Patterns Of Net Primary Productivity Research Articles

Evaluating net primary productivity dynamics and their response to land-use change in the loess plateau after the 'Grain for Green' program

Assessing net primary productivity (NPP) dynamics and the contribution of land-use change (LUC) to NPP can help guide scientific policy to better restore and control the ecological environment. Since 1999, the “Green for Grain” Program (GGP) has strongly affected the spatial and temporal pattern of NPP on the Loess Plateau (LP); however, the multifaceted impact of phased vegetation engineering measures on NPP dynamics remains unclear. In this study, the Carnegie-Ames-Stanford Approach (CASA) model was used to simulate NPP dynamics and quantify the relative contributions of LUC and climate change (CC) to NPP under two different scenarios. The results showed that the average NPP on the LP increased from 240.7 gC·m−2 to 422.5 gC·m−2 from 2001 to 2020, with 67.43% of the areas showing a significant increasing trend. LUC was the main contributor to NPP increases during the study period, and precipitation was the most important climatic factor affecting NPP dynamics. The cumulative amount of NPP change caused by LUC (ΔNPPLUC) showed a fluctuating growth trend (from 46.23 gC·m−2 to 127.25 gC·m−2), with a higher growth rate in period ΙΙ (2010–2020) than in period Ι (2001–2010), which may be related to the accumulation of vegetation biomass and the delayed effect of the GGP on NPP. The contribution rate of LUC to increased NPP in periods Ι and ΙΙ was 101.2% and 51.2%, respectively. Regarding the transformation mode, the transformation of grassland to forest had the greatest influence on ΔNPPLUC. Regarding land-use type, the increased efficiency of NPP was improved in cropland, grassland, and forest. This study provides a scientific basis for the scientific management and development of vegetation engineering measures and regional sustainable development.

Ecosystem services to support sustainable development: The modifiable areal unit problem in the transition between evaluation and management units

AbstractUnderstanding the role of ecosystem services (ES) and their interactions at different spatial scales in territorial space governance is crucial for sustainable development. However, a unified analysis of scale and zoning effects on ES supporting sustainable development remains a theoretical and practical gap. Therefore, this study utilized the traditional concept of the modifiable areal unit problem (MAUP) to establish the ES‐MAUP framework. Additionally, the highly urbanized region of Southern Jiangsu, China, was selected as a case study area to quantitatively evaluate four typical regulating ecosystem services in 2020: urban cooling (UC), flood mitigation (FM), soil conservation (SC), and net primary productivity (NPP). The spatial characteristic information of these four ES was effectively preserved with increasing spatial scale. Significant differences existed in the hotspot patterns of NPP, UC, and SC among different zoning units. Across the three zoning units, the correlations between NPP‐UC, NPP‐SC, and UC‐SC exhibited consistent positive trends, while notable differences in correlations between other ES pairs, such as NPP‐FM and UC‐FM.

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.

Spatio-Temporal Variation and Future Sustainability of Net Primary Productivity from 2001 to 2021 in Hetao Irrigation District, Inner Mongolia

The Hetao Irrigation District in Inner Mongolia, a vital grain-producing region in northern China, faces growing environmental challenges. Studying net primary productivity (NPP) is essential for understanding spatiotemporal vegetation shifts and guiding locally adapted restoration and management efforts. Utilizing MOD17A3/NPP data, this study applies the Theil–Sen median trend, Mann–Kendall significance, and the Hurst index to scrutinize the spatiotemporal distribution patterns of NPP from 2001 to 2021 and forecast future changes in the area. The findings reveal cyclic temporal trends, forming a “∧” shape with initial increases followed by decreases, notably during the July to August period each year. The multi-year average NPP exhibits a slight upward fluctuation trend, averaging 172.40 gCm−2a−1. Peaks occur approximately every three years, reaching the highest average in 2012 at 218.96 gCm−2a−1. Spatially, NPP distribution stays consistent over the years, influenced by various land cover types, especially cropland, shaping the spatial patterns. Monthly and yearly NPP trends over the 21 years indicate a significant decrease in May and June, with other months mostly showing a non-significant increase. The Hurst index for monthly and yearly NPP changes over 21 years shows relatively high weak anti-persistence. In summary, over the past 21 years, the NPP trend in the study area has not significantly improved and is expected to decline in the future. This study offers data support and a scientific foundation for refining the carbon cycle model, quantifying vegetation carbon sequestration capacity, addressing climate change policies, and striving for carbon peak and neutrality in the Hetao Irrigation District.

Spatiotemporal pattern of NPP and its response to climatic factors in the Yangtze River Economic Belt

Net primary productivity (NPP) of terrestrial ecosystems serves as a crucial carbon sink, playing a significant role in mitigating climate change. This study, focusing on the Yangtze River Economic Belt (YREB), a key area for both economic development and ecological conservation in China, evaluates the temporal and spatial changes in regional NPP and its responses to climatic factors against the backdrop of global change. Utilizing long-term NPP and meteorological grid data from 1981 to 2017, we analyzed the annual change patterns of NPP and its linear and nonlinear responses to climatic factors using copula functions. Our findings indicate that 57.00 % of the YREB has experienced a significant increase in NPP, with the most substantial decreases observed in Shanghai and its surrounding areas (P < 0.05). Temperature emerged as the primary climatic driver, positively correlating with NPP changes in over half of the study area (P < 0.05). Moreover, the nonlinear response of NPP to temperature and precipitation underscores the complex interactions between these factors, revealing a sensitivity to temperature variations that surpasses that to precipitation. The study also highlights the influence of solar radiation and topographic factors, with a significant positive correlation between NPP and solar radiation observed in 15.85 % of the area (P < 0.05). The practical significance of these findings lies in their implications for regional ecological management and climate resilience strategies. The positive correlation between temperature and NPP underscores the potential for targeted temperature management to optimize carbon sequestration across the YREB. Furthermore, the identified nonlinear responses and the role of solar radiation and topography in influencing NPP offer valuable insights for the formulation of adaptive strategies that enhance ecosystem productivity and contribute to achieving carbon neutrality goals. By elucidating the dynamics of NPP in response to a range of environmental factors, this study provides a foundation for informed decision-making in ecological conservation and climate change mitigation efforts within the YREB and similar regions globally.

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

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

Spatiotemporal patterns of net primary productivity of subtropical forests in China and its response to drought

Net primary productivity (NPP) is an important indicator used to evaluate the carbon sequestration capacity of forest ecosystems. Subtropical forest ecosystems play an indispensable role in maintaining the global carbon balance, while frequently occurring drought events in recent years have seriously damaged their productivity. However, the spatiotemporal patterns of NPP, as well as its response to drought, remain uncertain. In this study, the multiscale drought characteristics in subtropical China during 1981–2015 were analyzed based on the standardized precipitation evapotranspiration index. Then, simulated and analyzed the spatiotemporal NPP of subtropical forests by the boreal ecosystem productivity simulator model. Finally, the response of NPP to drought was analyzed based on multiple statistical indices. The results show that most regions in subtropical China experienced mild and moderate drought during 1981–2015. In particular, the extent of drought severity has shown a noticeable increasing trend after 2000. The forest NPP ranged from 622.64 to 1323.82 gC·m−2·a−1, with an overall increase rate of 16.15 gC·m−2·a−1; in particular, the contribution of the western forest NPP became increasingly important. Drought stress has limited the growth of subtropical forest NPP in China, with summer and wet season time scales of drought having the greatest impact on forest NPP anomalies, followed by autumn time scales. The limitation is mostly because the drought duration continually increased, leading to differences in the impact of drought on forest NPP before and after 2000, with declines of 59.55 % and 82.45 %, respectively, mainly concentrated in southwestern regions, such as Yunnan, Guangxi, and Sichuan provinces. This study quantitatively analyzed the impact of drought on subtropical forest NPP, and provides scientific basis for subtropical forest response and adaptation to climate change.

A comparative study on the spatio-temporal patterns and drivers of net primary productivity in three basins across different climate gradients in China

The comparative study on terrestrial net primary productivity in regions across climate gradients may help to better understand ecosystem response to climate change, yet is relatively understudied. Therefore, in this study, we compared the spatio-temporal patterns of net primary productivity during 2010-2019 and identify the different controls in three basins with typical climates in China: the Heihe River Basin with arid and semi-arid climate, Weihe River Basin with semi-arid and semi-humid climate, and Lower Yangtze River Basin with humid climate. Results indicated that the net primary productivity followed the order: Lower Yangtze River Basin (480.3 g C m−2 yr−1) &gt; Weihe River Basin (346.7 g C m−2 yr−1) &gt; Heihe River Basin (98.1 g C m−2 yr−1). The vegetation in the Heihe River Basin had severel hydrothermal limitation as the greatest importance of temperature and precipitation to the net primary productivity. In contrast, land cover type instead of climate became the most important variable on net primary productivity in the Weihe River Basin, and topography and land cover type were critical controls in the Lower Yangtze River Basin. In addition, the annual net primary productivity in all three areas exhibited an increasing trend during 2010-2019. However, the increase of net primary productivity in the Heihe River Basin was primarily driven by the increase of both temperature and precipitation due to the warming and humification in the northwestern of China. In contrast, the increase of temperature (especially spring warming) dominated the increase of net primary productivity in the Weihe River Basin and Lower Yangtze River Basin, due to the relatively sufficient precipitation. Furthermore, monthly net primary productivity exhibited a unimodal curve throughout the year. However, the increasing trend nearly stopped in June and July in the Lower Yangtze River Basin. This is possibly due to the light deficiency with abundant precipitation for plant photosynthesis in the natural ecosystem like forest and shrubland, and the rotation from wheat harvesting to rice planting in the cropland in these months.

Spatial–Temporal Variation Characteristics and Driving Factors of Net Primary Production in the Yellow River Basin over Multiple Time Scales

Vegetation net primary productivity (NPP) serves as a crucial and intuitive indicator for assessing ecosystem health. However, the nonlinear dynamics and influencing factors operating at various time scales are not yet fully understood. Here, the ensemble empirical mode decomposition (EEMD) method was used to analyze the spatiotemporal patterns of NPP and its association with hydrothermal factors and anthropogenic activities across different temporal scales for the Yellow River Basin (YRB) from 2000 to 2020. The results indicate that: (1) the annual average NPP was 236.37 g C/m2 in the YRB and increased at rates of 4.64 g C/m2/a1 (R2 = 0.86, p &lt; 0.01) during 2000 to 2020. Spatially, nonlinear analysis indicates that 72.77% of the study area exhibits a predominantly increasing trend in NPP, while 25.17% exhibits a reversing trend. (2) On a 3-year time scale, warming has resulted in an increase in NPP in the majority of areas of the study area (69.49%). As the time scale widens, the response of vegetation to climate change becomes more prominent; especially under the long-term trend, the percentage areas of the correlation between vegetation and precipitation and temperature increased with significance, reaching 48.21% and 11.57%, respectively. (3) Through comprehensive time analysis and multivariate regression analysis, it was confirmed that both human activities and climate factors had comparable impacts on vegetation growth. Among different vegetation types, climate was still the main factor affecting grassland NPP, and only 15.74% of grassland was affected by human activities. For shrubland, forest, and farmland, human activity was a dominating factor for vegetation NPP change. There are still few studies on vegetation change using nonlinear methods in the Yellow River Basin, and most studies have not considered the effect of time scale on vegetation evolution. The findings highlight the significance of multi-time scale analysis in understanding the vegetation dynamics and providing scientific guidance for future vegetation restoration and conservation efforts.

Plants alter their aboveground and belowground biomass allocation and affect community-level resistance in response to snow cover change in Central Asia, Northwest China

It is important to elucidate the changing distribution pattern of net primary productivity (NPP) to mechanistically understand the changes in aboveground and belowground ecosystem functions. In water-scarce desert environments, snow provides a crucial supply of water for plant development and the spread of herbaceous species. Yet uncertainty persists regarding how herbaceous plants' NPP allocation responds to variation in snow cover. The goal of this study was to investigate how variation in snow cover in a temperate desert influenced the NPP allocation dynamics of herbaceous species and their resistance to environmental change in terms aboveground and belowground productivity. In the Gurbantunggut Desert, wintertime snow cover depth was adjusted in plots by applying four treatments: snow removal (−S), ambient snow, double snow (+S), and triple snow (+2S). We examined their species richness, aboveground NPP (ANPP), belowground NPP (BNPP), and the resistance of ANPP and BNPP. We found that species diversity of the aboveground community increased significantly with increasing snow cover and decreased significantly Pielou evenness in plots. This resulted in greater ANPP with increasing snow cover; meanwhile, BNPP first increased and then decreased with increasing snow cover. However, this productivity in different soil layers responded differently to changed snow cover. In the 0–10 cm soil layer, productivity first rose and then declined, while it declined linearly in both the 10–20 cm and 20–30 cm soil layers, whereas in the 30–40 cm soil layer it showed an increasing trend. Belowground resistance would increase given that greater snow cover improved the BNPP in deeper soil and maintained the resource provisioning for plant growth, thus improving overall belowground stability. These results can serve as a promising research foundation for future work on how the functioning of desert ecosystems becomes altered due to changes in plant community expansion and, in particular, changes in snow cover driven by global climate change.

Integrated effects of meteorological factors, edaphic moisture, evapotranspiration, and leaf area index on the net primary productivity of Winter wheat − Summer maize rotation system

Net primary productivity (NPP) assumes a pivotal role in the realm of plant growth, organic matter production, and carbon cycling. Nevertheless, the mechanism underlying the integrated effects of meteorological factors, soil water content (SWC), evapotranspiration (ET), and leaf area index (LAI) on the NPP in agricultural systems remains unclear. Elucidating the evolution pattern of NPP in agricultural system and its responding mechanism to meteorological factors, SWC, ET, and LAI hold pronounced significant for sustainable agricultural operation, agroecological maintenance, and climate-adaptive strategy optimization. This study focused on the winter wheat - summer maize rotation, a predominant agricultural system, in the North China Plain (NCP). Spatiotemporal pattern of NPP was clarified using geostatistical technique, Mann-Kendall test, Sen's Slope, and Rescaled Range analysis. The mechanism underlying the integrated response of NPP to different meteorological factors, SWC, ET, and LAI was revealed through spatiotemporal coupling correlation analysis, Random Forest, and Structural Equation Modeling. The results demonstrated a widespread annual increase in NPP across the majority of rotation areas from 2000 to 2019, with a prominent geospatial heterogeneity. Meteorological factors, SWC, ET, and LAI collectively explained 70.27% of NPP variability. Of which, ET, FAPAR, P, LAI, Tmax, Tmin, and the SWC in 40–100 cm were predominant factors affecting NPP, explaining 63.59% of its variability. These factors exerted multidimensional effects on NPP, instead of a unilateral induction. Despite the limited direct effect, precipitation indirectly improved NPP by significantly increasing the SWC in 40–100 cm soil horizon. The latter not only directly enhanced NPP, but also indirectly promoted NPP by facilitating ET. In context of drought and water deficit, maintaining adequate soil moisture in the 40–100 cm layer through irrigation emerges as a potential strategy to ensure sustainable productivity. ET exerted the greatest comprehensive effect and the largest direct promotion on NPP. LAI, FAPAR, and SWC induced NPP variation indirectly through affecting ET. These consistently underscored the major relationship between productivity and water use. Future intensive agriculture in the NCP should prioritize the trade-off between carbon sequestration and water loss at plant physiological level. Improving the carbon sequestration per unit of water consumption through optimizing the photosynthesis-transpiration mechanism is an imperative climate-adaptative pathway for achieving sustainable food provision and mitigating water crisis.

Investigating the mechanism of urbanization on the net primary productivity of vegetation in the Yangtze River Economic Belt: a comprehensive analysis from global and local effects

The stressful effects of urbanization on vegetation net primary productivity (NPP) and vegetation–carbon cycle functions within the Yangtze River Economic Belt (YEB) under the sustainable development goals (SDG) and the concept of coordinated regional development, have garnered growing attention. Existing studies have been insufficient in comprehensively examining both the global effects and local variations resulting from urbanization in the region. Additionally, insufficient attention has been given to the heterogeneity of the ecological negative effects of urbanization in the three major urban agglomerations within the YEB. Based on multivariate remote sensing image and socioeconomic statistics data, this study integrates population, economic and land dimensions to construct comprehensive urbanization indexes and quantify the spatio-temporal evolution patterns of NPP and urbanization in the YEB. The focus is on detecting the global response of NPP to urbanization using the Spatial Durbin model and discussing the local heterogeneity of the effect in the Yangtze River Delta urban agglomeration (YRD), the middle reaches of Yangtze River urban agglomeration (MRYRU), and the Chengdu-Chongqing urban agglomeration (CCU) based on a geographically weighted regression model. The results show that the average NPP of the YEB increased from 592g*c/m2 to 670g*c/m2 at a rate of 0.621% from 2000 to 2020, with the most significant growth in the CCU, and the overall pattern of change is “increased in the north and decreased in the south”. The negative spatial autocorrelation between urbanization and NPP is becoming increasingly significant, and the negatively correlated clusters is the dominant type of local autocorrelation, among which the number of “High-Low” type cities is the largest and growing, mainly located in the northern regions of Anhui and Jiangsu. The significant negative effect of urbanization on the productive capacity of vegetation cover systems was verified, and a negative spillover effect that far exceeded the local negative effect was also confirmed. The effect of urbanization on NPP has significant local variability and gradually shifts to the effect pattern of positive effect in the east and negative effect in the west, while the pattern of urbanization-driven effects in the three urban agglomerations also continues to change. This study increases the concern about the negative ecological effects of urbanization, and more importantly, provides a basis for the joint action of ecological restoration and management in the Yangtze River Economic Belt and the implementation of differentiated governance policies around urban agglomerations.

Exploring quantification and analyzing driving force for spatial and temporal differentiation characteristics of vegetation net primary productivity in Shandong Province, China

Exploring the spatiotemporal changes of vegetation net primary productivity (NPP) and its driving mechanism is crucial for green and low-carbon development. Based on the MOD17A3HGF data, this study introduced the gravity center model, wavelet analysis, coefficient of variation, Hurst index, correlation analysis, and Thornthwaite Memorial model to explore the spatiotemporal patterns of NPP and its driving factors in Shandong Province from 2000 to 2019. The following results were attained. (1) Between 2000 and 2019, Shandong’s yearly average NPP showed an upward trend. The first main cycle of the NPP’s interannual cycle lasted 14 years. NPP was predicted to experience a short-term decline in the near future. (2) In Shandong, the NPP displayed a geographical pattern with high values in the east and low values in the west, high values in the south and low values in the north, and progressively declining values from the coast to the interior. The growth rate and increment of NPP in 2000–2019 were the largest in the northeast direction in the Southwest Plain, while those in the Jiaodong Hills, the Central and Southern Mountains, and the Northwest Plain were the largest in the northwest direction. Hurst index analysis showed that NPP would show weak anti-continuity changes in the Central and Southern Mountains and the Jiaodong Hills in the future. (3) Shandong’s NPP exhibited a “three zones and two lines” pattern of the effect of climate change and human activities. This research offers a scientific theoretical foundation for environmental protection and carbon management.

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.

Topography intensifies variations in the effect of human activities on forest NPP across altitude and slope gradients

The distribution pattern of forest net primary productivity (NPP) is mainly driven by biotic (climate) and abiotic (topography and human activity) factors. However, the influence of these factors on NPP's distribution along the elevation and slope gradient is uncertain. Additionally, it remains uncertain whether the pattern of NPP at the regional scale with significant altitude variations is comparable to that at the mountain scale. This study analyzed the NPP distribution pattern in the Yangtze River Basin, a region with high altitude heterogeneity, and investigated the impact of climate and human activity on the NPP along the elevation and slope gradient. The results revealed that as altitude increased, NPP first rose and then declined, reaching a peak at 2200–2300 m above sea level, This is in line with the distribution of NPP in mountainous areas and suggests that regions with large elevation differences may also experience vertical effects. NPP displayed an “N” shaped distribution along the slope gradient and the effect of climatic factors varied at different altitudes. Precipitation has a greater effect on NPP than the temperature in regions with less than 2300 m altitude, whereas temperature has the opposite effect in high-elevation regions (>2300 m). The study also found that afforestation and the returning farmland to forestland mainly occurred in low- and middle-altitude regions and middle-slope regions, leading to rapid NPP growth. These findings reveal that topography influences climate and human impacts on forest NPP, and future forest management strategies should consider the terrain's impact on tree growth and protect forests in high-altitude and steep-slope areas.

Above- and belowground net-primary productivity: A field-based global database of grasslands.

Net primary productivity (NPP) over global grasslands is crucial for understanding the terrestrial carbon cycling and for the assessments of wild herbivores food security. During the past few decades, numerous field investigations have been conducted to estimate grassland NPP since the measuring criterion released by the International Biological Program. However, a comprehensive NPP database, particularly for belowground NPP (BNPP), in global grasslands is rare to date. Here, field NPP measurements from 438 publications (1957-2018) in global grasslands were collected, critically filtered, and incorporated in a comprehensive global database with observations for aboveground NPP (ANPP), BNPP, total NPP (TNPP), and BNPP fraction (fBNPP ). Associated information on geographical locations, climatic records, grassland types, land use patterns, manipulations subjected to manipulative experiments, sampling year of study sites, as well as NPP measurement methods are also documented. This database included 2985 entries from 1785 study sites. Among them, 806 entries contained paired data of ANPP and BNPP, resulting in the 806 fBNPP data. The study sites encompassed global grasslands with latitudinal range of 54.5° S~78.9° N, longitudinal range of 157.4° W~175.8° E, and altitudes from 0 to 5168 m above sea level, covering broad climatic gradients (-17.6 to 28.8°C in mean annual temperature and 63-2052 mm in mean annual precipitation). This global database is the world's largest paired data of ANPP and BNPP field measurements in grasslands. It can be used to study the spatio-temporal patterns of NPP and its allocation, evaluate the responses of above- and below-ground carbon components to future global changes, and validate the NPP estimation by empirical or process-based models in global grasslands. The database can be freely used for noncommercial applications. We kindly request users cite this data paper when using the database, respecting all the hard work during data compilation.

Vegetation Productivity and Precipitation Use Efficiency across the Yellow River Basin: Spatial Patterns and Controls

In arid and semi-arid climate zones, understanding the spatial patterns and biogeographical mechanisms of net primary production (NPP) and precipitation use efficiency (PUE) is crucial for assessing the function and stability of ecosystem services, as well as directing ecological restoration. Although the vegetation coverage has changed dramatically after the construction of several ecological restoration projects, due to limited observation data, fewer studies have provided a thorough understanding of NPP and PUE’s recent spatial patterns and the controlling factors of different vegetation types in the Yellow River Basin (YRB). To narrow this gap, we integrated remote-sensing land-cover maps with long-term MODIS NPP and meteorological datasets to comprehend NPP and PUE spatial patterns in YRB. Furthermore, we applied structural equation models (SEM) to estimate the effect intensity of NPP and PUE controlling factors. The results showed that along geographical coordinates NPP and PUE decreased from southeast to northwest and trends were roughly consistent along latitude, longitude, and elevation gradients with segmented patterns of increasing and decreasing trends. As for climate gradients, NPP showed significant linear positive and negative trends across the mean annual precipitation (MAP) and the arid index (AI), while segmented changes for PUE. However, the mean annual average temperature (MAT) showed a positive slope for below zero temperature and no change above zero temperature for both NPP and PUE. SEM results suggested that AI determined the spatial pattern of NPP, whereas PUE was controlled by MAP and NPP. As the AI becomes higher in the further, vegetation tends to have decreased NPP with higher sensitivity to water availability. While artificial vegetation had a substantially lower NPP than original vegetation but increased water competition between the ecosystem and human society. Hence further optimization of artificial vegetation is needed to satisfy both ecological and economic needs. This study advanced our understanding of spatial patterns and biogeographic mechanisms of NPP and PUE at YRB, therefore giving theoretical guidance for ecological restoration and ecosystem function evaluation in the face of further climate change.

Recent variations in soil moisture use efficiency (SMUE) and its influence factors in Asian drylands

Soil moisture use efficiency (SMUE) is an important indicator for evaluating the suitability of plant growth. This study synthetically assesses changes in SMUE in different vegetation types, fraction of vegetation cover, and altitude in the Asian drylands from 2001 to 2019. It also illustrates the inherent mechanisms by which soil moisture(SM) and net primary production (NPP), which are both affected by CO2 and relative humidity (f), influence SMUE. The results show an increase in SMUE over the study period, with annual mean values ranging from 0 to 0.59 (g C/mm). Forested areas have the highest SMUE value, while shrub land has the lowest value. These changes in SMUE are dominated by the three vegetation spatial combination patterns of NPP, SM, and the coupling relationship between NPP and SM. Forests and cropland are dominated by NPP, while wetlands, grassland and shrub land are dominated by SM. NPP is mainly affected by CO2 and the greenhouse effect, whereas SM is mainly affected by f. The results obtained from this study provide scientific data to support the ecological security and development of agriculture and animal husbandry in the Asian drylands, which is critical for maintaining regional ecological stability and sustainable economic and social development.

How precipitation legacies affect broad-scale patterns of primary productivity: Evidence from the Inner Mongolia grassland

The legacy effects of precipitation, defined as the impact of precipitation from previous years on current-year net primary productivity (NPP), have been well recognized in field experiments and site-level observational studies. However, it remains unclear how consecutive dry or wet years influence the directions and magnitude of legacies and broad-scale patterns of NPP. Here, we quantified the spatial and temporal patterns of legacy effect across different numbers of consecutive wet and dry years from 2000 to 2020 in the Inner Mongolia grassland. Spatially, the response of legacies to precipitation transitions was asymmetric along the mean annual precipitation gradient. The positive response of legacies to precipitation decrease was found for desert steppe and typical steppe after preceding wetness. In contrast, the response of legacies to precipitation increase was negative for desert steppe and meadow steppe after preceding drought. Moreover, legacies were more sensitive in desert steppe than that in typical steppe and meadow steppe for both the preceding wetness and preceding drought. However, the meadow steppe showed the highest response to the inter-annual precipitation change among the three grassland types. Furthermore, the legacies responded more strongly to precipitation decrease (preceding consecutive wet years) than the increase (preceding consecutive dry years) for meadow steppe and typical steppe. Yet, the desert steppe showed the opposite response to precipitation change. Temporally, the legacy effects lasted for only one year and could be transmitted year by year. Our findings highlight that consecutive wet and dry years play essential roles in controlling the NPP responses to climate fluctuations in arid and semi-arid grasslands. Understanding ecosystem responses to climatic periods can provide insights into the effects of directional changes in rainfall associated with climate change.

Unequal weakening of urbanization and soil salinization on vegetation production capacity

Net Primary Productivity (NPP) has been widely used to estimate the productivity of the farmland ecosystem (FES) and the carbon budget of the terrestrial ecosystem. Changes in the NPP of FES have knock-on effects on food security, sustainable agricultural development, carbon sequestration, and environmental changes. Existing studies mainly focused on the impact of climate change and urbanization on the spatial-temporal pattern of NPP, largely ignoring the roles of soil condition and agricultural management practices (AMPs). At present, the joint impact of “climate-urbanization-soil-AMPs” on the NPP of FES remains unknown. To fill this knowledge gap, we use the NPP dataset retrieved by the vegetation photosynthesis model (VPM), daily meteorological records, field-collected soil data, AMPs data collected from the Government Statistical Yearbook, and land cover dataset to study the joint mechanism of “climate-urbanization-soil” that drives spatial-temporal variations of NPP. Taking the northern slope of Tianshan Mountains as the study area, our results indicate that NPP had increased by 3.86 Tg C from 2000 to 2015 (11.93 Tg C in 2000 and 15.79 Tg C in 2015). From the proposed conceptual framework, we found that climate variables (accumulated temperature, precipitation, evapotranspiration) play a major role in driving the growth of NPP (+4.01 Tg C). The AMPs (i.e., mulching filming, drip irrigation, and fertilizer application) make a positive contribution to NPP increase (+0.98 Tg C). We also found that soil salinization (-1.07 Tg C) weakens the growth of NPP more significantly than urbanization (−0.16 Tg C). This study provides new insights on the mechanism of climate change, urbanization, and soil conditions on crops, benefiting stakeholders in designing better management plans for sustainable agriculture, ecosystem cycling, and food security.