Net Primary Productivity Loss Research Articles

The Analysis of NPP Changes under Different Climatic Zones and under Different Land Use Types in Henan Province, 2001–2020

Net Primary Productivity (NPP) is a crucial indicator of ecological environment quality. To better understand the carbon absorption and carbon cycling capabilities of Henan Province, this study investigates the trends and driving factors of NPP across different climatic zones and land use types. The Theil–Sen Median trend analysis method and the Mann–Kendall trend test are employed to monitor NPP changes from 2001 to 2020. The average annual NPP in Henan Province during this period was 414.61 gC·m−2·year−1, showing a significant increasing trend with a growth rate of 3.73 gC·m−2·year−1. Spatially, both the annual average NPP and its increase rate were higher in the western part of Henan compared to the eastern part, and NPP variability was more stable in the southern region than in the northern region. By classifying climatic zones and using the Geodetector method to assess NPP sensitivity to natural factors, the results show that climate and vegetation factors jointly influence NPP variations, with annual precipitation being the primary natural factor affecting NPP trends in Henan Province from 2001 to 2020. By analyzing the NPP gain and loss matrix, the impact of land use changes on NPP was evaluated. Forests had the highest average annual NPP at 483.52 gC·m−2·year−1, and the conversion of arable land to urban areas was identified as the primary land change type leading to NPP reductions. In the subtropical zone of Henan, forests, croplands, and grasslands exhibited higher NPP values and increase rates compared to those in the warm belt. This study provides new insights into the spatial variation of NPP caused by changes in climatic zones and land use types.

Contribution of Fractional Cover Analysis for Monitoring Degraded Ecosystems at the Watershed Level

The purpose of the research was to use the data generated on degradation and perform spectral mixture analysis to determine the changes in photosynthetic, non-photosynthetic vegetation and soil fractions, in tactically selected sites, verifying degradation and on the other hand to use this analysis to verify the recovery of degraded ecosystem surfaces that have had recovery projects. Fractional coverages were determined through Normalized Difference Fraction Index (NDFI) by analyzing spectral mixtures using Google Earth Engine. In this sense, the degradation identified in the Ponasa watershed is related to specific degradation values indicated by the NDFI values, to prove that in effect the degradation of these ecosystems is linked to loss of photosynthetic activity, increase in bare soil values and non-photosynthetic activity derived from the process of disturbance of the vegetation cover. In the case of the present study, the NDFI finally explains the degradation processes produced by the loss of vegetation cover and the loss of net primary productivity of the ecosystem, but it is not related in the same way in the case of fragmentation. Ongoing monitoring of the NDFI is key to understanding ecosystem degradation and recovery and to making informed decisions.

Non-negligible cascading impacts of global urban expansion on net primary productivity

Abstract Accelerated global urban expansion not only directly occupies surrounding ecosystems, but also induces cascading losses of natural vegetation elsewhere through cropland displacement. Yet how such effects alter the net primary productivity (NPP) worldwide remains unclear. Here, we quantified the direct and cascading impacts of global urban expansion on terrestrial NPP from 1992 to 2020, and projected the impacts under the shared socioeconomic pathways (SSPs) framework by 2100. We found that global urban expansion caused a cascading loss of 7.2 to 44.6 Tg C/year of terrestrial NPP in the historical period (1992-2020), accounting for 3-20% of the total direct NPP loss. Instead, our projections indicate that during 2020-2100, mainly due to the increased relocation of displaced croplands to low-productive ecosystems, the cascading impacts gradually change from negative to positive, leading to a net NPP increase. Such an increase may offset up to 7% of the total direct NPP loss, better balancing crop compensation with NPP maintenance. Our findings highlight the unexpected large cascading impacts of urban expansion on the carbon cycle and stress the importance of regulating land transitions to curtail land use emissions.

Disentangling the Influential Factors Driving NPP Decrease in Shandong Province: An Analysis from Time Series Evaluation Using MODIS and CASA Model

Net Primary Productivity (NPP) is a critical metric for assessing terrestrial carbon sequestration and ecosystem health. While advancements in NPP modeling have enabled estimation at various scales, hidden anomalies within NPP time series necessitate further investigation to understand the driving forces. This study focuses on Shandong Province, China, generating a high-resolution (250 m) monthly NPP product for 2000–2019 using the Carnegie–Ames–Stanford Approach (CASA) model, integrated with satellite remote sensing and ground observations. We employed the Seasonal Mann–Kendall (SMK) Test and the Breaks For Additive Season and Trend (BFAST) algorithm to differentiate between gradual declines and abrupt losses, respectively. Beyond analyzing land use and land cover (LULC) transitions, we utilized Random Forest models to elucidate the influence of environmental factors on NPP changes. The findings revealed a significant overall increase in annual NPP across the study area, with a moderate average of 503.45 gC/(m2·a) during 2000–2019. Although 69.67% of the total area displayed a substantial monotonic increase, 3.89% of the area experienced abrupt NPP losses, and 8.43% exhibited gradual declines. Our analysis identified LULC transitions, primarily driven by urban expansion, as being responsible for 55% of the abrupt loss areas and 33% of the gradual decline areas. Random Forest models effectively explained the remaining areas, revealing that the magnitude of abrupt losses and the intensity of gradual declines were driven by a complex interplay of factors. These factors varied across vegetation types and change types, with explanatory variables related to vegetation status and climatic factors—particularly precipitation—having the most prominent influence on NPP changes. The study suggests that intensified land use and extreme climatic events have led to NPP diminishment in Shandong Province. Nevertheless, the prominent positive vegetation growth trends observed in some areas highlight the potential for NPP enhancement and carbon sequestration through targeted management strategies.

Effect of ocean outfall discharge volume and dissolved inorganic nitrogen load on urban eutrophication outcomes in the Southern California Bight

Climate change is increasing drought severity worldwide. Ocean discharges of municipal wastewater are a target for potable water recycling. Potable water recycling would reduce wastewater volume; however, the effect on mass nitrogen loading is dependent on treatment. In cases where nitrogen mass loading is not altered or altered minimally, this practice has the potential to influence spatial patterns in coastal eutrophication. We apply a physical-biogeochemical numerical ocean model to understand the influence of nitrogen management and potable wastewater recycling on net primary productivity (NPP), pH, and oxygen. We model several theoretical management scenarios by combining dissolved inorganic nitrogen (DIN) reductions from 50 to 85% and recycling from 0 to 90%, applied to 19 generalized wastewater outfalls in the Southern California Bight. Under no recycling, NPP, acidification, and oxygen loss decline with DIN reductions, which simulated habitat volume expansion for pelagic calcifiers and aerobic taxa. Recycling scenarios under intermediate DIN reduction show patchier areas of pH and oxygen loss with steeper vertical declines relative to a “no recycling” scenario. These patches are diminished under 85% DIN reduction across all recycling levels, suggesting nitrogen management lowers eutrophication risk even with concentrated discharges. These findings represent a novel application of ocean numerical models to investigate the regional effects of idealized outfall management on eutrophication. Additional work is needed to investigate more realistic outfall-specific water recycling and nutrient management scenarios and to contextualize the benefit of these management actions, given accelerating acidification and hypoxia from climate change.

Loss of Net primary production of seasonal winter wheat due to multiple drought types in the main Grain-Producing area of China

Droughts have a severe impact on ecosystems and food security. Net primary production (NPP), a critical component of the carbon cycle of an ecosystem, is strongly associated with crop yield and serves as an indicator of drought impact. In the present study, the loss of NPP in seasonal winter wheat was evaluated through an analysis of the changes in frequency and probability of exceeding NPP loss. This study also analyzed the drought thresholds for various types of drought, namely meteorological drought (MD), natural agricultural drought (NAD), and actual agricultural drought (AAD), in the North China Plain (NCP). The standardized precipitation evapotranspiration index, Palmer Drought Severity Index, and Vegetation Health Index were used to define these drought categories. The study findings reveal that although the NCP has experienced increased dryness, the severity of AAD has decreased. Within the study period, the frequency of winter wheat NPP loss due to drought in the area was within the range of 30% to 40%, with higher sensitivity to drought occurring during the middle growth period of winter wheat and in the NCP’s dry subhumid region. The highest probability of NPP loss was observed in March in the humid and dry subhumid regions of the NCP and in April in the semiarid region. Farmers in the NCP can effectively cope with extreme loss caused by drought. However, they have less experience with handling mild and moderate losses, which were the primary forms of NPP loss during the study period, particularly in the semiarid region. To ensure NPP can be sustained at a normal level or increased, MD and AAD must be prevented during the growing period of winter wheat, and NAD in the semiarid region must be managed to ensure its effects remain mild. Furthermore, farmers’ management of AAD may lead winter wheat to have a higher tolerance to MD and NAD. Our results deepen the understanding of seasonal NPP loss in winter wheat due to different types of drought, providing practical assistance to farmers in the region.

Evaluation of Future Trends Based on the Characteristics of Net Primary Production (NPP) Changes over 21 Years in the Yangtze River Basin in China

As the third largest river basin in the world, the Yangtze River basin in China has vegetation ecosystems in its plain, mountain, and alpine regions. Studying the change characteristics of the vegetation’s net primary productivity (NPP) and its relationship with natural factors and human activities can aid with understanding, to a certain extent, the response of the ecosystem to global climate change. Based on a total of 21 years of MOD17A3 data products from 2000 to 2020, this paper analyzed the spatial variation characteristics and future trends of the NPP in this region by using the coefficient of variation (CV), trend analysis (β), and Hurst index (H) methods. Meanwhile, correlation analysis was used to explore the influence of natural factors and human activities on the NPP. The results show the following: (1) the total amount of the NPP in the Yangtze River Basin was relatively high, and the overall change trend is rising, while the inter-annual fluctuation is evident. The total amount of NPP ranges from 0.786 PgC (2000) to 1.024 PgC (2020), and the annual average was 0.932 PgC. This increase was mainly caused by the increase in the average NPP of forest land, cultivated land, and construction land. (2) The mean value of the NPP in the different regions of the Yangtze River Basin ranged from 0 (construction land) to 1902.89 gC/m2·a. The mean value of the NPP in the Yangtze River Basin was high in the south and low in the north, as well as high in the middle and low in the east and west. The main high-value areas were located in the Hengduan Mountains and the Yunnan-Guizhou Plateau. The coefficient of variation (CV) was 0.0009–0.9980, and the mean CV was only 0.1126. Regarding the future development trend, 77.90% and 22.10% of the regions showed an increase, 22.10% showed a decrease, and 75.25% showed an anti-sustainable state. (3) The effect of human activities on the NPP was generally negative, and the loss of NPP due to land use change in 2020 was around 9.85 TgC when compared with the same in 2000. (4) The rainfall and temperature in the Yangtze River basin both showed a non-significant increase, and the correlation coefficient between the NPP and rainfall was between −0.874 and 0.910. Furthermore, the correlation coefficient of the temperature ranged from −0.928 to 0.929, with a positive correlation overall and a negative correlation locally, and the NPP changes were more susceptible to the influence of temperature than rainfall.

Effects of a changing climate and anthropogenic impacts on net primary production in Yinshanbeilu, Inner Mongolia, China

Inappropriate long-term reclamation has reduced ecological services, including carbon sequestration, in Inner Mongolia's interlocking agricultural and pastoral lands near the northern foot of Yinshanbeilu, making this one of China's most environmentally fragile areas. Regional ecosystem changes and sustainable development depend on the understanding of how climate change and anthropogenic activities affect the net primary production (NPP) of vegetation. (1) Fluctuations in vegetation NPP tended to increase at a ratio of 2.974 g·m−2·a−1. The vegetation NPP increased in 99.49% of the research area; 77.97% of this production was significant. (2) Precipitation and temperature restricted vegetation growth, and the impact of atmospheric precipitation on vegetation NPP exceeded that of both the spatial and temporal dimensions. Precipitation affected grassland NPP more than arable NPP. However, the direct and indirect effects of temperature were greater on arable NPP than on grassland NPP. (3) Changes in climate and anthropogenic activities changed the vegetation NPP by 46.23% and 53.77%, respectively, with the values showing significant spatial variability. Climate change dominated vegetation changes in sparsely populated and underdeveloped areas, whereas human activity was dominant in populated and economically developed areas. (4) Vegetation NPP loss in Yinsanbeilu occurred mostly when the land was changed from grassland to other land use types, whereas growth occurred mostly when the land was changed from arable land to grassland. These results improve the understanding of how climate change and anthropogenic activities affect vegetation dynamics and provide a foundation for vegetation restoration and quality enhancement.

Evaluating Impacts of Opencast Stone Mining on Vegetation Primary Production and Transpiration over Rajmahal Hills

Opencast mining has significantly triggered vegetation degradation in many ecologically sensitive regions across the globe. The detailed spatio-temporal information on mining-induced vegetation degradation and associated primary production loss are crucial inputs to authorities and policymakers to frame and implement sustainable development programs in the mining regions to conserve vegetation ecology. Thus, the present study aimed to decipher the mining-induced vegetation cover and subsequent productivity losses over the Rajmahal Hills in Jharkhand (India). The Gross Primary Productivity (GPP), Net Primary Productivity (NPP), and Vegetation Transpiration (VT) datasets were used for analyzing the mines-induced losses in vegetation cover and associated productivity. The key findings indicated a loss of vegetation cover by ~340 km2 and an expansion of the mining area by ~54 km2 over the Rajmahal Hills during 1990–2020. The change detection analysis at the decadal period revealed that ~3.06 km2, 8.10 km2, and 22.29 km2 of vegetation cover were lost only due to the mining activity during 2000–2010, 2010–2020, and 2000–2020, respectively. The replacement of vegetation cover by mining area has caused GPP loss of 0.01 tonnes carbon (tC) per day, 0.04 tC/day, and 0.09 tC/day; NPP loss of ~1.25 tC, 2.77 tC, and 7.27 tC; VT loss of 5200 mm/day, 13,630 mm/day, and 30,190 mm/day during 2000–2010, 2010–2020, and 2000–2020, respectively. Hence, the present study revealed that the mining-induced vegetation losses have caused an alteration of carbon sequestration, carbon stock, and VT over the Rajmahal Hills.

Correlation of climate change and human activities with agricultural drought and its impact on the net primary production of winter wheat

Drought is a major natural disaster worldwide. Understanding the correlation between meteorological drought (MD) and agricultural drought (AD) is essential for relevant policymaking. In this paper, standardized precipitation evapotranspiration index and standardized soil moisture index were used to estimate the MD and AD in the North China Plain (NCP) to identify the correlation between MD and AD during the growth period of winter wheat. In addition, we investigated the contributions of climate change (CC) and human activity (HA) to AD and the factors influencing the loss of winter wheat net primary production (NPP). Drought propagation time (PT) increased spatially from the southern to northern NCP (from 3 to 11 months). PT first increased and then decreased during the phenological period of winter wheat, and the decreasing trend was delayed with an increasing latitude. In general, the relative contribution of CC to AD was higher than that of HA; the correlation between MD and AD exhibited a weakening trend, particularly during the middle and late phenological stages of winter wheat. Precipitation was the main driver of the effects of HA on AD; the effects were stronger in areas with less precipitation. However, because of the improved irrigation conditions and scarce rainfall during the growth period of winter wheat in the study area, the effects of precipitation on AD were nonsignificant. Instead, temperature, wind, and total solar radiation, which are highly correlated with evapotranspiration, were identified as the primary drivers of AD; spatiotemporal variations were noted in these correlations. Prolonged drought PT reduced NPP; the sensitivity of winter wheat NPP to AD was higher in humid areas than in semiarid or semihumid areas. NPP loss occurred primarily due to HA. Our findings revealed a correlation between MD and AD in agroecosystems and may facilitate policymaking related to drought mitigation and food security.

Subsurface Lateral Flows Buffer Riparian Water Stress Against Snow Drought

AbstractIn the Sierra Nevada, CA, the Mediterranean climate exposes montane forests to water stress during the summer drought. Normally, spring snowmelt alleviates summer water stress, especially in riparian ecosystems that receive subsurface lateral inputs from groundwater. However, snow drought could potentially eliminate these beneficial effects. This research investigates how subsurface lateral redistribution mediates hillslope‐scale vegetation responses to snow drought. We apply a spatially‐distributed ecohydrologic model (Regional Hydro‐Ecologic Simulation System (RHESSys)) to a snow‐dominated watershed in the Sierra Nevada. We incorporate observed sap flow data along a hillslope to estimate relative differences in water stress for upslope and riparian sites, and constrain RHESSys drainage parameter uncertainty. Our model results show that subsurface lateral inputs buffer riparian water stress against snow drought. For all drought types, both upslope and riparian sites experience substantial losses of net primary productivity (NPP), and on average upslope sites are more adversely affected (upslope loss of NPP = 45% vs. riparian = 28%). Dry droughts from a lack of rain or snow induce substantial loss of biomass for upslope and riparian trees because of low annual precipitation, but a small snowpack retained during cold, dry years slightly alleviates these effects and delays water stress by 2 weeks in riparian areas and 3 weeks upslope. While riparian forests are often buffered against drought stress, our study also shows that riparian forests can suffer from water stress. We found 21% of drought scenarios where riparian trees experience greater water stress than upslope trees that were mostly associated with wet and warm snow droughts.

Greener cities cost more green: Examining the impacts of different urban expansion patterns on NPP

Urban expansion patterns whether rather “dispersed” or “compact”, have profound impacts on vegetation net primary productivity (NPP), which substantially alters the ecosystem functioning and its resources. However, there remains limited understanding of which pattern is more conducive towards NPP. Different studies have different and even contradictory views. Hence, to better understand the relationship of NPP and the underlying urban spatial patterns further research is needed. In this study, we compare the impacts of different urban expansion patterns on NPP at varying scales for the time period of 2000–2020. We exemplify this for differing city types in China (Chengdu and Hangzhou) and the USA (Chicago and Raleigh). The results showed cities with dispersed spatial patterns caused higher NPP loss rates (17.93%) than cities with compact spatial patterns (10.40%). The majority of NPP loss (more than 72%) caused by urbanization occurred predominantly in suburban and urban fringe areas. In both, suburban and urban fringe areas, the American cities with low population density and dispersed expansion patterns showed more NPP loss per new urban resident (880.713–8076.308 Mg C 10−4 persons) as well as more NPP loss per square kilometer of built-up land (51.480–881.737 Mg C km−2). The dispersed spatial pattern with high green space ratios significantly alleviated the NPP loss at the local scale but caused more overall NPP loss for the entire city. These findings shed new light on the scale dependence of urbanization-induced impacts on vegetation, and thus, help to better understand the effects of urban expansion patterns on our environment from local to planetary scales.

A Comparative Analysis of Farmland Occupation by Urban Sprawl and Rural Settlement Expansion in China

The farmland loss caused by urban–rural land development has exacerbated China’s challenges of using limited farmland to feed more than 1.4 billion people. Earlier studies shed light on the impacts of urban sprawl and rural settlement expansion, separately. However, there is little quantitative understanding of which one has more severe impacts on farmland and its net primary productivity (NPP). Thus, this study used spatially explicit satellite data including land-use maps and estimated NPP data, as well as spatiotemporal analysis methods to conduct a comparative analysis of farmland loss due to urban sprawl and rural settlement expansion at different scales from 2000 to 2020 in China. The results show that during the study period, urban sprawl resulted in a loss of 49,086.6 km2 of farmland area and 8.34 TgC of farmland NPP, while the loss of farmland area and farmland NPP due to rural settlement expansion reached 18,006.8 km2 and 3.88 TgC. The largest gap between the total area of farmland loss due to urban sprawl and the total loss area due to rural settlement expansion was 12,983.3 km2 in Eastern China, while the smallest gap was 1291.1 km2 in Northeastern China. The largest gap between the loss of farmland NPP due to urban sprawl and the total loss due to rural settlement expansion occurred in Eastern China at 1.97 TgC. Spatially, the total loss of farmland and its NPP due to urban sprawl and rural settlement expansion occurred mainly in the eastern and central regions of China; the areas of farmland loss by urban sprawl were more concentrated than that by rural settlement expansion. The negative impacts of urban sprawl on farmland area and its NPP were greater in southern China than that of rural settlement expansion. Noticeably, the loss of NPP per unit of farmland due to rural settlement expansion was higher than that by urban sprawl, especially in the Yangtze River Delta and Beijing–Tianjin–Hebei region. The results highlight the non-negligible impacts of rural settlement expansion on farmland in China. It is necessary to improve farmland protection policies by optimizing the spatial allocation of urban and rural construction land.

Unravelling net primary productivity dynamics under urbanization and climate change in the western Himalaya

Over the past few decades, climate change and urban expansion have strongly affected vegetation dynamics and overall carbon sink capacity of Himalayan ecosystem. However, the contribution of these two key factors on varying spatio-temporal scales in Himalayan landscapes still lacks in profound analyses. The present study takes Dharamsala and Pithoragarh urban landscapes as examples and uses the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM) as the image fusion technique to generate highly resolved, both spatially (30 m) and temporally (monthly), NDVI images. These are used as inputs for Carnegie-Ames-Stanford Approach (CASA) model for Net Primary Productivity (NPP) estimation over the past two decades (2000–2020). During the study period, the NPP loss due to urbanization was 2065.43 kg C in Dharamsala and 401.07 kg C in Pithoragarh. Climate change, measured in terms of interseasonal changes in temperature, rainfall and solar radiation, had considerably contributed to the NPP variations of vegetated areas in both the study sites, however its contribution ratio was relatively lower than residual factors. There was a significant distribution gradient between how and where urban expansion and climate change influenced the NPP. Urban expansion impacts NPP more in plain areas corresponding to new urban land developments while climate change impacts NPP in high elevation mountainous regions dominated by Oak species. The observed declining trend of NPP under the current threat of urban expansion and climate change in the Himalaya highlights and invites the need of attributing importance to ecological issues. The findings of our study encompassing complex Himalayan landscapes could offer scientific perspectives for the management of ecological environment of highly fragile and vulnerable landscapes of the Himalaya.

Exploring the Individualized Effect of Climatic Drivers on MODIS Net Primary Productivity through an Explainable Machine Learning Framework

Along with the development of remote sensing technology, the spatial–temporal variability of vegetation productivity has been well observed. However, the drivers controlling the variation in vegetation under various climate gradients remain poorly understood. Identifying and quantifying the independent effects of driving factors on a natural process is challenging. In this study, we adopted a potent machine learning (ML) model and an ML interpretation technique with high fidelity to disentangle the effects of climatic variables on the long-term averaged net primary productivity (NPP) across the Amazon rainforests. Specifically, the eXtreme Gradient Boosting (XGBoost) model was employed to model the Moderate-resolution Imaging Spectroradiometer (MODIS) NPP data, and the Shapley addictive explanation (SHAP) method was introduced to account for nonlinear relationships between variables identified by the model. Results showed that the dominant driver of NPP across the Amazon forests varied in different regions, with temperature dominating the most considerable portion of the ecoregion with a high importance score. In addition, light augmentation, increased CO2 concentration, and decreased precipitation positively contributed to Amazonia NPP. The wind speed for most vegetated areas was under the optimum, which benefits NPP, while sustained high wind speed would bring substantial NPP loss. We also found a non-monotonic response of Amazonia NPP to VPD and attributed this relationship to the moisture load in Amazon forests. Our application of the explainable machine learning framework to identify the underlying physical mechanism behind NPP could be a reference for identifying relationships between components in natural processes.

Projected Increases in Global Terrestrial Net Primary Productivity Loss Caused by Drought Under Climate Change

AbstractUnderstanding present and future impacts of drought on the terrestrial carbon budget is of great significance to the evaluation of terrestrial ecosystem disturbance and terrestrial carbon sink. Here, we evaluate the effect of vegetation net primary productivity (NPP) associated with drought through the difference between the mean NPP in the drought and normal years during a specific time period (30 years). Then, the NPP effects in different vegetation types and climatic zones under baseline stage (1981–2010) and future climate scenarios (RCP2.6, RCP4.5, and RCP8.5) is assessed. The results indicate that the negative NPP extremes are captured in most regions, except for the high‐latitude in the Northern Hemisphere. The NPP loss caused by extreme droughts in 2071–2100 is largest under RCPs, followed by the effects of severe and moderate droughts. Regionally, central United States, southern Africa, central Asia, India, Amazon tropical rainforest, and Australia are projected to experience a significant increase in negative NPP extremes and most of these regions are in arid and semi‐arid and tropical rain forest areas. In contrast, tropical Asia suffers little drought effects. For different vegetation, Evergreen Broadleaf Forest, Closed Shrubland, Open Shrubland, Croplands, and Grassland are the most affected by drought. The largest NPP loss occurs in most part of regions under RCP4.5 scenario, not RCP8.5. Climate change is projected to play the largest role in aggravating the risk of drought‐induced NPP reduction. And meanwhile, the adverse effects of drought on vegetation may be resisted through rational fertilizer utilization and land management in future.

Spatiotemporal changes in net primary productivity before and after the development of unused land in the hilly areas of Hebei, China.

Net primary productivity (NPP) plays an important role in the carbon cycle of an ecosystem. To explore the impact of unused land development on NPP, this study adopted an improved Carnegie Ames Stanford Approach (CASA) model to analyze the changes in NPP before and after the development of unused land in Tang County, Hebei Province, in 2000, 2007, and 2018. The results showed that, due to the changes in land use types from unused land, forestland, arable land with high NPP values to urban and rural residential land, traffic land with low NPP values, and the changes in precipitation and temperature, the NPP in the study area showed an overall trend of decreasing first and then rising from 2000 to 2018. Before the development of unused land in 2000, the total NPP was 38.45×1010 g C. After the development in 2007 and 2018, the total NPP was 36.44×1010 g C and 41.05×1010 g C, respectively. The NPP of each land type in 2018 was arable land (1046.18 g C m-2) > forestland (464.42 g C m-2) > unused land (356.34 g C m-2) > grassland (343.77 g C m-2) > waters (182.56 g C m-2) > urban and rural settlements (120.86 g C m-2) > traffic land (120.70 g C m-2). The distribution of NPP was generally high in the north and low in the south before and after development. NPP was mainly concentrated in the interval of 300 g C m-2 yr-1–400 g C m-2 yr-1, and the range of NPP change was mostly within 100 g C m-2. The influence of elevation, temperature and precipitation on the spatial distribution of NPP was significant. Elevation and precipitation were positively correlated with NPP, while temperature was negatively correlated with NPP. The increase in NPP mainly originated from the conversion of unused land to forestland and arable land. The loss of NPP was mainly due to the conversion from forestland with high vegetation productivity to a land use type with low vegetation productivity, such as the conversion from forestland to urban and rural residential land. The results can provide references for making reasonable land planning decisions and ecological environment construction.

Assessing the comprehensive impacts of different urbanization process on vegetation net primary productivity in Wuhan, China, from 1990 to 2020

• A new framework to explore the dynamic impacts of urbanization on NPP. • Indirect impact offset direct impact obviously when UEI reached less than 20%. • Compact urban process had a greater indirect impact than scattered process. • Low-medium UEI and compact urban process is the most ecologically beneficial. Urban expansion has complicated impacts on vegetation coverage and growth, including direct impact caused by the conversion of productive land to non-productive impervious surfaces and indirect impact due to urbanization effects on plant growth. Vegetation improves the urban environment and enhances residents’ quality of life, yet our understanding of impacts on vegetation under rapid urbanization remains limited. We proposed an improved framework to explore the dynamic comprehensive impacts of urbanization on vegetation net primary productivity (NPP) and further analyzed these impact characteristics in different expansion patterns in Wuhan during 1990–2020. The results showed 3378.92 g C m −2 yr −1 , 3453.56 g C m −2 yr −1 and 4090.82 g C m −2 yr −1 of NPP loss caused by direct impact during 1990–2000, 2000–2010 and 2010–2020, respectively, while NPP increased by 811.33 g C m −2 yr −1 , 2435.91 g C m −2 yr −1 and 4640.42 g C m −2 yr −1 due to indirect impact, during the same time periods. The indirect impact offset approximately 24.01%, 70.53% and 113.43% of NPP loss during the three periods. Direct loss and indirect impact strengthened as the urban expansion intensity (UEI) gradient increased, and the compensation of indirect impact to direct impact was more obvious when the UEI reached less than 20%. Compensation increased more steadily in the compact urban pattern. This study provides fundamental support for forecasting the ecological consequences of future urbanization as well as local ecological policy decision-making.

Impacts of landscape change on net primary productivity by integrating remote sensing data and ecosystem model in a rapidly urbanizing region in China

Land use and land cover patterns have been substantially changed under the intense global urbanization process. With the growing concern on the effects of land use/land cover change (LUCC) on the terrestrial carbon cycle, particularly net primary productivity (NPP), understanding the changing trends of LUCC and NPP and their correlation is essential for sustainable landscape planning. Using the integrated geographic information system, remote sensing, Carnegie–Ames–Stanford approach model, and statistical methods, the spatial-temporal variations in landscape and NPP in the Beijing–Tianjin–Hebei (BTH) region from 2005 to 2015 were analyzed. The results showed that the built-up areas increased by 36.7% from 2005 to 2015, 80.5% of which were in lowland areas and 19.5% in relatively high elevation areas. The urban area all showed a tendency to be aggregated and complete in the entire region. The NPP of urban area was the lowest and was 31% lower than the highest value of forest land. Instead of the most urbanized city center, the peripheral area outside the metropolitan city center was facing the most intense NPP loss of 17.13 g C∙m−2∙year−1 in average. In addition to the climatic factors, the LUCC accounted for 70% of the total NPP change in urban area, while approximately 20% in forest and grassland, showing that human constructions undoubtedly affect the land productivity. Through a spatial clustering analysis, the 206 counties in the BTH region could be classified into five categories based on their temporal urbanization degree and their ecological functions. Planning specific development models for different types of areas can give consideration to both urban development and ecological protection in the urbanization process. Our study highlights the necessity of evaluating various impacts of LUCC on NPP in an integrated region of complex ecosystem composition, which contributes to the future localized landscape planning in the global urbanization process.

Decline in net primary productivity caused by severe droughts: evidence from the Pearl River basin in China

AbstractUnderstanding the spatiotemporal characteristics of drought events and their impacts on terrestrial net primary productivity (NPP) is crucial for drought mitigation and environmental protection. This study, by taking the Pearl River basin as the case region, investigated drought duration, severity, intensity, affected area, and centroids during 1960–2015 based on the Standardized Evapotranspiration Deficit Index and three-dimensional clustering algorithm and then revealed how these drought characteristics have affected NPP. Results showed that there were altogether 32 severe drought events lasting at least 3 months in the basin, with half lasting longer than 6 months. The total NPP loss significantly correlated with drought severity and intensity. Most drought events caused a reduction in NPP across more than half of the drought-affected area; specifically, the February–December drought in 2011 has cut NPP by 31.85 Tg C, accounting for 11.7% of the regional annual mean NPP, while the September 2009–September 2010 drought caused a decrease of 20.26 Tg C in NPP. Our research improves the insight into the relationship between NPP and drought, which helps decision-makers manage droughts and provides guidance for drought-related studies across other regions.