Variation In Net Primary Production Research Articles

Quantitative Analysis of Human Activities and Climatic Change in Grassland Ecosystems in the Qinghai–Tibet Plateau

Net primary production (NPP) serves as a critical proxy for monitoring changes in the global capacity for vegetation carbon sequestration. The assessment of the factors (i.e., human activities and climate changes) influencing NPP is of great value for the study of terrestrial systems. To investigate the influence of factors on grassland NPP, the ecologically vulnerable Qinghai–Tibet Plateau region was considered an appropriate study area for the period from 2000 to 2020. We innovated the use of the RICI index to quantitatively represent human activities and analyzed the effects of RICI and climatic factors on grassland NPP using the geographical detector. In addition, the future NPP was predicted through the integration of two modeling approaches: The Patch-Generating Land Use Simulation (PLUS) model and the Carnegie–Ames–Stanford Approach (CASA) model. The assessment revealed that the expanded grassland contributed 7.55 × 104 Gg C (Gg = 109 g) to the total NPP, whereas the deterioration of grassland resulted in a decline of 1.06 × 105 Gg C. The climatic factor was identified as the dominant factor in grassland restoration, representing 70.85% of the total NPP, as well as the dominant factor in grassland degradation, representing 92.54% of the total NPP. By subdividing the climate change and human activity factors into sub-factors and detecting them with a geographical detector, the results show that climate change and anthropogenic factors have significant ability to explain geographic variation in NPP to a considerable extent, and the effect on NPP is greater when the factors interact. The q-values of the Relative Impact Contribution Index (RICI) and the RICI of the land use change NPP are consistently greater than 0.6, with the RICI of the human management practices NPP and the evapotranspiration remaining at approximately 0.5. The analysis of the interaction between climate and human activity factors reveals an average impact of greater than 0.8. By 2030, the NPP of the natural development scenario, economic development scenario (ED), and ecological protection scenario (EP) show a decreasing trend due to climate change, the dominant factor, causing them to decrease. Human activities play a role in the improvement. The EP indicates a positive expansion in the growth rate of forests, water, and wetlands, while the ED reveals rapid urbanization. It is notable that this is accompanied by a temporary suspension of urban greening.

Characteristics of Climate Change in Poyang Lake Basin and Its Impact on Net Primary Productivity

Climate change exerts substantial impacts on human society and the carbon cycle of terrestrial ecosystems. Studying the spatiotemporal characteristics of regional climate change and its impact on carbon sequestration is an important topic in ecology and environmental science. This study utilized meteorological and land use/cover data to explore these dynamics. Statistical methods such as the Mann–Kendall (M-K) test and wavelet analysis were used to simulate the changes in annual average temperature and precipitation in the Poyang Lake Basin from 1980 to 2020. The Carnegie–Ames–Stanford Approach (CASA) model was used to estimate the interannual variation in net primary productivity (NPP) in the region over the past 40 years. Additionally, the present study examined the influence of various factors on NPP changes. The main results are as follows: (1) Over the past four decades, the average temperature in the Poyang Lake Basin was 17.85 °C, while the average precipitation was 1621.35 mm. The average annual temperature rises at a rate of 0.27 °C per decade. (2) A significant shift in the average annual temperature occurred in the early 21st century, and annual precipitation exhibited multiple abrupt changes during the mid-to-late 1990s. Both temperature and precipitation changes follow a 25-year cycle, with temperature hotspots located in the south and precipitation hotspots in the northeast. (3) The impact of climate change on the change in NPP in the Poyang Lake Basin is about 70%, with the annual average temperature having a significant effect on the increase in NPP. This study can provide a scientific foundation for formulating policies aimed at mitigating climate-related disasters and enhancing carbon cycling in terrestrial ecosystems.

Atmospheric Nitrogen Deposition Controls Interannual Variability of Net Primary Production in the Bohai Sea

AbstractIncreasing human activities and climate change have resulted in significant changes in net primary production (NPP) of the marginal sea in the past several decades. The Bohai Sea (BHS) is a shallow semi‐enclosed marginal sea of North China, the knowledge of the relative impacts of human activities and climate change on the NPP in the BHS remains limited. This study primarily aimed to elucidate the interannual variability of NPP and its influencing factors in the BHS during the 2002–2021 period by synthesizing four widely‐used global NPP models, namely the vertically generalized production model (VGPM), the Eppley‐VGPM, the size‐fractioned phytoplankton pigment absorption‐based model (SABPM), and the carbon, absorption, and fluorescence euphotic‐resolving model (CAFE). The multi‐model average NPP showed significant interannual variation, with an increasing trend from 2002 to 2012 and a decreasing trend from 2012 to 2021. The concentration of DIN in the BHS was primarily affected by atmospheric nitrogen deposition. The structural equation model demonstrated that chlorophyll‐a (Chl‐a) concentration, influenced by DIN concentration, had an important effect on NPP. In brief, atmospheric nitrogen deposition impacted the DIN concentration and thus controlled the (Chl‐a) concentration and NPP change in the BHS. Furthermore, atmospheric nitrogen deposition in the BHS have potential ecological impacts on the red tide features. These findings hold valuable implications for future marine resource planning and marine ecological management in the BHS.

Analysis of spatial and temporal variations of vegetation NPP and TWS in the Yangtze River Basin

Net primary productivity (NPP) is an important parameter reflecting vegetation growth, and water is one of the necessary factors for vegetation growth. Investigating the mutual influence between NPP and water is significant for ensuring the stable development of the ecological environment. This study focuses on the Yangtze River Basin (YRB) as the research area, and based on medium-resolution imaging spectrometer (MODIS) data, climate data, and gravity recovery and climate experiment (GRACE) data, the spatiotemporal evolution characteristics of vegetation NPP and terrestrial water storage (TWS) in the YRB from 2000 to 2022 are explored and analyzes the mutual influence of NPP with climate factors and TWS. The results show that vegetation NPP (4.10 gC·m−2·a−1) and TWS (0.55 mm) in the YRB have exhibited an increasing trend from 2000 to 2022, with a strong correlation between the two, which is related to recent environmental policies. Analysis of the impact of climate factors on NPP reveals that temperature and TWS significantly positively impact NPP changes. Furthermore, comparisons between NPP and TWS indicate that changes in TWS substantially promote plant growth. In addition, the comparison between NPP and TWS indicates that changes in TWS have an important promoting effect on plant growth. Surface water (SWS) and soil water (SM) have a significant promoting effect on plant growth, but with a strong lag, while the consumption of groundwater (GWS) has been promoting plant growth without significant lag.

Spatiotemporal dynamics of vegetation net primary productivity and its response to climate variability

Despite its significance, net primary productivity is rarely used as an indicator of climate change. The purpose of this study was to assess the spatiotemporal dynamics of vegetation net primary productivity and its response to climate variability in the Welmel watershed, southeastern Ethiopia. The investigation utilized data from the Moderate Resolution Imaging Spectroradiometer, and the Climate Hazards Group Infrared Precipitation with Stations accessed through the Google Earth Engine cloud computing platform. To evaluate the trend and response of net primary productivity to climatic factors, the Mann-Kendall and Theil Sen’s tests, the Pearson correlation coefficient, and stability analysis through the coefficient of variation of net primary productivity were utilized. The analysis of the temporal trend of net primary productivity revealed that the entire watershed, forest, wood, and cultivated land areas exhibited decreasing trends with net primary productivity values of -0.681, -4.361, -1.41, and − 3.25 g C m− 2/year, respectively. On the other hand, shrubs and grazing land displayed increasing trends of 1.15 and 2.04 g C m− 2/year, respectively. The wood and shrubland trends were statistically significant (p < 0.05). In the spatial analysis, an area of 64.6% showed a decreasing trend, whereas 33.78% displayed an increasing trend in net primary productivity values. The areas with stable and unstable variations in net primary productivity accounted for 26.47% and 8.02%, respectively. The net primary productivity of the land cover types and entire watershed were positively correlated with rainfall, however, only forests and woodlands were statistically significantly correlated (p < 0.05). The net primary productivity and land surface temperature were negatively correlated, except for forests and cultivated land, which were positively correlated. The results of this study provide essential information for managing ecosystems, supporting agricultural practices, and enhancing community resilience in a changing climate.

Climate Change Drove the Decline in Yangtze Estuary Net Primary Production Over the Past Two Decades.

Net primary productivity (NPP) is highly sensitive to multiple stressors under progressive and intensifying climate change and anthropogenic impacts. The importance of understanding spatiotemporal distribution patterns and the associated driving factors that govern estuary NPP is paramount for regional carbon (C) budget assessments. Using a combined remote sensing and machine learning (ML) approach, the average NPP of the Yangtze Estuarine-offshore continuum (YEOC) was measured at 273.19 ± 21.26 mgC m-2 day-1 over the past two decades. Temporally, NPP exhibited a significant downward trend between 2002 and 2022. Climate factors (climate fluctuations, sea level rise, and discharge) drove phytoplankton biomass (Chl-a) while light conditions (PAR and Kd490) affected photosynthesis rates. Together, they can explain 65% of the NPP variation. Anthropogenic disturbances (i.e., damming and nutrient emissions) were not significant. Additionally, changes in NPP decreased phytoplankton C sequestration rates from 11.9 to 10.4 Tg C year-1, reducing the estuary's C sink capacity, which relies on biological C fixation. This study highlights the climate's influence on the spatiotemporal transformation of YEOC NPP while enhancing our understanding of the response of EOC C budgets to climate change and anthropogenic activities.

Detecting Drought-Related Temporal Effects on Global Net Primary Productivity

Drought has extensive, far-reaching, and long-lasting asymmetric effects on vegetation growth worldwide in the context of global warming. However, to date, few scholars have attempted the systematic quantification of the temporal effects of drought on global vegetation across various vegetation types and diverse climate zones. Addressing this gap, we quantitatively investigated the effects of drought on global vegetation growth under various scenarios, considering lagged and cumulative effects as well as combined effects in the 1982–2018 period. Our investigation was based on long-term net primary productivity (NPP) and two multiple-timescale drought indices: the standardised precipitation index (SPI) and the standardised precipitation and evapotranspiration index (SPEI). Our main findings were the following: (1) SPI and SPEI exhibited lagged effects on 52.08% and 37.05% of global vegetation, leading to average time lags of 2.48 months and 1.76 months, respectively. The cumulative effects of SPI and SPEI were observed in 80.01% and 72.16% of global vegetated areas, respectively, being associated with relatively longer cumulative timescales of 5.60 months and 5.16 months, respectively. (2) Compared to the scenario excluding temporal effects, there were increases in the explanatory powers of SPI and SPEI for variations in vegetation NPP based on the lagged, cumulative, and combined effects of drought: SPI increased by 0.82%, 6.65%, and 6.92%, respectively, whereas SPEI increased by 0.67%, 5.73%, and 6.07%, respectively. The cumulative effects of drought on global vegetation NPP were stronger than the lagged effects in approximately two-thirds (64.95% and 63.52% for SPI and SPEI, respectively) of global vegetated areas. (3) The effects of drought on vegetation NPP varied according to climate zones and vegetation types. Interestingly, vegetation in arid zones was the most sensitive and resilient to drought, as indicated by its rapid response to drought and the longest cumulative timescales. The vegetation NPP in tropical and temperate zones exhibited a relatively stronger response to drought than that in cold and polar zones. The strongest correlation of vegetation NPP with drought occurred in shrubland areas, followed by grassland, cropland, forest, and tundra areas. Moreover, for each vegetation type, the correlations between vegetation NPP and drought differed significantly among most climate zones. (4) The vegetation NPP in warming-induced drought regions displayed a higher correlation to drought than that in non-warming-induced drought regions, with shorter lagged and longer cumulative timescales. Our findings highlight the heterogeneity of the lagged, cumulative, and combined effects of drought across various climate zones and vegetation types; this could enhance our understanding of the coupling relationship between drought and global vegetation.

Monitoring the Net Primary Productivity of Togo’s Ecosystems in Relation to Changes in Precipitation and Temperature

Climate variability significantly impacts plant growth, making it crucial to monitor ecosystem performance for optimal carbon sequestration, especially in the context of rising atmospheric CO2 levels. Net Primary Productivity (NPP), which measures the net carbon flux between the atmosphere and plants, serves as a key indicator. This study uses the CASA (Carnegie–Ames–Stanford Approach) model, a radiation use efficiency method, to assess the spatio-temporal dynamics of NPP in Togo from 1987 to 2022 and its climatic drivers. The average annual NPP over 36 years is 4565.31 Kg C ha−1, with notable extremes in 2017 (6312.26 Kg C ha−1) and 1996 (3394.29 Kg C ha−1). Productivity in natural formations increased between 2000 and 2022. While climate change and land use negatively affect Total Production (PT) from 2000 to 2022, they individually enhance NPP variation (58.28% and 188.63%, respectively). NPP shows a strong positive correlation with light use efficiency (r2 = 0.75) and a moderate one with actual evapotranspiration (r2 = 0.43). Precipitation and potential evapotranspiration have weaker correlations (r2 = 0.20; 0.10), and temperature shows almost none (r2 = 0.05). These findings contribute to understanding ecosystem performance, supporting Togo’s climate commitments.

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.

Land cover dynamics and net primary productivity in Hubei Province, China: an integrative analysis of ecological and landscape transitions

ABSTRACT To better protect the ecological environment, this study investigates the evolution of the landscape in Hubei Province and its impact on Net Primary Production (NPP). By utilizing landscape assessment tools and neighborhood proxy methods, it quantifies the changes in NPP resulting from landscape transformations over periods of 5 and 20 years. The results indicate significant NPP variations, with changes ranging from −406.199 to 507.181 g*C/m2. The geographical detector model identifies key drivers, particularly noting significant changes in landscape features at type boundaries, which affect NPP. Land cover, especially transitions between forests, shrublands, and croplands, is identified as a critical factor. This research highlights the complex relationship between landscape modifications and NPP variations, emphasizing the importance of ecological considerations in landscape management amid urbanization. It offers valuable insights for future landscape management and conservation strategies in Hubei, aiming for ecological preservation alongside development. Additionally, this work fills a theoretical gap by linking changes in landscape features to NPP, proposing new perspectives for landscape protection and ecological capacity enhancement, and providing practical guidance for improving NPP and coordinated landscape management in Hubei.

Spatio-Temporal Changes and Driving Mechanisms of Vegetation Net Primary Productivity in Xinjiang, China from 2001 to 2022

Net primary productivity (NPP), a key indicator of terrestrial ecosystem quality and function, represents the amount of organic matter produced by vegetation per unit area and time. This study utilizes the MOD17A3 NPP dataset (2001–2022) to analyze the spatio-temporal dynamics of NPP in Xinjiang and projects future trends using Theil-Sen trend analysis, the Mann–-Kendall test, and the Hurst Index. By integrating meteorological data, this study employs partial correlation analysis, the Miami model, and residual analysis to explore the driving mechanisms behind NPP changes influenced by climatic factors and human activities. The results indicate that: (1) The average NPP in Xinjiang has increased over the years, displaying a spatial pattern with higher values in the north and west. Regions with increasing NPP outnumber those with declining trends, while 75.18% of the area shows un-certain future trends. (2) Precipitation exhibits a stronger positive correlation with NPP compared to temperature. (3) Climate change accounts for 28.34% of the variation in NPP, while human activities account for 71.66%, making the latter the dominant driving factor. This study aids in monitoring ecological degradation risks in arid regions of China and provides a scientific basis for developing rational coping strategies and ecological restoration initiatives.

Spatiotemporal Variation Characteristics and Driving Factors of Vegetation NPP in the Ulansuhai Nur Basin from 2001 to 2020

Vegetation net primary productivity （NPP） represents the ability of plants to fix ecosystem carbon, which is a key indicator to determine the health status and sustainable development of ecosystems. Its spatial and temporal changes and driving factors play an important role in revealing the status of vegetation restoration and guiding ecological restoration. Based on MODIS17A3 NPP data, land use, and meteorological data from 2001 to 2020, the temporal and spatial variation characteristics and driving factors of vegetation NPP in the Ulansuhai Nur Basin of Inner Mongolia were explored by using the methods of coefficient of variation, Theil-Sen Median trend analysis, Mann-Kendall significance test, Hurst index, and Geodetector. The results showed that： ① From 2001 to 2020, the vegetation NPP in the Ulansuhai Nur Basin showed a fluctuating upward trend, with an average value （in terms of C） of 141.03 g·（m2·a）-1 and an average increase rate of 2.33 g·（m2·a）-1. The vegetation NPP had obvious spatial differentiation, which was characterized by high in the southwest and low in the northeast and high in Hetao Plain and low in sandy land and mountainous areas. ② NPP mainly showed an increasing trend, and the area proportions of increasing, decreasing, and unchanged areas were approximately 80%, 3%, and 17%, respectively. The average coefficient of variation of vegetation NPP was 0.149, which mainly showed low fluctuation change, and the area accounted for approximately 51%. The future change trend of NPP was mainly characterized by anti-persistence, with an area ratio of approximately 75%. ③ Land use, altitude, maximum temperature, and slope were the dominant driving factors of variation NPP change in the Ulansuhai Nur Basin, and the q values were all above 0.200. The interaction between altitude and relative humidity had the greatest explanatory power for the spatial differentiation of vegetation NPP in the Ulansuhai Nur Basin. There were significant differences in the explanatory power of land use and all factors except nighttime light to the spatial differentiation of vegetation NPP in the Ulansuhai Nur Basin. According to the research results, in the future, we should strengthen the ecosystem management of the Ulansuhai Nur Basin； continue to implement strict ecological protection and restoration policies； and comprehensively consider factors such as climate, topography, and human activities to carry out comprehensive ecological management according to local conditions to improve the quality of ecosystem services.

Spatiotemporal Variation Characteristics and Driving Factors of Cultivated Land NPP in the Shandong Area Around the Bohai Sea

The Bohai Rim Plain is an important grain-producing area in China. The cultivated land resources have great potential for production, but there are many influencing factors. Understanding the spatiotemporal change characteristics and driving factors of the net primary productivity （NPP） of cultivated land vegetation in this region is of great significance to improve the regional cultivated land production conditions, excavate and enhance the production capacity of cultivated land, and ensure national food security. In this study, Theil-Sen Median trend analysis, Mann-Kendall significance test, Hurst index, and other methods were used to explore the spatiotemporal change characteristics, stability, and sustainability of regional cultivated land NPP. The influence of driving factors on the spatial heterogeneity of cultivated land NPP was analyzed by using optical parameters-based geographical detectors. The results showed that： ① From 2001 to 2019, due to the expansion of construction land during industrialization and urbanization, the cumulative decrease in the area of cultivated land in the Shandong area around the Bohai Sea was 2 004.51 km2. ② During the selected research period, the interannual variation of average cultivated land NPP showed a fluctuating and increasing trend. In terms of spatial distribution, the NPP of cultivated land was bounded by the Dongying District, with the spatial heterogeneity in the north being significantly lower than that in the south. ③ The area with increasing NPP of cultivated land accounted for 88.06% of the total area of cultivated land, mainly with low and medium fluctuations. The NPP of cultivated land will maintain an overall sustained trend of increase across the region in the future. ④ The average annual relative humidity study area had the strongest explanatory power for the spatial variability of NPP in cropland, with a q-value of 0.26, followed by surface soil salinity and subsoil salinity, with q-values greater than 0.2. The interactions between the different drivers all showed either nonlinear enhancement or bifactorial enhancement. The results of this study will help to reveal the characteristics of the changes in cultivated land production capacity and its driving forces in the Bohai Sea region and also provide a theoretical basis for the ecological protection and sustainable development of the region.

Analysis of Spatiotemporal Evolution Characteristics and Influencing Factors of Vegetation Net Primary Productivity in Shendong Mining Area

Coal plays a key role in the composition of energy production and consumption in China. The mineral is a crucial resource for human economic and social development. The surface subsidence caused by coal mining has attracted disturbance and damage to the surface ecological environments of mining areas. To quantitatively study vegetation carbon sequestration in coal mining areas, this article takes the Shendong mining area as its research object and analyzes the spatiotemporal distribution characteristics and influencing factors of vegetation net primary productivity (NPP). Based on meteorological data, remote sensing images, and land use data in the mining area, this research analyzed the vegetation NPP and its relationship with meteorological factors in the Shendong mining area from 2000 to 2023. The results show that (1) in the past 24 years, the range of NPP variation in the Shendong mining area has been 0–350 gC/m2. The overall NPP shows a fluctuating upward trend. The annual average change in NPP in the mining area is bounded by the two central dividing lines, with a lower value in the central part and a gradually increasing trend in the western and eastern parts. (2) The average vegetation NPP of the Shendong mining area over 24 years was 0–250 gC/m2; after 2011, the annual average NPP of vegetation was higher than this average level, which shows that the ecological environment of the mining area is gradually improving. Coal mining in the mining area has not caused a significant impact on the overall environment of the mining area. (3) There is a significant relationship between NPP and annual cumulative rainfall, average annual temperature, and average annual Normalized Difference Vegetation Index (NDVI). Overall, it is not significantly related to mining factors. The mining factors affect local areas and have a certain correlation.

Variation of ecosystem resilience across the anthropogenic biomes of India: A comprehensive analysis

Quantifying ecosystem resilience under drought is crucial for sustainable development strategies. This study aims to investigate the spatial and temporal variability of Net Primary Productivity (NPP) across anthropogenic biomes in India (2000 to 2020) and to understand the post-drought long-term ecosystem resilience. A time series study of monthly precipitation, standardized precipitation index (SPI), and NPP were applied to understand ecosystem resilience across twenty anthropogenic biomes. Mann-Kendall test was used to quantify the magnitude and direction of the trend. In addition, bivariate raster maps of mean precipitation and soil moisture were presented in relation to ecosystem resilience in India. The forested areas in the Himalayan region and the Western Ghats of India were identified with resilient ecosystem that can withstand climate change. However, the croplands and rangelands were non-resilient to drought, making them vulnerable to climate change. Northern and western part of India falls under catastrophic to critical non-resilient ecosystem. Soil moisture availability in the biome, forest cover, type of land use, agricultural practices, and climate shocks are mainly influencing the resilience of the anthropogenic biomes in India. The resilience assessment can be used by policymakers to plan anthropogenic interventions in harmony with nature.

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.

Net primary productivity response to precipitation varied with different ecosystems in the Tibetan Plateau over the past two millennia

The long-term pattern of terrestrial net primary productivity (NPP) response to climate change is important for estimating aboveground biomass and assessing its ecosystem function. NPP accumulation generally increased during warming intervals. However, the relationship between terrestrial NPP and precipitation change has not been comprehensively elucidated owing to the lack of long-term quantitative NPP records. Here, we present an NPP sequence quantitatively reconstructed from annual layers of fossil pollen assemblages spanning the past two millennia. We also explore the relationship between NPP and precipitation during the periods dominated by different ecosystem types. The results revealed that the NPP variation is positively correlated with the alpine meadow, dominated by Cyperaceae species, and negatively correlated with the alpine steppe, dominated by Artemisia and Poaceae species. Additionally, the NPP sequence recorded a remarkable ∼200-year periodic oscillation, which was also recorded in the precipitation sequence. The periodic NPP showed an in-phase relationship with precipitation when the regional ecosystem was marked by the symbiosis of alpine steppe and alpine meadow, and showed an anti-phase relationship with precipitation when the regional ecosystem was dominated by alpine steppe. This study elucidates the relationships between terrestrial NPP and precipitation during the past two millennia and provides foundations for predicting future terrestrial productivity.

Prediction of net primary productivity in the middle-to-high latitudes of Eurasia based on snow and soil temperature

Net primary productivity (NPP) is the net accumulation of organic matter by vegetation through photosynthesis and serves as a key indicator for exploring vegetation responses to climate change. Considering the remote and local impacts of soil heat capacities on vegetation growth through pathways of atmospheric circulation and land–atmosphere interaction, this paper develops a statistical prediction model for NPP from April to June (AMJ) across the middle-to-high latitudes of Eurasia. The model introduces two physically meaningful predictors: the snow water equivalent (SWE) from February to March (FM) over central Europe and the FM local soil temperature (ST). The positive phase of FM SWE triggers anomalous eastward-propagating Rossby waves, leading to an anomalous low-pressure system and cooling in the middle-to-high latitudes of Eurasia. This effect persists into spring through snow feedback to the atmosphere and affects subsequent NPP changes. The ST is closely related to the AMJ temperature and precipitation. With positive ST anomalies, the AMJ temperature and precipitation exhibit an east–west dipole anomaly distribution in this region. The single-factor prediction scheme using ST as the predictor is much better than using SWE as the predictor. Independent validation results from 2009 to 2014 demonstrate that the ST scheme alone has good predictive performance for the spatial distribution and interannual variability of NPP. The predictive skills of the multi-factor prediction schemes can be improved by about 13 % if the ST predictor is included. The findings confirm that local ST is a predictor that must be included for NPP prediction.摘要净初级生产力 (NPP) 是植被通过光合作用积累机物质的净效益, 是探索植被对气候变化响应的关键指标. 考虑到陆面热力异常通过陆气相互作用和大尺度环流对植被生长的影响, 本文研制了欧亚中高纬地区4–6月NPP预测模型. 该模型引入了两个具有明确物理意义的预测因子: 欧洲中部2–3月的雪水当量 (SWE) 和2–3月局地土壤温度 (ST). SWE的正异常会触发异常东传的Rossby波, 导致下游出现位势高度负异常并引起降温. 通过雪和温度的正反馈, 这种异常低温持续到春季并使得NPP下降. ST与随后季节的温度和降水密切相关, 当ST出现正异常时, 该地区的4–6月温度和降水呈现出东西向偶极子异常分布.对比各方案的预测效果发现, ST比SWE有更好的预测能力. 2009–2014年独立后报结果显示, ST方案对NPP的空间分布和年际变率都有很好的预测效果. 交叉检验的结果显示, 多因子方案中引入ST后能提高模型13 %的预测技巧.

Spatio-Temporal Changes of Vegetation Net Primary Productivity and Its Driving Factors on the Tibetan Plateau from 1979 to 2018

The Net Primary Productivity (NPP) of the Tibetan Plateau (TP) has undergone significant changes since the 1980s. The investigation of the spatiotemporal changes of NPP and its driving factors is of significant importance. Here, we analyze the spatial and temporal trends of Net Primary Production (NPP) and the effects of meteorological factors on the NPP change on the Tibetan Plateau (TP) using version 5.0 of the Community Land Model. The results showed that the average NPP was 256 (g C·m2·yr−1) over the past 40 years, with a continuously increasing trend of 2.38 (g C·m2·yr−1). Precipitation was the main factor affecting NPP changes, temperature had no significant effect on NPP changes, while radiation showed a negative trend. Changes in precipitation, temperature and radiation account for approximately 91%, 5.3%, and 3.8% of NPP variation, respectively. Based on grass coverage, we categorized alpine grasslands into three types: high, medium, and low coverage. Our findings indicate the NPP change of the high-coverage grasslands was mainly affected by precipitation, and then the temperature and radiation. Comparatively, the precipitation change is the driving factor of the increased NPP of low-coverage grasslands, but the temperature increase is the negative factor. Our studies have implications for assessing and predicting vegetation responses to future climate change.

Spatiotemporal variation and prediction of NPP in Beijing-Tianjin-Hebei region by coupling PLUS and CASA models

Vegetation productivity is crucial for human production and livelihoods. Understanding net primary productivity (NPP) in historical contexts and predicting its future fluctuations is imperative for assessing the environmental sustainability of a region. However, relatively few researches have been conducted on predicting NPP, requiring further development and refinement of NPP prediction methods and models. This study introduces a novel approach that discretely couples the PLUS and CASA models for NPP prediction, and it validates the applicability of this approach in the research area. The objective of our study is to analyze the spatiotemporal patterns of NPP change in the Beijing-Tianjin-Hebei (BTH) region from 2001 to 2020, predict NPP under three different climate scenarios (SSP 1-2.6, SSP 2-4.5, SSP 5-8.5) in 2030, and identify an appropriate path for the future development of this region. The results indicate:(1) From 2001 to 2020, NPP in the research area has shown a gradual improvement trend and maintained a certain spatial distribution pattern in general. (2) The study discovered a correlation coefficient of 0.83 and an RMSE of 102.86 between predicted and actual NPP for 2020. This suggests that the method introduced in our study is suitable for predicting NPP in the research area. (3) NPP in the study area is predicted to decline in 2030 compared with 2020 under all three scenarios. Moreover, the SSP 1-2.6 scenario, representing a low-emission scenario, is suitable for the BTH region compared with other climate scenarios. This research sheds light on NPP variations in the BTH region over the past 20 years and the next 10 years, offering a scientific basis for relevant departments to formulate future policies.