Biogeography and impact of nitrous oxide reducers in rivers across a broad environmental gradient on emission rates.

Microbial communities that reduce nitrous oxide (N2O) are divided into two clades, nosZI and nosZII. These clades significantly differ in their ecological niches and their implications for N2O emissions in terrestrial environments. However, our understanding of N2O reducers in aquatic systems is currently limited. This study investigated the relative abundance and diversity of nosZI- and nosZII-type N2O reducers in rivers and their impact on N2O emissions. Our findings revealed that stream sediments possess a high capacity for N2O reduction, surpassing N2O production under high N2O/NO3- ratio conditions. This study, along with others in freshwater systems, demonstrated that nosZI marginally dominates more often in rivers. While microbes containing either nosZI and nosZII were crucial in reducing N2O emissions, the net contribution of nosZII-containing microbes was more significant. This can be attributed to the nir gene co-occurring more frequently with the nosZI gene than with the nosZII gene. The diversity within each clade also played a role, with nosZII species being more likely to function as N2O sinks in streams with higher N2O concentrations. Overall, our findings provide a foundation for a better understanding of the biogeography of stream N2O reducers and their effects on N2O emissions.

Full-day profiling of a beam attenuation coefficient using a single-photon underwater lidar with a large dynamic measurement range.

A compact underwater lidar system, utilizing a single-photon detection technology, is proposed to effectively eliminate interference from the sea-air interface and enhance the accuracy of water optical property measurements. However, the high sensitivity of the single-photon detector poses challenges, including daytime operation difficulties due to strong solar radiation noise and detector saturation from near-field lidar signals. To address these issues, the laser and optical receiver of the lidar are optimized to suppress solar radiation noise, and a dual-telescope structure is introduced to improve the dynamic measurement range beyond 70 dB. In addition, a Monte Carlo simulation establishes the relationship between beam attenuation coefficients (c) and lidar attenuation coefficients (Klidar), enabling the retrieval of c profiles from Klidar. A field experiment conducted in the South China Sea, spanning from inshore to offshore waters, demonstrates the effectiveness of the lidar. The results highlight its potential applications, including the assessment of subsurface particulate organic carbon (POC).

Hydrophilic Fraction of Dissolved Organic Matter Largely Facilitated Microplastics Photoaging: Insights from Redox Properties and Reactive Oxygen Species.

Dissolved organic matter (DOM) exists widely in natural water, which inevitably influences microplastic (MP) photoaging. Nevertheless, the impacts of DOM fractions with diverse molecular structures on MP photoaging remain to be elucidated. This study explored the photoaging mechanisms of polylactic acid (PLA)-MPs and polystyrene (PS)-MPs in the presence of DOM and its subfractions (hydrophobic acid (HPOA), hydrophobic neutral (HPON), and hydrophilic (HPI)). Across DOM fractions, HPI exhibited the highest electron accepting capacity (23 µmol e- (mg C)-1) due to its abundant tannin-like species (36.8%) with carboxylic groups, which facilitated more reactive oxygen species generation (particularly hydroxyl radical), leading to the strongest photoaging rate of two MPs by HPI. However, the sequences of bond cleavage during photoaging of each MPs were not clearly shifted as revealed by two-dimensional infrared correlation spectra. Inconspicuous effects on the extent of PS- and PLA-MPs photoaging were observed for HPOA and HPON, respectively. This was mainly ascribed to the occurrence of inhibitory mechanisms (e.g., light-shielding and quenching effect) counteracting the reactive oxygen species-promoting effects. The findings identified the HPI fraction of DOM for promoting PS- and PLA-MPs photoaging rate and first constructed a link among DOM molecular structures, redox properties, and effects on MP photoaging.

Cooling Effect of Green Spaces on Urban Heat Island in a Chinese Megacity: Increasing Coverage versus Optimizing Spatial Distribution.

Enhancing the cooling effectiveness of green spaces (GSs) is crucial for improving urban thermal environments in the context of global warming. Increasing GS coverage and optimizing its spatial distribution individually proved to be effective urban cooling measures. However, their comparative cooling effectiveness and potential interaction remain unclear. Here, using the moving window approach and random forest algorithm, we established a robust model (R2 = 0.89 ± 0.01) to explore the relationship between GS and land surface temperature (LST) in the Chinese megacity of Guangzhou. Subsequently, the response of LST to varying GS coverage and its spatial distribution was simulated, both individually and in combination. The results indicate that GS with higher coverage and more equitable spatial distribution is conducive to urban heat mitigation. Increasing GS coverage was found to lower the city's average LST by up to 4.73 °C, while optimizing GS spatial distribution led to a decrease of 1.06 °C. Meanwhile, a synergistic cooling effect was observed when combining both measures, resulting in additional cooling benefits (0.034-0.341 °C). These findings provide valuable insights into the cooling potential of GS and crucial guidance for urban green planning aimed at heat mitigation in cities.

Integrated simulation-surrogate-optimization modeling framework for multiple tradeoffs among socioeconomic and ecological targets in reservoir operations.

Integrated reservoir water quantity and quality management is significant for water supply security and river ecosystem health. However, the spatiotemporal heterogeneity of water quality and the nonuniform response of multiple indicators to operation changes make it difficult to determine optimal operation schedules. This study proposes a coupled simulation-surrogate-optimization modeling approach for compromising multiple water quantity and quality targets in reservoir operations. The Environmental Fluid Dynamics Code (EFDC) was used to simulate spatiotemporal reservoir water quality dynamics. Subsequently, an ecological damage assessment method was established, accounting for the spatiotemporal heterogeneity of multiple water quality indicators and the nonlinear relationship between the water quality deterioration and ecological damage. To quickly simulate the ecological damage, a surrogate model was developed using the nonlinear autoregressive network with exogenous inputs (NARX). Finally, the surrogate model was integrated into a reservoir operation optimization model for compromising socioeconomic and ecological targets. By applying the methods to China's Danjiangkou Reservoir as a case, it was shown that more even nutrient distribution in the reservoir increased water eutrophication area while reducing concentration peak values, which helped decrease the ecological damage. Operation changes could lead to opposite effects on in-reservoir and downstream ecological targets, increasing operation optimization complexity. Both ecological and socioeconomic benefits significantly increased (by 9.4%-16.4%) during dry years under the optimized operation scheme, implying that synergies were obtained. This study offers implications and a management tool for reservoir operations to address the multiple tradeoffs among socioeconomic and ecological benefits.

Environmental DNA and remote sensing datasets reveal the spatial distribution of aquatic insects in a disturbed subtropical river system.

Biodiversity datasets with high spatial resolution are critical prerequisites for river protection and management decision-making. However, traditional morphological biomonitoring is inefficient and only provides several site estimates, and there is an urgent need for new approaches to predict biodiversity on fine spatial scales throughout the entire river systems. Here, we combined the environmental DNA (eDNA) and remote sensing (RS) technologies to develop a novel approach for predicting the spatial distribution of aquatic insects with high spatial resolution in a disturbed subtropical Dongjiang River system of southeast China. First, we screened thirteen RS-based vegetation indices that significantly correlated with the eDNA-inferred richness of aquatic insects. In particular, the green normalized difference vegetation index (GNDVI) and normalized difference red-edge2 (NDRE2) were closely related to eDNA-inferred richness. Second, using the gradient boosting decision tree, our data showed that the spatial pattern of eDNA-inferred richness could achieve a high spatial resolution to 500 m reach and accurate prediction of more than 80%, and the prediction efficiency of the headwater streams (Strahler stream order = 1) was slightly higher than the downstream (Strahler stream order >1). Third, using the random forest algorithm, the spatial distribution of aquatic insects could reach a prediction rate of over 70% for the presence or absence of specific genera. Overall, this study provides a new approach to achieving high spatial resolution prediction of the distribution of aquatic insects, which supports decision-making on river diversity protection under climate changes and human impacts.

Regional mangrove vegetation carbon stocks predicted integrating UAV-LiDAR and satellite data.

Using satellite RS data predicting mangrove vegetation carbon stock (MVC) is the popular and efficient approach at a large scale to protect mangroves and promote carbon trading. Satellite data have performed poorly in predicting MVC due to saturation issues. UAV-LiDAR data overcomes these limitations by providing detailed structural vegetation information. However, how to cross-scale integration of UAV-LiDAR and satellite RS data and the selection of features and machine learning methods hampered the practitioner in making a lightweight but efficient model to predict the MVC. Our study integrated UAV-LiDAR, Sentinel-1, and Sentinel-2 to extract spectral, structural, and textural features at the regional scale. We estimated the influences of different combinations between three vegetation features and machine learning methods (Support Vector Machine (SVM), Random Forest (RF), Gradient Boosting Regression Tree (GBDT), and Extreme Gradient Regression Tree (XGBOOST)) on the results of MVC prediction, and constructed a framework for estimating mangrove vegetation aboveground (ACG) and belowground (BCG) carbon storage in Zhanjiang, the largest mangrove area of China. Our research shows: 1) Compared to using satellite remote sensing (RS), integrating UAV and satellite RS data and fusing multiple vegetation features significantly improved the accuracy of mangrove vegetation carbon stock (MVC) predictions. 2) Structural features, particularly canopy height retrieved from UAV and satellite RS, are essential indicators for predicting MVC. Combined with spectral and structural features, regional MVC was precisely predicted. 3)Although the influence of different machine learning methods on MVC prediction was not significant, XGBOOST demonstrated relatively high precision. We recommend that mangrove practitioners integrate UAV and satellite RS data to predict MVC at a regional scale. Importantly, governments should prioritize the application of UAV-LiDAR in forestry monitoring and establish a long-term mangrove monitoring database to aid in estimating blue carbon resources and promoting blue carbon trading.

Prostaglandin E2 inhibits the differentiation of T regulatory cells by Peroxisome Proliferator-Activated Receptor-Gamma during allergic rhinitis.

BACKGROUND: Allergic rhinitis (AR) represents a significant global health concern that can give rise to numerous diseases and result in labor productivity. T regulatory (Treg) cells are pivotal players in the pathogenesis of AR, and their deficiencies are closely related to Prostaglandin E2 (PGE2). However, the downstream mechanisms of this relationship remain poorly understood. OBJECTIVE: This study aims to investigate the inhibitory mechanisms through which PGE2 impacts the differentiation of Treg cells. METHODS: We compared the differentiation of Treg cells from naïve CD4+ T cells of AR patients and healthy controls, with or without the presence of PGE2 by flow cytometry. Intracellular cAMP concentration, mRNA and protein levels of cyclic-AMP dependent protein kinase A (PKA), as well as their downstream target, Peroxisome Proliferator-Activated Receptor-γ (PPAR-γ) were examined in Treg cells from AR and healthy donors. AR mouse model was established by pollen administration. RESULTS: PGE2 suppressed the differentiation of Treg cells from human naïve CD4+ T cells through the EP4 receptor. Furthermore, in AR patients and AR mouse, the expression of EP4 receptor were observed enhanced. The PGE2-EP4 signal was carried out by activating cAMP-PKA signaling pathway. Subsequently, phospholated PKA would suppress PPAR-γ expression. Treatment of Pioglitazone, a PPAR-γ agonist, was demonstrated to rescue the differentiation of Treg and help alleviate inflammation in the AR mouse model. CONCLUSION: In AR disease, the PGE2-EP4 signaling exerts an inhibitory effect on Treg differentiation by influencing the cAMP-PKA pathway and its downstream target PPAR-γ.

Tailoring d­Band Center of Single-Atom Nickel Sites for Boosted Photocatalytic Reduction of Diluted CO2 from Flue Gas.

Photocatalytic reduction of diluted CO2 from anthropogenic sources holds tremendous potential for achieving carbon neutrality, while the huge barrier to forming *COOH key intermediate considerably limits catalytic effectiveness. Herein, via coordination engineering of atomically scattered Ni sites in conductive metal-organic frameworks (CMOFs), we propose a facile strategy for tailoring the d­band center of metal active sites towards high-efficiency photoreduction of diluted CO2. Under visible-light irradiation in pure CO2, CMOFs with Ni-O4 sites (Ni-O4 CMOFs) exhibits an outstanding rate for CO generation of 13.3 µmol h-1 with a selectivity of 94.5%, which is almost double that of its isostructural counterpart with traditional Ni-N4 sites (Ni-N4 CMOFs), outperforming most reported systems under comparable conditions. Interestingly, in simulated flue gas, the CO selectivity of Ni-N4 CMOFs decreases significantly while that of Ni-O4 CMOFs is mostly unchanged, signifying the supremacy for Ni-O4 CMOFs in leveraging anthropogenic diluted CO2. In-situ spectroscopy and density functional theory (DFT) investigations demonstrate that O coordination can move the center of the Ni sites' d-band closer to the Fermi level, benefiting the generation of *COOH key intermediate as well as the desorption of *CO and hence leading to significantly boosted activity and selectivity for CO2-to-CO photoreduction.

Day and night continuous high-resolution shallow-water depth detection with single-photon underwater lidar.

Single-photon lidar has emerged as a strong technology for bathymetric measurements. However, its heightened sensitivity additionally makes it susceptible to solar radiation noise, particularly in the green light wavelength where solar radiation is strong, posing challenges for its daytime operation. To address this issue, a single-photon underwater lidar system is proposed and demonstrated. This scheme has these features. 1) Underwater applications not only mitigate the impact of the air-water interface on laser transmission but also significantly attenuate solar radiation reaching the lidar due to the absorption and scattering properties of water. 2) The telescope is designed with a small aperture and narrow field of view to significantly suppress solar radiation. 3) A combination of a narrowband laser and narrowband filter technique is effectively employed to minimize residual solar radiation, thus enabling continuous bathymetric observation capabilities during both day and night. 4) After acquiring the backscattered signal from the bottom, a water depth extraction algorithm utilizing bi-Gaussian fitting is proposed. To demonstrate the robustness of the lidar and the effectiveness of the algorithm, the underwater single-photon lidar system is deployed on a ship to conduct cruise surveys of two bays in the nearshore area, as well as a full-day stationary observation experiment. The lidar measurements are highly consistent with the synchronized sonar observations. The full-day stationary observation experiment showcased its capability to deliver continuous measurements throughout the day and night. These results demonstrate the potential of the system in various applications, including high-precision underwater terrain mapping, obstacle avoidance for underwater platforms, and underwater target imaging.

Response of macrophyte litter decomposition in global blue carbon ecosystems to climate change.

Blue carbon ecosystems (BCEs) are important nature-based solutions for climate change-mitigation. However, current debates question the reliability and contribution of BCEs under future climatic-scenarios. The answer to this question depends on ecosystem processes driving carbon-sequestration and -storage, such as primary production and decomposition, and their future rates. We performed a global meta-analysis on litter decomposition rate constants (k) in BCEs and predicted changes in carbon release from 309 studies. The relationships between k and climatic factors were examined by extracting remote-sensing data on air temperature, sea-surface temperature, and precipitation aligning to the decomposition time of each experiment. We constructed global numerical models of litter decomposition to forecast k and carbon release under different scenarios. The current k averages at 27 ± 3 × 10-2 day-1 for macroalgae were higher than for seagrasses (1.7 ± 0.2 × 10-2 day-1 ), mangroves (1.6 ± 0.1 × 10-2 day-1 ) and tidal marshes (5.9 ± 0.5 × 10-3 day-1 ). Macrophyte k increased with both air temperature and precipitation in intertidal BCEs and with sea surface temperature for subtidal seagrasses. Above a temperature threshold for vascular plant litter at ~25°C and ~20°C for macroalgae, k drastically increased with increasing temperature. However, the direct effect of high temperatures on k are obscured by other factors in field experiments compared with laboratory experiments. We defined "fundamental" and "realized" temperature response to explain this effect. Based on relationships for realized temperature response, we predict that proportions of decomposed litter will increase by 0.9%-5% and 4.7%-28.8% by 2100 under low- (2°C) and high-warming conditions (4°C) compared to 2020, respectively. Net litter carbon sinks in BCEs will increase due to higher increase in litter C production than in decomposition by 2100 compared to 2020 under RCP 8.5. We highlight that BCEs will play an increasingly important role in future climate change-mitigation. Our findings can be leveraged for blue carbon accounting under future climate change scenarios.

Microbial Community Structure and Metabolic Potential at the Initial Stage of Soil Development of the Glacial Forefields in Svalbard.

Microbial communities have been identified as the primary inhabitants of Arctic forefields. However, the metabolic potential of microbial communities in these newly exposed soils remains underexplored due to limited access. Here, we sampled the very edge of the glacial forefield in Svalbard and performed the 16S rRNA genes and metagenomic analysis to illustrate the ecosystem characteristics. Burkholderiales and Micrococcales were the dominant bacterial groups at the initial stage of soil development of glacial forefields. 214 metagenome-assembled genomes were recovered from glacier forefield microbiome datasets, including only 2 belonging to archaea. Analysis of these metagenome-assembled genomes revealed that 41% of assembled genomes had the genetic potential to use nitrate and nitrite as electron acceptors. Metabolic pathway reconstruction for these microbes suggested versatility for sulfide and thiosulfate oxidation, H2 and CO utilization, and CO2 fixation. Our results indicate the importance of anaerobic processes in elemental cycling in the glacial forefields. Besides, a range of genes related to adaption to low temperature and other stresses were detected, which revealed the presence of diverse mechanisms of adaption to the extreme environment of Svalbard. This research provides ecological insight into the initial stage of the soil developed during the retreating of glaciers.

Multiperspective Decoupling Analyses between Global Embodied Carbon Chains and Global Value Chains.

Decoupling global economic growth from carbon emissions is essential for mitigating global climate change while maintaining continuous economic growth. Traditional production-side decoupling analysis alone is insufficient to capture the decoupling status between carbon emissions and the value added throughout global supply chains. This study investigates the decoupling status between value added and greenhouse gas (GHG) emissions during 1995-2019 from consumption and income perspectives. We find that the decoupling statuses of 17 regions (especially Russia, Australia, and Malta) show significant differences across multiple perspectives. For example, Malta's direct GHG emissions decreased with its GDP growth from a production perspective (i.e., achieved strong decoupling). However, its consumption-based GHG emissions increased with the growth of consumption-based value added (i.e., expansive negative decoupling). Moreover, most international pairs have not yet achieved strong decoupling from consumption and income perspectives. International multilateral cooperation is crucial for decoupling global GHG emissions from economic growth across global supply chains. This study provides insights into the decoupling between embodied GHG emissions and value added from consumption and income perspectives. The findings of this study can complement existing policies on global GHG emission mitigation and sustainable development.

Shifting Emphasis from Electro- to Catalytically Active Sites: Effects of Pore Size of Flow-Through Anodes on Water Purification.

A flow-through anode has demonstrated high efficiency for micropollutant abatement in water purification. In addition to developing novel electrode materials, a rational design of its porous structure is crucial to achieve high electrooxidation kinetics while sustaining a low cost for flow-through operation. However, our knowledge of the relationship between the pore structure and its performance is still incomplete. Therefore, we systematically explore the effect of pore size (with a median from 4.7 to 49.4 µm) on the flow-through anode efficiency. Results showed that when the pore size was <26.7 µm, the electrooxidation kinetics was insignificantly improved, but the permeability declined dramatically. Traditional empirical evidence from hydrodynamic modeling and electrochemical tests indicated that a flow-through anode with a smaller pore size (e.g., 4.7 µm) had a high mass transfer capability and large electroactive area. However, this did not further accelerate the micropollutant removal. Combining an overpotential distribution model and an imprinting method has revealed that the reactivity of a flow-through anode is related to the catalytically active volume/sites. The rapid overpotential decay as a function of depth in the anode would offset the merits arising from a small pore size. Herein, we demonstrate an optimal pore size distribution (∼20 µm) of typical flow-through anodes to maximize the process performance at a low energy cost, providing insights into the design of advanced flow-through anodes in water purification applications.

Consumption in Non-Pastoral Regions Drove Three-Quarters of Forage-Livestock Conflicts in China.

Forage-livestock conflict (FLC) is a major anthropogenic cause of rangeland degradation. It poses tremendous threats to the environment owing to its adverse impacts on carbon sequestration, water supply and regulation, and biodiversity conservation. Existing policy interventions focus on the in situ FLCs induced by local production activities but overlook the role of consumption activities in driving FLCs. Here, we investigate the spatiotemporal variations in China's FLCs and the domestic final consumers at the county level by combining remote sensing data and multi-regional input-output model. Results show that during 2005-2015, China's pastoralism induced an average of 82 million tons of FLCs per year. Domestic final demand was responsible for 85-93% of the FLCs in China. There was spatiotemporal heterogeneity in domestic consumption driving China's FLCs. In particular, the final demand of non-pastoral regions was responsible for around three-quarters (74-79%) of the total FLCs throughout the decade. The rangeland-based livestock raising, agricultural and sideline product processing, and catering sectors are important demand-side drivers. These findings can support targeted demand-side strategies and interregional cooperation to reduce China's FLCs, thus mitigating rangeland degradation.

Differentially Charged Nanoplastics Induce Distinct Effects on the Growth and Gut of Benthic Insects (Chironomus kiinensis) via Charge-Specific Accumulation and Perturbation of the Gut Microbiota.

Nanoplastics (NPs), as an emerging contaminant, have usually been found charged in the environment, posing threats to aquatic animals. However, the underlying mechanisms governing the gut toxicity of differentially charged NPs to benthic insects are not well understood. In this study, the gut toxicity in larvae of Chironomus kiinensis exposed to negatively charged NPs (PS-COOH, 50 nm) and positively charged NPs (PS-NH2, 50 nm) at 0.1 and 1 g/kg was investigated through fluorescence imaging, histopathology, biochemical approaches, and 16S rRNA sequencing. The results showed that PS-NH2 caused more adverse effect on the larval growth performance and induced more severe oxidative stress, epithelial damage, and inflammatory responses in the gut than PS-COOH. The stronger impact caused by PS-NH2 was because the gut accumulated PS-NH2 more readily than PS-COOH for its negatively charged cell membrane. In addition, PS-NH2 were less agglomerated compared with PS-COOH, leading to an increased interaction with gut cell membranes and microbiota. Furthermore, alpha diversity and relative abundance of the keystone microbiota related to gut barrier and nutrient absorption were markedly lower exposed to PS-NH2 than PS-COOH, indirectly exacerbating stronger gut and growth damage. This study provides novel insights into the effect mechanisms underlying differentially charged NPs on benthic insects.

Source or sink role of an urban lake for microplastics from Guangdong-Hong Kong-Macao greater bay area, China.

Plastic production and consumption in China are larger than others in the world, and the challenge of microplastic pollution is widespread. With the development of urbanization in the Guangdong-Hong Kong-Macao Greater Bay Area, China, the environmental pollution of microplastics is becoming an increasingly prominent issue. Here, the spatial and temporal distribution characteristics, sources, and ecological risks of microplastics were analyzed in water from an urban lake, Xinghu Lake, as well as the contribution of rivers. Importantly, the roles of urban lakes for microplastics were demonstrated through the investigations of contributions and fluxes for microplastic in rivers. The results showed that the average abundances of microplastics in water of Xinghu Lake were 4.8 ± 2.2 and 10.1 ± 7.6 particles/m3 in wet and dry seasons, and the average contribution degree of the inflow rivers was 75%. The size of microplastics in water from Xinghu Lake and its tributaries was concentrated in the range of 200-1000 µm. In general, the average comprehensive potential ecological risk indexes of microplastics in water were 247 ± 120.6 and 273.1 ± 353.7 in wet and dry seasons, which the high ecological risks of them were found through the adjusted evaluation method. There were also mutual effects among microplastic abundance, the concentrations of total nitrogen and organic carbon. Finally, Xinghu Lake has been a sink for microplastics both in wet and dry seasons, and it would be a source of microplastics under the influence of extreme weather and anthropogenic factors.

Remote sensing oil in water with an all-fiber underwater single-photon Raman lidar.

The detection of oil in water is of great importance for maintaining subsurface infrastructures such as oil pipelines. As a potential technology for oceanic application, an oceanic lidar has proved its advantages for remote sensing of optical properties and subsea materials. However, current oceanic lidar systems are highly power-consuming and bulky, making them difficult to deploy underwater to monitor oil in water. To address this issue, we have developed a compact single-photon Raman lidar by using a single-photon detector with high quantum efficiency and low dark noise. Due to the single-photon sensitivity, the detection of the relatively weak Raman backscattered signal from underwater oil was realized with a laser with a pulse energy of 1 µJ and a telescope with a diameter of 22.4 mm. An experimental demonstration was conducted to obtain the distance-resolved Raman backscatter of underwater oil of different thicknesses up to a distance of 12 m. The results indicate the single-photon Raman lidar's potential for inspecting underwater oil pipelines.

On the accuracy of official Chinese crop production data: Evidence from biophysical indexes of net primary production.

With rapid economic growth and urbanization, self-sufficiency in crop production has become central to China's agriculture policy. Accurate crop production statistics are essential for research, monitoring, and planning. Although researchers agree that China's statistical authority has considerably modernized over time, China's economic statistics have still been viewed as unreliable and often overstated to meet growth targets at different administrative levels. Recent increases in crop production reported by national statistics have also come under increasing scrutiny. This paper investigates crop production data quality from a planetary boundary perspective-comparing net primary production (NPP) harvested obtained from national statistics with satellite-driven NPP estimates that are supported by detailed observation of land cover, combined with observations on physical factors that limit plant growth. This approach provides a powerful means to check the plausibility of China's grain production statistics at different administrative levels that can generate insights about their discrepancies and can contribute to improved crop production measurements. We find some evidence of potential misreporting problems from the lower administration level where the risk of manipulation of statistics is higher. We also find problems from provincial-level major grain producers. These values can also affect the national totals. Although the numbers are affected by large uncertainties, we find that improving the spatial resolution of key agricultural parameters can greatly improve the reliability of the indicator that in turn can help improve data quality. More reliable production data will be vital for relevant research and provide better insights into food security problems, the carbon cycle, and sustainable development.

Disentangling the effects of phosphorus loading on food web stability in a large shallow lake.

Excessive nutrient loads reduce ecosystem resilience, resulting in fundamental changes in ecosystem structure and function when exceeding a certain threshold. However, quantitative analysis of the processes by which nutrient loading affects ecosystem resilience requires further exploration. Food web stability is at the heart of ecosystem resilience. In this study, we simulated the dynamics of the food web under different phosphorus loads for Lake Baiyangdian using the PCLake model and calculated the food web stability. Our results showed that there was a good correspondence between the food web stability and ecosystem state response to phosphorus loads. This relationship confirmed that food web stability could be regarded as a signal for the state transition in a real lake ecosystem. Moreover, our estimates suggested that food web stability was influenced only by several functional groups and their interaction strength. Diatoms and zooplankton were the key functional groups that affected food web stability. Phosphorus loads alter the distribution of functional group biomass, which in turn affects energy delivery and, ultimately, the stability of the food web. Corresponding to functional groups, the interactions among zooplankton, diatoms and detritus had the greatest impact, and the interaction strength of the three was positively correlated with food web stability. Overall, our study explained that food-web stability was critical to characterize ecosystem resilience response to external disturbances and can be turned into a scientific tool for lake ecosystem management.