Net Ecosystem Production Research Articles

Study of Regional Spatial and Temporal Changes of Net Ecosystem Productivity of Crops from Remotely Sensed Data

Net ecosystem productivity (NEP) is a crucial indicator of the carbon balance and health of an ecosystem. Until now, few studies have estimated the NEP of crops and analyzed it in space and time. The study of NEP in crops is crucial for comprehending the carbon cycle of agroecosystems and determining the status of carbon sources and sinks in farmland at the regional scale. In this study, we calculated the net primary productivity (NPP) and NEP of agricultural crops in Jiangsu Province, China, from 2001 to 2022 by using remote sensing data, land cover data and meteorological data. The modified Carnegie Ames Stanford Approach (CASA) model was employed to estimate the NPP, and the soil heterotrophic respiration model was used to calculate the soil heterotrophic respiration (Rh). Then, the availability of the NPP was evaluated. On this basis, the NEP was obtained by calculating the difference between the NPP and Rh. We explored the spatial and temporal changes in the NEP of crops and analyzed the correlation between the NEP and crop cultivation activities and climatic factors under the context of agricultural production information using the NEP datasets of agricultural crops. The study indicated that (1) the NEP of crops in Jiangsu Province showed a north-to-south pattern, being higher in the north and lower in the south. Over the course of 22 years, the average NEP of the crops in Jiangsu Province stands at 163.4 gC/m2, highlighting a positive carbon sink performance. Nonetheless, up to 88.04% of the crops exhibited declining NEP trends. (2) The monthly fluctuations in the NEP of crops in Jiangsu Province exhibited a bimodal pattern, with peaks occurring during spring and summer. The changes in the NEP of the crops were significantly associated with various agricultural production activities. (3) Significant regional differences were observed in the NEP of the crop response to temperature and precipitation, both of which directly impacted the annual performance of the NEP. This study could serve as a reference for research on the carbon cycle in agriculture and the development of policies aimed at reducing emissions and enhancing carbon sinks in local farmland.

Dry-season length affects the annual ecosystem carbon balance of a temperate semi-arid shrubland

Semi-arid ecosystems have been shown to dominate over tropical forests in determining the trend and interannual variability of land carbon (C) sink. However, the magnitude and variability of ecosystem C balance remain largely uncertain for temperate semi-arid shrublands at the decadal scale. Using eddy-covariance and micro-meteorological measurements, we quantified the interannual variation in net ecosystem production (NEP) and its components, gross primary production (GPP) and ecosystem respiration (Reco, i.e., the sum of autotrophic and heterotrophic respiration), in a semi-arid shrubland of the Mu Us Desert, northern China during 2012–2022. This shrubland was an overall weak C sink over the 11 years (NEP = 12 ± 46 g C m−2 yr−1, mean ± SD). Annual NEP ranged from −66 to 77 g C m−2 yr−1, with the ecosystem frequently switching between being an annual C sink and a C source. GPP was twice as sensitive as Reco to prolonged dry seasons, leading to a close negative relationship between annual NEP and dry-season length (R2 = 0.80, P < 0.01). Annual GPP (R2 = 0.51, P = 0.01) and NEP (R2 = 0.58, P < 0.01) were positively correlated with annual rainfall. Negative annual NEP (the ecosystem being a C source) tended to occur when the dry season exceeded 50 d yr−1 or rainfall dropped below 280 mm yr−1. Increases in dry-season length strengthened the effects of low soil moisture relative to high vapor pressure deficit in constraining NEP. Both GPP and NEP were more closely correlated with C uptake amplitude (annual maximum daily values) than with C uptake period. These findings indicate that dry-season extension under climate change may reduce the long-term C sequestration in semi-arid shrublands. Plant species adapted to prolonged dry seasons should be used in ecosystem restoration in the studied area to enhance ecosystem functions.

Atmospheric water demand constrains net ecosystem production in subtropical mangrove forests

Subtropical mangroves have great potential to sequester atmospheric carbon dioxide (CO2) and thus significantly contribute to climate change mitigation. Meanwhile, the carbon cycling processes in subtropical mangroves are vulnerable to the changing climatic conditions, such as the warming-induced vapor pressure deficit (VPD) increases. However, the impacts of VPD on net ecosystem production (NEP) in subtropical mangroves remain poorly understood due to a lack of detailed assessment of NEP responses to VPD among different mangrove forests over a long-term observational period. In this study, we deployed eddy-covariance systems to measure net ecosystem CO2 exchange at three subtropical mangrove forests for 16 site-years, comprising two natural and one artificial forests. We employed a state-of-the-art data-driven modeling approach (i.e., Shapley additive explanations (SHAP) framework based on extreme gradient boosting model), which enabled us to explore the interactive effects of meteorological and tidal factors (e.g. salinity) with VPD on the mangrove NEP. We revealed that air temperature, global solar radiation (GR) and wind speed have significant interactions on the response of NEP to VPD stress in subtropical mangroves. For instance, when GR was high, the SHAP interaction values of VPD and GR on NEP decreased with increasing VPD, but when GR was low, the trends were the opposite. However, instead of identifying interactive effects between tidal salinity and VPD on mangrove NEP, we came across potential independent influence of salinity on the same. SHAP analysis was also able to disentangle the impact of VPD from other abiotic drivers. Thus, we evaluated the threshold effect of VPD stress on NEP loss in subtropical mangroves and observed a range of 2.50–2.95 kPa. Above this range, VPD stress leveled off. The subtropical mangrove responses to VPD should be therefore considered in the dynamic global vegetation models to increase the accuracy in carbon cycle simulations in the future.

Responses of Coastal Wetlands to Rising Sea-Level Revisited: The Importance of Organic Production

A network of 15 Surface Elevation Tables (SETs) at North Inlet estuary, South Carolina, has been monitored on annual or monthly time scales beginning from 1990 to 1996 and continuing through 2022. Of 73 time series in control plots, 12 had elevation gains equal to or exceeding the local rate of sea-level rise (SLR, 0.34 cm/year). Rising marsh elevation in North Inlet is dominated by organic production and, we hypothesize, is proportional to net ecosystem production. The rate of elevation gain was 0.47 cm/year in plots experimentally fertilized for 10 years with N&P compared to nearby control plots that have gained 0.1 cm/year in 26 years. The excess gains and losses of elevation in fertilized plots were accounted for by changes in belowground biomass and turnover. This is supported by bioassay experiments in marsh organs where at age 2 the belowground biomass of fertilized S. alterniflora plants was increasing by 1,994 g m−2 year−1, which added a growth premium of 2.4 cm/year to elevation gain. This was contrasted with the net belowground growth of 746 g m−2 year−1 in controls, which can add 0.89 cm/year to elevation. Root biomass density was greater in the fertilized bioassay treatments than in controls, plateauing at about 1,374 g m−2 and 472 g m−2, respectively. Growth of belowground biomass was dominated by rhizomes, which grew to 3,648 g m−2 in the fertilized treatments after 3 years and 1,439 g m−2 in the control treatments after 5 years. Depositional wetlands are limited by an exogenous supply of mineral sediment, whereas marshes like North Inlet could be classified as autonomous because they depend on in situ organic production to maintain elevation. Autonomous wetlands are more vulnerable to SLR because their elevation gains are constrained ultimately by photosynthetic efficiency.

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.

Calcification and trophic responses of mesophotic reefs to carbonate chemistry variability

Mesophotic coral ecosystems (MCEs) are extensions of adjacent shallow water coral reefs. Accessibility to these ecosystems is challenging due to their depth limits (~ 30 – 150 m) and as a result, scientific knowledge of these reef systems is limited. It has been posited that the depth limits of MCEs diminish anthropogenic effects experienced by shallow reef systems. A lack of empirical measurements to date has made this hypothesis impossible to determine for mesophotic reef metabolism. The alkalinity anomaly technique was utilized to determine rates of net ecosystem calcification (NEC) and net ecosystem production (NEP) from 30, 40 and 60 m mesophotic reefs during a 15-month period. Seawater chemistry was determined to be chemically conducive for calcification (average aragonite saturation Ωaragonite of 3.58, average calcite saturation Ωcalcite of 5.44) with estimates of NEC indicating these reef systems were net accretive and within global average values for shallow coral reefs (&amp;lt; 30 m). The strongest periods of calcification occurred in late summer and were coupled with strong autotrophic signals. These episodes were followed by suppressed calcification and autotrophy and in the case of the 60 m reefs, a switch to heterotrophy. Whilst there was variability between the three reefs depths, the overall status of the mesophotic system was net autotrophic. This determination was the opposite of trophic status estimates previously described for adjacent shallow reefs. Whilst there were periods of net dissolution, the mesophotic reef system was net accretive (i.e., gross calcification &amp;gt; gross CaCO3 dissolution). The measured inorganic carbon chemistry and estimates of NEC and NEP represent the first such biogeochemical measurements for MCEs. The values established by this study demonstrate just how close these understudied ecosystems are in terms of the known boundary thresholds for low saturation state reefs. Making predictions on how these ecosystems will respond to future climatic conditions, will require greater sampling effort over long times scales to decouple the environmental controls exerted on such ecosystems.

Use of Remote Sensing and Biogeochemical Modeling to Simulate the Impact of Climatic and Anthropogenic Factors on Forest Carbon Fluxes

The current communication presents the application of a consolidated model combination strategy to analyze the medium-term carbon fluxes in two Mediterranean pine wood ecosystems. This strategy is based on the use of a NDVI-driven parametric model, Modified C-Fix, and of a biogeochemical model, BIOME-BGC, the outputs of which are combined taking into account the actual development phase of each ecosystem. The two pine ecosystems examined correspond to an old-growth forest and to a secondary succession after clearcuts, which differently respond to the same climatic condition during a ten-year period (2013–2022). Increasing dryness, in fact, exerts a fundamental role in controlling the gross primary and net ecosystem production of the mature stand, while the effect of forest regeneration is prevalent for the uprising of the same variables in the other stand. In particular, the simulated net carbon exchange fluctuates around 200 g C m−2 year−1 in the first stand and rises to over 600 g C m−2 year−1 in the second stand; correspondingly, the accumulation of new biomass is nearly undetectable in the former case while becomes notable in the latter. The study, therefore, supports the potential of the applied strategy for predicting the forest carbon balances consequent on diversified natural and human-induced factors.

Impact of meteorological variability on diurnal and seasonal net ecosystem productivity in a desert riparian forest ecosystem.

The desert riparian forests are susceptible to meteorological changes and contribute significantly to the net ecosystem productivity (NEP) variations of arid ecosystems. However, the responsive patterns of their NEP variations to the meteorological variabilities remain inadequately comprehended. To address this gap, we utilized seven years of eddy covariance flux measurements in a representative desert riparian forest to investigate the NEP variations and its response to changing meteorological factors across diverse temporal scales. The results revealed significant periodic variations in half-hourly NEP, with dominant cycles spanning from five hours to one year, with a principal oscillation period of one day. Key meteorological factors including global solar radiation (Rg), relative humidity (RH), air temperature (Ta), soil temperature (Ts), and vapor pressure deficit (VPD) exhibited synchronization with NEP on daily scales. This synchronization, coupled with the observed one-day periodic NEP variations, provides robust evidence supporting the existence of a circadian rhythm in the ecosystem carbon exchange of desert riparian forest regulated by meteorological conditions. Seasonal patterns were significant in the impact of Rg phase, Ta diurnal amplitude, and VPD diurnal amplitude on NEP diurnal amplitude and phase. The NEP diurnal amplitude significantly, directly, and positively affected daily NEP in both the dormant and growing seasons, whereas its phase yielded significant negative effects (P< 0.05). The averages, amplitudes, and phases of diurnal meteorological conditions controlled the daily NEP by regulating NEP diurnal amplitude and phase. These findings provide evidence that the variability in circadian rhythms, caused by the increase in diurnal Ta and VPD, significantly impact the daily NEP at an ecosystem scale. This study enriches our comprehension of the meteorological mechanisms governing diurnal and seasonal carbon uptake dynamics within desert riparian forests, providing fresh insights into the direct and indirect roles of climate change in shaping patterns of ecosystem carbon exchange.

A High-Resolution Simulation of Forest Ecosystem Carbon Budget Change with Complex Terrain

Forest ecosystems represent important carbon sinks within terrestrial ecosystems. Simulating carbon budgets in forest ecosystems located within complex terrains forms the foundation for understanding global carbon cycle dynamics. In this study, employing the FORCCHN model and utilizing mountain climate data as forcing parameters, the impact of the terrain factors of the Changbai Mountain Nature Reserve on carbon budget change in 1998–2017 was studied. The dynamics and distribution patterns of carbon fluxes at different slope aspects and elevations were discussed. Findings demonstrated that between 1998 and 2017, the per-unit area gross primary production (GPP), net primary production (NPP), and net ecosystem production (NEP) for the Changbai Mountain Reserve were 839.35, 462.03, and 192.72 gC m −2 a −1 , respectively. The carbon fluxes varied significantly with elevation: the GPP of the north, south, and west and the NPP of the east, south, and west decreased, and the NEP of the south and west increased. The total amount in GPP and NPP of the Changbai Mountain Nature Reserve fluctuated slightly year by year, but the carbon sequestration capacity decreased from year to year. The reserve had an average annual total GPP, NPP, and NEP of 1.62, 0.89, and 0.37 TgC a −1 , respectively. The north was the strongest carbon sink in the study area, contributing 35.98%, 35.88%, and 36.80% to the total amount of GPP, NPP, and NEP, respectively. This study emphasized the significance of precise mountain meteorological data to accurately quantify the carbon fluxes of mountain forest ecosystems.

Phosphorus limitation on CO2 fertilization effect in tropical forests informed by a coupled biogeochemical model

Tropical forests store more than half of the world's terrestrial carbon (C) pool and account for one-third of global net primary productivity (NPP). Many terrestrial biosphere models (TBMs) estimate increased productivity in tropical forests throughout the 21st century due to CO2 fertilization. However, phosphorus (P) limitations on vegetation photosynthesis and productivity could significantly reduce the CO2 fertilization effect. Here, we used a carbon-nitrogen-phosphorus coupled model (Dynamic Land Ecosystem Model; DLEM-CNP) with heterogeneous maximum carboxylation rates to examine how P limitation has affected C fluxes in tropical forests during 1860–2018. Our model results showed that the inclusion of the P processes enhanced model performance in simulating ecosystem productivity. We further compared the simulations from DLEM-CNP, DLEM-CN, and DLEM-C and the results showed that the inclusion of P processes reduced the CO2 fertilization effect on gross primary production (GPP) by 25% and 45%, and net ecosystem production (NEP) by 28% and 41%, respectively, relative to CN-only and C-only models. From the 1860s to the 2010s, the DLEM-CNP estimated that in tropical forests GPP increased by 17%, plant respiration (Ra) increased by 18%, ecosystem respiration (Rh) increased by 13%, NEP increased by 121% per unit area, respectively. Additionally, factorial experiments with DLEM-CNP showed that the enhanced NPP benefiting from the CO2 fertilization effect had been offset by 135% due to deforestation from the 1860s to the 2010s. Our study highlights the importance of P limitation on the C cycle and the weakened CO2 fertilization effect resulting from P limitation in tropical forests.

Response of stomatal conductance, transpiration, and photosynthesis to light and CO2 for rice leaves with different appearance days.

To investigate the dynamics of stomata, transpiration, and photosynthesis under varying light intensities and CO2 conditions during leaf development, the light response and CO2 response of stomatal conductance (g sw), transpiration rate (T r), and net photosynthetic rate (P n) were observed for rice leaves at different days after leaf emergence (DAE). The results showed that (1) as photosynthetically active radiation (PAR) increased, leaf g sw, T r, and P n initially increased rapidly and linearly, followed by a more gradual rise to maximum values, and then either stabilized or showed a declining trend. The maximum g sw, T r, and P n were smaller and occurred earlier for old leaves than for young leaves. The g sw, T r, and P n all exhibited a linear decreasing trend with increasing DAE, and the rate of decrease slowed down with the reduction in PAR; (2) as the CO2 concentration (C a) increased, g sw and T r decreased gradually to a stable minimum value, while P n increased linearly and slowly up to the maximum and then kept stable or decreased. The g sw, T r, and P n values initially kept high and then decreased with the increase of DAE. These results contribute to understanding the dynamics in g sw, T r, and P n during rice leaf growth and their response to varied light and CO2 concentration conditions and provide mechanistic support to estimate dynamic evapotranspiration and net ecosystem productivity at field-scale and a larger scale in paddy field ecosystems through the upscaling of leaf-level stomatal conductance, transpiration, and photosynthesis.

Multi-Temporal and Time-Lag Responses of Terrestrial Net Ecosystem Productivity to Extreme Climate from 1981 to 2019 in China

The escalating frequency and severity of extreme climate greatly impact the carbon dynamics of terrestrial ecosystems worldwide. To understand the multi-temporal response of net ecosystem productivity (NEP) to extreme climate, we investigated 11 temperature and precipitation extreme indices across different vegetation types in China. From 1981 to 2019, the results showed that NEP in China increased at a rate of 0.64 g·m−2·a−2. Extreme climate demonstrated a significant warming trend and a non-significant moistening trend; specifically, maximum daily minimum temperature (TNx) exhibited a significant increase at a rate of 0.34 °C/10 a, while maximum 5-day precipitation (Rx5day) showed an insignificant increase at a rate of 1.78 mm/10 a. NEP was significantly impacted by extreme temperature at the annual, seasonal, and monthly scales, but moderately impacted by extreme precipitation. Specifically, extreme temperature had the most significant effect on grassland, with minimal influence on cropland. In contrast, extreme precipitation had the most significant effect on forest, with minimal impact on cropland. Moreover, the lagged time for extreme precipitation was longer than that for extreme temperature. Extreme precipitation exhibited a corresponding lagged time of at least 2 months (p &lt; 0.01), while extreme temperature exhibited a lagged time of at least 1 month (p &lt; 0.01). The maximum lag time observed was 4 months (p &lt; 0.01). Our findings provide valuable insights into the multi-temporal response of NEP to extreme climate in China and inform sustainable development practices in the region.

Temperature response of soil respiration decreases with latitude and elevation in abandoned croplands

Soil respiration (Rs), a critical component of the global carbon cycle, is highly sensitive to warming. Agricultural soils, including abandoned croplands, are large sources of carbon dioxide to the atmosphere. However, the responses of Rs and its components to warming from abandoned croplands with no further management activities remain elusive at the national scale. Here, we report the warming responses of Rs, heterotrophic respiration (Rh), and autotrophic respiration (Ra) from China’s abandoned croplands spanning a large range in latitude (22.33–46.58°N) and elevation (2–3734 m) from three-year in situ warming experiments. We found that warming treatment (+1.6 °C) significantly stimulated Rs, Rh, and Ra by 30.4%, 37.2%, and 37.3%, respectively. The response of Rs to warming was higher in abandoned croplands (19.1% °C−1) than in other terrestrial ecosystems (5.4%–9.2% °C−1), attributing to greater increases in plant biomass and soil organic carbon induced by warming. Rs was more responsive to warming in low latitude or elevation regions with high plant biomass. Under the warming conditions, the apparent temperature sensitivity (Q10) of Rs increased in low latitude and elevation regions due to a decrease in soil carbon availability but decreased in high latitude and elevation regions due to an increase in carbon availability induced by warming. Despite the positive warming response of Rs, the net ecosystem productivity in abandoned croplands slightly increased by 18.7% attributing to increased plant productivity under warming. These findings demonstrate that Rs in abandoned croplands was more sensitive to warming in warmer regions than in colder regions, underscoring the importance of latitude- or elevation-induced variations in soil carbon availability in determining the response of Rs to warming and projecting cropland carbon-climate feedback.

Data assimilation of soil moisture and leaf area index effectively improves the simulation accuracy of water and carbon fluxes in coupled farmland hydrological model

Real time status of farmland hydrology and crop growth is essential for agricultural management. Data assimilation is a common method to improve the prediction accuracy of the model by fusing observed and simulated data. For the farmland hydrological processes, evapotranspiration (ET) and net ecosystem productivity (NEP) are widely concerned and strongly affected by crop growth and soil moisture. In this study, data assimilation for soil water content (SWC) and leaf area index (LAI) was combined with a coupled farmland hydrological model, and the potential of Kalman filter (KF) and ensemble Kalman filter (EnKF) methods to enhance model accuracy were explored. Furthermore, the impact of observation density of assimilated data and different assimilation strategies (single-factor or dual-factor assimilation) were analyzed. The findings revealed that both KF and EnKF methods effectively improved the simulation ability of SWC and LAI. When assimilation was performed daily, KF could obtain results comparable to EnKF with assimilation efficiency coefficient (Eff) exceeded 70%. However, with a reduced assimilation frequency for LAI to ten-day interval, EnKF exhibited superior applicability, demonstrating a 13% increase in Eff. The assimilation of soil moisture could positively affect the simulation results of ET with Eff close to 10%, and the assimilation of LAI could improve the simulation accuracy of NEP with Eff close to 15%. Overall, dual-factor assimilation proved to have a more substantial impact than single-factor, even reducing the frequency to ten-day interval. The sensitivity analysis showed that the coupling model could resist the influence of the preset observation error in the filter, with data assimilation effectively mitigating the influence of parameter errors in coupling model. These analyses supply an effective basis to deepen the understanding of improve real time simulation accuracy of farmland hydrological model with data assimilation.

Reducing nitrogen application by 20% under the condition of multiple cropping using green manure after wheat harvesting can mitigate carbon emission without sacrificing maize yield in arid areas

ContextAt the agro-ecosystem scale, a combination of green manure and chemical nitrogen fertilizer improves crop yield but also exacerbates soil CO2 emissions. However, it is unclear whether reducing nitrogen by reapplying green manure to fields can achieve high crop yields and improve carbon mitigation. ObjectiveThis study aims to investigate the effects and underlying mechanisms of carbon emissions in maize fields under green manure reapplication combined with a reduction in nitrogen. MethodsA field experiment comprising five treatments (green manure reapplication combined with traditional nitrogen application (N100), green manure reapplication combined with a reduction in nitrogen of 10% (N90), green manure reapplication combined with a reduction in nitrogen of 20% (N80), green manure reapplication combined with a reduction in nitrogen of 30% (N70), and green manure reapplication combined with a reduction in nitrogen of 40% (N60)) was conducted at an arid oasis region in northwestern China from 2020 to 2022. This study investigated the effects of reducing nitrogen application while reapplying green manure to the field on maize grain yield, soil respiration rate, and carbon emission efficiency (CEE) and analyzed the relationship between soil respiration rate and soil temperature (Ts), soil water content (SWC), and crop biomass accumulation (BA). ResultsThe N80 treatment significantly reduced soil carbon emissions (CE) but did not reduce maize grain yield, and it showed a significant increase in CEE of 7.7% compared with the N100 treatment. In addition, this system can ensure no reduction in net primary production (NPP), net ecosystem production (NEP), and carbon sequestration (CS) potential compared with N100 and significantly improves the NPP/CE value. Soil temperature and crop biomass significantly correlated with soil respiration, which explained 68.4–72.9% and 84.4–88.8% of the seasonal variation of soil respiration, respectively. However, there was no correlation between soil moisture and soil respiration. ConclusionTherefore, reducing nitrogen application by 20% while multiple cropping with green manure application after wheat was a suitable nitrogen fertilizer management measure for improving carbon mitigation in arid areas without sacrificing maize yield. ImplicationsThe results of this study provide valuable insights into long-term agricultural management strategies for achieving high agricultural production and environmental friendliness.

Spatial and temporal evolutions of terrestrial vegetation drought and the influence of atmospheric circulation factors across the Mainland China

Vegetation drought can reduce the net ecosystem productivity, resulting in disturbances to the sustainable development of humans and nature. In this study, Vegetation Health Index (VHI) was used to identify vegetation drought. The spatial and temporal evolution of vegetation drought was characterized using the Pixel-based Trend Identification Method (PTIM) in China from 1982 to 2020. Moreover, multiple cross-wavelet techniques were used for revealing the correlations between atmospheric circulation factors and their combinations with vegetation drought. The results indicates that: (1) there is a decreasing trend of vegetation drought in China during the study period, while it will show an increasing trend in the future; (2) the South China is prone to spring drought and summer drought, and the Sichuan Basin is prone to autumn drought and winter drought; (3) in spring, the most obvious trend of vegetation drought mitigation appears; (4) a combination of atmospheric circulation factors, North Pacific Index (NPI)-North Atlantic Oscillation (NAO)-Arctic Oscillation (AO), has the most significant impact on vegetation drought across China.

Synergistic Application of Multiple Machine Learning Algorithms and Hyperparameter Optimization Strategies for Net Ecosystem Productivity Prediction in Southeast Asia

The spatiotemporal patterns and shifts of net ecosystem productivity (NEP) play a pivotal role in ecological conservation and addressing climate change. For example, by quantifying the NEP information within ecosystems, we can achieve the protection and restoration of natural ecological balance. Monitoring the changes in NEP enables a more profound understanding and prediction of ecosystem alterations caused by global warming, thereby providing a scientific basis for formulating policies aimed at mitigating and adapting to climate change. The accurate prediction of NEP sheds light on the ecosystem’s response to climatic variations and aids in formulating targeted carbon sequestration policies. While traditional ecological process models provide a comprehensive approach to predicting NEP, they often require extensive experimental and empirical data, increasing research costs. In contrast, machine-learning models offer a cost-effective alternative for NEP prediction; however, the delicate balance in algorithm selection and hyperparameter tuning is frequently overlooked. In our quest for the optimal prediction model, we examined a combination of four mainstream machine-learning algorithms with four hyperparameter-optimization techniques. Our analysis identified that the backpropagation neural network combined with Bayesian optimization yielded the best performance, with an R2 of 0.68 and an MSE of 1.43. Additionally, deep-learning models showcased promising potential in NEP prediction. Selecting appropriate algorithms and executing precise hyperparameter-optimization strategies are crucial for enhancing the accuracy of NEP predictions. This approach not only improves model performance but also provides us with new tools for a deeper understanding of and response to ecosystem changes induced by climate change.

Ecosystem carbon exchange across China's coastal wetlands: Spatial patterns, mechanisms, and magnitudes

Coastal wetlands are of great importance for global carbon cycle and climate mitigation because of their strong carbon uptake capacity. However, the national-scale ecosystem carbon exchange dynamics in coastal wetlands, including magnitudes, spatial patterns, and controlling mechanisms, remains poorly understood. In this study, we utilized eddy covariance measurements from China's coastal wetlands to quantify carbon fluxes, assess their spatial patterns, and explore the controlling mechanisms. Integrating climate, vegetation, and soil factors, we constructed a cascaded relationship network to reveal the potential controlling mechanisms of spatial variations in carbon fluxes. The results revealed that gross primary production (GPP) and ecosystem respiration (ER) were 1405 ± 656 (mean ± sd) gC m−2 yr−1and 893 ± 465, respectively. Net ecosystem production (NEP) in coastal wetlands (567 ± 348 gC m−2 yr−1) exceeded China's terrestrial and marine ecosystems by 2–8 times, highlighting their significant carbon sink capacity. The carbon sink capacity in mangroves was significantly higher than salt marsh, exhibiting a twofold difference in NEP. Spatially, carbon fluxes displayed negative correlations with latitude, indicating the influence of climate features. Although tropical climate zone exhibited significantly higher carbon fluxes than temperate zone, no differences were observed between subtropics zone with others due to the distribution of mixed plants and largest area. The structural equation model (SEM) showed that the climate factors, including temperature, precipitation, and net radiation indirectly promoted GPP and ER through regulating the physiological process of mangrove and salt marsh, as well as soil carbon production and consumption. The cascaded relationship of climate-vegetation-soil showed in SEM explained 71–85 % of the spatial variations in GPP and ER, and ultimately accounted for 85 % of NEP. The carbon consumption efficiency (ER/GPP) in coastal vegetations was of 0.6, lower than that of global and China's terrestrial ecosystems, suggesting their strong efficiency in carbon fixation in coastal wetlands. Lastly, the scenario simulation results implied the importance of coastal vegetation restoration on enhancing blue carbon benefits.

Seasonal Dynamics of Soil Respiration and Its Autotrophic and Heterotrophic Components in Subtropical Camphor Forests

On a global scale, soil respiration (Rs), representing the CO2 flux between the soil surface and the atmosphere, ranks as the second-largest terrestrial carbon (C) flux. Understanding the dynamics between Rs and its autotrophic (Ra) and heterotrophic (Rh) components is necessary for accurately evaluating and predicting global C balance and net ecosystem production under environmental change. In this study, we conducted a two-year root exclusion experiment in subtropical China’s Camphor (Cinnamomum camphora (L.) Presl.) forests to assess seasonal changes in Ra and Rh and their relative contributions to Rs. Additionally, we examined the influence of environmental factors on the dynamics of Ra, Rh, and Rs. Our results showed that seasonal mean Rs values were 2.88 µmol m−2 s−1, with mean Ra and Rh of 1.21 and 1.67 µmol m−2 s−1, respectively, in the studied forests. On an annual basis, the annual values of mean Rs in the studied forests were 405 ± 219 g C m−2 year−1, with Rh and Ra accounting for 240 ± 120 and 164 ± 102 g C m−2 year−1, respectively. The seasonal mean ratio of Rh to Rs (Rh/Rs) was 58%, varying from 45 to 81%. Seasonal changes in Rs and Rh were strongly correlated with soil temperature but not soil water content. Both Rh and Rs increased exponentially with the average soil temperature measured in the topsoil layer (about 5 cm), with Q10 values of 2.02 and 1.73 for Rh and Rs, respectively. Our results suggest that the composition and activity of soil microbes and fauna play a primary role in releasing carbon flux from soil to the atmosphere in the studied forest ecosystems.

Quantitative Assessment of Factors Influencing the Spatiotemporal Variation in Carbon Dioxide Fluxes Simulated by Multi-Source Remote Sensing Data in Tropical Vegetation

Vegetation plays a vital role in the global carbon cycle, a function of particular significance in regulating carbon dioxide fluxes within tropical ecosystems. Therefore, it is crucial to enhance the precision of carbon dioxide flux estimates for tropical vegetation and to explore the determinants influencing carbon sequestration. In this study, Landsat series images and Sentinel-2 Multispectral Instrument satellite data were used to invert vegetation biophysical parameters, thereby improving the timeliness and resolution of state variables from the boreal ecosystem productivity simulator (BEPS). The BEPS model at a 30 m resolution was developed to accurately capture tropical vegetation carbon dioxide fluxes across Hainan Island (HN) over the preceding two decades. The impacts of climate variations and anthropogenic activities on the carbon dioxide fluxes of tropical vegetation were further quantified using quantile regression models and a land-use transfer matrix. Results indicate significant increases in both net primary productivity (NPP) and net ecosystem productivity (NEP) in HN during the period 2000–2020, by 5.81 and 4.29 g C/m2 year, respectively. Spatial trends in vegetation carbon dioxide fluxes exhibited a consistent decline from inland regions to coastal zones. Anthropogenic activities were the dominant factor in the reduced stability of coastal NPP, while the post-2005 vegetation restoration promoted the southward expansion of high NPP (&gt;1200 g C/m2) in the central part of HN. NPP in this tropical island was more sensitive to temperature than to precipitation, with a 1 °C temperature increase resulting in 4.1 g C/m2 reduction in dry-season NPP compared to wet-season NPP. Upgrades of cropland quality and grassland restoration have improved NPP yields, and land use transfers have resulted in a 0.301 Tg C net increase in NPP. This study provides new insight into the improvement of the carbon dioxide flux model at a finer scale for tropical vegetation and highlights ecological construction as an adaptation strategy to enhance the carbon sinks of tropical vegetation under negative climate change conditions.