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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.

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ABSTRACTDrought presents a major challenge to the management of rocky desertification and ecological restoration in the delicate karst ecosystems of Guangxi. In this study, the normalized difference vegetation index (NDVI), fractional vegetation cover (FVC) and net primary productivity (NPP) were selected as vegetation remote sensing parameters, and the spatial response characteristics of different types of vegetation in karst areas of Guangxi Province to light, moderate, severe and extreme drought were analyzed to provide scientific basis for the evaluation of the impact of drought on vegetation in karst areas. The results are as follows: (1) NDVI, FVC and NPP showed a fluctuating increasing trend from 2000 to 2022, and the increasing rates were 0.058, 6.90%, and 43.3gC.m-2 per decade respectively. During this period, the number of light, moderate and severe drought days showed a decreasing trend, but the number of extreme drought days tended to increase. (2) The negative correlation of NDVI, FVC and NPP and drought increased from moderate to extreme drought, and from light to extreme drought, the negative correlation between NDVI and FVC and drought decreased, while that of NPP increased. (3) Light and moderate droughts had obvious negative impact on Chinese fir and broad-leaved forest, whereas severe and extreme droughts had obvious negative effect on eucalyptus and bamboo forest.

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Measurements of net primary productivity (NPP) and litter decomposition from tropical peatlands are severely lacking, limiting our ability to parameterise and validate models of tropical peatland development and thereby make robust predictions of how these systems will respond to future environmental and climatic change. Here, we present total NPP (i.e., above- and below-ground) and decomposition data from two floristically and structurally distinct forested peatland sites within the Pastaza Marañón Foreland Basin, northern Peru, the largest tropical peatland area in Amazonia: (1) a palm (largely Mauritia flexuosa) dominated swamp forest and (2) a hardwood dominated swamp forest (known as 'pole forest', due to the abundance of thin-stemmed trees). Total NPP in the palm forest and hardwood-dominated forest (9.83 ± 1.43 and 7.34 ± 0.84 Mg C ha-1 year-1, respectively) was low compared with values reported for terra firme forest in the region (14.21-15.01 Mg C ha-1 year-1) and for tropical peatlands elsewhere (11.06 and 13.20 Mg C ha-1 year-1). Despite the similar total NPP of the two forest types, there were considerable differences in the distribution of NPP. Fine root NPP was seven times higher in the palm forest (4.56 ± 1.05 Mg C ha-1 year-1) than in the hardwood forest (0.61 ± 0.22 Mg C ha-1 year-1). Above-ground palm NPP, a frequently overlooked component, made large contributions to total NPP in the palm-dominated forest, accounting for 41% (14% in the hardwood-dominated forest). Conversely, Mauritia flexuosa litter decomposition rates were the same in both plots: highest for leaf material, followed by root and then stem material (21%, 77% and 86% of mass remaining after 1 year respectively for both plots). Our results suggest potential differences in these two peatland types' responses to climate and other environmental changes and will assist in future modelling studies of these systems.

Mediciones de la productividad primaria neta (PPN) y la descomposición de materia orgánica de las turberas tropicales son escasas, lo que limita nuestra capacidad para parametrizar y validar modelos de desarrollo de las turberas tropicales y, en consecuencia, realizar predicciones sólidas sobre la respuesta de estos sistemas ante futuros cambios ambientales y climáticos. En este estudio, presentamos datos de PPN total (es decir, biomasa aérea y subterránea) y descomposición de la materia orgánica colectada en dos turberas boscosas con características florísticas y estructurales contrastantes dentro de la cuenca Pastaza Marañón al norte del Perú, el área de turberas tropicales más grande de la Amazonia: (1) un bosque pantanoso dominado por palmeras (principalmente Mauritia flexuosa) y (2) un bosque pantanosos dominado por árboles leñosos de tallo delgado (conocido como 'varillal hidromórfico'). La PPN total en el bosque de palmeras y el varillal hidromórfico (9,83 ± 1,43 y 7,34 ± 0,84 Mg C ha­1 año­1 respectivamente) fue baja en comparación con los valores reportados para los bosques de tierra firme en la región (14,21­15,01 Mg C ha­1 año­1) y para turberas tropicales en otros lugares (11,06 y 13,20 Mg C ha­1 año­1). A pesar de que la PPN total fue similar en ambos tipos de bosque, hubo diferencias considerables en la distribución de la PPN. La PPN de las raíces finas fue siete veces mayor en el bosque de palmeras (4,56 ± 1,05 Mg C ha­1 año­1) que en el varillal hidromórfico (0,61 ± 0,22 Mg C ha­1 año­1). La PPN de la biomasa aérea de las palmeras, un componente ignorado frecuentemente, contribuyó en gran medida a la PPN total del bosque de palmeras, representando el 41% (14% en el varillal hidromórfico). Por el contrario, la tasa de descomposición de materia orgánica de Mauritia flexuosa fue la misma en ambos sitios: la más alta corresponde a la hojarasca, seguida por las raíces y luego el tallo (21%, 77% y 86% de la masa restante después de un año, respectivamente para ambos sitios). Nuestros resultados sugieren diferencias potenciales en la respuesta de estos dos tipos de turberas al clima y otros cambios ambientales, y ayudarán en futuros estudios de modelamiento de estos sistemas.

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Species energy theory suggests that, because of limitations on reproduction efficiency, a minimum density of plant individuals per viable species exists and that this minimum correlates the total number of plant individuals N with the number of species S. The simplest assumption is that the mean energy input per individual plant is independent of the number of individuals, making N, and thus S as well, proportional to the total energy input into the system. The primary energy input to a plant-dominated ecosystem is estimated as its Net Primary Productivity (NPP). Thus, species energy theory draws a direct correspondence from NPP to S. Although investigations have verified a strong connection between S and NPP, strong influences of other factors, such as topography, ecological processes such as competition, and historical contingencies, are also at play. The lack of a simple model of NPP expressed in terms of the principal climate variables, precipitation P, and potential evapotranspiration, PET, introduces unnecessary uncertainty to the understanding of species richness across scales. Recent research combines percolation theory with the principle of ecological optimality to derive an expression for NPP(P, PET). Consistent with assuming S is proportional to NPP, we show here that the new expression for NPP(P, PET) predicts the number of plant species S in an ecosystem as a function of P and PET. As already demonstrated elsewhere, the results are consistent with some additional variation due to non-climatic inputs. We suggest that it may be easier to infer specific deviations from species energy predictions with increased accuracy and generality of the prediction of NPP(P, PET).

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The fraction of net primary productivity (NPP) allocated to belowground organs (fBNPP) in grasslands is a critical parameter in global carbon cycle models; moreover, understanding the effect of precipitation changes on this parameter is vital to accurately estimating carbon sequestration in grassland ecosystems. However, how fBNPP responds to temporal precipitation changes along a gradient from extreme drought to extreme wetness, remains unclear, mainly due to the lack of long-term data of belowground net primary productivity (BNPP) and the fact that most precipitation experiments did not have a gradient from extreme drought to extreme wetness. Here, by conducting both a precipitation gradient experiment (100-500 mm) and a long-term observational study (34 years) in the Inner Mongolia grassland, we showed that fBNPP decreased linearly along the precipitation gradient from extreme drought to extreme wetness due to stronger responses in aboveground NPP to drought and wet conditions than those of BNPP. Our further meta-analysis in grasslands worldwide also indicated that fBNPP increased when precipitation decreased, and the vice versa. Such a consistent pattern of fBNPP response suggests that plants increase the belowground allocation with decreasing precipitation, while increase the aboveground allocation with increasing precipitation. Thus, the linearly decreasing response pattern in fBNPP should be incorporated into models that forecast carbon sequestration in grassland ecosystems; failure to do so will lead to underestimation of the carbon stock in drought years and overestimation of the carbon stock in wet years in grasslands.

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Understanding the spatiotemporal changes in net primary productivity (NPP) and the driving factors behind these changes in climate-vulnerable regions is crucial for ecological conservation. This study simulates the actual NPP (NPPA) and climate potential NPP (NPPC) in the Three-River Headwaters Region from 2000 to 2020. The Theil-Sen Median method and Mann-Kendall mutation analyses are employed to explore their spatiotemporal variation patterns, while geographic weighted regression and machine learning are used to investigate the influence of anthropogenic activities and climatic factors on NPPA, the results indicate that the average NPPA across the entire region over multiple years is 382.506 g C m - 2 yr - 1 , which is 0.132 times the average annual NPPC over the past 21 years, showing an overall distribution pattern of low in the northwest and high in the southeast. The annual increase in NPPA from 2000 to 2020 is approximately 1.034 g C m - 2 yr - 1 . The source region of the Yangtze River shows the largest improvement in vegetation, with 74.1% of the area showing improvement. Between 2002 and 2003, the annual NPPA in the Three-River Headwaters Region experienced a sudden change, lagging behind the NPPC change by 1 year, and after 2005, the upward trend in NPPA became more pronounced. The impact of anthropogenic activities on NPPA shifted from positive to negative to positive from 2000 to 2020, with significant impact areas mainly concentrated in the northeast and a few areas in the central and southern parts. The proportion of areas with extremely significant impact increased from 1.9% in 2000 to 3.7% in 2020. Over the past 21 years, the main factors influencing NPPA changes in the Three-River Headwaters Region have been soil moisture and precipitation, with the influence of different climate factors on NPP changing over time. Additionally, NPP is more sensitive to changes in altitude in low-altitude areas. This study can provide more accurate theoretical support for ecological environment assessment and subsequent protection efforts in the Three-River Headwaters Region.

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Based on the food equivalent unit (FEU), this article analyzed Chinese food consumption patterns, spatial mismatch, and production potential to explore agricultural reform strategies. Assessing production-demand mismatch involved the spatial mismatch model, drawing data from statistical yearbooks. Calculations of food production potential utilized the CASA model and the Thornthwaite Memorial model, with net primary productivity (NPP) derived from remote sensing data as indicators. The results showed that livestock product consumption is on the rise, and the spatial mismatch index for herbivorous livestock products was the largest, ranging from 22.81 to 98.12 in 2019. The mismatched degree distribution of rations and food-consuming livestock products showed a trend of increasing on both sides, with the Hu Huanyong line as the center line. Production factors played a predominant role in food production-to-demand mismatch. Climatic productivity and actual productivity decreased from the southeast to northwest in space in 2019, and human activities significantly impacted productivity. When grassland agriculture is pursued as the adjustment orientation, the production potential can reach up to 4540.76 × 107 kg·FEU. Moreover, a grassland agriculture plan was devised, prioritizing its development in the developed southern regions.

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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.

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A crucial physiological indicator known as water use efficiency (WUE) (Foley et al.) assesses the trade-off between water loss and carbon uptake. The carbon and water coupling mechanisms, energy balance, and hydrological cycle processes in the ecosystem are impacted by climate change, vegetation dynamics, and land use change. In this study, we employed Sen trend analysis, the Mann-Kendall test, the land-use transfer matrix, and multiple linear regression analysis to investigate the regional and temporal dynamics of WUE and its reaction to climate change and land-use transfer changes in China. According to the findings, the annual average WUE in China was 0.998 gC/mm·m2 from 2000 to 2017. Of the nine major river basins, the Continental Basin had the lowest WUE (0.529 gC/mm·m2), and the Southwest River Basin had the highest WUE (0.691 gC/mm·m2), while the Pearl River Basin and the Southeast River Basin had the highest WUEs (1.184 gC/mm·m2). The Haihe River Basin and the Yellow River Basin were the key regions with elevated WUE. Forest had the greatest WUE (1.134 gC/mm·m2; out of the nine major river basins), followed by shrub (1.109 gC/mm·m2). Vegetation dynamics changes had a higher impact on WUE than climate change and land use changes, when the contributions of climate change, vegetation dynamics changes, and land use changes to WUE were separated. The largest climatic factor influencing variations in WUE was VPD (28.04% ± 3.98%), whereas among the vegetation dynamics factors, NDVI (33.75% ± 6.90%) and LAI (22.21% ± 2.11%) contributed the most. The transition from high to low vegetation cover led to a relative decrease in WUE, and vice versa, according to data on land use change in China from 2000 to 2017. Land use change made a positive impact to WUE change. The findings of this study may be helpful in China for choosing a suitable regional plant cover and managing local water resources sustainably.

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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.

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The emission reduction of atmospheric pollutants during the COVID-19 caused the change in aerosol concentration. However, there is a lack of research on the impact of changes in aerosol concentration on carbon sequestration potential. To reveal the impact mechanism of aerosols on rice carbon sequestration, the spatial differentiation characteristics of aerosol optical depth (AOD), gross primary productivity (GPP), net primary productivity (NPP), leaf area index (LAI), fraction of absorbed photosynthetically active radiation (FPAR), and meteorological factors were compared in the Sanjiang Plain. Pearson correlation analysis and geographic detector were used to analyze the main driving factors affecting the spatial heterogeneity of GPP and NPP. The study showed that the spatial distribution pattern of AOD in the rice-growing area during the epidemic was gradually decreasing from northeast to southwest with an overall decrease of 29.76%. Under the synergistic effect of multiple driving factors, both GPP and NPP increased by more than 5.0%, and the carbon sequestration capacity was improved. LAI and FPAR were the main driving factors for the spatial differentiation of rice GPP and NPP during the epidemic, followed by potential evapotranspiration and AOD. All interaction detection results showed a double-factor enhancement, which indicated that the effects of atmospheric environmental changes on rice primary productivity were the synergistic effect result of multiple factors, and AOD was the key factor that indirectly affected rice primary productivity. The synergistic effects between aerosol-radiation-meteorological factor-rice primary productivity in a typical temperate monsoon climate zone suitable for rice growth were studied, and the effects of changes in aerosol concentration on carbon sequestration potential were analyzed. The study can provide important references for the assessment of carbon sequestration potential in this climate zone.

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Nonnative species are a key agent of global change. However, nonnative invertebrates remain understudied at the community scales where they are most likely to drive local extirpations. We use the North American NEON pitfall trapping network to document the number of nonnative species from 51 invertebrate communities, testing four classes of drivers. We sequenced samples using the eDNA from the sample's storage ethanol. We used AICc informed regression to evaluate how native species richness, productivity, habitat, temperature, and human population density and vehicular traffic account for continent-wide variation in the number of nonnative species in a local community. The percentage of nonnatives varied 3-fold among habitat types and over 10-fold (0%-14%) overall. We found evidence for two types of constraints on nonnative diversity. Consistent with Capacity rules (i.e., how the number of niches and individuals reflect the number of species an ecosystem can support) nonnatives increased with existing native species richness and ecosystem productivity. Consistent with Establishment Rules (i.e., how the dispersal rate of nonnative propagules and the number of open sites limits nonnative species richness) nonnatives increased with automobile traffic-a measure of human-generated propagule pressure-and were twice as common in pastures than native grasslands. After accounting for drivers associated with a community's ability to support native species (native species richness and productivity), nonnatives are more common in communities that are regularly seasonally disturbed (pastures and, potentially deciduous forests) and those experiencing more vehicular traffic. These baseline values across the US North America will allow NEON's monitoring mission to document how anthropogenic change-from disturbance to propagule transport, from temperature to trends in local extinction-further shape biotic homogenization.

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

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Understanding the spatial variability of ecosystem functions is an important step forward in predicting changes in ecosystems under global transformations. Plant functional traits are important drivers of ecosystem functions such as net primary productivity (NPP). Although trait-based approaches have advanced rapidly, the extent to which specific plant functional traits are linked to the spatial diversity of NPP at a regional scale remains uncertain. Here, we used structural equation models (SEMs) to disentangle the relative effects of abiotic variables (i.e., climate, soil, nitrogen deposition, and human footprint) and biotic variables (i.e., plant functional traits and community structure) on the spatial variation of NPP across China and its eight biomes. Additionally, we investigated the indirect influence of climate and soil on the spatial variation of NPP by directly affecting plant functional traits. Abiotic and biotic variables collectively explained 62.6 % of the spatial differences of NPP within China, and 28.0 %-69.4 % across the eight distinct biomes. The most important abiotic factors, temperature and precipitation, had positive effects for NPP spatial variation. Interestingly, plant functional traits associated with the size of plant organs (i.e., plant height, leaf area, seed mass, and wood density) were the primary biotic drivers, and their positive effects were independent of biome type. Incorporating plant functional traits improved predictions of NPP by 6.7 %-50.2 %, except for the alpine tundra on the Qinghai-Tibet Plateau. Our study identifies the principal factors regulating NPP spatial variation and highlights the importance of plant size traits in predictions of NPP variation at a large scale. These results provide new insights for involving plant size traits in carbon process models.

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Clarifying the spatial distribution of the impact of different human disturbance activities on the net primary productivity (NPP) in regions with single climatic conditions is of considerable importance to ecological protection. Time-series NPP from 2000 to 2020 was simulated in Northwest Hubei, China, and the effects of the climate and human activities on the NPP changes were separated. Research results showed that from 2000 to 2020, the NPP change with an area of 10,166.63 km2 in Northwest Hubei is influenced by climate and human activities. Among them, human activities account for as high as 84.53%. From 2000 to 2020, the NPP in Northwest Hubei showed a slight upward trend at a rate of 1.61 g C m-2 year-1. The significantly increased NPP accounted for 21.4% of the total, which was mainly distributed in north of Northwest Hubei. And the farming of cultivated land led to the increase of NPP in west as well as the reduced human distribution in cultivated land, which was scattered in forests. Only 6.67% of the total area demonstrated a significantly decreased NPP, which was distributed mainly in the central affected by the expansion of rural-urban land and change of broad-leaved forests to shrubs and in southeast regions of Northwest Hubei caused by the increase in potential evapotranspiration. This study refined the driving factors of spatial heterogeneity of NPP changes in Northwest Hubei, which is conducive to rational planning of terrestrial ecosystem protection measures.

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Tropical vegetation plays a critical role in terrestrial carbon budget and supply many ecological functions such as carbon sequestration. In recent decades, India has witnessed an increase in net primary productivity (NPP), an important measure of carbon sequestration. However, uncertainties persist regarding the sustainability of these land carbon sinks in the face of climate change. The enhanced NPP is driven by the strong CO2 fertilization effect (CFE), but the temporal patterns of this feedback remain unclear. Using the carbon flux data from the Earth System Models (ESMs), an increasing trend in NPP was observed, with projections of NPP to 2.00 ± 0.12 PgCyr-1 (25 % increase) during 2021-2049, 2.36 ± 0.12 PgCyr-1 (18 % increase) during 2050-2079, and 2.67 ± 0.07 PgCyr-1 (13 % increase) during 2080-2099 in Indian vegetation under SSP585 scenario. This suggests a significant decline in the NPP growth rate. To understand the feedback mechanisms driving NPP, the relative effects of CFE and warming were analyzed. Comparing simulations from the biogeochemically coupled model (BGC) with the fully coupled model, the BGC model projected a 74.7 % increase in NPP, significantly higher than the 55.9 % increase projected by the fully coupled model by the end of the century. This indicates that the consistent increase in NPP was associated with CO2 fertilization. More importantly, results reveal that the decrease in the NPP growth rate was due to the declining contribution of CFE at a rate of -0.62 % per 100 ppm CO2 increase. This decline could be attributed to factors such as nutrient limitations and high temperatures. Additionally, significant shifts in the strength of carbon sinks in offsetting the CO2 emissions were identified, decreasing at a rate of -1.15 % per decade. This decline in the strength of vegetation carbon sequestration may increase the societal dependence on mitigation measures to address climate change.

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Biochar is widely recognized as a soil amendment to reduce greenhouse gas emissions and enhance soil carbon storage in agroecosystems; however, the systematic focus on carbon balance and ecological benefits in cropping systems remains unclear in saline-alkali areas under water-saving irrigation. Here, a 2-yr field experiment with carbon footprint method was conducted to determine soil carbon budgets, biochar carbon efficiency performance, and the economic and ecological benefits of mulched drip-irrigated sorghum production, in an arid salinized region of Inner Mongolia, China. Corn straw-derived biochar dosages of 0 (CK), 15 (B15), 30 (B30), and 45 (B45) t hm-2 were just applied into the soil in the first crop growing season. A single application of biochar to soil significantly reduced CO2 emissions for the current and subsequent crop-growing seasons, with 13.1%, 16.7%, and 12.5% reductions for B15, B30, and B45, respectively. Compared with the non-biochar control plots, B15, B30, and B45 also increased NPP by 36.7%, 38.4%, and 27.1%, respectively. The actual effects on improving net carbon sequestration for B15, B30, and B45 in the first year were higher than those in the second year, with mean increases of 1.27, 1.47, and 1.36 times, respectively; however, the efficiencies of biochar for fixing carbon per biochar dosage input for B15 were 72.8% and 64.1% higher than those of B30 and B45, respectively. Net profits were significantly improved by 57.2-87.1% by biochar treatments. The environmental benefits of biochar carbon trading revenues for B15, B30, and B45 increased by 105.9%, 162.1%, and 109.6%, respectively. The minimum observation for carbon productivity and the maximum measurements for both the economic and ecological benefits were B15. The B15 also significantly increased sorghum yield and grain number. Results demonstrate that biochar application in the current growing season helps reduce soil carbon emissions, increases net carbon sequestration for current and subsequent sorghum agroecosystems, and enhances net profit and ecological benefits. The optimal positive synergistic effect was observed at a biochar application rate of 15 t hm-2 for reducing soil carbon emissions, increasing crop production, and improving the ecological environment.

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Studying the spatiotemporal variation in vegetation net primary productivity (NPP) and exploring its influencing factors are of considerable practical significance for understanding the spatiotemporal variation in vegetation and for guiding ecological restoration and management projects based on local conditions. Based on MODIS NPP data, combined with in situ meteorological data, land use data, and vegetation type data, this study explores the spatiotemporal variation in different types of vegetation NPP in southwest China via the Mann-Kendall significance test and Theil-Sen Median slope estimator. It reveals the influencing factors of spatial differentiation of different types of vegetation NPP and the interaction between influencing factors in combination with stability analysis and Geo Detectors. The results revealed that on the temporal scale, from 2000 to 2021, vegetation NPP, NPPPre (vegetation NPP exclusively under the influence of climate change), and NPPRes (vegetation NPP exclusively under the influence of human activities) in southwest China showed a fluctuating upward trend. Among different vegetation types, NPP, NPPPre, and NPPRes exhibited an upward trend, except for a minor decline in NPPRes of tree vegetation at a rate of -0.183 g·(m2·a)-1. Among them, NPP, NPPPre, and NPPRes of economic vegetation showed the most significant upward rates, 5.96, 3.09, and 2.94 g·(m2·a)-1, respectively. On the spatial scale, the tree vegetation NPP with the most significant downward trend was mainly distributed in Tibet and southern Yunnan, while the economic vegetation NPP with the highest upward trend was primarily distributed in eastern Sichuan Province. The stability of vegetation NPP in southwest China presented a spatial distribution pattern of "low in the south and high in the north," and the average value of the correlation coefficient increased in the ascending order of arbor vegetation (0.101), shrub vegetation (0.105), herb vegetation (0.110), and economic vegetation (0.114). The interaction between surface temperature and relative humidity was the main influencing factor for spatial differentiation of vegetation NPP, while the interaction between sunshine duration and warmth index had the most significant impact on vegetation in southwest China, with an increasing percentage of 30.91%. Different types of vegetation had different requirements for different climatic factors, but their requirements for surface temperature and warmth index were significantly consistent. When the surface temperature was 21.03-28.49℃, and the warmth index was 106.46-167.2, the NPP of different vegetation types peaked. Under natural succession, the impact of climate change on vegetation was inversely proportional to the stability of the vegetation community. The arbor vegetation community with high stability was less affected, while the herb vegetation community with low stability was highly affected by climate. In contrast, the stability of economic vegetation was directly proportional to the impact of climate due to the influence of human activities. This study establishes a theoretical foundation for evaluating the impact of regional climate on the growth of different vegetation types and can be crucial for formulating ecological restoration and management strategies in southwest China that are adapted to the local conditions.

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

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Climate change will impact gross primary productivity (GPP), net primary productivity (NPP), and carbon storage in wooded ecosystems. The extent of change will be influenced by thermal acclimation of photosynthesis-the ability of plants to adjust net photosynthetic rates in response to growth temperatures-yet regional differences in acclimation effects among wooded ecosystems is currently unknown. We examined the effects of changing climate on 17 Australian wooded ecosystems with and without the effects of thermal acclimation of C3 photosynthesis. Ecosystems were drawn from five ecoregions (tropical savanna, tropical forest, Mediterranean woodlands, temperate woodlands, and temperate forests) that span Australia's climatic range. We used the CABLE-POP land surface model adapted with thermal acclimation functions and forced with HadGEM2-ES climate projections from RCP8.5. For each site and ecoregion we examined (a) effects of climate change on GPP, NPP, and live tree carbon storage; and (b) impacts of thermal acclimation of photosynthesis on simulated changes. Between the end of the historical (1976-2005) and projected (2070-2099) periods simulated annual carbon uptake increased in the majority of ecosystems by 26.1%-63.3% for GPP and 15%-61.5% for NPP. Thermal acclimation of photosynthesis further increased GPP and NPP in tropical savannas by 27.2% and 22.4% and by 11% and 10.1% in tropical forests with positive effects concentrated in the wet season (tropical savannas) and the warmer months (tropical forests). We predicted minimal effects of thermal acclimation of photosynthesis on GPP, NPP, and carbon storage in Mediterranean woodlands, temperate woodlands, and temperate forests. Overall, positive effects were strongly enhanced by increasing CO2 concentrations under RCP8.5. We conclude that the direct effects of climate change will enhance carbon uptake and storage in Australian wooded ecosystems (likely due to CO2 enrichment) and that benefits of thermal acclimation of photosynthesis will be restricted to tropical ecoregions.

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