Net ecosystem productivity (NEP) is a key indicator of the carbon sink function of forests, reflecting the combined influence of forest structural characteristics and climatic factors. However, the relative contributions of climate variables to carbon sink formation remain uncertain. This study focuses on forest ecosystems in Xinjiang, China, and develops a statistical regression model relating NEP to forest age over the period 2000-2020. Through residual analysis, the dominant influence of forest age on carbon sinks was effectively isolated. A linear regression model was then applied to quantify the relative contribution of climatic factors to the residual NEP, enabling the decoupling of different driving factors in this region. The results indicate that: (1) Forest age contributes 45-49% to NEP in Xinjiang, confirming its dominant role. (2) The contribution of climatic factors varies with vegetation type, mean annual temperature (MAT) explains a larger proportion of variance (R²= 0.401) in coniferous forests than mean annual precipitation (MAP), whereas broadleaf forests show the opposite pattern, with MAP explaining more variance (R²= 0.399) than MAT. Overall, climatic factors account for 24.52% of the annual total NEP in Xinjiang forests. (3) Decoupling analysis reveals that neglecting forest age may lead to an overestimation of climatic contributions to NEP by approximately tenfold. This approach provides a reliable framework for accurately quantifying the independent effects of different drivers. Considering that younger forests currently constitute a substantial portion of Xinjiang’s forests, they are expected to exhibit a stronger carbon sequestration capacity under current climatic conditions. These findings provide a scientific basis for the precise assessment of forest carbon sink functions in arid regions.

Understanding temporal variation in population productivity is critical for effective assessment and management of pelagic fish stocks under a changing climate. In this study, we applied a stochastic surplus production model in continuous time (SPiCT) with time-varying parameters to evaluate the productivity dynamics of yellowfin tuna (Thunnus albacares) in the western and central Pacific Ocean and to examine the influence of environmental variability on productivity. Multiple time-varying parameterization scenarios were explored to characterize uncertainties in productivity estimates and associated biological reference points. Generalized additive models were subsequently used to quantify the relationships between environmental variables and time-varying productivity. Results indicate that productivity estimates exhibit consistent temporal patterns across alternative modeling scenarios, while their magnitude and associated uncertainty are sensitive to model structure. Among the environmental factors examined, the Pacific Decadal Oscillation (PDO) and mixed layer thickness (MLT) showed consistent and statistically significant associations with maximum net productivity. Higher PDO values and greater MLT were both positively associated with population productivity. Overall, the results highlight the importance of environmental variability in shaping time-varying productivity of yellowfin tuna and demonstrate the feasibility of incorporating key environmental indicators into a state-space model. This approach provides a complementary framework for interpreting stock dynamics and supports the development of ecosystem-based fisheries management strategies in the western and central Pacific.

Background/Objectives: This study examined the association between dietary acid load (DAL) and metabolic syndrome (MetS)-related parameters in Korean adults undergoing eating habit modification. Methods: Forty-eight Korean adults (≥19 years) with at least one MetS risk factor were recruited via public advertisement. Anthropometric and biochemical parameters, Nutrition Quotient (NQ) scores, and nutrient intake were assessed. The DAL was calculated and expressed as the potential renal acid load (PRAL) and the net endogenous acid production (NEAP). Results: Forty participants completed the 8-week intervention. Overall improvements were observed in total and domain-specific NQ scores, along with improvements in body composition, blood pressure, and glycemic parameters. Among all participants, the mean DAL scores did not change significantly after FDR correction, although the NEAP showed a modest non-significant decrease. Baseline PRAL and NEAP values did not differ between participants with and without MetS risk improvement. At weeks 4 and 8, DAL indices tended to decrease in the improved group and increase in the non-improved group, with a significant between-group difference observed only for the 8-week change in NEAP after FDR correction. While no significant associations were detected at baseline after FDR adjustment, cross-sectional associations between DAL indices and adiposity-related parameters were observed at week 8, particularly when DAL was expressed as NEAP. However, change-to-change analyses did not remain significant after FDR correction. Conclusions: In this exploratory study, DAL levels, especially NEAP, were associated with anthropometric and metabolic status at week 8; however, the absence of significant change-to-change correlations limits causal interpretation. Larger randomized controlled trials are needed to determine whether modification of DAL independently contributes to metabolic improvement (Trial registration number: KCT0011528).

Fluctuating irradiance forces leaves to balance energy conversion with protection against reactive oxygen species (ROS) produced when light harvesting exceeds metabolic demand. In chloroplasts, this balance is strongly governed by the thylakoid proton motive force (pmf, ΔμH + ) and by its partitioning between a pH gradient (ΔpH) and an electric field (Δψ). A proton-circuit framework in which proton deposition by linear and cyclic electron flow builds pmf, chloroplast ATP synthase spends pmf as ATP with an effective proton conductivity g(H + ), and counter-ion fluxes reshape ΔpH:Δψ on seconds-to-minutes timescales. Δψ-relieving anion pathways (VCCN1, CLCe) promote rapid ΔpH expression during light increases, enabling timely engagement of PsbS-dependent qE and ΔpH-dependent photosynthetic control at cytochrome b 6 f, whereas the K + /H + antiporter KEA3 accelerates ΔpH relaxation after transitions to lower light to speed recovery. These dynamics link to stromal metabolism by describing how stromal alkalinization and Mg² + /thioredoxin regulation activate Calvin–Benson–Bassham enzymes, how CEF pathways (PGR5/PGRL1 and NDH) increase pmf without net NADPH production, and how phosphate recycling and triose-phosphate utilization constrain ATP synthase flux. This review examines how thylakoid architecture could generate spatial heterogeneity in proton dynamics and highlight what remains inferred versus directly measured. Finally, we present an operating-regime map and a minimal diagnostic toolkit—multiwavelength ECS (pmf, ΔpH/Δψ, g(H + )) combined with NPQ, P700, and gas exchange—to translate mechanism into testable predictions and improve cross-study comparability. The unifying design principle is timing: rapid ΔpH formation to protect PSI during upshifts, followed by timely relaxation to minimize unnecessary quenching and sustain CO 2 assimilation.

Effects of varying the human-edible fraction of concentrates offered on dairy cow performance and nutrient utilization.

Nitrous oxide (N2O) can be both produced and reduced to dinitrogen (N2) during microbial denitrification, with the balance between these steps controlling the net flux of this potent climate gas. Here, we first used a meta-analysis of published studies to predict how warming may regulate N2O and N2 production in soils and sediments. However, as most of these former studies used nitrate at far higher than ambient concentrations, the applicability of these predictions to ambient conditions may be limited. In addition, few studies separated denitrification from other microbial pathways contributing to N2O and N2 production. To address these limitations, we used 15N-isotope labelling experiments in freshwater sediments to test how temperature sensitivity varies with limited (10 μM) and replete (100 μM) nitrate. Temperature affected N2O and N2 production only when nitrate was replete, where N2 production increased but net N2O production declined with warming, leading to a lower N2O:N2 production ratio at higher temperatures. These results show that substrate availability can outweigh temperature in controlling the balance between N2O and N2 production, indicating that temperature-based predictions of N2O emissions alone may overestimate the effects of climate warming.

Synergistic importance of memory and spatial neighbourhood effects in modelling net ecosystem productivity

Methylmercury hotspots in hybrid constructed wetlands: Mechanisms and controls.

Driving mechanisms of vegetation carbon sink distribution based on explainable machine learning and evaluation of carbon sequestration in open-pit mines.

Abstract Hydroclimatic extremes are critical regulators of terrestrial carbon sink dynamics, yet their representation in terrestrial biosphere models remains highly uncertain. Here, we assessed uncertainties in TRENDY v12 model simulations of carbon sink responses to hydroclimatic extremes during 1980–2022 by systematically comparing model outputs across regions, event types, and biomes. Site-level evaluations reveal that the multi-model ensemble mean correctly captures the sign of net biome productivity (NBP) anomalies at approximately 60% of stations; however, while the multi-model ensemble mean generally replicates NBP variations during dry events, its performance degrades during wet events. Spatially, most regions act as anomalous carbon sinks during wet extremes, a pattern that largely reverses during dry events. Despite these general trends, substantial inter-model heterogeneity persists. Inter-model uncertainties are more pronounced under dry events between 30°S and 30°N, while other latitudes exhibit comparable or even greater spreads under wet events. Specifically, inter-model spread is more sensitive to wet anomalies in arid and semi-arid regions, but to drought-induced stress in semi-humid and humid regions. Across biomes, uncertainties are greater for grasslands, savannas, and shrublands during wet events, shifting to forests and croplands during dry events. Finally, we demonstrate that the divergent NBP responses primarily originate from uncertainties in simulating gross primary production (GPP). Our findings highlight the persistent challenges TRENDY models face in capturing ecosystem responses to hydroclimatic extremes, underscoring the urgent need to improve simulation fidelity in a rapidly changing climate.

ABSTRACT Net ecosystem productivity (NEP) of terrestrial ecosystems is a key indicator for measuring carbon sink capacity, and its high-precision simulation is of great significance for achieving the ‘dual carbon’ strategic goals. In view of the limitations of traditional methods in characterizing the temporal nonlinearity of NEP, this paper proposes a prediction framework that integrates deep temporal modelling with ensemble learning. First, a long short-term memory network (LSTM) is employed to extract key time-dependent features from multi-source driving variables; these features are then introduced as auxiliary variables into an XGBoost model to improve prediction accuracy and stability. Based on daily observations from nine eddy-covariance flux sites in China (2003–2010), we constructed a multi-source input feature set and compared the proposed framework with mainstream models such as Random Forest (RF), Support Vector Machine (SVM) and ensemble learning. The results show that extracting key temporal features with LSTM and feeding them into XGBoost significantly enhances the accuracy and stability of carbon-flux prediction: the mean R 2 increases by approximately 2%, the error is markedly reduced, and the model’s temporal sensitivity and ecological adaptability are improved. In addition, Shapley Additive Explanations (SHAP) were employed to interpret model predictions and quantify the contributions of key environmental drivers to daily NEP dynamics. This study integrates deep time-series features with ensemble-learning methods for NEP estimation, achieving a dual improvement in predictive accuracy and ecological interpretability and providing a useful technical tool for regional carbon-flux monitoring and carbon-neutrality planning.

Mitigating nitrous oxide (N2O) emissions from municipal wastewater treatment plants (WWTPs) requires a clear understanding of their in situ production. This study employed microelectrodes to perform in situ profiling of N2O dynamics within sludge aggregates across anaerobic, anoxic, and aerobic tanks of a full-scale WWTP. The results showed that N2O production was heterogeneous: highest in the anoxic tank, lower in the aerobic tank, and minimal in the anaerobic tank. Specifically, the inlet section of the anoxic tank exhibited the maximum net production (1380.99 µmol·cm−2·h−1), 1.4 times that of the front aerobic section (986.09 µmol·cm−2·h−1). Denitrification (anoxic zone) and ammonia oxidation (aerobic zone) were identified as the two dominant pathways. Optimizing substrate availability, dissolved oxygen levels, and nitrite concentration can effectively reduce N2O production potential. This study provides novel insights into the source identification of N2O in full-scale WWTPs, forming an important basis for the sustainable optimization and greenhouse gas mitigation of wastewater treatment.

Abstract From 1758 to 1768 the Tableau Économique of François Quesnay took successively three forms, the Zig-zag, the Précis, and finally the Formule. This article explains the reasons for the two form changes, from the Zig-zag to the Précis and from the Précis to the Formule. From Philosophie rurale (1763), Quesnay improves the tool that the Tableau already was so that it can account for France's gradual transition from a current net production rate of 30 percent to a future rate of 100 percent. The Zig-zag could not account for the progress of agriculture. The Précis, which is a compacted Zig-zag, remains too rigid. It is a transitional form toward the modified Précis and then toward the Formule. The Formule is a very efficient and flexible tool. The Formule affirms a stock-flow approach. It facilitates the start of the exchanges between the three classes of society. It gives an account simultaneously of the monetary payments and of the real deliveries between the different classes. From an economic point of view, the Formule appears superior to the Zig-zag and the Précis. It constitutes for that reason the definitive form of the Tableau.

Abstract Changes in the physical and biogeochemical conditions of the ocean over time can affect marine ecosystems. In this study, we use biogeochemical observational data for the past 25 years (1999–2023) to investigate ocean acidification and changes in biological production at site K2 (47˚ N, 160˚ E) in the western subarctic region of the North Pacific Ocean. During this period, satellite-derived sea surface temperatures increased at a rate of 0.056 °C yr –1 , while the surface mixed-layer salinity decreased by 0.004 yr −1 . As a result of the oceanic uptake of anthropogenic CO 2 from the atmosphere, the deseasonalized annual mean surface mixed-layer pH and saturation states of calcium carbonate minerals of calcite and aragonite decreased at rates of 0.0013 ± 0.0004, 0.007 ± 0.003, and 0.004 ± 0.002 yr −1 , respectively. These rates are consistent with those calculated for winter. Under these acidification conditions, no significant trends were observed in either the annual mean or winter concentrations of nutrients (phosphate, nitrate, and silicate), or in total alkalinity in the surface mixed layer. However, the decadal trends in nutrient concentrations show a significant increase in May and decrease in July. Net community production (NCP), which is an index of biological production, was estimated from differences in nutrient concentrations between winter and May or July. This analysis revealed significant decreasing trends in NCP from winter to May, followed by increasing trends from winter to July. The stoichiometric molar ratio of Si associated with the July NCP increase (P:N:Si = 1:15:55) is higher than the previously reported ratio (1:16:40). A significant decreasing trend in satellite-derived photosynthetically active radiation (PAR) was observed in May (0.20 ± 0.08 yr −1 ), which may be linked to reduced biological production during that month. This decrease may be offset by increased production in summer that is likely due to a shift in the timing of the diatom bloom. These findings highlight the effects of long-term changes of potential drivers of both atmospheric and deep oceanic origin on oceanic biological production.

Abstract Egyptian agriculture faces significant risks from climate change due to limited water resources, as rising irrigation demands strain fixed or declining water supplies. For sustainable, long-term agriculture, it is essential to improve water-use efficiency in converting water into crop yields and economic benefits, especially since farming consumes the most water. This study examined how climate change affects irrigation water efficiency in Rashid City, Beheira Governorate. The research employed a descriptive-quantitative method, collecting primary data through a structured survey of 120 farmers during the summer of 2024. The focus was on four main crops: cotton, rice, maize, and wheat, covering yields, net irrigation water requirements, irrigation practices, production costs, and crop prices. Baseline conditions were established using secondary climate and agricultural data from 2006–2020, yielding water productivity values of 0.25-1.08 kg/m³. Projections indicate that, by 2050, different crops will respond uniquely to a warming climate. Under warming scenarios of +2°C to +4°C, cotton is expected to increase water productivity by 8–20%, leading to a 2.7–38% rise in net income per unit of water used. Conversely, rice shows an opposite trend: at +4°C, water productivity decreases by 21.95%, but net income per water unit increases by 154%. For maize, water productivity is projected to decline by 29.1% with a 3.5°C temperature increase, along with an 80% reduction in economic efficiency. Wheat faces the greatest decline, with water productivity dropping by 14.55% at +2°C and 21.82% at +4°C increases, while economic efficiency decreases by 92% and 114%, respectively. These findings highlight the need to develop climate-resilient varieties and improve irrigation management to sustain the productivity and economic value of limited water resources.

Abstract. Assessing ecosystem functioning is crucial for managing and conserving ecosystems and their services. Numerous ways to evaluate ecosystem functioning have been developed, using species traits, such as Plant Functional Types (PFTs), flux measurements with the Eddy Covariance (EC) technique, and remote sensing techniques. We propose that the spatial heterogeneity in ecosystem functioning at a regional scale can be assessed and monitored using satellite-derived Ecosystem Functional Types (EFTs): groups of ecosystems or patches of the land surface that share similar dynamics of matter and energy exchanges. We hypothesize that, as observed for PFTs, different EFTs should have distinct patterns and magnitudes of Net Ecosystem Exchange (NEE) of carbon dioxide measured using the EC technique. We derived EFTs from 2001–2014 time-series of satellite images of the Enhanced Vegetation Index (EVI) and compared them with NEE measurements (derived from in situ field observations using the EC technique) across 50 European sites. Our results show that distinct EFTs classes display significantly different dynamics and magnitudes of NEE and that EFTs perform marginally better than PFTs in explaining NEE regional patterns. Land-cover maps based on PFTs are difficult to update on an annual basis and are not sensitive to changes in ecosystem performance (e.g., droughts or pests) that do involve short-term changes in PFT composition. In contrast, satellite-derived EFTs are sensitive to short-term changes in ecosystem performance. Satellite-derived EFTs are an ecosystem functional classification built from satellite observations that allow the identification of homogeneous land patches based on ecosystem functions, e.g., ecosystem net productivity measured on the ground as NEE. Satellite-derived EFTs can be recalculated annually, providing a straightforward way to assess and monitor interannual changes in ecosystem functioning and functional diversity.

Abstract. Ground-level ozone (O3) pollution has recently become of increasing concern in China. Studies have shown that conventional models often fail to predict accurately the net O3 production rate (P(O3)net) due to the absence of certain mechanisms, particularly the kinetics from missing reactive volatile organic compounds (VOCs) species, and hence affects the reliability of evaluation for O3 formation sensitivity (OFS). Therefore, we conducted a field observation of P(O3)net and OFS using a P(O3)net (NPOPR) detection system based on a dual-channel reaction chamber technique at the Guangdong Atmospheric Supersite of China in Heshan, Pearl River Delta (PRD) in autumn of 2023. The in-situ monitoring data were then compared with results from a zero-dimensional model incorporating the Master Chemical Mechanism (MCM v3.3.1). We tested the model performance by incorporating parameterization for 4 processes including HO2 uptake by ambient aerosols, dry deposition, N2O5 uptake, and ClNO2 photolysis, and found that the discrepancies between the modelled P(O3)net (P(O3)net_Mod) and measured data (P(O3)net_Mea) did not change evidently, the maximum daily P(O3)net differed by ∼ 44.8 %. Meanwhile, we found that the agreement of OFS assessment results between the direct measurements and the modelling study was lower in the P(O3)net rising phase (08:00–09:00 LT, 63.6 %) than in the P(O3)net stable phase (10:00–12:00 LT, 72.7 %) and P(O3)net declining phase (13:00–17:00 LT, 72.7 %). The results in this study reflected that unmeasured oxygenated VOCs (OVOCs) were the most effective compensating factor for the discrepancies between observed and computed P(O3)net and OFS, hinting clearly at the importance of quantitative understanding the total reactivity of VOCs in O3 chemistry.

The impact of photochemical loss of VOCs from anthropogenic and biogenic emissions on ozone formation mechanisms.

Abstract Tropical forests play a vital role in the global carbon cycle and land–atmosphere interactions. Estimating tropical forest carbon–water dynamics is challenging due to observational and modeling uncertainties. This study leverages the “Trends and drivers of the regional scale terrestrial sources and sinks of carbon dioxide” (TRENDY) project models and satellite observations to assess changes (2003–2021) in vegetation carbon, gross primary production (GPP), evapotranspiration (ET), and net biosphere production (NBP) in the Amazon and Congo. Atmospheric CO 2 , climate variability, and land use and land cover changes constrain these variables between 1700 and 2021 with the overall increasing trends of carbon stock and fluxes. The models overestimate vegetation carbon and GPP, while ET and NBP are consistent with observations. Fire‐activated models predict lower values for vegetation carbon and GPP, ET, and NBP, aligning more closely with observations. The higher ET from fire‐activated models may result from enhanced soil evaporation due to increased canopy openings. Fire‐inactivated models could well estimate the magnitudes of NBP. The high vegetation carbon in nitrogen‐enabled models points to simulation uncertainties and imbalance in model numbers regarding the nitrogen cycle. Although the nitrogen cycle enhances water use efficiency in both the Amazon and Congo, the models show a higher sensitivity to the nitrogen cycle in the Congo. This study highlights the challenges in accurately representing tropical biogeochemical cycles and the values of satellite products in model evaluations, underscoring the need for standard modeling protocols that address biogeochemical components (e.g., nutrient cycles) to better resolve process‐based representations.

Given the co-limitation of water and nitrogen (N) acquisition under drought, it is essential to mechanistically explore how plants respond to these limitations individually and in combination. To understand the general effect that N availability plays in water use efficiency across Sorghum bicolor ssp. bicolor, which has diverse mechanisms conferring tolerance to water limitations, we grew six genotypes ranging in drought tolerance under greenhouse conditions under three treatments: full water/high N, limited water/high N, and limited water/low N availability. We measured a suite of above- and below-ground plant traits to understand growth allocation and physiological responses. Under high N but limited water, two genotypes increased allocation to fine root production and reduced allocation to coarse root production, which could limit deep water foraging under field conditions. In contrast, limited N and water availability together stimulated coarse root production in those genotypes. High N with limited water did not increase net photosynthesis or total plant biomass production compared to limited N and water availability in any genotype. These results suggest that adding N to S. bicolor ssp. bicolor is unlikely to be an effective strategy for rescuing growth or yield under drought conditions. Moreover, limiting coarse root growth may have detrimental effects under field conditions. It is crucial for future studies to follow up on the effects of N and water availability on the grain yield of S. bicolor ssp. bicolor under water-limited field conditions to better understand the potentially negative effects of high nitrogen on water foraging under drought.