Trade-off Mechanism Research Articles

The Trade-Off Relationship between Particle Proximity Effect and Low-Pt Loading to Optimize Oxygen Reduction and Methanol Oxidation Reaction Activity

Pt-based electrocatalysts have long been considered as the most effective oxygen reduction reaction (ORR) and methanol oxidation reaction (MOR) catalysts due to their excellent intrinsic activity. For supported catalysts, Pt loading, particle size, interparticle distance (ipd), and interaction with support are identified as key contributors for high activity and selectivity. The proximity effect is a relatively new topic in catalysis research. There is a contradiction between the traditional view which induces the electronic interaction to reduce the activity and the new view which causes the electrical double-layer overlap of adjacent nanoclusters, changes the potential distribution and improves the specific activity. [1, 2]To this end, we have developed the nitrogen-doped graphite-like carbon sheets supporting low-Pt loading (Pt@N-GC) with uniform sizes and controllable ipd, and disentangled the main effect of ipd on ORR activity/selectivity and MOR activity/CO tolerance. Combining electrochemical tests and the trade-off mechanism between proximity effect and low-Pt loading, the following trends were obtained:1) 10.0 wt% Pt@N-GC with highest Pt loading and lowest ipd inhibits 2e- ORR by strong adsorption and reabsorption of *OOH due to the presence of closer Pt sites, and improves 4e- ORR selectivity. However, the mass activity/specific activity reached the maximum under the optimal low-Pt loading of 5.0 wt%.2) Similarly, 10.0 wt% Pt@N-GC weakened the adsorption of the -OH group of oxidized COads intermediates, led to the strong adsorption of COads on the catalyst surface, inactivated of Pt sites and reduced the CO resistance. Considering the need to improve CO tolerance while increasing MOR activity, the 5.0 wt% low-Pt loading catalyst exhibiting the best MOR performance under the optimal ipd.3) Benefiting by the synergistic effect of Pt nanoparticles and N-GC support, all Pt@N-GCs exhibit bifunctional electrocatalytic activity and durability.We attribute these findings to the underlying mechanism trade-off between the particle proximity effect and low-Pt loading under the uniform particle size and controlled ipd (Figure. 1). We believe the proximity effect has positive and negative effects, how to maximize the advantages of proximity effect can provide valuable guidance for the design and optimization of low-Pt loading bifunctional electrocatalysts in the future.[1] M. Nesselberger, M. Roefzaad, R.F. Hamou, P.U. Biedermann, F.F. Schweinberger, S. Kunz, K. Schloegl, G.K. Wiberg, S. Ashton, U. Heiz, K.J. Mayrhofer, M. Arenz, Nat. Mater., 12 (2013) 919-924.[2] M. Watanabe, H. Sei, P. Stonehart, J. Eelectroanal. Chem., 261 (1989) 375-387. Figure 1. The trade-off mechanism analysis between proximity effect and low-Pt loading. Figure 1

Towards Smart Parking Management: Econometric Analysis and Modeling of Public-Parking-Choice Behavior in Three Cities of Binh Duong, Vietnam

In developing cities, newly emerging cities have started facing the problem of insufficient public parking facilities and ineffective regulations. To support the planning, design and management of the public parking system towards a smart and sustainable city vision, it is necessary to study deeply parking behaviors. This paper presents an empirical study on parking-choice behaviors of motorcycle users and car users in the emerging cities of developing countries through a case study of three cities in Binh Duong, Vietnam. To explore the behavioral mechanisms and influential factors, the multinomial logit parking choice models are developed using revealed preference and stated preference data. The users’ overall satisfaction and perceived importance of parking lot design and service aspects are analyzed using order logistic regression. The revealed choices show no trade-off between parking fee and walking distance, as the users are not fully aware of parking locations and service features. However, the stated choice experiments prove a potential existence of the trade-off mechanism and differentiate significant factors in the decision of choices for the two user groups. The results bring insightful implications for the development of a smart public parking system.

Trade-off Mechanism Between Reliability and Performance for Data-flow Soft Error Detection

Trade-off Mechanism Between Reliability and Performance for Data-flow Soft Error Detection

Facial Fracture Injury Criteria from Night Vision Goggle Impact.

INTRODUCTION: Military personnel extensively use night vision goggles (NVGs) in contemporary scenarios. Since NVGs may induce or increase injuries from falls or vehicular accidents, biomechanical risk assessments would aid design goal or mitigation strategy development.METHODS: This study assesses injury risks from NVG impact on cadaver heads using impactors modeled on the PVS-14 NVG. Impacts to the zygoma and maxilla were performed at 20° or 40° angles. Risks of facial fracture, neurotrauma, and neck injury were assessed. Acoustic sensors and accelerometers assessed time of fracture and provided input variables for injury risk functions. Injuries were assessed using the Abbreviated Injury Scale (AIS); injury severity was assessed using the Rhee and Donat scales. Risk functions were developed for the input variables using censored survival analyses.RESULTS: The effects of impact angle and bone geometry on injury characteristics were determined with loading area, axial force, energy attenuation, and stress at fracture. Probabilities of facial fracture were quantified through survival analysis and injury risk functions. These risk functions determined a 50% risk of facial bone fracture at 1148 N (axial force) at a 20° maxillary impact, 588 N at a 40° maxillary impact, and 677 N at a 20° zygomatic impact. A cumulative distribution function indicates 769 N corresponds to 50% risk of fracture overall.DISCUSSION: Results found smaller impact areas on the maxilla are correlated with higher angles of impact increasing risk of facial fracture, neck injuries are unlikely to occur before fracture or neurotrauma, and a potential trade-off mechanism between fracture and brain injury.Davis MB, Pang DY, Herring IP, Bass CR. Facial fracture injury criteria from night vision goggle impact. Aerosp Med Hum Perform. 2023; 94(11):827-834.

Early prediction of Lithium-ion cell degradation trajectories using signatures of voltage curves up to 4-minute sub-sampling rates

Feature-based machine learning models for capacity and internal resistance (IR) curve prediction have been researched extensively in literature due to their high accuracy and generalization power. Most such models work within the high frequency of data availability regime, e.g., voltage response recorded every 1–4 s. Outside premium fee cloud monitoring solutions, data may be recorded once every 3, 5 or 10 min. In this low-data regime, there are little to no models available. This literature gap is addressed here via a novel methodology, underpinned by strong mathematical guarantees, called ‘path signature’.This work presents a feature-based predictive model for capacity fade and IR rise curves from only constant-current (CC) discharge voltage corresponding to the first 100 cycles. Included is a comprehensive feature analysis for the model via a relevance, redundancy, and complementarity feature trade-off mechanism. The ability to predict from subsampled ‘CC voltage at discharge’ data is investigated using different time steps ranging from 4 s to 4 min. It was discovered that voltage measurements taken at the end of every 4 min are enough to generate features for curve prediction with End of Life (EOL) and its corresponding IR values predicted with a mean absolute percentage error (MAPE) of approximately 13.2% and 2.1%, respectively. Our model under higher frequency (4 s) produces an improved accuracy with EOL predicted with an MAPE of 10%. Full implementation code publicly available.

Leaf functional traits vary among growth forms and vegetation zones in the Himalaya

Compression of life zones along elevational gradients in mountains supports diverse vegetation types, and therefore offers ideal setting to study plant functional traits. Functional traits, the features that enable plants to live in varied environmental conditions, help in understanding ecological interactions, evolutionary adaptations, and predicting plant response to global change drivers. To date, little is known how the trait diversity varies across different growth forms and vegetation zones in mountains. Here, we aimed to investigate interspecific leaf trait variability among different growth forms and vegetation zones along a wide elevation gradient (2000–4200 m) in Kashmir Himalaya. We measured leaf functional traits (specific leaf area—SLA, leaf thickness — LT, leaf dry matter content —LDMC) of 76 plant species corresponding to three growth forms (trees, shrubs and herbs) and three vegetation zones (Himalayan dry temperate forests, subalpine forests and alpine grasslands). Our results revealed high trait variability across the regional species pool studied. We found significant variation in leaf functional traits among the different growth forms, with higher values of LT and LDMC recorded for woody species than herbaceous ones. Among different vegetation zones, the SLA was found to be significantly higher at lower to middle elevations, while the other leaf traits (LT and LDMC) showed an opposite trend. Across all the vegetative zones, we also found a negative correlation between SLA and the other leaf traits, and the latter showed a positive trait-trait correlation. Overall, our study contributes to a deeper understanding of trait-trait, trait-growth form and trait-vegetation zone relationships. Our findings suggest that the variation in leaf functional traits among different growth forms seems to be a trade-off mechanism between resource acquisition and leaf construction, and also help in identifying species' adaptive functional traits that are critical for plant survival in the face of ongoing climate change in the Himalaya.

Multifunctional trade-off and compensation mechanism of arable land under the background of rural revitalization: a case study in the West Mountain Regions of Hubei Province.

Exploring the spatial relationship and ecological compensation mechanism of each function of arable land in poor mountainous areas is important to promote rural revitalization and enhance arable land protection. Taking the mountainous region of Western Hubei (MRWH) as an example, this study quantified the "three living" functions of arable land and its secondary functions. Using the root mean square deviation method to calculate the trade-off index, a quantitative method can more scientifically reflect the trade-off relationship between arable land functions and measure the overall ecological compensation. Studies have shown that (1) the value of the production function exhibits a growing and subsequently a falling trend, whereas the value of living function and ecological function exhibits an increasing trend over time, with an average functional value of 5310, 220 and 6496 million yuan, respectively. The spatial pattern of the "three living" functional values decreases from west to east. Among them, water conservation and soil conservation function values show a high distribution in the south and low in the north, gas purification and agricultural pollution functional values show a scattered spatial pattern, and the value of other functions shows an increasing trend from southeast to northwest; (2) among the primary functions, the trade-off between production and ecological functions is the strongest, decreasing, and then increasing over time, with an average trade-off index of 0.89. Among the secondary functions, there is the most obvious trade-off between the food supply function and the five ecological functions, which requires coordination; (3) overall, the total amount of ecological compensation has shown an upward trend, with priority areas for level I ecological compensation increasing year by year. Optimized compensation zones and potential compensation zones are concentrated in the northwest, ecological balance zones are located in the central part, and optimized development compensation zones and key development compensation zones are located in the southeast. According to the research, MRWH is oriented to ecological function, followed by the production function, supplemented by the living function. Green agriculture should be vigorously developed and ecological function space should be compressed by strictly limiting the excessive expansion of production activities. Promoting the improvement ofproduction function through ecological function, while exploring the potential value of living function. Ecological compensation in strict accordance with the priority of ecological compensation, zoning. Realizing cross-regional cooperation, low compensation areas drive high compensation areas to achieve sustainable development of arable land.

Control dilemma: Evidence of the stability–flexibility trade-off

Cognitive control can be applied flexibly when task goals or environments change (i.e., cognitive flexibility), or stably to pursue a goal in the face of distraction (i.e., cognitive stability). Whether these seemingly contradictory characteristics have an inverse relationship has been controversial, as some studies have suggested a trade-off mechanism between cognitive flexibility and cognitive stability, while others have not found such reciprocal associations. This study investigated the possible antagonistic correlation between cognitive flexibility and stability using a novel version of the flexibility–stability paradigm and the classic cued task switching paradigm. In Experiment 1, we showed that cognitive flexibility was inversely correlated with cognitive stability, as increased distractor proportions were associated with decreased cognitive flexibility and greater cognitive stability. Moreover, cognitive flexibility and stability were regulated by a single control system instead of two independent control mechanisms, as the model selection results indicated that the reciprocally regulated model with one integration parameter outperformed all other models, and the model parameter was inversely linked to cognitive flexibility and stability. We found similar results using the classic cued task switching paradigm in Experiment 2. Therefore, a trade-off between cognitive flexibility and stability was observed from the paradigms used in this study.

The OsSGS3-tasiRNA-OsARF3 module orchestrates abiotic-biotic stress response trade-off in rice

Recurrent heat stress and pathogen invasion seriously threaten crop production, and abiotic stress often antagonizes biotic stress response against pathogens. However, the molecular mechanisms of trade-offs between thermotolerance and defense remain obscure. Here, we identify a rice thermo-sensitive mutant that displays a defect in floret development under high temperature with a mutation in SUPPRESSOR OF GENE SILENCING 3a (OsSGS3a). OsSGS3a interacts with its homolog OsSGS3b and modulates the biogenesis of trans-acting small interfering RNA (tasiRNA) targeting AUXIN RESPONSE FACTORS (ARFs). We find that OsSGS3a/b positively, while OsARF3a/b and OsARF3la/lb negatively modulate thermotolerance. Moreover, OsSGS3a negatively, while OsARF3a/b and OsARF3la/lb positively regulate disease resistance to the bacterial pathogen Xanthomonas oryzae pv. oryzae (Xoo) and the fungal pathogen Magnaporthe oryzae (M. oryzae). Taken together, our study uncovers a previously unknown trade-off mechanism that regulates distinct immunity and thermotolerance through the OsSGS3-tasiRNA-OsARF3 module, highlighting the regulation of abiotic-biotic stress response trade-off in plants.

Feature Attention as a Control Mechanism for the Balance of Speed and Accuracy in Visual Search

Finding an object amongst a cluttered visual scene is an everyday task for humans but presents a fundamental challenge to computational models performing this feat. Previous attempts to model efficient visual search have focused on locating targets as swiftly as possible, but so far have not considered balancing the costs of lengthy searches against the costs of making errors. Here, we propose a neuro-inspired model of visual search that offers an attention-based control mechanism for this speed-accuracy trade-off. The model combines a goal-based fixation policy, which captures human-like behaviour on a simple visual search task, with a deep neural network that carries out the target detection step. The neural network is patched with a target-based feature attention model previously applied to standalone classification tasks. In contrast to image classification, visual search introduces a time component, which places an additional demand on the model to minimise the time cost of the search whilst also maintaining acceptable accuracy. The proposed model balances these two costs by modulating the attentional strength given to characteristic features of the target class, thereby minimising an associated cost function. The model offers a method for optimising the costs of visual search and demonstrates the value of a decision theoretic approach to modelling more complex visual tasks involving attention.

Discovering a uniform functional trade-off of the CBC-type 2,3-oxidosqualene cyclases and deciphering its chemical logic.

Many functionally promiscuous plant 2,3-oxidosqualene cyclases (OSCs) have been found, but complete functional reshaping is rarely reported. In this study, we have identified two new plant OSCs: a unique protostadienol synthase (AoPDS) and a common cycloartenol synthase (AoCAS) from Alisma orientale (Sam.) Juzep. Multiscale simulations and mutagenesis experiments revealed that threonine-727 is an essential residue responsible for protosta-13 (17),24-dienol biosynthesis in AoPDS and that the F726T mutant completely reshapes the native function of AoCAS into a PDS function to yield almost exclusively protosta-13 (17),24-dienol. Unexpectedly, various native functions were uniformly reshaped into a PDS function by introducing the phenylalanine → threonine substitution at this conserved position in other plant and non-plant chair-boat-chair-type OSCs. Further computational modeling elaborated the trade-off mechanisms of the phenylalanine → threonine substitution that leads to the PDS activity. This study demonstrates a general strategy for functional reshaping by using a plastic residue based on the decipherment of the catalytic mechanism.

Beyond Trade-Off: An Optimized Binocular Stereo Vision Based Depth Estimation Algorithm for Designing Harvesting Robot in Orchards

Depth estimation is one of the bottleneck parts for harvesting robots to determine whether the operation of grasping or picking succeeds or not directly. This paper proposed a novel disparity completion method combined with bilateral filtering and pyramid fusion to improve the issues of incorrect outputs due to the missed or wrong matching when achieving 3D position from 2D images in open-world environments. Briefly, our proposed method has two significant advantages in general. Firstly, occlusion between leaves, branches, and fruits is a universal phenomenon in unstructured orchard environments, which results in the most depth estimation algorithms facing great challenges to obtain accurate outputs in these occluded regions. To alleviate these issues, unlike other research efforts that already exist, we optimized the semi-global matching algorithm to obtain high accuracy sparse values as an initial disparity map; then, an improved bilateral filtering algorithm is proposed to eliminate holes and discontinuous regions caused by occlusion to obtain precise and density disparity outputs. Secondly, due to taking the practical high-efficiency requirements of the automated harvesting robot in its working status into consideration, we attempted to merge multiple low-resolution bilateral filtering results through the pyramid fusion model which goes beyond the trade-off mechanism to improve the performance of both accuracy and time cost. Finally, a prototype harvesting robot was designed to conduct experiments at three kinds of different distances (0.6~0.75 m, 1~1.2 m, and 1.6~1.9 m). Experiment results showed that our proposed method achieved density disparity maps and eliminated holes and discontinuous defects in the disparity map effectively. The average absolute error of our proposed method is 3.2 mm, and the average relative error is 1.79%. In addition, the time cost is greatly reduced more than 90%. Comprehensive experimental results demonstrate that our proposed algorithm provides a potential possibility for designing harvesting.

A simple biochemical plasma test as an indicator of maternal energy balance predicts offspring survival in bighorn sheep

In species where offspring survival is highly variable relative to adult survival, such as bighorn sheep (Ovis canadensis), physiological indicators of maternal investment could clarify the functional mechanisms of life history trade-offs and serve as important predictors of population dynamics. From a management perspective, simple predictors of juvenile survival measured non-lethally from maternal samples could aid in identifying at-risk populations or individuals before significant mortality occurs. Blood biochemical parameters can offer low-cost insights into animal health and physiology, therefore we sought to develop a simple biochemical predictor of juvenile survival based on maternal blood samples. We measured biochemical indicators of energy balance in adult bighorn sheep at a single time point in January or February, and then monitored survival through August of the same year to assess how those measures related to survival of individual adults and their juvenile offspring. Juvenile survival was lower over the subsequent spring and summer when maternal adult serum beta-hydroxybutyric acid (β-HBA) concentration was high, indicating a negative energy balance in the mothers. However, serum β-HBA did not correlate with adult survival over the same period. Our findings suggest that even when maternal body condition is high, short-term caloric deficit may be sufficient trigger to decrease investment in offspring survival. This mechanism could protect adult females from investing heavily in juvenile survival when resources become too limited to support population growth. Our study suggests that β-HBA could be a powerful monitoring tool for bighorn sheep and other threatened ruminant populations under resource limitation.

Understanding the Phage-Host Interaction Mechanism toward Improving the Efficacy of Current Antibiotics in Mycobacterium abscessus.

Pulmonary infections caused by Mycobacterium abscessus (MAB) have been increasing in incidence in recent years, leading to chronic and many times fatal infections due to MAB's natural resistance to most available antimicrobials. The use of bacteriophages (phages) in clinics is emerging as a novel treatment strategy to save the lives of patients suffering from drug-resistant, chronic, and disseminated infections. The substantial research indicates that phage-antibiotic combination therapy can display synergy and be clinically more effective than phage therapy alone. However, there is limited knowledge in the understanding of the molecular mechanisms in phage-mycobacteria interaction and the synergism of phage-antibiotic combinations. We generated the lytic mycobacteriophage library and studied phage specificity and the host range in MAB clinical isolates and characterized the phage's ability to lyse the pathogen under various environmental and mammalian host stress conditions. Our results indicate that phage lytic efficiency is altered by environmental conditions, especially in conditions of biofilm and intracellular states of MAB. By utilizing the MAB gene knockout mutants of the MAB_0937c/MmpL10 drug efflux pump and MAB_0939/pks polyketide synthase enzyme, we discovered the surface glycolipid diacyltrehalose/polyacyltrehalose (DAT/PAT) as one of the major primary phage receptors in mycobacteria. We also established a set of phages that alter the MmpL10 multidrug efflux pump function in MAB through an evolutionary trade-off mechanism. The combination of these phages with antibiotics significantly decreases the number of viable bacteria when compared to phage or antibiotic-alone treatments. This study deepens our understanding of phage-mycobacteria interaction mechanisms and identifies therapeutic phages that can lower bacterial fitness by impairing an antibiotic efflux function and attenuating the MAB intrinsic resistance mechanism via targeted therapy.

Counteraction of stability-activity trade-off of Nattokinase through flexible region shifting

The widespread trade-off between stability and activity severely limits enzyme evolution. Although some progresses have been made to overcome this limitation, the counteraction mechanism for enzyme stability-activity trade-off remains obscure. Here, we clarified the counteraction mechanism of the Nattokinase stability-activity trade-off. A combinatorial mutant M4 was obtained by multi-strategy engineering, exhibiting a 20.7-fold improved half-life; meanwhile, the catalytic efficiency was doubled. Molecular dynamics simulation revealed that an obvious flexible region shifting in the structure of mutant M4 was occurred. The flexible region shifting which contributed to maintain the global structural flexibility, was considered to be the key factor for counteracting the stability-activity trade-off. Further analysis illustrated that the flexible region shifting was driven by region dynamical networks reshaping. This work provided deep insight into the counteraction mechanism of enzyme stability-activity trade-off, suggesting that flexible region shifting would be an effective strategy for enzyme evolution through computational protein engineering.

Control the hydrophilic layer thickness of Janus membranes by manipulating membrane wetting in membrane distillation

Janus membranes with asymmetric wettability have attracted wide attentions for their robust anti-oil-wetting/fouling abilities in membrane distillation (MD). Compared to traditional surface modification approaches, in this study, we provided a new approach which manipulated surfactant-induced wetting to fabricate Janus membrane with a controllable thickness of the hydrophilic layer. The membranes with 10, 20, and 40 μm of wetted layers were obtained by stopping the wetting induced by 40 mg L−1 Triton X-100 (J = 25 L m−2 h−1) at about 15, 40, and 120 s, respectively. Then, the wetted layers were coated using polydopamine (PDA) to fabricate the Janus membranes. The resulting Janus membranes showed no significant change in porosities or pore size distributions compared with the virgin PVDF membrane. These Janus membranes exhibited low in-air water contact angles (< 50°), high underwater oil contact angles (> 145°), and low adhesion with oil droplets. Therefore, they all showed excellent oil-water separation performance with ∼100% rejection and stable flux. The Janus membranes showed no significant decline in flux, but a trade-off existed between the hydrophilic layer thicknesses and the vapor flux. Utilizing membranes with tunable hydrophilic layer thickness, we elucidated the underlying mechanism of such trade-off in mass transfer. Furthermore, the successful modification of membranes with different coatings and in-situ immobilization of silver nanoparticles indicated that this facile modification method is universal and can be further expanded for multifunctional membrane fabrication.

Periploca sepium leaf dry weight, area, and thickness scale differently under different light environments in Taohe riparian forests

Understanding the variation in plant morphological characteristics under heterogeneous light environments is important to comprehend the adaptation strategies of riparian forest plants. Among the plant parts, leaves are the most sensitive to changes in the environment, and their functional traits and correlations among them can reflect the pathways and mechanisms of a plant's response to environmental changes. The allometric relationship between leaf dry weight (LDW), leaf area (LA) and leaf thickness (LT) in Periploca sepium under three natural habitat conditions, namely, under canopy, gap, and full sun areas in the Taohe riparian forest, was examined by using the standardized major axis (SMA) estimation method and correlation analysis. In the under canopy area, LDW and LA showed an allometric growth relationship (SMA slope < 1), whereas LDW and LT displayed an isometric relationship (SMA slope = 1). In the gap area, LDW was isometrically related to the LA and LT (SMA slope = 1). In the full sun area, LDW and LT showed an allometric relationship (SMA slope > 1), whereas LDW and LA showed an isometric relationship (SMA slope = 1). LA, LT, and LDW decreased by 34.3%, 45.0%, and 40.4%, respectively, in plants from the under canopy area to the full light area. Moreover, the transpiration rate (Tr), net photosynthetic rate (Pn), stomatal conductance (Gs), and vapour pressure deficit (VPD) of Periploca sepium increased 1.29-fold, 13.5%, 63.2%, and 29.7%, respectively, from the under canopy area to the full sun area. Periploca sepium developed large, thick leaves in the under canopy area, and small, thin leaves in the full sun area, demonstrating the investment trade-off mechanism of plant leaf functional traits to adapt to the heterogeneous light environment.

Balancing resilience and efficiency in supply chains: Roles of disruptive technologies under Industry 4.0

In the Industry 4.0 era, disruptive technologies such as big data analytics, blockchain, Internet-of-Things, and additive manufacturing have become major forces driving supply chain transformation. Under such circumstances, particular attention should be attached to balancing resilience and efficiency of the supply chain, especially in the presence of more turbulence. In this study, we first summarize the conflicts between supply chain efficiency and supply chain resilience regarding practices and objectives. Then, we discuss the positive effects of disruptive technologies in improving resilience and efficiency. Afterwards, we propose a research agenda that covers both the influence mechanism and trade-off mechanism of these technologies in terms of resilience and efficiency.

Crop yield and carbon sink potential with precipitation in maize and potato cropland ecosystems over the summertime monsoon transition zone of China

AbstractChina has significantly enhanced vegetation coverage and terrestrial carbon sink functions through ecological restoration. However, cropland ecosystems are sensitive to a changing climate over the summertime monsoon transition zone of China (SMTZC), which has implications for carbon cycling. For example, it is unclear how changes in precipitation will affect the cropland ecosystem carbon sinks (CSe) and carbon sink potential (CSp), and the mechanisms of tradeoffs that develop between plant and soil organic carbon (SOC) are unclear. Here, we integrated crop yield, total biomass (TB) and water coefficient in a combined field and modelling experimental. We explored the mechanisms of ecosystem carbon cycling and CSp in the SMTZC under different precipitation scenarios. We found that soil organic carbon sink (SOCs) was strongly correlated with the plant organic carbon sink (POCs) and discovered. Significant differences in CSp between ecosystems resulting from interannual precipitation. The C4 (maize, Zea mays) and C3 (potato, Solanum tuberosum L) carbon sinks (CSs) were 68.59, 190.73, 160.37 Mt and 10.21, 30.97, 14.59 Mt for the 3 years, respectively. Precipitation effectively increased TB and yield, but excessive precipitation in them, which was most obvious in C3 ecosystem (R2 &gt; 0.60) and reduced POCs, evident in C4 ecosystem (R2 &gt; 0.16). This study provides data and a scientific basis for increasing CS and achieving carbon neutrality in cropland.

Response of plant element traits to soil arsenic stress and its implications for vegetation restoration in a post-mining area

The ecological environment in mining area is fragile, and the carbon (C), nitrogen (N), and phosphorus (P) content of dominant plants is closely related to plant nutrient limitation, community composition and ecosystem function. Clarifying the response of dominant plants to soil properties and the corresponding trade-off mechanism are essential for rebuilding the ecological resilience and self-sustaining ability of mining areas. In order to explore the response of dominant plant element traits to soil physico-chemical properties under the stress of soil arsenic (As) pollution, an abandoned metal mining area threatened by heavy soil As pollution was selected as the research area, the soil physico-chemical properties and soil As content in different speciation, and the contents of C, N and P in dominant plants were measured. The results showed that: (1) The soil As pollution was serious in the mining area, while the contents of soil nutrient were relatively low. (2) The soil As content in different speciation affected the absorption and utilization of P by plants. (3) The dominant plants responded to soil As toxicity by allocating more nutrients to leaves to reduce toxicity and ensure growth. This study helps to reveal the nutrient driving law of plant diversity processes and community succession in heavy metal-contaminated sites and is of great significance to restore the fragile ecosystems in mining areas.