Exploring the response of net primary productivity variations to urban expansion and climate change: a scenario analysis for Guangdong Province in China

Climate change and Land Use/Land Cover Change (LUCC) leading to spatial shifts in net primary productivity in Anhui Province, China

As an important part of terrestrial carbon cycle research, net primary productivity is an important parameter to evaluate the quality of terrestrial ecosystem and plays an important role in the analysis of global climate change and carbon balance. Anhui Province is in the Yangtze River Delta region in eastern China. Based on the theoretical basis of CASA model, this paper uses MODIS NDVI, vegetation type data, meteorological data, and LUCC to estimate the NPP of Anhui Province during 2001-2020 and analyzes its spatial-temporal pattern. The results showed that the average NPP in Anhui province was 508.95 gC· (m2 ·a) -1, and the spatial heterogeneity of NPP was strong, and the high value areas were mainly distributed in the Jiangnan Mountains and Dabie Mountains. NPP increased in most areas of Anhui Province, but decreased significantly in 17.60% of the area, mainly in the central area affected by urban and rural expansion and the transformation of the Yangtze River. The dynamic change of NPP in Anhui province is the result of climate change and land use change. Meteorological data are positively correlated with NPP. Among them, the correlation between temperature and solar radiation is higher, and the correlation between NPP and precipitation is the lowest among the three. The NPP of all land cover types was more affected by temperature than precipitation, especially forest land and grassland. The decrease of cultivated land and the increase of Artificial Surfaces (AS) may have contributed to the decrease of NPP in Anhui Province. Human activities have weakened the increase in NPP caused by climate change. In conclusion, this study refined the drivers of spatial heterogeneity of NPP changes in Anhui province, which is conducive to rational planning of terrestrial ecosystems and carbon balance measures.

Spatiotemporal characteristics and influencing factors of net primary production from 2000 to 2021 in China

With the rapid development of remote sensing, variously high temporal and spatial resolution products of different sensors were gradually applied aspects of researches, which could achieve rapid and low-cost monitors of terrestrial environment. It was meaningful to analyze the latest and long-term changes of net primary production (NPP), which could reflect the human-induced effects on ecological environment. In our study, we used Sen's slope and Mann-Kendall test to analyze the spatiotemporal changes of NPP. Then, we used fluctuation model and Moran model to reveal the stability and clusters of NPP, respectively. Next, we quantitatively analyzed NPP changes in the perspectives of land use types and provinces. Finally, we used geographically weighted regression (GWR) model to analyze effects of different factors on NPP. The result showed that NPP presented significant increase in most areas of China from 2000 to 2021. Especially, Loess Plateau showed obvious NPP increase. Meanwhile, "high-high" cluster of NPP difference were mainly distributed in the ecological policies-influenced areas. The slope in 5-15° has the highest growth trend, and the slope > 25° has the slowest growth trend. Cropland, forests, and shrub revealed an obvious improvement of NPP, which indicated afforestation and intensive farmed played a key role. Temperature, precipitation, population density, and elevation had significant effects on NPP (p < 0.05) in 2000, 2011, and 2021. The degree of effects of human activities was gradually increase in GWR model. In this scenario, related ecological policies had vita influencing on NPP improvement. Our study could provide a help for monitor of ecological environment and government policies.

Coupling coordination degree and driving factors of new-type urbanization and low-carbon development in the Yangtze River Delta: based on nighttime light data

The coordination relationship between new-type urbanization and urban low-carbon development under the goal of carbon neutrality has become a hot issue that needs to be focused on when formulating policies. Based on the estimation of urban CO2 emissions by night light data, this study used spatial autocorrelation, spatial Markov chain and geographically weighted regression model to measure the spatial correlation and spillover effects of the coupling coordination degree of two systems in the Yangtze River Delta urban agglomeration from 2005 to 2018 and analyzed the influencing factors. The results showed that (1) the coupling coordination degree showed an increasing trend, but the club effect was quite obvious, and the regional pattern was higher in southeast and lower in northwest; (2) the spatial spillover effect of coupling coordination degree is significant, which aggravates the long-term persistence of the imbalance pattern; (3) regional economic level, government fiscal regulation, and industrial upgrading are the main driving forces for the increase of coupling coordination degree, while over-concentration of population and low energy efficiency are the main obstacles. Finally, on the basis of these conclusions, we provide targeted policy planning suggestions for policy makers.

Linking MSPA and Circuit Theory to Identify the Spatial Range of Ecological Networks and Its Priority Areas for Conservation and Restoration in Urban Agglomeration

Rapid urbanization has led to the continuous degradation of natural ecological space within large urban agglomerations, triggering landscape fragmentation and habitat loss, which poses a great threat to regional ecological sustainability. Ecological networks (ENs) are a comprehensive control scheme to protect regional ecological sustainability. However, in the current research about ENs, most studies can only determine the orientation of ecological corridors but not their specific spatial range. This leads to the fact that ENs can only be abstract concepts composed of points and lines, and cannot be implemented into concrete spatial planning. In this study, taking the Shandong Peninsula urban agglomeration as an example, ecological sources were identified by morphological spatial pattern analysis (MSPA) and habitat quality assessment, ecological resistance surfaces were constructed based on habitat risk assessment (HRA). And circuit theory was used to simulate the ecosystem processes in heterogeneous landscapes via by calculating the cumulative current value and cumulative current recovery value, to identify the spatial range and key areas of ecological corridors. The results showed that the ENs includes 6,263.73 km2 of ecological sources, 12,136.61 km2 of ecological corridors, 283.61 km2 of pinch points and 347.51 km2 of barriers. Specifically, ecological sources were distributed in a spatial pattern of five groups, and ecological corridors were short and dense within groups, long in distance and narrow in width between groups. The pinch points and barriers mainly exist in the ecological corridors connecting the inner and outer parts of the central city and in the inter-group corridors. In order to ensure the connectivity and effectiveness of ENs, it is necessary to focus on the pinch points and barriers and include them in the priority areas for protection and restoration. Based on MSPA and circuit theory, this study provides a new method for determining the spatial range of ENs and the specific locations of priority areas, and provides a feasible solution for the concrete implementation of ENs to achieve effective ecological protection and restoration.

A Semi-Parametric Geographically Weighted Regression Approach to Exploring Driving Factors of Fractional Vegetation Cover: A Case Study of Guangdong

Ecological degradation caused by rapid urbanisation has presented great challenges in southern China. Fractional vegetation cover (FVC) has long been the most common and sensitive index to describe vegetation growth and to monitor vegetation degradation. However, most of the studies have failed to adequately explore the complexity of the relationship between fractional vegetation cover (FVC) and impact factors. In this research, we first constructed a Semi-parametric Geographically Weighted Regression (SGWR) model to analyse both the stationary and nonstationary spatial relationships between FVC and driving factors in Guangdong province in southern China on a county level. Then, climate, topographic, land cover, and socio-economic factors were introduced into the model to distinguish impacts on FVC from 2000–2015. Results suggest that the positive and negative effects of rainfall and elevation coefficients alternated, and local urban land and population estimates indicated a negative association between FVC and the modelled factors in each period. The SGWR FVC make significantly improves performance of the geographically weighted regression and ordinary least squares models, with adjusted R2 higher than 0.78. The findings of this research demonstrated that, although urbanisation in the Pearl River Delta in Guangdong has encroached on the regional vegetation cover, the total vegetation area remained unchanged with the implementation of protection policies and regulations.

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.

Effects of urbanization on productivity of terrestrial ecological systems based on linear fitting: a case study in Jiangsu, eastern China

The terrestrial ecosystem productivity and foundation of regional ecosystem services have been significantly influenced by recent urbanization processes. This study assesses the changes in terrestrial ecosystem productivity in Jiangsu from the years of 2000 to 2015 in response to the urbanization. A linear model that incorporates the traditional equalization method is proposed to improve the estimation accuracy of net primary productivity (NPP) loss. Results revealed that the land area of urban construction expanded rapidly during the research period to encompass an area of 8672.8 km². The rate of expansion was highest during 2005-2010. Additionally, the expansion rate of urban construction land was considerably higher in southern Jiangsu compared to the northern areas. The NPP exhibited a rising tendency from the year of 2000 to 2015, and varied from 33.30 to 40.23 Tg C/y. It was higher in the central parts, which include the cities of Yancheng and Nantong. The increase in urban construction land has resulted in a significant reduction in the terrestrial ecosystem productivity, i.e. a cumulative NPP loss of 2.55-2.88 Tg C during the research period. The NPP losses due to the conversion from cropland to constrction land were the highest, followed by the wetland. The work in this paper indicates that the rate of future productivity losses in terrestrial ecosystem in northern Jiangsu would be faster than the southern areas.

Assessing the Impacts of Extreme Climate Events on Vegetation Activity in the North South Transect of Eastern China (NSTEC)

Extreme climate events frequently exert serious effects on terrestrial vegetation activity. However, these effects are still uncertain in widely distributed areas with different climate zones. Transect analysis is important to understand how terrestrial vegetation responds to climate change, especially extreme climate events, by substituting space for time. In this paper, seven extreme climate indices and the Normalized Difference Vegetation Index (NDVI) are employed to examine changes in the extreme climate events and vegetation activity. To reduce the uncertainty of the NDVI, two satellite-derived NDVI datasets, including the third generation Global Inventory Monitoring and Modeling System (GIMMS-3g) NDVI dataset and the NDVI from the National Oceanic and Atmospheric Administration (NOAA) satellites on Star Web Servers (SWS), were employed to capture changes in vegetation activity. The impacts of climate extremes on vegetation activity were then assessed over the period of 1982–2012 using the North–South Transect of Eastern China (NSTEC) as a case. The results show that vegetation activity was overall strengthened from 1982 to 2012 in the NSTEC. In addition, extreme high temperature events revealed an increased trend of approximately 5.15 days per decade, while a weakened trend (not significant) was found in extreme cold temperature events. The strengthened vegetation activities could be associated with enhanced extreme high temperature events and weakened extreme cold temperature events over the past decades in most of the NSTEC. Despite this, inversed changes were also found locally between vegetation activity and extreme climate events (e.g., in the Northeast Plain). These phenomena could be associated with differences in vegetation type, human activity, as well as the combined effects of the frequency and intensity of extreme climate events. This study highlights the importance of accounting for the vital roles of extreme climate effects on vegetation activity.

Impacts by expansion of human settlements on nature reserves in China

Expansion of human settlements affects nature reserves in various ways. Planning ahead can help to divert or mitigate the impacts but a good understanding of these impacts is a prerequisite. In this study, we estimated the impacts caused by the expansion of human settlements on nature reserves in China by 2050 under different development and conservation scenarios. Our results show that 5016 km² of nature reserves may be encroached by the expansion of human settlements under the scenario of high growth and weak protection, a ten-fold increase compared to 2010. In addition, new settlements may fragment landscapes in 243 nature reserves and increase the level of fragmentation in 109 nature reserves. Furthermore, expansion of human settlements in surrounding areas may expose 164 nature reserves to threats of human activities and increase the threat levels to 540 nature reserves. The impacts will be lower if protection is stronger or economic growth is slower. Among all nature reserves, those administered at the county level will be affected the most. Nature reserves that protect forests and inland wetlands will be affected more than nature reserves protecting other objects. Nature reserves in East and South China will be influenced more than reserves in other regions. Findings from China show that the expansion of human settlements poses serious challenges to nature reserves in the future, especially in places where economic growth is fast and nature reserves are weakly protected. Proactive conservation strategies have to be developed and implemented forcefully to manage these impacts. Our findings contribute to a better understanding of the potential conflict between human settlements and nature reserves.

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.

Response of net primary production to land use and land cover change in mainland China since the late 1980s

Land use and land cover patterns in mainland China have substantially changed in the recent decades under the economic reform policies of the government. The terrestrial carbon cycle, particularly the net primary productivity (NPP), has been substantially changed on both local and national scales. With the growing concern over the effects of the terrestrial carbon cycle on global climate changes, the impacts of land use and cover change (LUCC) on NPP need to be understood. In this study, variations in NPP caused by LUCC (e.g., urbanization and conversion of other land use to forest and grassland) in mainland China from the late 1980s to 2015 were evaluated based on land cover datasets and NPPs simulated from the Carnegie-Ames-Stanford Approach model. The results indicate that the national total losses in NPP attributed to urbanization reached 1.695 TgC between the late 1980s and 2015. A large proportion (63.02%) of the total losses was due to the transformation from cropland to urban land. Urban expansion decreased the monthly and total NPPs over southern China, which includes the South China Region, Southwest China Region, and the middle and lower regions of the Yangtze River. However, the total NPP increased in the majority of urbanized areas in Northern China, including the Huang-Huai-Hai Region, Inner Mongolia Region (MGR), Gan-Xin Region (GXR), and Northeast China Region; monthly NPP in GXR and MGR increased throughout the year. By contrast, the conversion to grassland or forestland increased the monthly and total NPPs of Northern China, suggesting that returning to forestland and grassland could increase the carbon sequestration capacity of terrestrial ecosystems in mainland China. Among the sub-regions, the Loess Plateau Region contributed the largest increase in NPP, which was prompted by the conversion to grassland and forestland.

Drought-Induced Reduction in Net Primary Productivity across Mainland China from 1982 to 2015

Terrestrial net primary productivity (NPP) plays an essential role in the global carbon cycle as well as for climate change. However, in the past three decades, terrestrial ecosystems across mainland China suffered from frequent drought and, to date, the adverse impacts on NPP remain uncertain. This study explored the spatiotemporal features of NPP and discussed the influences of drought on NPP across mainland China from 1982 to 2015 using the Carnegie Ames Stanford Application (CASA) model and the standardized precipitation evapotranspiration index (SPEI). The obtained results indicate that: (1) The total annual NPP across mainland China showed an non-significantly increasing trend from 1982 to 2015, with annual increase of 0.025 Pg C; the spring NPP exhibited a significant increasing trend (0.031 Pg C year−1, p < 0.05) while the summer NPP showed a higher decreasing trend (0.019 Pg C year−1). (2) Most areas of mainland China were spatially dominated by a positive correlation between annual NPP and SPEI and a significant positive correlation was mainly observed for Northern China; specific to the nine sub-regions, annual NPP and SPEI shared similar temporal patterns with a significant positive relation in Northeastern China, Huang-Huai-Hai, Inner Mongolia, and the Gan-Xin Region. (3) During the five typical drought events, more than 23% areas of mainland China experienced drought ravage; the drought events generally caused about 30% of the NPP reduction in most of the sub-regions while the NPP in the Qinghai-Tibet Plateau Region generally decreased by about 10%.

Spatial-temporal dynamics of carbon emissions and carbon sinks in economically developed areas of China: a case study of Guangdong Province

This study analysed spatial-temporal dynamics of carbon emissions and carbon sinks in Guangdong Province, South China. The methodology was based on land use/land cover data interpreted from continuous high-resolution satellite images and energy consumption statistics, using carbon emission/sink factor method. The results indicated that: (1) From 2005 to 2013, different land use/land cover types in Guangdong experienced varying degrees of change in area, primarily the expansion of built-up land and shrinkage of forest land and grassland; (2) Total carbon emissions increased sharply, from 76.11 to 140.19 TgC yr⁻¹ at the provincial level, with an average annual growth rate of 10.52%, while vegetation carbon sinks declined slightly, from 54.52 to 53.20 TgC yr⁻¹. Both factors showed significant regional differences, with Pearl River Delta and North Guangdong contributing over 50% to provincial carbon emissions and carbon sinks, respectively; (3) Correlation analysis showed social-economic factors (GDP per capita and permanent resident population) have significant positive impacts on carbon emissions at the provincial and city levels; (4) The relationship between economic growth and carbon emission intensity suggests that carbon emission efficiency in Guangdong improves with economic growth. This study provides new insight for Guangdong to achieve carbon reduction goals and realize low-carbon development.

Assessment of ecosystem productivity damage due to land use

Land use can affect ecosystems on land and their services. Because land use has mainly local effects, damage to ecosystem productivity due to land use should be modelled spatially dependent. Unfortunately, even though land use of impacts are particular importance for countries whose economies are highly agriculture-based, ecosystem productivity damage due to land use has not yet been assessed in Thailand so far. This study presents the method for assessing the damage to ecosystem productivity due to land use (land occupation and land transformation) in Thailand. Ecosystem productivity damage is expressed through net primary production (NPP). To convert the damage into monetary units, this study performs an economic valuation of NPP using the production function approach. The results show that the value of marginal product of NPP is around 10-15 Thai baht (THB) (1 USD≈36 THB), per tonne dry weight biomass. The results are applied to the case of biodiesel production. The method presented in this paper could be a guideline for future land use impact assessment research. In addition, converting the NPP damage results into monetary units facilitates integration of impact assessment and economic analysis results for supporting decision support tools such as cost benefit analysis.