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

Dual effects on vegetation from urban expansion in the drylands of northern China: A multiscale investigation using the vegetation disturbance index

Drylands contribute roughly 40 % of the global net primary productivity and are essential for achieving sustainable development. Investigating the effects on vegetation from urban expansion in drylands within the context of rapid urbanization could help enhance the sustainability of dryland cities. With the use of the drylands of northern China (DNC) as an example, we applied the vegetation disturbance index to investigate the negative and positive effects on vegetation from urban expansion in drylands. The results revealed that the DNC experienced massive and rapid urban expansion from 2000 to 2020. Urban land in the entire DNC increased by 19,646 km2 from 8141 to 27,787 km2, with an annual growth rate of 6.3 %. Urban expansion in the DNC imposed both negative and positive effects on regional vegetation. The area with negative effects reached 7736 km2 and was mainly concentrated in the dry subhumid zones. The area with positive effects amounted to 5011 km2 and was comparable among the dry subhumid, semiarid, and arid zones. Land use/cover change induced by population growth significantly contributed to these negative effects, while the positive effects were largely caused by economic growth. Therefore, it is recommended to strike a balance between urban growth and vegetation conservation to mitigate the adverse effects on vegetation from urban expansion in drylands. Simultaneously, it is imperative to expand urban green spaces and build sustainable and livable ecological cities to facilitate sustainable urban development.

Urbanization promotes carbon storage or not? The evidence during the rapid process of China

China's commitment to attaining carbon neutrality by 2060 has galvanized research into carbon sequestration, a critical approach for mitigating climate change. Despite the rapid urbanization observed since the turn of the millennium, a comprehensive analysis of how urbanization influences urban carbon storage throughout China remains elusive. Our investigation delves into the nuanced effects of urbanization on carbon storage, dissecting both the direct and indirect influences by considering urban-suburban gradients and varying degrees of urban intensity. We particularly scrutinize the roles of climatic and anthropogenic factors in mediating the indirect effects of urbanization on carbon storage. Our findings reveal that urbanization in China has precipitated a direct reduction in carbon storage by approximately 13.89 Tg of carbon (Tg C). Remarkably, urban sprawl has led to a diminution of vegetation carbon storage by 8.65 Tg C and a decrease in soil carbon storage by 5.24 Tg C, the latter resulting from the sequestration of impervious surfaces and the elimination of organic matter inputs following vegetation removal. Meanwhile, carbon storage in urban greenspaces has exhibited an increase of 6.90 Tg C and offsetting 49.70% of the carbon loss induced by direct urbanization effects. However, the indirect effects of urbanization predominantly diminish carbon storage in urban greenspaces by an average of 5.40%. The degree of urban vegetation management emerges as a pivotal factor influencing the indirect effects of urbanization on carbon storage. To bolster urban carbon storage, curbing urban sprawl and augmenting urban green spaces are imperative strategies. Insights from this study are instrumental in steering sustainable urban planning and advancing towards the goal of carbon neutrality.

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.

Interannual Variations in Terrestrial Net Ecosystem Productivity and Climate Attribution in the Southern Hilly Region of China

The vegetation ecosystem in the southern hilly region of China (SHRC) plays a crucial role in the country's carbon reservoir. Clarifying the dynamics of net primary productivity (NPP) in this area and its response to climate factors in the context of climate change is important for national forest ecology, management, and carbon neutrality efforts. This study, based on remote sensing and meteorological data spanning the period 2001 to 2021, aims to unveil the spatiotemporal patterns of vegetation productivity and climate factors in the southern hilly region, explore interannual variation characteristics of vegetation productivity with altitude, and investigate the response characteristics of NPP to various climate factors. The results indicate that from 2001 to 2021, the annual average NPP in the southern hilly region had a significant increasing trend of 2.13 ± 0.78 g m-2 a-1. The trend of NPP varies significantly with altitude. Despite a general substantial upward trend in vegetation NPP, regions at lower elevations exhibit a faster rate of increase, suggesting a diminishing difference in the NPP of different elevation ranges. The overall rise in average temperature has positive implications for the southern hilly region, while the impact of precipitation on vegetation NPP demonstrates noticeable spatial heterogeneity. Regions in which vegetation NPP is significantly negatively correlated with precipitation are mainly concentrated in the southern areas of Guangdong, Fujian, and Jiangxi provinces. In contrast, other regions further away from the southeastern coast tend to exhibit a positive correlation. Over the past two decades, there has been an asymmetry in the diurnal temperature variation in the SHRC, with the nighttime warming rate being 1.8 times that of the daytime warming rate. The positive impact of daytime warming on NPP of vegetation is more pronounced than the impact of nighttime temperature changes. Understanding the spatiotemporal patterns of NPP in the SHRC and the characteristics of its response to climate factors contributes to enhancing our ability to protect and manage vegetation resources amidst the challenges of global climate change.

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 of global urban expansion on the terrestrial vegetation carbon sequestration capacity

Continuous urban expansion has a negative impact on the potential of terrestrial vegetation. Till now, the mechanism of such impact remains unclear, and there have been no systematic investigations. In this study, we design a theoretical framework by laterally bridging urban boundaries to explain the distress of regional disparities and longitudinally quantify the impacts of urban expansion on net ecosystem productivity (NEP). The findings demonstrate that global urban expanded by 37.60 × 10⁴ km² during 1990-2017, which is one of the causes of vegetation carbon loss. Meanwhile, certain climatic changes (e.g., rising temperature, rising CO₂, and nitrogen deposition) caused by urban expansion indirectly boosted vegetation carbon sequestration potential through photosynthetic enhancement. The direct decrease in NEP due to the urban expansion (occupying 0.25 % of the Earth's land area) offsets the 1.79 % increase due to the indirect impact. Our findings contribute to a better understanding of the uncertainty associated with urban expansion towards carbon neutrality and provide a scientific reference for sustainable urban development worldwide.

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.

Spatial scale transformation-based estimation model for fresh grass yield: a case study of the Xilingol Grassland, Inner Mongolia, China

Estimating the grass yield of a grassland area is of vital theoretical and practical significance for determining grazing capacity and maintaining ecological balance. Due to the spatial inconsistency between sampling and remote sensing data, improving the accuracy of fresh grass yield (FGY) estimation based on remote sensing is difficult. Using vegetation coverage at different spatial scales, this paper proposes a spatial scale transformation (SST)-based estimation model for FGY adopting normalized difference vegetation index (NDVI) as its estimation factor, using the grassland in Xilingol League, Inner Mongolia, as the study area. Results showed that the SST-based FGY estimation model was able to greatly improve estimation precision; the relative estimation error (REE) of the estimation models constructed using linear with intercept zero (linear-0) and power functions were 18.16% and 18.35%, respectively. The estimation models constructed using linear-0 and power functions were employed to estimate the grass yield of the grassland in Xilingol League, and the total FGYs estimated were 8.777 × 10¹⁰ kg and 8.583 × 10¹⁰ kg, respectively. The two models obtained roughly the same estimates, but there were significant differences between them in the spatial distributions of FGY per unit. Taking net primary productivity (NPP) as an example, the effectiveness of other remote sensing data as estimation factors was further verified, and the results showed that SST-based estimation for FGY also effectively improved the estimation accuracy of grass yield.

Evaluation of urban expansion and the impacts on vegetation in Chinese Loess Plateau: a multi-scale study

Vegetation degradation caused by rapid urban expansion is a pressing global challenge. Focusing on the Chinese Loess Plateau (CLP), we use satellite observations from 2000 to 2017 to evaluate the spatiotemporal pattern of urban expansion, and its imprint on vegetation across old urban, new urban, urban, non-urban areas as well as the entire urbanization intensity (UI) gradient (from 0 to 100%). We found a massive increase of urban impervious surface area (UISA) in the CLP from 2000 to 2017, and an uneven expansion of UISA at different urban agglomerations and cities. Less green were found in urban and new urban areas, while old urban and non-urban areas generally showed an improved greening pattern. In addition, the annual maximum EVI (EVI_max) differences between urban and non-urban areas were - 0.0995 on average from 2000 to 2017. The Guanzhong Plain urban agglomeration (GPUA) witnessed the most significant EVI_max differences (- 0.120), and the Ningxia Yanhuang urban agglomeration (NYUA) witnessed the lowest EVI_max differences (- 0.012). The EVI_max showed significantly decreased trends along the entire spectrum of urbanization gradient for 97.4% (38 of 39) cities and five urban agglomerations. The most significant decrease was found in the GUPA (slope =  - 0.0197/10a, p < 0.01), while the smallest drop was found in the NYUA (slope =  - 0.011/10a, p < 0.01). This study offered a fundamental support for understanding the vegetation variation along the urban-rural gradient, which may help stakeholders to make better ecological management policies for urban vegetation in ecologically fragile areas.

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.

Nonlinear Characteristics of NPP Based on Ensemble Empirical Mode Decomposition from 1982 to 2015—A Case Study of Six Coastal Provinces in Southeast China

Monitoring vegetation net primary productivity (NPP) is very important for evaluating ecosystem health. However, the nonlinear characteristics of the vegetation NPP remain unclear in the six provinces along the Maritime Silk Road in China. In this study, using NDVI and meteorological data from 1982 to 2015, NPP was estimated with the Carnegie-Ames-Stanford Approach (CASA) model based on vegetation type dynamics, and its nonlinear characteristics were explored through the ensemble empirical mode decomposition (EEMD) method. The results showed that: (1) The total NPP in the changed vegetation types caused by ecological engineering and urbanization increased but decreased in those caused by agricultural reclamation and vegetation destruction, (2) the vegetation NPP was dominated by interannual variations, mainly in the middle of the study area, while by long-term trends, mainly in the southwest and northeast, (3) for most of the vegetation types, NPP was dominated by the monotonically increasing trend. Although vegetation NPP in the urban land mainly showed a decreasing trend (monotonic decrease and decrease from increase), there were large areas in which NPP increased from decreasing. Although vegetation NPP in the farmland mainly showed increasing trends, there were large areas that faced the risk of NPP decreasing; (4) dynamical changes of vegetation type by agricultural reclamation and vegetation destruction made the NPP trend monotonically decrease in large areas, leading to ecosystem degradation, while those caused by urbanization and ecological engineering mainly made the NPP increase from decreasing, leading to later recovery from early degradation. Our results highlighted the importance of vegetation type dynamics for accurately estimating vegetation NPP, as well as for assessing their impacts, and the importance of nonlinear analysis for deepening our understanding of vegetation NPP changes.

Spatiotemporal Dynamics of Vegetation Net Primary Productivity and Its Response to Climate Change in Inner Mongolia from 2002 to 2019

Understanding vegetation dynamics and their responses to climate change are essential to enhance the carbon sequestration of the terrestrial ecosystem under global warming. Although some studies have identified that there is a close relationship between vegetation net primary productivity and climate change, it is unclear whether this response exists in ecologically fragile areas, especially in Inner Mongolia, in which multiple ecological ecotones are related to vegetation types. This study uses the Carnegie–Ames–Stanford Approach (CASA) model to estimate vegetation NPP in Inner Mongolia from 2002 to 2019 and focuses on the spatial and temporal changes of NPP of different vegetation types and their responses to three typical climate factors: precipitation, temperature, and solar radiation. The results show that the NPP estimated by the CASA model agrees well with the observed NPP (R2 = 0.66, p < 0.001). The vegetation NPP in Inner Mongolia decreases gradually from northeast to southwest, and the average NPP is 223.50 gC ∙ m−2. From 2002 to 2019, the NPP of all vegetation types trended upward, but exhibiting different rates. The vegetation types, ranked in order of decreasing NPP, are forest, cropland, grassland, and desert. The NPP response of different vegetation types to climate factors possesses significant differences. The cropland NPP and grassland NPP are mainly affected by precipitation, the desert NPP is controlled by both precipitation and solar radiation, and the forest NPP is determined by all three climate factors.

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.

Land Degradation and Development Processes and Their Response to Climate Change and Human Activity in China from 1982 to 2015

Land degradation and development (LDD) has become an urgent global issue. Quick and accurate monitoring of LDD dynamics is key to the sustainability of land resources. By integrating normalized difference vegetation index (NDVI) and net primary productivity (NPP) based on the Euclidean distance method, a LDD index (LDDI) was introduced to detect LDD processes, and to explore its quantitative relationship with climate change and human activity in China from 1985 to 2015. Overall, China has experienced significant land development, about 45% of China’s mainland, during the study period. Climate change (temperature and precipitation) played limited roles in the affected LDD, while human activity was the dominant driving force. Specifically, LDD caused by human activity accounted for about 58% of the total, while LDD caused by climate change only accounted for 0.34% of the total area. Results from the present study can provide insight into LDD processes and their driving factors and promote land sustainability in China and around the world.

Estimating the distribution and productivity characters of Larix kaempferi in response to climate change

Understanding the distribution, net primary productivity (NPP) and environmental constraints of Larix kaempferi is crucial to predict how global climate change will affect its growth and future dynamics. We simulated future changes in the globally suitable distribution patterns and the NPP dynamics under different representative concentration pathways (RCPs) using MaxEnt and Physiological Principles in Predicting Growth (3-PG) models. The results showed that suitable distribution areas for Larix kaempferi were concentrated in Europe and Asia, followed by North America, under current climate conditions. Globally, about 33.75% of the suitable area was in China. Suitable areas decreased and shifted northward in Asia, Europe and China in the RCP scenarios. Larix kaempferi could adapt or move to higher latitudes/altitudes to mitigate the negative impacts of climate change. The NPP of Larix kaempferi in China was 241.85-863.57 g m^-2 a^-1 simulated by the 3-PG model after local parameterization, which was consistent with the measured NPP. Changes in NPP were predicted in future climates. When the correlations between climate factors and NPP were examined, under the more optimistic scenarios, NPP would increase significantly. The key parameters of the 3-PG model were the optimal temperature for growth, forest age, and the number of days of lost productivity in each frost period. Therefore, climate change has a quantitative and significant impact on the distribution and productivity of L. kaempferi, which was estimated successfully with the two modeling approaches. Our results will contribute to the improved cultivation, environment and management of L. kaempferi and potentially of other deciduous gymnosperms.

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.

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.

Severe drought events inducing large decrease of net primary productivity in mainland China during 1982-2015

The analysis of the impact of drought events on terrestrial net primary productivity (NPP) is significant to understand the effects of droughts on regional/global carbon cycling. During the past three decades, terrestrial ecosystems in mainland China have been frequently impacted by drought events. However, quantitative analyses of the variation of NPP induced by droughts are still not enough. Therefore, this study explored the response of NPP to drought events from 1982 to 2015 based on the standardized evapotranspiration deficit index (SEDI) and an NPP dataset obtained from the Carnegie-Ames-Stanford Approach model. We first identified drought events and analyzed the characteristics of drought events using a three-dimensional clustering algorithm. Subsequently, we determined the NPP variations in the drought-affected areas during the droughts and explored the correlation between the NPP variation and the drought characteristics. The results showed that 152 persistent drought events lasting at least 3 months were identified. Most events had durations between 3 and 5 months, and 19 events lasted >9 months. A negative NPP was detected in >60% of the drought-affected areas during long-term (>6 months) and severe (>4 × 10⁶ km² month) drought events and the total NPP showed a clear decrease during these events. In general, strong drought events reduced the total NPP by >30 TgC in the Northern Region, South Region, Southwest Region, and Northeast Region. The substantial decrease was mainly caused by the NPP anomaly from April to September. The NPP responses to drought events exhibited differences due to different drought characteristics. Although a high proportion of the drought-affected areas experienced a decrease in NPP during most short-term (<5 months) and less severe droughts (<2 × 10⁶ km² month), the total NPP did not exhibit a large change during these events.

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.

Impacts of Precipitation and Temperature on Changes in the Terrestrial Ecosystem Pattern in the Yangtze River Economic Belt, China

The terrestrial ecosystem plays an important role in maintaining an ecological balance, protecting the ecological environment, and promoting the sustainable development of human beings. The impacts of precipitation, temperature, and other natural factors on terrestrial ecosystem pattern change (TEPC) are the basis for promoting the healthy development of the terrestrial ecosystem. This paper took the Yangtze River Economic Belt (YREB) as the study area, analyzed the temporal and spatial characteristics of TEPC from 1995 to 2015, and used spatial transfer matrix and terrestrial ecosystem pattern dynamic degree models to analyze the area transformation between different terrestrial ecosystem types. A bivariate spatial autocorrelation model and a panel data regression model were used to study the impacts of precipitation and temperature on TEPC. The results show that: (1) The basic pattern of the terrestrial ecosystem developed in a relatively stable manner from 1995 to 2005 in the YREB, and transformations between the farmland ecosystem, forest ecosystem, and grassland ecosystem were more frequent. The temporal and spatial evolution of precipitation and temperature in the YREB showed significant regional differences. (2) There was a significant negative bivariate global spatial autocorrelation effect of precipitation and temperature on the area change of the forest ecosystem, and a positive effect on the area change of the settlement ecosystem. The local spatial correlation between precipitation or temperature and the terrestrial ecosystem showed significant scattered distribution characteristics. (3) The impacts of precipitation and temperature on TEPC showed significant regional characteristics on the provincial scale. The impact utility in the tail region is basically negative, while both positive and negative effects exist in the central and head regions of the YREB. Moreover, the impact showed significant spatial heterogeneity on the city scale. (4) The Chinese government has promulgated policies and measures for strategic planning, ecological environment protection, and economic support, which could effectively promote ecological and sustainable development of the YREB and promote the coordinated development of the ecology, economy, and society in China.