensors should be then selected. Images of different sensors with similar spectral bandwidth, the ones from adjacent years and seasons, can be alternately considered. (2) Fine-resolution NPP has higher accuracy than coarse-resolution NPP and has marked advantages in finely characterizing the QTE. In the past 20 years, the QTE in the GBA has shown a fluctuating increasing trend (0.20 Tg C/yr). (3) Human activities contributed 54.19% of the QTE changes in the GBA, and dominates the QTE changes in the central rapidly urbanizing areas. Residual factors accounted for an overall contribution ratio of 35.71%. Climate change dominants the peripheral forest variations in the GBA. (4) In the GBA, the improvement of QTE has a significant positive socio-economic impact, it contributes to the GDP increment firstly then the GDP aggregate indirectly. Our results highlight that it is of great urgent to estimate long-term continuous NPP with high spatio-temporal resolution globally. Controlling strategies should be implemented to reduce factitious impacts on QTE. High level of ecological and environmental protection promotes the sustainable development.

Impact assessment of urbanization on vegetation net primary productivity: A case study of the core development area in central plains urban agglomeration, China

Rapid urbanization process has a negative or positive impact on vegetation growth. Net primary productivity (NPP) is an effective indicator to characterize vegetation growth status. Taking the core development area of the Central Plains urban agglomeration as the study area, we estimated the NPP and its change trend in the past four decades using the Carnegie-Ames-Stanford Approach (CASA) model and statistical analysis based on meteorological and multi-source remote sensing data. Meanwhile, combined with the urbanization impact framework, we further analyzed urbanization's direct and indirect impact on NPP. The results showed that the urban area increased by 2688 km² during a high-speed urbanization process from 1983 to 2019. As a result of the intense urbanization process, a continuous NPP decrease (direct impact) can be seen, which aggravated along with the acceleration of the urban expansion, and the mean value of direct impact was 130.84 g C·m^-2·a^-1. Meanwhile, urbanization also had a positive impact on NPP (indirect impact). The indirect impact showed an increasing trend during urbanization with a mean value of 10.91 g C·m^-2·a^-1. The indirect impact was mainly related to temperature in climatic factors. The indirect impact has a seasonal heterogeneity, and high-temperature environments of urban areas are more effective in promoting vegetation growth in autumn and winter than in summer. Among different cities, high-speed development cities have higher indirect impact values than medium's and low's because of better ecological construction. This study is of great significance for understanding the impact of urbanization on vegetation growth in the Central Plains urban agglomeration area, supporting urban greening plans, and building sustainable and resilient urban agglomerations.

Net Primary Productivity Variations Associated with Climate Change and Human Activities in Nanjing Metropolitan Area of China

Rapid economic development has changed land use and population density, which in turn affects the stability and carbon sequestration capacity of regional ecosystems. Net primary productivity (NPP) can reflect the carbon sequestration capacity of ecosystems and is affected by both climate change and human activities. Therefore, quantifying the relative contributions of climate change and human activities on NPP can help us understand the impact of climate change and human activities on the carbon sequestration capacity of ecosystems. At present, researchers have paid more attention to the impact of climate change and land use change on NPP. However, few studies have analyzed the response of the NPP to gross domestic product (GDP) and population density variations on a pixel scale. Therefore, this paper analyzes the impact of climate change and human activities to NPP on a pixel scale in the Nanjing metropolitan area. During the period 2000-2019, the annual mean NPP was 494.89 g C·m^-2·year^-1, and the NPP in the south of the Nanjing metropolitan area was higher than that in the north. The NPP was higher in the forest, followed by unused land, grassland, and cropland. In the past 20 years, the annual mean NPP showed a significant upward trend, with a growth rate of 3.78 g C·m^-2·year^-1. The increase in temperature and precipitation has led to an increasing trend of regional NPP, and the impact of precipitation on NPP was more significant than that of temperature. The transformation of land use from low-NPP type to high-NPP type also led to an increase in NPP. Land use change from high-NPP type to low-NPP type was the main cause of regional NPP decline. Residual analysis was used to analyze the impact of human activities on NPP. Over the last 20 years, the NPP affected by human activities (NPP_hum) showed a high spatial pattern in the south and a low spatial pattern in the north, and the annual mean NPP_hum also showed a fluctuating upward trend, with a growth rate of 2.00 g C·m^-2·year^-1. The NPP_hum was influenced by both GDP and population density, and the impact of population density on NPP was greater than that of GDP.

Response of Land Use and Net Primary Productivity to Coal Mining: A Case Study of Huainan City and Its Mining Areas

The terrestrial ecosystem carbon cycle is essential to the global carbon cycle. Mining activities have seriously damaged the terrestrial ecosystem and destroyed the carbon sequestration ability of vegetation, which is of great significance to studying the effect of coal mining on land structure change and carbon sink function in cities and mining areas. However, the existing research lacks the targeted analysis of the carbon sink level of the mining area combined with the mining data. Based on the coal-mining information, land-use data, and MODIS NPP data, this study analyzed the spatio-temporal change characteristics of land use and NPP in Huainan City and its mining areas from 2001 to 2020. The results showed that: (1) 22.5% of the land types in the mining area have changed, much higher than 3.2% in Huainan; 40.08 km2 of the cropland in the mining area has been transformed into waterbodies, seriously affecting regional food security. (2) NPP fluctuates with rainfall, has a weak correlation with temperature, and is restricted by coal-mining factors. The average NPP of most coal mines is significantly lower than that of non-mining areas. The NPP of Huainan City showed an overall growth trend of 2.20 g/(m2 × a), which was much higher than the average value of 0.43 g/(m2 × a) in the mining area. Especially in the Guqiao mine, the difference in NPPslope before and after mining was as high as 16.92 g/(m2 × a). (3) The probability integral method was used to estimate that 195.16 km2 of land in Huainan would be damaged by mining in 2020. The distribution of damage degree was negatively correlated with NPPslope, which meant the more serious the damage was, the less NPPslope was. This study revealed the characteristics of land-use change and NPP spatio-temporal response in resource-based cities and mining-disturbed areas. It quantitatively estimated the impact of mining activities on regional carbon sink function. It can provide theory and data support for mining areas to carry out ecological protection and restoration, improve the environmental service function of resource-based cities, and formulate sustainable development strategies.

The Warming Effect of Urbanization in the Urban Agglomeration Area Accelerates Vegetation Growth on the Urban–Rural Gradient

Urbanization has changed the environmental conditions of vegetation growth, such as the heat island effect, which has an indirect impact on vegetation growth. However, the extent to which the direct and indirect effects of the thermal environment changes caused by urbanization on vegetation growth are unclear. In this study, taking the example of the Guangdong–Hong Kong–Macao Greater Bay Area, a fast-growing national urban agglomeration in China, the relationship between vegetation growth and warming conditions during the period from 2001 to 2020 were explored by the net primary productivity (NPP) and land surface temperature (LST), based on the vegetation growth theory, in urban environments. The results show that there is a significant exponential relationship between the warming and the growth of large-scale vegetation. This relationship is mainly attributable to thermal environmental factors, since their multi-year average contribution rate on the interannual scale is 95.02%. The contribution rate varies on the seasonal scale, according to which the contribution rate is the largest in autumn and the smallest in winter. This research is of great significance for predicting the potential response of vegetation growth to future climate warming and improving vegetation growth in urban areas.

The Relative Roles of Climate Variation and Human Activities in Vegetation Dynamics in Coastal China from 2000 to 2019

Vegetation in the terrestrial ecosystem, sensitive to climate change and human activities, exerts a crucial influence on the carbon cycles in land, ocean, and atmosphere. Discrimination between climate and human-induced vegetation dynamics is advocated but still limited, especially in coastal China, which is characterized by a developed economy, a large population, and high food production, but also by unprecedented climate change and warming. Taking coastal China as the research area, our study used the normalized difference vegetation index (NDVI) in growing seasons, as well as precipitation, temperature, and sunlight hours datasets, adopted residual trend analysis at pixel and regional scales in coastal China from 2000–2019 and aims to (1) delineate the patterns and processes of vegetation changes, and (2) separate the relative contributions of climate and human activities by adopting residual trend analysis. The results indicated that (1) coastal China experienced the most vegetation greening (83.04% of the whole region) and partial degradation (16.86% of the whole region) with significant spatial heterogeneity; (2) compared with climate change, human activities have a greater positive impact on NDVI, and the regions were mainly located in the north of the North China Plain and the south of southern China; (3) the relative contribution rates of climate change and human activities were detected to be 0–60% and 60–100%, respectively; (4) in the northern coastal areas, the improvement of cultivated land management greatly promoted the greening of vegetation and thus the increase of grain yield, while in southern coastal areas, afforestation and the restoration of degraded forest were responsible for vegetation restoration; and (5) similar results obtained by partial correlation between nighttime lights and NDVI indicated the reliability of the residual trend analysis. The linear relationships of precipitation, temperature, and radiation on NDVI may limit the accurate estimation of climate drivers on vegetation, and further ecosystem process-modeling approaches can be used to estimate the relative contribution of climate change and human activities. The findings in our research emphasized that the attribution for vegetation dynamics with heterogeneity can provide evidence for the designation of rational ecological conservation policies.

Monitoring and Evaluation of Eco-Environment Quality Based on Remote Sensing-Based Ecological Index (RSEI) in Taihu Lake Basin, China

Rapid and effective access to the spatiotemporal patterns and evolutionary trends of the regional eco-environment is key to regional environment protection and planning. Based on the Google Earth Engine platform, we use 165 Landsat images from the summer and autumn seasons (May–November) of 2000, 2010, and 2018 as data sources to calculate the RSEI, which represents the quality of the eco-environment, and then analyze the factors influencing the spatial heterogeneity of the eco-environment and the relationship between eco-environment and land-use changes based on RSEI. The results showed the following: (1) From 2000 to 2018, the overall ecological environment quality of the Taihu Lake Basin showed a stage of rapid decline (2000–2010) and a stage of slow decline (2010–2018). (2) The factors were ranked in order of their explanatory power for the spatial heterogeneity of the RSEI: land-use (0.594) > population density (0.418) > slope (0.309) > elevation (0.308) > GDP (0.304) > temperature (0.233) > precipitation (0.208). An interactive effect was found for each factor of the RSEI, which is mainly represented by a mutual enhancement. (3) From 2000 to 2010, the rapid urban expansion was the main reason for the deterioration of ecological quality. From 2010 to 2018, urban expansion slowed down, and the trend of ecological quality deterioration was effectively curbed. Therefore, promoting the intensive use of land and reducing construction land expansion are key to ensuring sustainable regional socio-economic development.

Seasonal and inter-annual variability of bacterioplankton communities in the subtropical Pearl River Estuary, China

It is widely recognized that environmental factors substantially influence on the seasonal and inter-annual variability of bacterioplankton communities, yet little is known about the seasonality of bacterioplankton communities in subtropical estuaries at longer-term time scales. Here, the bacterioplankton communities from the eight major outlets of the subtropical Pearl River Estuary were investigated across 3 years (2017-2019) using full-length 16S rRNA gene sequencing. Significant seasonal and inter-annual variation was observed in bacterioplankton community compositions across the 3 years (p < 0.05). In addition, the inferred functional composition of the communities varied with seasons, although not significantly, suggesting that functional redundancy existed among communities and across seasons that could help to cope with environmental changes. Five evaluated environmental parameters (temperature, salinity, pH, total dissolved solids (TDS), total phosphorus (TP)) were significantly correlated with community composition variation, while only three environmental parameters (temperature, pH, and TDS) were correlated with variation in inferred functional composition. Moreover, community composition tracked the seasonal temperature gradients, indicating that temperature was a key environmental factor that affected bacterioplankton community's variation along with seasonal succession patterns. Gammaproteobacteria and Alphaproteobacteria were the most dominant classes in the surface waters of Pearl River Estuary, and their members exhibited divergent responses to temperature changes, while several taxa within these group could be indicators of low and high temperatures that are associated with seasonal changes. These results strengthen our understanding of bacterioplankton community variation in association with temperature-dependent seasonal changes in subtropical estuarine ecosystems.

Where Anthropogenic Activity Occurs, Anthropogenic Activity Dominates Vegetation Net Primary Productivity Change

Anthropogenic activities and climate change affect the type, structure and function of ecosystems, resulting in important changes in vegetation net primary productivity (NPP). Therefore, in this study we used the vegetation photosynthesis model (VPM) to reveal the spatiotemporal variations in NPP in Xinjiang from 2000 to 2019. The impacts of climate change and anthropogenic activities on NPP changes were quantified and separated by the residual analysis-control variables (RES-CON) method. The results showed that the average NPP in Xinjiang increased by 17.77% from 2000 to 2019. Anthropogenic activities and climate change generally had a positive impact on NPP from 2000 to 2019. The most important anthropogenic activity was land use and land cover (LULC) transformation from grass to arable land, which significantly increased vegetation productivity. Regarding climate change, precipitation has played a significant role in promoting the productivity of vegetation. Overall, the average contribution of climate change (temperature and precipitation) to NPP variation (21.44%) is much greater than the contribution of anthropogenic activities (3.46%), but in areas where anthropogenic activities occur, the average contribution of anthropogenic activities to NPP variation (75.01%) is much greater than the average contribution of climate change (15.53%). Where there are no anthropogenic activities, the average contribution of climate change to NPP variation is 21.72%. In summary, anthropogenic activities are the main driver of NPP variation in areas where anthropogenic activities occur, while the total area in Xinjiang where climate change is the most important driver is larger than the total area where anthropogenic activities are the dominant driver.

Decoupling Relationship between Urbanization and Carbon Sequestration in the Pearl River Delta from 2000 to 2020

Rapid urbanization has a significant impact on the ecological environment. Net primary productivity (NPP) can effectively reflect the growth of urban vegetation and the carbon sequestration capacity of an ecosystem. Taking the rapidly growing Pearl River Delta (PRD) as our study area, the relative contributions of human activities and climate change to NPP were analyzed using an improved two-step method based on residual trend analysis. The decoupling index was used to compare the coordinated development of socioeconomic factors and the NPP in different time periods. This study lays the foundation for formulating comprehensive and reasonable urban low-carbon development measures. The results showed that (1) NPP decreased significantly before 2010, but by 2019, NPP in most regions of the PRD showed a slight increase. The NPP of new urban land was better than that of original urban land. (2) The negative contribution of climatic factors to NPP was clearer than that of human activities, and human activities contributed positively to NPP outside urban land. (3) The decoupling status of socioeconomic factors and NPP is improving, and the degree of decoupling in 2010–2019 was higher than that in 2000–2010. In conclusion, as the first forest urban agglomeration in China, the PRD has shown a good implementation of carbon sequestration policies, which can provide a reference for the coordinated development of urbanization and carbon sequestration.

The Dominant Driving Force of Forest Change in the Yangtze River Basin, China: Climate Variation or Anthropogenic Activities?

Under the combined effect of climate variations and anthropogenic activities, the forest ecosystem in the Yangtze River Basin (YRB) has experienced dramatic changes in recent decades. Quantifying their relative contributions can provide a valuable reference for forest management and ecological sustainability. In this study, we selected net primary productivity (NPP) as an indicator to investigate forest variations. Meanwhile, we established eight scenarios based on the slope coefficients of the potential NPP (PNPP) and actual NPP (ANPP), and human-induced NPP (HNPP) to quantify the contributions of anthropogenic activities and climate variations to forest variations in the YRB from 2000 to 2015. The results revealed that in general, the total forest ANPP increased by 10.42 TgC in the YRB, and forest restoration occurred in 57.25% of the study area during the study period. The forest degradation was mainly observed in the Wujiang River basin, Dongting Lake basin, and Poyang Lake basin. On the whole, the contribution of anthropogenic activities was greater than climate variations on both forest restoration and degradation in the YRB. Their contribution to forest restoration and degradation varied in different tributaries. Among the five forest types, shrubs experienced the most severe degradation during the study period, which should arouse great attention. Ecological restoration programs implemented in YRB have effectively mitigated the adverse effect of climate variations and dominated forest restoration, while rapid urbanization in the mid-lower region has resulted in forest degradation. The forest degradation in Dongting Lake basin and Poyang Lake basin may be ascribed to the absence of the Natural Forest Conservation Program. Therefore, we recommend that the extent of the Natural Forest Conservation Program should expand to cover these two basins. The current research could improve the understanding of the driving mechanism of forest dynamics and promote the effectiveness of ecological restoration programs in the YRB.

Quantifying Influences of Natural and Anthropogenic Factors on Vegetation Changes Based on Geodetector: A Case Study in the Poyang Lake Basin, China

Understanding the driving mechanism of vegetation changes is essential for vegetation restoration and management. Vegetation coverage in the Poyang Lake basin (PYLB) has changed dramatically under the context of climate change and human activities in recent decades. It remains challenging to quantify the relative contribution of natural and anthropogenic factors to vegetation change due to their complicated interaction effects. In this study, we selected the Normalized Difference Vegetation Index (NDVI) as an indicator of vegetation growth and used trend analysis and the Mann-Kendall test to analyze its spatiotemporal change in the PYLB from 2000 to 2020. Then we applied the Geodetector model, a novel spatial analysis method, to quantify the effects of natural and anthropogenic factors on vegetation change. The results showed that most regions of the basin were experiencing vegetation restoration and the overall average NDVI value in the basin increased from 0.756 to 0.809 with an upward yearly trend of +0.0026. Land-use type exerted the greatest influence on vegetation change, followed by slope, elevation, and soil types. Except for conversions to construction land, most types of land use conversion induced an increase in NDVI in the basin. The influence of one factor on vegetation NDVI was always enhanced when interacting with another. The interaction effect of land use types and population density was the largest, which could explain 45.6% of the vegetation change, indicating that human activities dominated vegetation change in the PYLB. Moreover, we determined the ranges or types of factors most suitable for vegetation growth, which can be helpful for decision-makers to optimize the implementation of ecological projects in the PYLB in the future. The results of this study could improve the understanding of the driving mechanisms of vegetation change and provide a valuable reference for ecological restoration in subtropical humid regions.

Assessing the impact of land surface temperature on urban net primary productivity increment based on geographically weighted regression model

Urbanization had a huge impact on the regional ecosystem net primary productivity (NPP). Although the urban heat island (UHI) caused by urbanization has been found to have a certain promoting effect on urban vegetation NPP, the factors on the impact still are not identified. In this study, the impact of urbanization on NPP was divided into direct impact (NPP_dir) and indirect impact (NPP_ind), taking Kunming city as a case study area. Then, the spatial heterogeneity impact of land surface temperature (LST) on NPP_ind was analyzed based on the geographically weighted regression (GWR) model. The results indicated that NPP, LST, NPP_dir and NPP_ind in 2001, 2009 and 2018 had significant spatial autocorrelation in Kunming based on spatial analytical model. LST had a positive impact on NPP_ind in the central area of Kunming. The positively correlation areas of LST on NPP_ind increased by 4.56%, and the NPP_ind caused by the UHI effect increased by an average of 4.423 gC m^-2 from 2009 to 2018. GWR model can reveal significant spatial heterogeneity in the impacts of LST on NPP_ind. Overall, our findings indicated that LST has a certain role in promoting urban NPP.

Simulation and Analysis of the Effects of Land Use and Climate Change on Carbon Dynamics in the Wuhan City Circle Area

In a climate and land use change context, the sequestration of atmospheric carbon in urban agglomeration is key to achieving carbon emission and neutrality targets. It is thus critical to understand how various climate and land use changes impact overall carbon sequestration in large-scale city circle areas. As the largest urban agglomeration in central China, carbon dynamics in the Wuhan City Circle area have been deeply affected by rapid urbanization and climate change in the past two decades. Here, we applied monthly climate data, spatially explicit land use maps, NDVI (Normalized Difference Vegetation Index) images and the CASA (Carnegie–Ames–Stanford Approach) model to estimate the spatial and temporal changes of carbon dynamics in the Wuhan City Circle area from 2000 to 2015. We designed six different scenarios to analyze the effects of climate change and land use change on carbon dynamics. Our simulation of NPP (Net Primary Productivity) increased from 522.63 gC × m⁻² to 615.82 gC × m⁻² in the Wuhan City Circle area during 2000–2015. Climate change and land use change contributed to total carbon sequestration by −73.3 × 10¹⁰ gC and 480 × 10¹⁰ gC, respectively. Both precipitation and temperature had a negative effect on carbon sequestration, while radiation had a positive effect. In addition, the positive effect on carbon sequestration from afforestation was almost equal to the negative effect from urbanization between 2000 and 2015. Importantly, these findings highlight the possibility of carrying out both rapid urbanization and ecological restoration simultaneously.

Seawater intrusion: an appraisal of taxa at most risk and safe salinity levels

Seawater intrusion into low-lying coastal ecosystems carries environmental risks. Salinity levels at these coastal ecosystems may vary substantially, causing ecological effects from mortality to several sublethal endpoints, such as depression of rates of feeding, somatic growth, or reproduction. This review attempts to establish safe salinity levels for both terrestrial and freshwater temperate ecosystems by integrating data available in the literature. We have four specific objectives: (i) to identify the most sensitive ecological taxa to seawater intrusion; (ii) to establish maximum acceptable concentrations-environmental quality standards (MAC-EQSs) for sea water (SW) from species sensitivity distributions (SSDs); (iii) to compile from the literature examples of saline intrusion [to be used as predicted environmental concentrations (PECs)] and to compute risk quotients for the temperate zone; and (iv) to assess whether sodium chloride (NaCl) is an appropriate surrogate for SW in ecological risk assessments by comparing SSD-derived values for NaCl and SW and by comparing these with field data. Zooplankton, early life stages of amphibians and freshwater mussels were the most sensitive ecological receptors for the freshwater compartment, while soil invertebrates were the most sensitive ecological receptors for the terrestrial compartment. Hazard concentration 5% (HC₅ ) values, defined as the concentration (herein measured as conductivity) that affects (causes lethal or sublethal effects) 5% of the species in a distribution, computed for SW were over 22 and 40 times lower than the conductivity of natural SW (≈ 52 mS/cm) for the freshwater and soil compartment, respectively. This sensitivity of both compartments means that small increments in salinity levels or small SW intrusions might represent severe risks for low-lying coastal ecosystems. Furthermore, the proximity between HC₅ values for the soil and freshwater compartments suggests that salinized soils might represent an additional risk for nearby freshwater systems. This sensitivity was corroborated by the derivation of risk quotients using real saline intrusion examples (PECs) collected from the literature: risk was >1 in 34 out of 37 examples. By contrast, comparisons of HC₅ values obtained from SSDs in field surveys or mesocosm studies suggest that natural communities are more resilient to salinization than expected. Finally, NaCl was found to be slightly more toxic than SW, at both lethal and sublethal levels, and, thus, is suggested to be an acceptable surrogate for use in risk assessment.

The Modified Normalized Urban Area Composite Index: A Satelliate-Derived High-Resolution Index for Extracting Urban Areas

The accurate and efficient extraction of urban areas is of great significance for better understanding of urban sprawl, built environment, economic activities, and population distribution. Night-Time Light (NTL) data have been widely used to extract urban areas. However, most of the existing NTL indexes are incapable of identifying non-luminous built-up areas. The high-resolution NTL imagery derived from the Luojia 1-01 satellite, with low saturation and the blooming effect, can be used to map urban areas at a finer scale. A new urban spectral index, named the Modified Normalized Urban Areas Composite Index (MNUACI), improved upon the existing Normalized Urban Areas Composite Index (NUACI), was proposed in this study, which integrated the Human Settlement Index (HSI) generated from Luojia 1-01 NTL data, the Normalized Difference Vegetation Index (NDVI) from Landsat 8 imagery, and the Modified Normalized Difference Water Index (MNDWI). Our results indicated that MNUACI improved the spatial variability and differentiation of urban components by eliminating the NTL blooming effect and increasing the variation of the nighttime luminosity. Compared to urban area classification from Landsat 8 data, the MNUACI yielded better accuracy than NTL, NUACI, HSI, and the EVI-Adjusted NTL Index (EANTLI) alone. Furthermore, the quadratic polynomial regression analysis showed the model based on MNUACI had the best R2 and Root-Mean Square Error (RMSE) compared with NTL, NUACI, HSI, and EANTLI in terms of estimation of impervious surface area. It is concluded that MNUACI could improve the identification of urban areas and non-luminous built-up areas with better accuracy.

Spatial and Temporal Differences in Alpine Meadow, Alpine Steppe and All Vegetation of the Qinghai-Tibetan Plateau and Their Responses to Climate Change

Alpine meadow and alpine steppe are the two most widely distributed nonzonal vegetation types in the Qinghai-Tibet Plateau. In the context of global climate change, the differences in spatial-temporal variation trends and their responses to climate change are discussed. It is of great significance to reveal the response of the Qinghai-Tibet Plateau to global climate change and the construction of ecological security barriers. This study takes alpine meadow, alpine steppe and the overall vegetation of the Qinghai-Tibet Plateau as the research objects. The normalized difference vegetation index (NDVI) data and meteorological data were used as the data sources between 2000 and 2018. By using the mean value method, threshold method, trend analysis method and correlation analysis method, the spatial and temporal variation trends in the alpine meadow, alpine steppe and the overall vegetation of the Qinghai-Tibet Plateau were compared and analyzed, and their differences in the responses to climate change were discussed. The results showed the following: (1) The growing season length of alpine meadow was 145~289 d, while that of alpine steppe and the overall vegetation of the Qinghai-Tibet Plateau was 161~273 d, and their growing season lengths were significantly shorter than that of alpine meadow. (2) The annual variation trends of the growing season NDVI for the alpine meadow, alpine steppe and the overall vegetation of the Qinghai-Tibet Plateau increased obviously, but their fluctuation range and change rate were significantly different. (3) The overall vegetation improvement in the Qinghai-Tibet Plateau was primarily dominated by alpine steppe and alpine meadow, while the degradation was primarily dominated by alpine meadow. (4) The responses between the growing season NDVI and climatic factors in the alpine meadow, alpine steppe and the overall vegetation of the Qinghai-Tibet Plateau had great spatial heterogeneity in the Qinghai-Tibet Plateau. These findings provide evidence towards understanding the characteristics of the different vegetation types in the Qinghai-Tibet Plateau and their spatial differences in response to climate change.

Using Vegetation Indices to Characterize Vegetation Cover Change in the Urban Areas of Southern China

Vegetation is essential for the provision of ecosystem services. To ensure that ecosystem services are provided, urban planning must consider vegetation cover in both urban core areas and in peripheral areas. This study explored changes in vegetation cover in both urban core and peripheral areas (buffers of 5, 10 and 15 km from the urban core areas) and the relationships between these changes and urban development. To compare the differences in vegetation cover between the urban core and peripheral areas, we developed two vegetation indices, the vegetation influence strength index (VISI) and the vegetation restoration index (VRI), using normalized difference vegetation index datasets and nighttime stable light data from 50 cities in southern China. Using these two indices, we clustered the cities into four types based on their vegetation cover characteristics. The city types varied among the different regions of the study area and cities of the same type tended to occur together geographically. In addition, the two indices showed temporal changes during the study period: A downtrend from 1992 to 2000, an uptrend from 2000 to 2005, and stability from 2005 to 2013. Furthermore, in all cities, the range of the VISI was larger in the peripheral areas than in the urban core areas. However, the range of the VRI was smaller in the peripheral areas than in the urban core areas. As the distance to the urban core areas increased, the fluctuation range of both the VISI and VRI decreased, suggesting that there was less vegetation disturbance farther from the urban core areas. We also showed that changes in vegetation cover were related to differences in urbanization rates, gross domestic products, population densities, and stages of urban development among the cities. These results provide scientific support for urban planning and sustainable development in rapid urbanization areas.

Green Infrastructure Offset of the Negative Ecological Effects of Urbanization and Storing Water in the Three Gorges Reservoir Area, China

Land use planning usually increases the uncertainties of the ecosystem structures and functions because various human demands usually bring both positive and negative ecological effects. It is critical for estimating various land use changes and their ecological effects, but the previous studies have failed to decouple the respective and the combined effects of different land use changes on ecosystem services. Net primary productivity (NPP) could be used to indicate many ecosystem services such as carbon sequestration and storage. Here, we employed a light use efficiency model to estimate the spatial and temporal dynamics of NPP in the Three Gorges Reservoir (TGR) area from 2000 to 2015, and designed four scenarios to analyze the relative roles of afforestation, urbanization and storing water on NPP dynamics. Our results documented that terrestrial NPP of the TGR area increased from 547.40 gC•m^-2 to 629.96 gC•m^-2, and carbon sequestration capacities were 31.66 TgC (1Tg = 10¹²g) and 36.79 TgC in 2000 and 2015, respectively. Climate change and land use change both could contribute to carbon sequestration with 4.08 TgC and 1.05 TgC. Among these land use changes, only afforestation could sequester carbon with 2.04 TgC, while urbanization-induced and impoundment-induced emissions were 0.12 TgC and 0.32 TgC, respectively, and other land use changes also could release 0.55 TgC of carbon. This finding suggested that although positive and negative environmental effects happened simultaneously over the past decades, green infrastructure could effectively offset the carbon emissions from urbanization and storing water in the TGR area, which provides some fundamental supports for further ecological restoration and contributes to empowering land use policies towards carbon sequestration and storage at the regional scale.

Controls of Climate and Land-Use Change on Terrestrial Net Primary Productivity Variation in a Subtropical Humid Basin

Knowledge of vegetation dynamics in relation to climatic changes and human activities is essential for addressing the terrestrial carbon cycle in the context of global warming. Scientific detection and quantitative attribution of vegetation dynamic changes in different climatic zones and human activities are the focus and challenge of the relevant research. Taking the Poyang Lake basin as the research area, this study aimed to reveal how climate and land use drive changes in net primary productivity (NPP) in the subtropical humid basin. Change patterns of vegetation NPP and their relationships with meteorological factors across the basin were first investigated based on the estimation of 18 year (2000–2017 year) NPP by using a typical light energy utilization model, the Carnegie-Ames-Stanford Approach (CASA) model. Quantitative analysis was then conducted to explicitly distinguish the driving effects of climate change and land-use change on NPP dynamics in two different periods. Results show that annual NPP and total production (TP) of the Poyang Lake basin increased significantly from 2000 to 2017. During this period, land-use change in the basin was driven by the process of urbanization expansion and the efforts of ecological protection. Climatically, the temperature is the major influencing climatic factor in determining vegetation productivity in the subtropical humid basin, followed by precipitation and solar radiation. In addition, our investigation also revealed that with comparison to the period of 2000s, the increased TP of the Poyang Lake basin due to climate change in 2010s was much bigger than the decreased TP due to land-use change. However, in the areas where the land-use change occurred, the decreased TP was mainly attributed to the impact of land-use change, even though climate change showed a positive effect of increasing productivity.

Spatial-temporal analysis of net primary production (NPP) and its relationship with climatic factors in Iran

Fluctuations of the climate variables have increased in the recent years. These fluctuations are different in each climatic region. Net primary production (NPP) indicating the plant growth and carbon stabilization over period of time is influenced by these fluctuations. Investigation of the variations in the NPP and analysis of its relationship with the climatic and environmental variables can play a key role in determining the effects of fluctuations of climatic variables on the NPP. Therefore, the present study was conducted to investigate the spatiotemporal changes in the NPP and its correlation with precipitation rate and temperature during 2000-2014 based on the annual NPP estimates determined by the moderate resolution imaging spectroradiometer (MODIS) sensor and precipitation and temperature data of the synoptic stations in eight climate regions in Iran. The slope of variations in the NPP was calculated in these climatic regions, and then, the changes in the NPP trend at two confidence levels of 95 and 99% were investigated based on the pixel-based method using the Mann-Kendall test. The sensitivity of NPP to climatic variables of temperature and precipitation was also estimated by calculating the correlation. The results showed the significant spatial distribution of NPP in the whole region under study indicating a declining trend from north to south and from west to east directions. The results also indicated the nonlinear variations in the temporal distribution of NPP. The annual mean NPP was found to follow the climatic boundaries in the climatic regions except for climate region 2, and region with the higher annual mean precipitation had higher annual mean NPP. Analysis of the trend by the Mann-Kendall method revealed that 3.2% of the pixels in the whole region followed a certain trend. Among the pixels, 70% of them followed a negative trend and the remaining 30% followed a positive trend. The greatest number of pixels with a certain trend was found in the Gulf of Oman coast climate region so that 93% of the pixels had a positive trend. The lowest number of pixels with a certain trend was observed in eastern Alborz foothills so that 87% of the pixels showed a negative trend. Slope variations of the NPP in the whole region varied from - 35 to 46 gC m² year^-1. The eastern plateau had the highest negative slope variations among the climate regions, and the highest positive slope variation of 42% was observed in the highlands climate region. In general, the precipitation rate and temperature showed a mean partial coefficient of 0.22 and 0.02, respectively, and the correlation between the NPP and temperature and precipitation was different in each climatic region. The temperature was negatively correlated with the NPP in four climatic regions with higher annual mean temperatures and in other climatic regions; it had a weak positive correlation. Therefore, the sensitivity of NPP to precipitation and temperature was different in each climatic region.

Dynamic Changes of Net Primary Productivity and Associated Urban Growth Driving Forces in Guangzhou City, China

Urban growth has caused environmental problems around the world and profoundly altered the terrestrial carbon cycle, especially net primary productivity (NPP). Sustainable urban development requires a better understanding of the impacts of urban growth on ecosystems. We selected Guangzhou City to analyze the impacts of urban development processes and urban geographic changes on NPP, as well as the correlation between urbanization intensity and NPP, using a deep-learning urbanization characteristic index (UCI). The results showed that the NPP in the study area had clear spatial heterogeneity and declined overall from 2001 to 2013. Guangzhou's urbanization became more and more intense, the mean UCI increased significantly from 0.1293 in 2001 to 0.2879 in 2013, and urban geographic type was dominated by urban exurbs in 2001 and 2013 while urban fringe areas increased most significantly and about 2,320.24 km² of urban exurbs were converted to urban fringes. There was a significant negative correlation between UCI and NPP in 2001 and 2013, implying that NPP had been negatively influenced by the increasing urban development intensity. The transition of urban exurbs to urban fringes was associated with the highest NPP losses, which was caused by cropland loss and built-up land expansion.

The effects of climate factors and human activities on net primary productivity in Xinjiang

Net primary productivity (NPP) is an index of the increase in plant biomass. Plant biomass is an important component of the global carbon cycle that indicates the health of an ecosystem. Environmental restoration has recently received much attention in Xinjiang, and it is thus important to quantify the dynamic effects of the drivers of NPP in the region. NPP was calculated for the annual growing season from 1982 to 2013 using the Carnegie-Ames-Stanford Approach (CASA) model. The effects of climate factors on NPP were analyzed, and the relationships between NPP and climate factors as well as human activity were quantified. Additionally, an innovative method based on partial derivatives and residual error was proposed to calculate the contributions of climate factors and human activities. The results show that average annual NPP in Xinjiang was 57.45 g C m^-2 from 1982 to 2013 and that the average increase in annual NPP was 0.23 g C m^-2 year^-1. The average increases in annual NPP due to temperature, precipitation, and solar radiation were 0.0095, 0.2679, and 0.2541 g C m^-2 year^-1; the average decreases were respectively - 0.0133, - 0.0521, and - 0.0725 g C m^-2 year^-1. Precipitation and solar radiation influence NPP more than temperature. Precipitation had the greatest effect on NPP in the first 19 years, but solar radiation became more influential after 2000. Climate conditions were favorable for increase in NPP before 2000. The environmental restoration also occurred in Xinjiang during that period, and human activity slightly decreased NPP. Human activity increased and had a greater effect on NPP after 2000.

Simulation of climate change and thinning effects on productivity of Larix olgensis plantations in northeast China using 3-PGmix model

Understanding the effects of thinning on forest productivity under climate change is vital to adaptive forest management. In the present study, the 3-PG_mix model was applied to simulate the thinning effects on productivity of Larix olgensis plantations under climate change using 164 sample plots collected from the 6th, 7th and 8th National Forest Inventories in Jilin Province, northeast China. Climate scenarios of RCP 4.5 and RCP 8.5 were adopted from 2011 to 2100 with corresponding reference years (1981-2010). We simulated four cutting intensities: no-thinning, NT; low intensity thinning with 10% stem removal, LT; moderate thinning with 20% stem removal, MT and heavy thinning with 30% stem removal, HT for three times with 5- and 10-year thinning intervals. The results indicated that the mean net primary productivity (NPP) during the simulated 90 years was increased under RCP 4.5 and RCP 8.5. The LT and MT had positive but HT had negative effects on the mean NPP for the same climate scenario. Increased thinning intensity facilitated the positive effects of climate change on NPP but without a significant interaction effect. During the simulation, LT had the highest NPP value and HT had the biggest NPP increase under future climate change. We also discussed the management of larch plantations under climate change and advocated low intensity thinning with 10-year thinning interval to gain maximum NPP for mitigating climate change.

Rapid urbanisation threatens fertile agricultural land and soil carbon in the Nile delta

Agriculture land in Egypt represents only 3.8% of the total area. The Nile delta provides two thirds of Egypt's agriculture land, but is threatened by urban sprawl. The paper aims to quantify urban expansion over a 45 year period using 6 time points from 1972 to 2017, and its impacts on agricultural potential, soil organic carbon stocks, and implications for water use. The study used multi-temporal satellite data and remote sensing techniques (Maximum Likelihood supervised classification, and NDVI), soil sampling and analysis, data on water irrigation, and agroecological system and ecosystem services model (MicroLEIS, InVEST) to assess the effects of land use change. Urban area increased by a factor of 5, from 452 km2 in 1972 to 2644 km2 in 2017. The greatest losses occurred to the fertile Vertic Torrifluvent soils on the older delta, which lost 1734 km2. Soil organic carbon (0-75 cm depth) lost as a result of soil sealing from urbanisation rose from 25,000 to 141,000 Mg C over the 45 years. As a result of increased pressure on delta land, agriculture expanded into the higher desert areas outside the delta, on marginal land sustained by intensive fertiliser use and irrigation, which in turn puts pressure on water use. Therefore, rapid urban expansion has resulted in a loss of soil carbon and a shift in agriculture from fertile soils to marginal soils, requiring more capital inputs, which is ultimately less sustainable. Modelling suggested that soil management improvement could make better use of fertile soils within the Delta currently affected by high salinity and poor drainage. Future planning should encourage urban expansion on the less fertile soils outside of the delta, while improving suitability of existing agricultural land and minimising land degradation within the delta.

Global urban expansion offsets climate-driven increases in terrestrial net primary productivity

The global urbanization rate is accelerating; however, data limitations have far prevented robust estimations of either global urban expansion or its effects on terrestrial net primary productivity (NPP). Here, using a high resolution dataset of global land use/cover (GlobeLand30), we show that global urban areas expanded by an average of 5694 km² per year between 2000 and 2010. The rapid urban expansion in the past decade has in turn reduced global terrestrial NPP, with a net loss of 22.4 Tg Carbon per year (Tg C year⁻¹). Although small compared to total terrestrial NPP and fossil fuel carbon emissions worldwide, the urbanization-induced decrease in NPP offset 30% of the climate-driven increase (73.6 Tg C year⁻¹) over the same period. Our findings highlight the urgent need for global strategies to address urban expansion, enhance natural carbon sinks, and increase agricultural productivity.

Robust estimates of either urban expansion worldwide or the effects of such phenomenon on terrestrial net primary productivity (NPP) are lacking. Here the authors used the new dataset of global land use to show that the global urban areas expanded largely between 2000 and 2010, which in turn reduced terrestrial NPP globally.

Impact of Urbanization and Climate on Vegetation Coverage in the Beijing–Tianjin–Hebei Region of China

Worldwide urbanization leads to ecological changes around urban areas. However, few studies have quantitatively investigated the impacts of urbanization on vegetation coverage so far. As an important indicator measuring regional environment change, fractional vegetation cover (FVC) is widely used to analyze changes in vegetation in urban areas. In this study, on the basis of a partial derivative model, we quantified the effect of temperature, precipitation, radiation, and urbanization represented as nighttime light on vegetation coverage changes in the Beijing–Tianjin–Hebei (BTH) region during its period of rapid resident population growth from 2001 to 2011. The results showed that (1) the FVC of the BTH region varied from 0.20 to 0.26, with significant spatial heterogeneity. The FVC increased in small cities such as Cangzhou and in the Taihang Mountains, while it decreased in megacities with populations greater than 1 million, such as Beijing and Zhangjiakou Bashang. (2) The BTH region experienced rapid urbanization, with the area of artificial surface increasing by 18.42%. From the urban core area to the fringe area, the urbanization intensity decreased, but the urbanization rate increased. (3) Urbanization and precipitation had the greatest effect on FVC changes. Urbanization dominated the FVC changes in the expanded area, while precipitation had the greatest impacts on the FVC changes in the core area. For future studies on the major influencing factors of FVC changes, quantitative analysis of the contribution of urbanization to FVC changes in urban regions is crucial and will provide scientific perspectives for sustainable urban planning.

Determining the impacts of climate change and urban expansion on terrestrial net primary production in China

Climate change and urbanization strongly affect the variations of terrestrial net primary production (NPP), but the relative contributions of these two factors to NPP changes have not been determined yet (especially on a macroscale). In this study, spatial-temporal variations of NPP in China from 2000 to 2010 were estimated using the Carnegie-Ames-Stanford Approach model, and the effects induced by urbanization and climate change were quantified. The obtained results showed that during the study period, the NPP in China exhibited an annual increase of 0.03 Pg C accompanied by large spatial heterogeneities. During the whole study period, the urban area in China increased by 16.44 × 10³ km², and the corresponding NPP losses amounted to 11.60 × 10^-3 Pg C. Urban expansion significantly offset the climate change-induced NPP increases and worsened NPP decreases (the offsetting ratio calculated for China was 5.42%, and its exact magnitudes varied by province). The largest NPP variations were observed over the regions with rapid urban expansion, whose contribution ratio was 32.20% for China and exceeded 30% for most provinces. Climate change contributed considerably to the NPP variations in both the newly urbanized (30.45%) and purely vegetated (46.92%) areas, but its contribution ratios were slightly lower than those of residual factors. Moreover, climate change strongly affected the NPP levels over the arid and semi-arid regions as well as over the Tibet Plateau; however, residual factors dominated the NPP variations over the central and southeast China. Our study highlights a significant role of urbanization in driving terrestrial NPP variations on a macroscale and provides a new perspective on disentangling the impacts of external factors on NPP values.

A long-term and comprehensive assessment of the urbanization-induced impacts on vegetation net primary productivity

Urbanization not only directly alters the regional ecosystem net primary productivity (NPP) through land-cover replacement, but it is also accompanied by huge indirect impacts due to the associated climate change and anthropogenic activities. However, to date, limited efforts have been made to quantitatively separate the two types of urbanization impacts, and the continuous variations over a long-time span are not well understood. In this study, both the long-term direct and indirect impacts of urbanization on NPP were established and analyzed based on multi-source remote sensing data, taking the city of Kunming in China as a case study area. The results indicated that the intense urbanization process has led to a continuous decrease in NPP from 1990 to 2014, due to the direct impact of land-cover replacement. Nevertheless, the urbanization has also resulted in an apparently positive indirect impact on NPP, which has offset about 30% of the direct impact in recent years. The increasing trend of the indirect impact was found to be higher than the NPP trend in the surrounding forest areas, which proves that vegetation growth has been promoted by the urban environment. The indirect impact has also shown great spatial and temporal heterogeneity, with generally higher values in the old city area and winter season. This can mostly be attributed to the distribution of temperature, i.e., the urban heat island effect, which has shown a significantly positive correlation with the indirect impact. However, the correlations between NPP and climatic factors were found to be completely different, which confirmed the need to separate the direct and indirect impacts. Overall, this study has demonstrated that urbanization has reduced the total NPP over the region, but has promoted some vegetation growth, and the knowledge of the indirect impact will help to support urban greening planning.

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

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

Comparative Assessment of Vegetation Dynamics under the Influence of Climate Change and Human Activities in Five Ecologically Vulnerable Regions of China from 2000 to 2015

Ongoing climate change and human activities have a great effect on vegetation dynamics. Understanding the impact of climate change and human activities on vegetation dynamics in different ecologically vulnerable regions has great significance in ecosystem management. In this study, the predicted NPP (Net Primary Productivity) and the actual NPP based on different ecological process data and models were combined to estimate the vegetation dynamics and their driving forces in the Northern Wind-sand, Loess Plateau, Arid Desert, Tibetan Plateau, and Karst regions from 2000 to 2015. The results indicated that the NPP in all ecologically vulnerable regions showed a restoration trend, except for that in the Karst region, and the percentage of areas in which NPP increased were, in order, 78% for the Loess Plateau, 71% for the Northern Wind-sand, 69% for the Arid Desert, 54% for the Tibetan Plateau, and 31% for the Karst regions. Vegetation restorations in the Northern Wind-sand and Arid Desert regions were primarily attributable to human activities (86% and 61% of the restoration area, respectively), indicating the success of ecological restoration programs. The Loess Plateau had the largest proportion of vegetation restoration area (44%), which was driven by combined effects of climate and human factors. In the Tibetan Plateau, the vegetation changes due to climate factors were primarily distributed in the west, while those due to human factors were primarily distributed in the east. Human activities caused nearly 60% of the vegetation degradation in the Karst region. Based on these results, it is recognizable that regional climate conditions are the key factor that limits ecological restoration. Therefore, future policy-making should pay more attention to the local characteristics of different ecological vulnerable regions in regional ecosystem management to select reasonable restoration measures, improve restoration efficiency, and maximize the benefits of ecological restoration programs.

A 110-year pollen record of land use and land cover changes in an anthropogenic watershed landscape, eastern China: Understanding past human-environment interactions

Land use and land cover changes (LUCCs) have largely altered terrestrial ecosystems and landscapes during the Anthropocene. Reconstructing past LUCCs is necessary to better understand terrestrial ecosystem succession and human-environment interactions so that ecosystem services can be used conservatively and developed sustainably. In this paper, we reconstructed the LUCCs over the past century in a typical anthropogenic watershed based on a high-resolution pollen record from Changdang Lake, eastern China. The sediment core was ²¹⁰Pb dated and constrained cluster analysis identified different periods of LUCCs associated with the 110-year pollen record. Multi-sedimentary proxies, historical records, and remote sensing LUCC maps were analyzed to complement the palynological results. Our results demonstrate that pollen records can accurately capture LUCCs during different historical periods. Extra-regional arboreal pollen, fern spores, and pollen concentration can record the hydrological variations of waterbodies under both climatic and anthropogenic impacts. Multiple agriculture-related pollen indicators, such as cereal, Cruciferae, and wetland taxa are significantly related to the corresponding vegetation cover and landscape variations. Specifically, the anthropochore taxa to wetland taxa ratio is a good indicator of agricultural intensity. Dominant arboreal pollen (Pinus and Quercus) and the arboreal taxa to non-arboreal taxa ratio reflects the forestry landscape changes. Urban greening arboreal pollen (including Platanus, Salix, and Ulmus) is found to be an indirect indicator of urbanization. In addition, agriculture and urbanization in the region are causing the pollen diversity to increase in lake sediments. This study from a shallow lake in eastern China contributes to our understanding of pollen-based LUCC studies in similar climatic and anthropogenic regions around the world.

Urban Sprawl Sustainability of Mountainous Cities in the Context of Climate Change Adaptability Using a Coupled Coordination Model: A Case Study of Chongqing, China

In recent years, a noticeable contradiction has emerged between the disorderly sprawl and fragile climate environment of many cities, especially in mountainous cities. Therefore, this paper respectively constructed evaluation indicators for urban sprawl sustainability (USS) and climate change adaptability (CCA). Next, a coupling coordination degree model was used to measure the coordinated development of USS and CCA. Finally, this paper analyzed the coordinated development type of USS and CCA in the Chongqing metropolitan area from 2007 to 2017. The results of this paper show that USS and CCA have gradually shifted to coordinated development in the Chongqing metropolitan area during the study period. However, there were obvious regional differences in the type of coordinated development in the Chongqing metropolitan area. The coordinated development degree of USS and CCA in nine districts ranged from 0.635 to 0.721 in 2017. It can be divided into three types: slightly coordinated development with lagging CCA; slightly coordinated development with lagging USS; and moderately coordinated development with lagging CCA. Those districts should give priority to the use of Nature-Based Solutions (NBS), and multi-center and multi-group approaches to enhance the coordinated development between USS and CCA, which is also helpful for mountainous cities in China and other countries.

Quantitative assessment of human-induced impacts based on net primary productivity in Guangzhou, China

Urban expansion and land cover change driven primarily by human activities have significant influences on the urban eco-environment, and together with climate change jointly alter net primary productivity (NPP). However, at the spatiotemporal scale, there has been limited quantitative analysis of the impacts of human activities independent of climate change on NPP. We chose Guangzhou city as a study area to analyze the impacts of human activities on NPP, as well as the spatiotemporal variations of those impacts within three segments, using a relative impact index (RII) based on potential NPP (NPP_p), actual NPP (NPP_act), and NPP appropriation due to land use/land cover change (NPP_lulc). The spatial patterns and dynamics of NPP_act and NPP_lulc were evaluated and the impacts of human activities on NPP during the process of urban sprawl were quantitatively analyzed and assessed using the RII. The results showed that NPP_act and NPP_lulc in the study area had clear spatial heterogeneity, between 2001 and 2013 there was a declining trend in NPP_act while an increasing trend occurred in NPP_lulc, and those trends were especially significant in the 10-40-km segment. The results also revealed that more than 91.0% of pixels in whole study region had positive RII values, while the lowest average RII values were found in the > 40-km segment (39.03%), indicating that human activities were not the main cause for the change in NPP there; meanwhile, the average RII was greater than 65.0% in the other two, suggesting that they were subjected to severe anthropogenic disturbances. The RII values in all three segments of the study area increased, indicating an increasing human interference. The 10-40-km buffer zone had the largest slope value (0.5665), suggesting that this segment was closely associated with growing human disturbances. Particularly noteworthy is the fact that the > 40-km segment had a large slope value (0.3323) and required more conservation efforts. Based on the above results, we suggest that continuous efforts may be necessary to improve the intensity of protection and management in the urban environment of Guangzhou.

Assessing the impacts of urban sprawl on net primary productivity using fusion of Landsat and MODIS data

Urbanization has profoundly altered the terrestrial ecosystem carbon cycle, especially the net primary productivity (NPP). Many attempts have been made to assess the influence of urbanization on NPP at coarse resolutions (e.g., 250m or larger), which may ignore many smaller and highly fragmented urban lands, and to a large extent, underestimate the NPP variations induced by urban sprawl. Hence, we attempted to analyze the NPP variations influenced by urban sprawl at a fine resolution (e.g., 30m), toward which the accuracy of NPP was improved using remotely sensed data fusion algorithm. In this paper, this assumption was tested in the Pearl River Delta of China. The land cover datasets from the Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper Plus (ETM+) were acquired to quantify the urban sprawl. The synthetic Normal Differential Vegetation Index (NDVI) data was obtained by fusing Landsat and Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI via spatiotemporal fusion algorithm. The Carnegie-Ames-Stanford Approach (CASA) model was driven by land cover map, synthetic NDVI and meteorological data to estimate the 30-m resolution NPP. Then, we analyzed the influence of urban sprawl on 30-m resolution NPP during the period of 2001-2009. Additionally, we also simulated the spatiotemporal change of future urban sprawl under different scenarios using the Future Land Use Simulation (FLUS) model, and further analyzed its influence on 30-m resolution NPP. Our results showed that the accuracy of 30-m resolution NPP from synthetic NDVI is better than 500-m resolution NPP from MODIS NDVI. The loss in 30-m resolution NPP due to urban sprawl was much higher than 500-m resolution NPP. Moreover, the harmonious development scenario, characterized by a reasonable size of urban sprawl and a corresponding lower NPP loss from 2009 to 2050, would be considered as a more human-oriented and sustainable development strategy.

Trade-offs among ecosystem services in a typical Karst watershed, SW China

Nowadays, most research results on ecosystem services in Karst areas are limited to a single function of an ecosystem service. Few scholars conduct a comparative study on the mutual relationships among ecosystem services, let alone reveal the trade-off and synergic relationships in typical Karst watershed. This research aims to understand and quantitatively evaluate the relationships among ecosystem services in a typical Karst watershed, broaden the depth and width of trade-off and synergic relationships in ecosystem services and explore a set of technical processes involved in these relationships. With the Shibantang Karst watershed in China as the research site, we explore the trade-off and synergic relationships of net primary productivity (NPP), water yield, and sediment yield by coupling Soil and Water Assessment Tool (SWAT) and Carnegie-Ames-Stanford Approach (CASA), and simulating and evaluating these three ecosystem services between 2000 and 2010. Results of this study are as follows. (1) The annual average water yield decreased from 528mm in 2000 to 513mm in 2010, decreasing by 2.84%. (2) The annual average sediment yield decreased from 26.15t/ha in 2000 to 23.81t/ha in 2010, with an average annual reduction of 0.23t/ha. (3) The annual average NPP increased from 739.38gCm(-2)a(-1) in 2000 to 746.25gCm(-2)a(-1) in 2010, increasing by 6.87gCm(-2)a(-1) . (4) Water yield and sediment yield are in a synergic relationship. The increase of water yield can accumulate the soil erosion amount. NPP is in a trade-off relationship with water yield and sediment yield. The improvement of NPP is good for decreasing water yield and soil erosion amount and increasing soil conservation amount. This study provides policy makers and planners an approach to develop an integrated model, as well as design mapping and monitoring protocols for land use change and ecosystem service assessments.

Vegetation dynamics and its driving forces from climate change and human activities in the Three-River Source Region, China from 1982 to 2012

The Three-River Source Region (TRSR), a region with key importance to the ecological security of China, has undergone climate changes and a shift in human activities driven by a series of ecological restoration projects in recent decades. To reveal the spatiotemporal dynamics of vegetation dynamics and calculate the contributions of driving factors in the TRSR across different periods from 1982 to 2012, net primary productivity (NPP) estimated using the Carnegie-Ames-Stanford approach model was used to assess the status of vegetation. The actual effects of different climatic variation trends on interannual variation in NPP were analyzed. Furthermore, the relationships of NPP with different climate factors and human activities were analyzed quantitatively. Results showed the following: from 1982 to 2012, the average NPP in the study area was 187.37gcm(-2)yr(-1). The average NPP exhibited a fluctuation but presented a generally increasing trend over the 31-year study period, with an increase rate of 1.31gcm(-2)yr(-2). During the entire study period, the average contributions of temperature, precipitation, and solar radiation to NPP interannual variation over the entire region were 0.58, 0.73, and 0.09gcm(-2)yr(-2), respectively. Radiation was the climate factor with the greatest influence on NPP interannual variation. The factor that restricted NPP increase changed from temperature and radiation to precipitation. The average contributions of climate change and human activities to NPP interannual variation were 1.40gcm(-2)yr(-2) and -0.08gcm(-2)yr(-2), respectively. From 1982 to 2000, the general climate conditions were favorable to vegetation recovery, whereas human activities had a weaker negative impact on vegetation growth. From 2001 to 2012, climate conditions began to have a negative impact on vegetation growth, whereas human activities made a favorable impact on vegetation recovery.

The Influences of Drought and Land-Cover Conversion on Inter-Annual Variation of NPP in the Three-North Shelterbelt Program Zone of China Based on MODIS Data

Terrestrial ecosystems greatly contribute to carbon (C) emission reduction targets through photosynthetic C uptake.Net primary production (NPP) represents the amount of atmospheric C fixed by plants and accumulated as biomass. The Three-North Shelterbelt Program (TNSP) zone accounts for more than 40% of China’s landmass. This zone has been the scene of several large-scale ecological restoration efforts since the late 1990s, and has witnessed significant changes in climate and human activities.Assessing the relative roles of different causal factors on NPP variability in TNSP zone is very important for establishing reasonable local policies to realize the emission reduction targets for central government. In this study, we examined the relative roles of drought and land cover conversion(LCC) on inter-annual changes of TNSP zone for 2001–2010. We applied integrated correlation and decomposition analyses to a Standardized Evapotranspiration Index (SPEI) and MODIS land cover dataset. Our results show that the 10-year average NPP within this region was about 420 Tg C. We found that about 60% of total annual NPP over the study area was significantly correlated with SPEI (p<0.05). The LCC-NPP relationship, which is especially evident for forests in the south-central area, indicates that ecological programs have a positive impact on C sequestration in the TNSP zone. Decomposition analysis generally indicated that the contributions of LCC, drought, and other Natural or Anthropogenic activities (ONA) to changes in NPP generally had a consistent distribution pattern for consecutive years. Drought and ONA contributed about 74% and 23% to the total changes in NPP, respectively, and the remaining 3% was attributed to LCC. Our results highlight the importance of rainfall supply on NPP variability in the TNSP zone.