Net Primary Productivity Values Research Articles

Short-term effect of the harvesting method on ecosystem carbon budget in hemiboreal Scots pine forest: Shelterwood cutting versus clear-cut

Shelterwood cutting (SC) has been highlighted as an alternative method to clear-cut (CC)-based even-aged forest management. However, compared to CC, the effect of SC on stand carbon (C) balance is still poorly understood at the ecosystem level. We examined the prompt effect of SC versus CC on ecosystem net primary production (NEP) on a short-term scale, using the C budgeting method combined with eddy covariance (EC) measurements in hemiboreal mature Scots pine stands.The early effect of SC on annual C budget after removing 30–40 % of the growing stock revealed diverse patterns in the studied stands; NEP varied from 0.62 to −1.3 t C ha−1 yr−1 for the C sink and the C source, respectively. However, C loss decreased already in the second post-thinning year and levelled out attaining −0.41 t C ha−1 yr−1, which is close to balance.Furthermore, C loss declined in the second post-harvesting year at the CC sites as a result of the increased production of the ground vegetation and the decreased soil heterotrophic respiration (Rh) flux. However, C loss from dry mesotrophic clear-cuts was almost −1.8 t C ha−1 yr−1 for both study sites. Since estimation of the individual C fluxes for C budgeting is associated with variability-induced errors, the estimated values of NEP contain uncertainties of various levels.The estimated annual cumulative Rh flux was significantly higher in the SC versus CC areas and the mean annual Rh values across the study sites were 3.57 ± 0.25 and 2.59 ± 0.09 t C ha−1 yr−1, respectively.Annual estimated NEE after SC was 1.8 ± 0.52 t C ha−1 yr−1, gross primary ecosystem production was 9.28 ± 0.97 and total ecosystem respiration was 7.47± 0.28 t C ha−1 yr−1. The discrepancy between the estimated values of NEE and NEP was 1.2 t C ha−1 yr−1.In the short term SC demonstrated some advantage over CC from the perspective of the C cycle, but the difference in NEP values between the SC and CC treatments was not convincingly overwhelming. Hence, SC allows to maintain the forest cover for a longer period and to avoid drastic changes in the landscape; still, after SC, C budget varied between the C sink and the C source.

Unveiling the Impact of Urbanization on Net Primary Productivity: Insights from the Yangtze River Delta Urban Agglomeration

Urbanization has significantly altered the carbon cycle of the terrestrial environment, particularly in relation to net primary productivity (NPP). Gaining a more comprehensive comprehension of how NPP is affected by urbanization is crucial for obtaining fresh perspectives on sustainable urban landscape design and decision making. While there is a significant body of research examining the geographical and temporal patterns of NPP supply capacity, there are only a few studies that have investigated the spatial relationships between NPP and urbanization, particularly at the grid scale. This research investigated the temporal and geographical features and patterns of NPP and their impact mechanisms. In order to estimate NPP and the level of urbanization in the Yangtze River Delta Urban Agglomeration (YRDUA), we used a combination of different models and datasets. To evaluate the geographical correlations and dependence between NPP and urbanization, we utilized local bivariate autocorrelation methods and spatial regression models to describe and visualize these relationships. The findings revealed that there was a consistent negative relationship between NPP and urbanization on a global scale from 1990 to 2020. However, when examining the local scale, the geographical correlations could be classified into four distinct categories: areas with both low NPP and low urbanization, areas with high NPP and high urbanization, areas with low NPP and high urbanization, and areas with high NPP and low urbanization. Our analysis showed that spatial regression models are more suitable for quantifying the spatial relationship between NPP and urbanization due to their ability to include the impacts of spatial Moran’s I techniques. Due to the growing urbanization, the highest NPP value was recorded in 2005, followed by 2000, 2020, and 2010. Conversely, the smallest association was observed in 2015. Examining the geographical connection between NPP and urbanization offers theoretical and practical insights for urban planning that prioritizes human needs and promotes sustainable development. It also aids in the development of reasonable methods for organizing ecological functional systems.

Net Primary Production of Ecoregions Across North America in Response to Drought and Wildfires From 2015 to 2022

AbstractEcosystem models are valuable tools to make climate‐related assessments of change when ground‐based measurements of water and carbon fluxes are not adequate to realistically capture regional variability. The Carnegie‐Ames‐Stanford Approach (CASA) is one such model based on satellite observations of monthly vegetation cover to estimate net primary production (NPP) of terrestrial ecosystems. CASA model predictions from 2015 to 2022 revealed several notable high and low periods in growing season NPP totals in certain biomes. Both Temperate Broadleaf and Boreal Forest production shifted from relatively high average NPP values in 2015 through 2019 to lower levels in 2020, typically representing a loss of 10%–14% of growing season NPP flux. This rapid decline in growing season NPP from 2019 to 2020–2021 was also estimated for the Temperate Grasslands and Savanna, Temperate Conifer Forest, and Tundra biomes. In contrast to the climate patterns in the temperate biomes that developed into severe widespread drought in 2020 and 2021 due to low precipitation totals and extreme hot temperatures, growing season NPP in the Tundra biome was depressed in these same years by colder temperature induced drought conditions at the high latitudes of North America. Drought severity classes were closely associated with different levels of decline in NPP in most biomes. Trends in NPP in areas of the largest wildfires in North America that burned between 2012 and 2021 were examined to assess recovery of vegetation and the resiliency of ecosystems during extreme drought periods.

Assessing the spatial occupation and ecological impact of human activities in Chengguan district, Lhasa city, Tibetan Plateau

In this study, the ecological impact of human activities and the space occupied by construction and arable land on the Tibetan Plateau were examined, focusing on changes in the net primary productivity (NPP) as a key indicator of ecological health. With the utilization of land use data and multiyear average NPP data from 2002 to 2020, we analyzed the effects of the conversion of zonal vegetation into construction and arable land on carbon sequestration and oxygen release in Chengguan District, Lhasa city. Our findings indicated a marked spatial difference in the NPP among different land types. Regarding the original zonal vegetation, the NPP ranged from 0.2 to 0.3 kg/m2. Construction land showed a decrease in the NPP, with values ranging from 0.16 to 0.26 kg/m2, suggesting a decrease in ecological productivity. Conversely, arable land exhibited an increase in the NPP, with average values exceeding 0.3 kg/m2. This increase suggested enhanced productivity, particularly in regions where the original zonal vegetation provided lower NPP values. However, this enhanced productivity may not necessarily indicate a positive ecological change. In fact, such increases could potentially disrupt the natural balance of ecosystems, leading to unforeseen ecological consequences. The original zonal vegetation, with NPP values ranging from 0.12 to 0.43 kg/m2, exhibited higher ecological stability and adaptability than the other land types. This wider NPP range emphasizes the inherent resilience of native vegetation, which could sustain diverse ecological functions under varying environmental conditions. These findings demonstrate the urgent need for sustainable land use management on the Tibetan Plateau. This study highlights the importance of considering the ecological impact of land use changes in regional development strategies, ensuring the preservation and enhancement in the unique and fragile plateau ecosystem.

Productivity response characteristics of different grasslands to flash drought and their relationship with drought tolerance

Flash droughts have attracted worldwide attention because of their rapid outbreak and extensive influence. However, studies regarding the characteristics and effects of flash droughts in grassland ecosystems are insufficient. In this study, the frequency and intensity characteristics of flash droughts in the Xilinguole Grassland in China were studied. The response characteristics of the productivity of different types of grassland to flash droughts and the relationship between these characteristics and the drought tolerance of grassland were revealed. The results show that (1) flash droughts had the greatest impact on grassland net primary productivity (NPP) and rain use efficiency (RUE) in summer and spring, respectively, with a level of intensity above that of moderate drought. Strong evapotranspiration flash droughts (SEFD) require more attention from decision-makers than heat wave flash droughts (HWFD). A higher frequency and intensity of flash droughts had a greater impact on vegetation. (2) Flash droughts caused moderate negative anomalies in the NPP and RUE indices in more than 90 % of the grasslands. The longest lag time of the NPP response to flash droughts was 2 months, and NPP anomalies were affected by flash droughts for nearly 2 months. RUE was more sensitive to flash droughts than NPP. RUE responded to flash droughts within 10 days, with a decrease of more than 80 % in magnitude, which was 30 % higher than that of the NPP, and the duration of the anomaly was half that of the NPP. (3) Grasslands with a high sensitivity to flash droughts had shorter response durations, fewer abnormalities, better recovery abilities and better drought tolerance. The drought tolerance of grasslands did not increase in association with large NPP and RUE values. Desert grasslands were the most drought tolerant, while meadow grasslands were the least drought tolerant, with the highest risk of flash droughts. This study provides theoretical support for improving the ability of an ecosystem to cope with flash drought risk and scientific grassland management.

Impacts of Extreme Climate Events at Different Altitudinal Gradients on Vegetation NPP in Songhua River Basin

Vegetation net primary production (NPP) is an essential index for determining the quality of terrestrial ecosystems and their potential carbon storage ability. The impacts of extreme climate events on vegetation NPP are different under different altitude gradients. However, the research on the impact of extreme climate events on the spatial variation in vegetation NPP and the coupling effects under different altitude conditions remain insufficient. Using the MOD17A3HGF remote sensing data set and RClimDex 1.9 software, the vegetation NPP and 10 extreme climate indices in the Songhua River Basin from 2001 to 2020 were calculated, respectively. The spatial and temporal evolution characteristics of vegetation NPP and its response mechanism to extreme climate events in the Songhua River Basin under different altitude gradients were analyzed by means of trend analysis, correlation analysis, regression analysis, GeoDetector, and relative importance analysis. The results showed that:① the vegetation NPP (calculated by C) in the Songhua River Basin increased significantly at the rate of 4.13 g·(m2·a)-1 from 2001 to 2020 (P < 0.01), and the rates of 3.65, 4.04, 4.70, 5.09, and 4.57 g·(m2·a)-1 at the altitude gradients of 29-255, 255-440, 440-658, 658-935, and 935-2 589 m, respectively (P < 0.01). ② The spatial distribution pattern of vegetation NPP presented "high around and low in the middle," and the fluctuation of vegetation NPP in high altitude areas was more obvious than that in low altitude areas; for example, the average value of vegetation NPP at an altitude gradient from 29 to 255 m had a lower value, whereas the other altitude gradients had higher mean values than the mean value of the basin. ③ The extreme precipitation events in the Songhua River Basin were the main influencing factors of vegetation NPP, i.e., the vegetation NPP in low-altitude areas was mainly affected by extreme precipitation events, whereas the values in high-altitude areas were affected by both extreme precipitation events and extreme temperature events. The results of this research can provide a scientific basis for improving the carbon cycle model of the terrestrial ecosystem in the Songhua River Basin, quantifying the ability of carbon storage of vegetation and formulating policies to deal with climate change.

Multi-source data-driven estimation of urban net primary productivity: A case study of Wuhan

Amidst urban expansion, numerous ecological challenges have surfaced, notably the swift alterations in the net primary productivity (NPP), presenting complexities in discerning their scale and spatial distribution. Leveraging meteorological data, multi-modal remote sensing datasets, field sampling data, and a digital elevation model (DEM), this research amalgamates field assessments, model simulations, and cutting-edge remote sensing techniques to craft a city-scale NPP estimation model for vegetation rooted in the Carnegie-Ames-Stanford Approach (CASA). This improved CASA model facilitated the computation of monthly NPP for Wuhan over 2017–2020. Our analysis divulged NPP spatiotemporal trends and distribution nuances in Wuhan, and assessed meteorological influences on the same. Salient conclusions encompass: (1) Wuhan's annual NPP maximum between 984.40 and 1310.51 gC/(m2 a), averaging from 316.78 to 430.32 gC/(m2 a), and culminating in totals from 170.15 to 231.60 × 1010 gC/a. (2) Monthly NPP trajectories in Wuhan exhibited a unimodal pattern: ascending from January to June, peaking in July–August, and tapering off through September-December, with a spatial distribution characterized by lower NPP values centrally and higher values peripherally. (3) Regionally, temperature markedly influenced NPP over precipitation. This research underpins urban ecological planning, offering empirical insights and strategic guidance for fostering a sustainable coexistence between humans and their environment, and charting future urban development paradigms.

Bioenergy potential from agricultural by-product in 2030: An AI-based spatial analysis and climate change scenarios in a Chinese region

Addressing the pressing need for sustainable bioenergy sources amid the growing climate crisis, this study investigates potential crop bioenergy output in the Jianghan Plain, Hubei, China. The research leverages Backpropagation Artificial Neural Network models to predict the accumulated net primary productivity (NPP) of various crops, i.e., single rice, double rice, maize, and wheat, in Jianghan Plain. The models highlight a strong predictive performance, with the SE model achieving an R2 of 0.83 and wheat model an R2 of 0.90, implying these models can be utilized reliably for future NPP forecasting. Our evaluation of past and future NPP values reveals a negative correlation between the increase in NPP values and observed temperature trends. This emphasizes the significant impact of temperature on crop bioenergy potential. For future NPP predictions, scenario (S3a) under Temperature Control strategies at medium-effort mitigation yields a favourable outcome for all crops, particularly SE. Additionally, the results suggest that aggressive decarbonization and global warming mitigation strategies are vital for enhancing NPP values. However, the study also highlights potential trade-offs and stresses the necessity for region-specific climate reconciliation strategies; for instance, midland counties benefit from temperature control, whereas the sideline favours CO2 mitigation. The study further investigates the spatial distribution of potential bioenergy, with the southwestern part of the plain holding more bioenergy potential, providing an essential reference for future energy planning. By 2030, in Jianghan Plain, when fully integrated with reasonable climate responses, there could be substantial bioenergy potential from crop residues reaching (1.2–1.9) × 109 MJ, which is 11% less than the current.

Assessing Phytoplankton Primary Productivity Variability in the Changjiang Estuary, East China Sea From Coupled Fast Repetition Rate (FRR) Fluorometry and Chlorophyll‐a Measurements

AbstractPhytoplankton primary productivity (PP) varies significantly over environmental gradients, particularly in physically‐dynamic systems such as estuaries and coastal seas. During summer, runoff peaks in the Changjiang River driving large environmental gradients in both the Changjiang estuary and adjacent East China Sea (ECS), likely driving significant variability in PP. As satellite models of PP often underperform in coastal waters, we aimed to develop a novel approach for assessing net PP variability in such a dynamic environment. Parallel in situ measurements of Fast Repetition Rate (FRR) fluorometry and carbon (C) uptake rates were conducted for the first time in this region during two summer cruises in 2019 and 2021. A series of 13C‐incubations (n = 31) were performed, with measured PP ranging from ∼6 to 1,700 mgC m−3 d−1. Net PP values were significantly correlated with salinity (r = 0.45), phytoplankton chlorophyll a (Chl‐a, r = 0.88), Photosystem II (PSII) functional absorption cross‐section (σPSII, r = −0.76) and maximum PSII quantum yield (Fv/Fm, r = 0.59). Stepwise regression analysis showed that Chl‐a and σPSII were the strongest predictors of net PP. A generalized additive model (GAM) was also used to estimate net PP considering nonlinear effects of Chl‐a and σPSII. We demonstrate that GAM outperforms linear modeling approaches in estimating net PP in this study, as evidenced by a lower root mean square error (∼140 vs. 250 mgC m−3 d−1). Our novel approach provides a valuable tool to examine carbon cycling dynamics in this important region.

The Bogs in a Forest–Steppe Region of Western Siberia: Plant Biomass and Net Primary Production (NPP)

Hereby, we report the new experimental data of plant biomass and biological productivity (net primary production, NPP) of wetland/peatland plant communities of oligotrophic bogs located on the same latitude, but at a distance of 1300 km west-east in the forest–steppe region of Western Siberia. The data were collected by implementing direct in situ measurements based on a unique methodology developed by authors. The study revealed that the values of net primary production (NPP) are basically constrained by the live fraction of plant biomass (or phytomass). It also revealed that the dead fraction of plant biomass (mortmass), along with the live fraction of biomass (phytomass) and net primary production (NPP), all major components of the carbon cycle, differ significantly at the two study sites. The values of dead biomass (mortmass), live biomass (phytomass) and net primary production (NPP) were found at significantly higher values in bog ecosystems studied in western regions than in those of the eastern regions.

Dry matter dynamics and carbon flux along riverine forests of Gori valley, Western Himalaya

IntroductionRiverine forests in the Himalaya represent a biodiverse, dynamic, and complex ecosystem that offers numerous ecosystem services to local and downstream communities and also contributes to the regional carbon cycle. However, these forests have not been assessed for their contribution to dry matter dynamics and carbon flux. We studied these parameters along three classes of riverine forests in eastern Uttarakhand, dominated by Macaranga, Alnus, and Quercus-Machilus forest.MethodsUsing volume equations, we assessed tree biomass, carbon storage, and sequestration in the study area.ResultsThe total standing tree biomass in Macaranga, Alnus, and Quercus-Machilus forest ranged from 256.6 to 558.1 Mg ha−1, 460.7 to 485.8 Mg ha−1, and 508.6 to 692.1 Mg ha−1, respectively. A total of 77.6–79.6% of vegetation biomass was stored in the aboveground biomass and 20.4–22.4% in belowground plant parts across the riverine forests. The carbon stock in Macaranga forest ranged from 115.5 to 251.1 Mg ha−1, in Alnus forest from 207.3 to 218.6 Mg ha−1, and in Quercus-Machilus forest from 228.9 to 311.4 Mg ha−1. The mean annual litterfall was accounted maximum for Quercus-Machilus forest (5.94 ± 0.54 Mg ha−1 yr.−1), followed by Alnus (5.57 ± 0.31 Mg ha−1 yr.−1) and Macaranga forest (4.67 ± 0.39 Mg ha−1 yr.−1). The highest value of litterfall was recorded during summer (3.40 ± 0.01 Mg ha−1 yr.−1) and the lowest in winter (0.74 ± 0.01 Mg ha−1 yr.−1). The mean value of net primary productivity and carbon sequestration was estimated to be highest in Quercus-Machilus forest (15.8 ± 0.9 Mg ha−1 yr.−1 and 7.1 ± 0.9 Mg C ha−1 yr.−1, respectively) and lowest in Alnus forest (13.9 ± 0.3 Mg ha−1 yr.−1 and 6.1 ± 0.3 Mg C ha−1 yr.−1, respectively).DiscussionThe results highlight that riverine forests play a critical role in providing a large sink for atmospheric CO2. To improve sustainable ecosystem services and climate change mitigation, riverine forests must be effectively managed and conserved in the region.

Dynamic changes in net primary productivity of marsh wetland vegetation in China from 2005 to 2015

Wetlands are one of the world's three major ecosystems. Marsh wetland vegetation, with its unique characteristics, is playing an increasingly prominent role in absorbing atmospheric carbon dioxide and mitigating climate warming. This study estimated the annual, seasonal, and monthly trends of marsh wetland vegetation net primary productivity (NPP) in China from 2005 to 2015 based on the Carnegie–Ames–Stanford approach (CASA) model. The temporal and spatial characteristics of NPP were analyzed and the driving factors were discussed. The results showed that the annual marsh wetland vegetation NPP had an increasing trend from 2005 to 2015 on national scale in China, with the lowest and highest values in 2005 (202.03 gCm−2a−1) and 2015 (222.58 gCm−2a−1), respectively. The monthly seasonal variations in marsh wetland vegetation NPP consistent with the typical growth pattern of vegetation observed in China. Monthly marsh wetland vegetation NPP showed a unimodal distribution, and May to September were the main months for NPP accumulation. The highest vegetation NPP values occurred during the summer season. Marsh wetland vegetation types did impact the NPP distribution, Gramineous marsh vegetation contributed most to the total NPP (29%). Spatially, the NPP was higher in east than in the west, and higher in the center than in the south and north. An overall positive impact of precipitation and temperature on the Chinese marsh wetland vegetation NPP was revealed. The study recommended to give greater attention the conservation of Gramineous vegetation alongside the overall protection of Chinese marsh wetlands. Our findings can offer important evaluation results and guidance for the future addressing climate change and conservation and maintenance of the carbon sink capacity of marsh wetland vegetation in China.

Vegetation Dynamics and Its Trends Associated with Extreme Climate Events in the Yellow River Basin, China

As a vital ecological barrier in China, Yellow River Basin (YRB) is strategically significant for China’s national development and modernization. However, YRB has fragile ecosystems, and is sensitive to climatic change. Extreme climate events (e.g., heavy precipitation, heatwaves, and extreme hot and cold) occur frequently in this basin, but the implications (positive and negative effects) of these events on vegetation dynamics remains insufficiently understood. Combing with net primary productivity (NPP), the normalized difference vegetation index (NDVI) and extreme climate indexes, we explored the spatio–temporal characteristics of plants’ growth and extreme climate, together with the reaction of plants’ growth to extreme climate in the Yellow River Basin. This study demonstrated that annual NPP and NDVI of cropland, forest, and grassland in the study region all revealed a climbing tendency. The multi-year monthly averaged NPP and NDVI were characterized by a typical unimodal distribution, with the maximum values of NPP (66.18 gC·m−2) and NDVI (0.54) occurring in July and August, respectively. Spatially, multi–year averaged of vegetation indicators decreased from southeast to northwest. During the study period, carbon flux (NPP) and vegetation index (NDVI) both exhibited improvement in most of the YRB. The extreme precipitation indexes and extreme high temperature indexes indicated an increasing tendency; however, the extreme low temperature indexes reduced over time. NPP and NDVI were negatively associated with extreme low temperature indexes and positively correlated with extreme high temperature indexes, and extreme precipitation indicators other than consecutive dry days. Time lag cross–correlation analysis displayed that the influences of extreme temperature indexes on vegetation indexes (NPP and NDVI) were delayed by approximately six months, while the effects of extreme precipitation indexes were immediate. The study outcomes contribute to our comprehension of plants’ growth, and also their reaction to extreme climates, and offer essential support for evidence–based ecological management practices in the Yellow River Basin.

Dynamic Changes and Driving Mechanisms of Net Primary Production (NPP) in a Semi-Arid Region of China

The objective of this study is to analyze the spatiotemporal dynamics of net primary production (NPP) change combined with land use and to further explore the driving factors of NPP change, allowing us to provide a scientific reference point for optimizing the land-use structure and improving regional carbon sequestration capacity. The average annual NPP ranged from 200 to 300 gC/m2•a in the period of 2001–2020 in our study area. We used trend analysis and linear regression analysis to explore the spatial and temporal dynamic changes in annual NPP and analyzed the driving mechanism in a semiarid region (western Jilin Province) of China in the period of 2001–2020. The results showed that NPP presented a trend of fluctuating growth, and the spatial distribution of NPP showed that NPP values of cultivated land, forest and grassland were generally higher than those of other land-use types. The high value in the southeastern region and low value in the northwestern region were identified because there were large areas of cultivated land distributed in the southeastern part of the study area in the period of 2001–2020. The main driving factors that affected NPP were annual precipitation, CO2 emissions, GDP and hours of sunshine. NPP was positively correlated with annual precipitation, CO2 emissions and GDP, and it had a significant negative correlation with hours of sunshine. Our study provides important support for research into land-use structure and improvements to the regional carbon sequestration capacity, making an important contribution to regional sustainable development.

Changes in Water-Use Efficiency of Eucalyptus Plantations and Its Driving Factors in a Small County in South China

Ecosystem water-use efficiency (WUE) has been central in revealing the variability in terrestrial carbon and water cycles. Short-rotation plantations such as Eucalyptus plantations can simultaneously impact net primary production (NPP) and actual evapotranspiration (ETa), components of WUE, resulting in changes in terrestrial carbon and water cycles. However, there are few detailed studies on the changes in the WUE of Eucalyptus plantations at the catchment scale with high spatial remote sensing imagery. Here, we present the changes in the WUE of Eucalyptus plantations and its driving factors (i.e., NPP and ETa) using satellite-based models combined with 5-m spatial resolution RapidEye imagery in a small county in South China. The increases in ETa of Eucalyptus plantations are primarily the result of climate warming and result in low WUE of Eucalyptus plantations. The management practice used (short rotation in this study) can enhance the effect of climate warming on WUE by varying the NPP of Eucalyptus plantations. A high value of NPP leads to a high WUE of Eucalyptus plantations at the end of a short rotation, while a low value of NPP results in a low WUE at the beginning of another short rotation. Changes in the WUE of Eucalyptus plantations indicated large spatial and temporal variability, associated with climate warming and short-rotation practices.

NPP and Vegetation Carbon Sink Capacity Estimation of Urban Green Space Using the Optimized CASA Model: A Case Study of Five Chinese Cities

Urban area is a major source of CO2 and other greenhouse gases. Urban green space (UGS) is an essential element to increase carbon sequestration directly and reduce emission indirectly. In this study, the net primary production (NPP) and net ecosystem productivity (NEP) was monitored in order to enhance the carbon sequestration function of UGS and promote urban low-carbon development. Based on the Sentinel-2 L2A satellite images, meteorological data, and vegetation type data in 2019, we used the optimized Carnegie Ames Stanford Approach (CASA) model to estimate the NPP values of UGS types including attached green space, park green space, protective green space, and regional space in Beijing, Guangzhou, Shanghai, Shenyang, and Xi’an. The NEP values were evaluated based on NPP and soil heterotrophic respiration (RH) to quantify the vegetation carbon sink capacity. The accuracy test shows that the estimated NPP values based on the optimized CASA model are effective. The results indicate that the average NPP values (1008.5 gC·m−2·a−1) and vegetation carbon sink capacity (771.49 gC·m−2·a−1) of UGS in Beijing rank first among the cities, which is followed by the values in Guangzhou. The regional green space and park green space in five cities function as carbon sinks with high NPP values and have vegetation carbon sink capacity, whereas the attached green space in Shanghai and Xi’an as well as the protective green space in Guangzhou and Xi’an function as carbon sources. Moreover, the NEP distribution shows obvious spatial aggregation characteristics, that is, the high NEP values of UGS are clustered in mountainous forest areas in the west and north of Beijing, Northeast Guangzhou, and South Xi’an whereas the low NEP values are mostly concentrated in the urban built-up areas under strong influences of human activities. This research provides a new method for NPP and NEP estimation of UGS at the city scale and the scientific basis for the improvement of the vegetation carbon sink capacity of UGS.

Temporal and Spatial Characteristics of Soil Salinization and Its Impact on Cultivated Land Productivity in the BOHAI Rim Region

Soil salinization can have an inhibitory effect on crop productivity and pose a serious threat to regional agricultural resource utilization and sustainable development. However, there are scarce studies on the quantitative impact of soil salinization on crop productivity. The purpose of this study is to identify the spatial and temporal characteristics of the cultivated land, the soil salinization degree, and the net primary productivity (NPP) of vegetation in the Shandong region around the Bohai Sea and to couple the quantitative relationship between soil salinization and the productivity of the cultivated land. We found that the amount of cultivated land in the study area gradually decreased from 2001 to 2019. The degree of soil salinization in the cultivated land in the north of the study area increased slightly from 2001 to 2005 and decreased continuously after 2011. The NPP value of the cultivated land increased, fluctuating from 2001 to 2019. The spatial distribution of the NPP value was generally lower in the north than in the south, with Dongying District as the boundary. In addition, in different soil salt content (g/kg) intervals, the change trends in cultivated land NPP varied. When the salt content of cultivated soil was in the range of 0–3 g/kg, 3–7 g/kg, or 7–15 g/kg, for every 1 g/kg increase in salt content, the NPP value decreased by 43.62 gC m−2a−1, 30.36 gC m−2a−1, and 44.19 gC m−2a−1, respectively. These results are expected to provide decision-making support for strengthening the dynamic monitoring and regulation of cultivated land salinization and promoting sustainable utilization of salinized cultivated land in the coastal areas to alleviate the food crisis.

Insights into Spatiotemporal Variations in the NPP of Terrestrial Vegetation in Africa from 1981 to 2018

The net primary productivity (NPP) of vegetation is an important indicator used to evaluate the quality of terrestrial ecosystems and characterize the carbon balance of ecosystems. In this study, the spatiotemporal distribution and dynamic change in NPP in Africa from 1981 to 2018 were analyzed using the long time series data of NPP. The results of the trend and fluctuation analysis showed that the NPP in the Sahara arid region in northern Africa and the arid region in South Africa exhibited a significant reduction and a high degree of fluctuation; most of the NPP in the tropical rainforests in central Africa and the deciduous broadleaved forests and deciduous needle-leaved forests on the north and south sides of the tropical rainforests increased and showed a low degree of fluctuation; the Congo basin, Gabon, Cameroon, Ghana, Nigeria, Tanzania, and other regions were affected by human activities, while the NPP in these regions exhibited a significant reduction and a high degree of fluctuation. Anomaly analysis showed that the NPP in Africa generally exhibited a slow upward trend during the period from 1981 and 2018. The trend was basically consistent in different seasons, and can be segmented into three phases: (1) a phase of descent from 1981 to 1992, with the NPP below the average value in most years; (2) a phase of steady growth from 1993 to 2000, reaching a peak in 2000; (3) a phase of fluctuations from 2001 to 2018, where the NPP value was above the average value in all years except 2015 and 2016, when the NPP value was low due to abnormally high temperatures and drought. The Mann–Kendall test further showed that the annual and seasonal NPP in Africa exhibited a significant upward trend, and the mutation time points occurred around 1995. The wavelet time series analysis revealed obvious periodic changes in the time series of NPP in Africa. The annual and seasonal NPP showed clear oscillations on time scales of 7, 20, 29, and 55 years. The 55-year period had the strongest signal, and was the first main period. The study can provide a scientific gist for the sustainable development of environmental ecology, agricultural production, and the social economy in Africa.

Spatiotemporal Distribution of Carbon Sink Indicators—NPP and Its Driving Analysis in Ordos City, China

Ordos City is an important energy supply city for Chinese provinces and cities, providing a secure energy supply for China while also generating corresponding environmental pollution. Examining the spatiotemporal patterns of net primary productivity (NPP) in Ordos City and its driving factors is relevant to the realization of the carbon emission policy in Inner Mongolia. This study was undertaken to analyze NPP and its driving factors in Ordos City from 2000 to 2019 using NPP data, CO2 spatial grid data, meteorological data and statistical yearbook data accordingly. The NPP in Ordos City increased significantly from 2000 to 2019, mainly showing low values of NPP in the northwest and high values in the southeast. The usable grassland area and annual mean precipitation had a significant positive correlation with NPP, whereas the other factors had a more significant negative correlation. The usable grassland area had the largest influence on NPP, and fixed asset investment had the smallest influence on NPP. The total NPP–anthropogenic factor regression model and the mean NPP–natural factor regression model constructed allow for the prediction of NPP. Anthropogenic carbon emissions, population growth and usable grassland area were the main causes of NPP changes. Planting and protecting green plants and scientific and effective energy extraction plans are measures that enhance the degree of carbon sequestration in Ordos City.

Estimating net primary productivity of semi-arid Crimean pine stands using biogeochemical modelling, remote sensing, and machine learning

The aim of the paper was to predict net primary productivity (NPP) in pure Pinus nigra J.F. Arnold (Crimean pine) stands by consecutively implementing remote sensing, biogeochemical modelling, and machine learning techniques. In this context, NPP was estimated using Carnegie-Ames-Stanford Approach (CASA). Following, NPP was re-modelled with spectral characteristics of the P.nigra using multi-temporal remotely sensed images (Landsat 8 OLI and Sentinel-2), land use, soils and meteorological information in a total of 180 temporary sample plots. The model results were validated using litterfall samples from 30 stations for each forest stand, including needle, branch, cone, bark, male flower, and others. The highest relationship was between NPP and male flowers (r =‐−0.75). In addition, reflectance (R), vegetation indices (VI) and texture (TEX) values (calculated according to filter and degree) for each sample plot were calculated from each sensor. Multiple linear regression (MLR) was applied to define the best subset to model the NPP values with R, VI and TEX values using MLR, support vector machines (SVM) and deep learning (DL) methods. The best prediction accuracy was obtained in TEX data in the SVM method and Sentinel-2 sensor combination. NPP testing determination co-efficiency (R2) values were 0.95. The performance of the male flower litterfall in the validation control was promising for the modelling of NPP in Crimean pine. The TEX properties of the satellite images were well reflected by using different filters, degrees, and functions, resulting in achieving a high success.