Search Results (539)

Probabilistic streamflow models play a pivotal role in quantifying hydrological uncertainty and form the backbone of modern risk management strategies for flood and drought forecasting, water allocation planning, and the design of resilient infrastructure. Unlike deterministic approaches that yield single-point estimates, these models provide a spectrum of possible outcomes, enabling a more realistic assessment of extreme events and supporting informed, sustainable water resource decisions. By explicitly accounting for natural variability and uncertainty, probabilistic models promote transparent, robust, and equitable risk evaluations, helping decision-makers balance economic costs, societal benefits, and environmental protection for long-term sustainability. In this study, we introduce the bounded half-logistic distribution (BHLD), a novel heavy-tailed probability model constructed using the T–Y method for distribution generation, where T denotes a transformer distribution and Y represents a baseline generator. Although the BHLD is conceptually related to the Pareto and log-logistic families, it offers several distinctive advantages for streamflow modeling, including a flexible hazard rate that can be unimodal or monotonically decreasing, a finite lower bound, and closed-form expressions for key risk measures such as Value at Risk (VaR) and Tail Value at Risk (TVaR). The proposed distribution is defined on a lower-bounded domain, allowing it to realistically capture physical constraints inherent in flood processes, while a log-logistic-based tail structure provides the flexibility needed to model extreme hydrological events. Moreover, the BHLD is analytically characterized through a governing differential equation and further examined via its characteristic function and the maximum entropy principle, ensuring stable and efficient parameter estimation. It integrates a half-logistic generator with a log-logistic baseline, yielding a power-law tail decay governed by the parameter $\beta$, which is particularly effective for representing extreme flows. Fundamental properties, including the hazard rate function, moments, and entropy measures, are derived in closed form, and model parameters are estimated using the maximum likelihood method. Applied to four real streamflow data sets, the BHLD demonstrates superior performance over nine competing distributions in goodness-of-fit analyses, with notable improvements in tail representation. The model facilitates accurate computation of hydrological risk metrics such as VaR, TVaR, and tail variance, uncovering pronounced temporal variations in flood risk and establishing the BHLD as a powerful and reliable tool for streamflow modeling under changing environmental conditions. Full article

A living organism can be regarded as a dissipative, self-organizing physical system operating far from thermodynamic equilibrium. Such systems can be effectively described within the framework of Markov jump processes subjected to an external driving force that sustains the system away from equilibrium—leading, in the special case of stabilization, to a non-equilibrium steady state (NESS). By combining the Markov formalism with concepts from stochastic thermodynamics, we demonstrate the temporal evolution of entropy in such systems: entropy decreases during growth and development, stabilizes at maturity under NESS conditions, and subsequently increases during aging, death, and decomposition. This characteristic trajectory, which we term the entropy bathtub, highlights the universal thermodynamic structure of living systems. We further show that the system exhibits continuous yet time-dependent positive entropy production, in accordance with fundamental thermodynamic principles. Perturbations of the driving force—whether reversible or irreversible—naturally capture the impact of external stressors, providing a conceptual analogy to pathological processes in biological organisms. Although the model does not introduce fundamentally new elements to the physics of life, it offers a simple tool for exploring entropy-driven mechanisms in living matter. Full article

Introduction: Massage therapy delivers structured mechanosensory input that can influence brain function, yet the central mechanisms and potential for neuroplastic change have not been synthesized across neuroimaging modalities. This mechanistic review integrates evidence from electroencephalography (EEG), functional MRI (fMRI), and functional near-infrared spectroscopy (fNIRS) to map how massage alters human brain activity acutely and over time and to identify signals of longitudinal adaptation. Materials and Methods: We conducted a scoping, mechanistic review informed by PRISMA/PRISMA-ScR principles. PubMed/MEDLINE, Cochrane Library, Google Scholar, and ResearchGate were queried for English-language human trials (January 1990–July 2025) that (1) delivered a practitioner-applied manual massage (e.g., Swedish, Thai, shiatsu, tuina, reflexology, myofascial techniques) and (2) measured brain activity with EEG, fMRI, or fNIRS pre/post or between groups. Non-manual stimulation, structural-only imaging, protocols, and non-English reports were excluded. Two reviewers independently screened and extracted study, intervention, and neuroimaging details; heterogeneity precluded meta-analysis, so results were narratively synthesized by modality and linked to putative mechanisms and longitudinal effects. Results: Forty-seven studies met the criteria: 30 EEG, 12 fMRI, and 5 fNIRS. Results: Regarding EEG, massage commonly increased alpha across single sessions with reductions in beta/gamma, alongside pressure-dependent autonomic shifts; moderate pressure favored a parasympathetic/relaxation profile. Connectivity effects were state- and modality-specific (e.g., reduced inter-occipital alpha coherence after facial massage, preserved or reorganized coupling with hands-on vs. mechanical delivery). Frontal alpha asymmetry frequently shifted leftward (approach/positive affect). Pain cohorts showed decreased cortical entropy and a shift toward slower rhythms, which tracked analgesia. Somatotopy emerged during unilateral treatments (contralateral central beta suppression). Adjuncts (e.g., binaural beats) enhanced anti-fatigue indices. Longitudinally, repeated programs showed attenuation of acute EEG/cortisol responses yet improvements in stress and performance; in one program, BDNF increased across weeks. In preterm infants, twice-daily massage accelerated EEG maturation (higher alpha/beta, lower delta) in a dose-responsive fashion; the EEG background was more continuous. In fMRI studies, in-scanner touch and reflexology engaged the insula, anterior cingulate, striatum, and periaqueductal gray; somatotopic specificity was observed for mapped foot areas. Resting-state studies in chronic pain reported normalization of regional homogeneity and/or connectivity within default-mode and salience/interoceptive networks after multi-session tuina or osteopathic interventions, paralleling symptom improvement; some task-based effects persisted at delayed follow-up. fNIRS studies generally showed increased prefrontal oxygenation during/after massage; in motor-impaired cohorts, acupressure/massage enhanced lateralized sensorimotor activation, consistent with use-dependent plasticity. Some reports paired hemodynamic changes with oxytocin and autonomic markers. Conclusions: Across modalities, massage reliably modulates central activity acutely and shows convergent signals of neuroplastic adaptation with repeated dosing and in developmental windows. Evidence supports (i) rapid induction of relaxed/analgesic states (alpha increases, network rebalancing) and (ii) longer-horizon changes—network normalization in chronic pain, EEG maturation in preterm infants, and neurotrophic up-shifts—consistent with trait-level recalibration of stress, interoception, and pain circuits. These findings justify integrating massage into rehabilitation, pain management, mental health, and neonatal care and motivate larger, standardized, multimodal longitudinal trials to define dose–response relationships, durability, and mechanistic mediators (e.g., connectivity targets, neuropeptides). Full article

Socio-ecological systems in basin regions characterized by diverse cultural traditions and hierarchical village spatial structure are undergoing profound transformation driven by multifunctional demands and spatial restructuring. This study develops an analytical framework encompassing economic production, socio-cultural functions, and ecological potential to examine the spatial differentiation and socio-ecological coupling mechanisms within the Yilong Lake Basin, Yunnan Province. Through the entropy weighting method and a coupling coordination model, the framework evaluates the “lake–mountain–village” gradient of spatial differentiation. The results indicate that: (1) the overall coordination level of multifunctional systems in the region remains relatively low, exhibiting a decreasing trend from lakeshore to the mountain periphery; (2) village-level dependencies of spatial functions can be summarized into three coupling categories—associated with institutional embedding, self-organization, and value mismatch—revealing distinct socio-ecological interaction patterns; and (3) three coupling categories correspond to three differentiated governance pathways, namely coupling optimization, functional transition, and conflict mitigation. The study advances theoretical and methodological insights into the spatial differentiation and evolution of complex village systems, highlighting the nonlinear coexistence of interdependence and constraint among economic, social, and ecological functions. It further provides practical guidance for coordinated governance and sustainable spatial planning in similar rural and basin environments worldwide. Full article

Excavation of underground spaces often causes significant initial damage to surrounding rock, which can notably alter its mechanical properties. However, most studies on loading rate effects neglect the role of initial damage. This study investigates how initial damage and loading rate together affect granite’s mechanical behavior and fracturing characteristics. Granite specimens with different initial damage levels were subjected to uniaxial compression at varying loading rates to assess their mechanical parameters, stress thresholds, failure modes, energy evolution, and associated acoustic emission (AE) activity. Results indicate that granite’s mechanical behavior exhibits greater sensitivity to loading rate than to initial damage. As the loading rate increases, both strength and elastic modulus initially decrease and then rise, while the dissipated-to-input energy ratio reaches a maximum when the strength is at its lowest. This phenomenon occurs because, when cracks are allowed to fully develop, a relatively higher loading rate increases the likelihood of crack initiation and propagation, thereby reducing strength. The AE responses of initial damage granite samples (IDGSs), including counts, RA/AF value, b-value, and entropy, exhibit stage-dependent variations and contain precursory information before failure. Moreover, AE signals display multifractal characteristics across different loading rates. These findings reveal the mechanisms underlying granite’s mechanical response when both initial damage and loading rate act together: initial damage primarily affects the complexity and number of local microcracks, while loading rate determines the dominant crack initiation and propagation modes. Moreover, how the failure time of IDGSs varies with loading rate can be described by an inverse exponential function. These findings enhance insight into the coupling mechanism of initial damage and loading rate, with significant implications for failure warning and the cost-effectiveness of underground excavation. Full article

The development of agricultural new productive forces (ANPFs) represents a vital pathway to overcoming the bottlenecks of agricultural modernization and reshaping agricultural competitiveness. As sustainable development and green transformation have become global priorities, the formation of ANPFs is increasingly viewed as a key engine for promoting resource-efficient agriculture, low-carbon production, ecological protection, and resilient food systems. Using panel data from 16 prefecture-level cities in Anhui Province, China, spanning the period 2010–2023, this study employs the entropy-weighted TOPSIS method to measure the levels of ANPFs and sustainable agricultural development (SAD). A panel data model is then applied to examine the impact of ANPFs on SAD, while a mediation-effect model is used to test the underlying transmission mechanisms. Finally, a spatial econometric model is employed to assess the spatial spillover effects between ANPFs and SAD. The results reveal that ANPFs exert a significant and robust positive impact on Anhui’s SAD, with the strength of this effect decreasing gradually from central to southern and northern regions. Further analysis indicates that the driving influence of ANPFs operates through three key mediating pathways: the improvement of new-type infrastructure, the enhancement of agricultural scientific and technological innovation, and the advancement of agricultural digital transformation. Moreover, ANPFs demonstrate a positive spatial spillover effect, suggesting that the development of new productive forces in one region promotes agricultural modernization in neighboring areas. These findings demonstrate that ANPFs not only enhance productivity but also contribute to sustainable agricultural development. Accordingly, strengthening ANPFs development can serve as an effective strategy for promoting long-term agricultural sustainability, indicating that central Anhui should be prioritized as a core hub for fostering ANPFs, enabling the gradient diffusion of infrastructure, innovation capacity, and digital services toward southern and northern Anhui. Strengthening regional coordination mechanisms will further amplify the spatial spillover of ANPFs, thereby advancing high-quality agricultural development across the province. This study provides new evidence for how ANPFs can support sustainable agricultural transformation, offering policy insights for green growth, food security, and rural revitalization. Full article

In arid regions, rainfall is scarce, summer-concentrated, and prone to extreme events, while evaporation exceeds precipitation, creating fragile ecosystems that need scientific stormwater management for flood resilience. Sponge cities, through the implementation of green infrastructure, can alleviate urban flooding, improve rainwater utilization, and enhance the urban ecological environment. Under the “dual carbon” target, sponge city construction has gained new developmental significance. It must not only ensure core functions and minimize construction costs but also fully leverage its carbon reduction potential, thereby serving as a crucial pathway for promoting urban green and low-carbon development. Therefore, this study focused on Xining, a typical arid city in Northwest China, and couples the Non-dominated Sorting Genetic Algorithm-III (NSGA-III) with the Storm Water Management Model (SWMM) to construct a multi-objective optimization model for Low Impact Development (LID) facilities. The layout optimization design of LID facilities is conducted from three dimensions: life cycle cost (LCC), rainwater utilization rate (K), and carbon emission intensity (CI). Hydrological simulations and scheme optimizations were performed under different design rainfall events. Subsequently, the entropy-weighted TOPSIS method was utilized to evaluate and compare these optimized schemes. It is shown by the results that: (1) The optimized LID schemes achieved a K of 76.2–80.43%, an LCC of 2.413–3.019 billion yuan, and a CI of −2.8 to 0.19 kg/m²; (2) Compared with the no-LID scenario, the optimized scheme significantly enhanced hydrological regulation, flood mitigation, and pollutant removal. Under different rainfall return periods, the annual runoff control rate increased from 64.97% to 80.66–82.23%, with total runoff reduction rates reaching 46.41–49.26% and peak flow reductions of 45–47.62%. Under the rainfall event with a 10-year return period, the total number of waterlogging nodes decreased from 108 to 82, and the number of nodes with a ponding duration exceeding 1 h was reduced by 62.5%. The removal efficiency of total suspended solids (TSS) under the optimized scheme remained stable above 60%. The optimized scheme is highly adaptable to the rainwater management needs of arid areas by prioritizing “infiltration and retention”. Vegetative swales emerge as the primary facility due to their low cost and high carbon sink capacity. This study provides a feasible pathway and decision-making support for the low-carbon layout of LID facilities in arid regions. Full article

Eye gaze plays an essential role in the organisation of human goal-directed behaviour. Stationary gaze entropy and gaze transition entropy are two informative measures of visual scanning in different tasks. In this work, we discuss the benefits of these eye gaze entropy measures in the context of driving behaviour. In our large-scale study, participants performed driving tasks in a simulator (N = 380, 44% female, age: 20–73 years old) and in on-road urban environments (N = 241, 44% female, age: 19–74 years old). We analysed measures of eye gaze entropy in relation to driving experience and compared their dynamics between the simulator and on-road driving. The results demonstrate that, in both driving conditions, gaze transition entropy is higher, whereas stationary gaze entropy is lower, in more experienced drivers of both genders. This suggests that gaining driving experience may be accompanied by a decrease in overall gaze dispersion and an increased unpredictability of visual scanning behaviour. These results are in line with previously reported trends on experience-related dynamics of eye gaze entropy measures. We discuss our findings in the framework of the system-evolutionary theory, which explains the organisation of behaviour through the history of individual development, corresponding to the growing complexity of individual–environment interactions. Experience-related dynamics of eye gaze complexity can be a useful factor in the development of practical applications, such as driver monitoring systems and other human–machine interfaces. Full article

To enhance the operational damage resistance of hydraulic machinery, this study employed laser cladding technology to fabricate a Co_37.4Cr₃₀Ni₂₀Al₅Ti₅Nb_2.6 high-entropy alloy coating on 04Cr13Ni5Mo substrate. The influence of laser power on the microstructure and properties of the coating was systematically investigated. Based on preliminary research, the friction-wear performance and cavitation erosion behavior of the coatings prepared at 3000 W, 3200 W, and 3400 W were specifically examined. Results indicate that as the laser power increased from 3000 W to 3400 W, the microhardness of the coating gradually decreased from 345.3 HV_0.2. At 3000 W, the precipitation of trace strengthening phases significantly enhanced the mechanical properties. In wear tests under a 20 N load for 30 min, the wear rate of the coating prepared at 3000 W was 1.41 × 10⁻⁴ mm³/(N·m), which is 13.5% lower than that of the 3200 W coating (1.63 × 10⁻⁴ mm³/(N·m)) and 16.07% higher in wear resistance compared to the substrate. Cavitation erosion tests revealed that after 20 h of ultrasonic vibration, the mass loss of the 3000 W coating was only 2.35 mg, representing an 88.89% reduction compared to the substrate (21.15 mg), and significantly lower than that of the 3200 W (4.57 mg) and 3400 W (3.85 mg) coatings. This study demonstrates that precise control of laser power can effectively optimize the cavitation erosion resistance of high-entropy alloy coatings, providing technical support for their application in harsh environments. Full article

Background: The rapid rise in antimicrobial resistance has become one of the 10 most pressing health problems worldwide in recent years. Antibiotic stewardship offers hope in the fight against antibiotic resistance, but it is currently still falling short of expectations. A better understanding of the dynamics of the interaction between antibiotic consumption and the emergence and spread of resistance is urgently needed. Methods: We discuss a simple dynamic model based on a differential equation to describe the increase in the proportion of a pathogen’s antimicrobial resistance to an antibiotic as a function of the time-dependent consumption of that antibiotic. Furthermore, we investigate the association of heterogeneity in the consumption of antibiotics with the rate of resistant pathogens. Data basis is the hospital information system and the patient data-management system of a German hospital, restricted to the intensive care unit. To quantify heterogeneity, we discuss and compare different entropy measures. Results: For some pathogen–antibiotic pairs, the consumption-dependent dynamic model for the growth in the proportion of antimicrobial resistance provides acceptable predictions, while for others, the model is less suitable. Cross-resistance and complex interactions with other pathogens and antibiotics may be responsible for this, suggesting that the observed dynamic behavior should be complementary, described using heterogeneity models. Time courses of Shannon entropy, the Antibiotic Heterogeneity Index, and the negative Gini Index correlate positively with the time series of the resistance rate. Thus, an increase in heterogeneity correlates with a decreasing resistance rate. However, a time-delayed cross-correlation of a differential entropy measure with resistance share suggests a functional dependence that can be utilized for antibiotic stewardship. Conclusions: Evidence is provided that the amount of consumption of certain antibiotics drives the corresponding proportions of pathogens’ resistance to these antibiotics; however, the model predictions of these univariable models are generally not sufficiently good, pointing to a more complex interaction dynamics. Therefore, we switch to the level of structural features and show that the degree of constantly mixing of the shares of antibiotic consumption has a control function regarding the incidence of resistance. Controlling differential consumption heterogeneity, therefore, appears to be a feasible operational basis for antibiotic stewardship. Experimental studies are demanded to identify functional dependencies; however, the integration of clinical expertise with model-based prediction appears to be a feasible antibiotic stewardship strategy. Full article

This study fabricated six types of NiCr–Cr₃C₂ composite coatings using high-velocity oxygen fuel (HVOF) spraying and systematically evaluated their tribological behavior at 350 °C and 500 °C, along with their electrochemical corrosion performance in 3.5 wt.% NaCl solution. The objective was to elucidate how compositional design regulates the coatings’ microstructure, mechanical properties, and service performance. Results indicate that the 75NiCr–25Cr₃C₂ coating (C) formed a stable oxide film under both temperatures, exhibiting oxidation-dominated wear and the lowest friction coefficient and wear rate. When the temperature increased from 350 °C to 500 °C, the wear rates of coatings C, B, E, and F decreased significantly. Notably, coatings E and F, which contained CoCrFeNiMo high-entropy alloy, showed more than a 50% reduction in wear rate, demonstrating the contribution of the high-entropy phase to high-temperature wear resistance. At 350 °C, coatings B, D, E, and F experienced primarily abrasive wear; at 500 °C, however, E and F shifted to oxidative wear as the dominant mechanism, leading to a marked improvement in wear resistance. Electrochemical measurements revealed that coating E exhibited the best corrosion resistance, while the NiCr coating (A) performed the worst. The findings highlight that optimizing Cr₃C₂ content and incorporating high-entropy alloy elements can synergistically enhance both high-temperature tribological properties and corrosion resistance. Full article

This study examines the effects of different stereoscopic technologies on physiological responses in immersive virtual reality (VR) environments. Five participant groups were evaluated: a control group (no stereoscopy) and four groups using anaglyph, passive, active glasses, or VR helmets. Heart rate variability (HRV) was measured in both time (MeanRR, SDNN, RMSSD, pNN50) and frequency (LF, HF, LF/HF) domains to assess autonomic nervous system activity. Active, polarized glasses and VR helmets significantly reduced SDNN and RMSSD compared to the control group (p < 0.01), with VR helmets causing the largest decrease (MeanRR −70%, RMSSD −51%). Anaglyph glasses showed milder effects. Nonlinear analysis revealed reduced entropies and Hurst parameter in highly immersive conditions, indicating impaired fractal heart rate structure and increased physiological load. These results demonstrate a clear relationship between immersion level and cardiovascular response, emphasising that higher immersion increases physiological stress. The scientific contribution lies in the combined application of linear and nonlinear HRV analysis to systematically compare different stereoscopic display types under controlled gaming immersion. The study proposes a practical methodology for assessing HRV in VR settings, which can inform the ergonomic design of VR systems and ensure users’ physiological safety. By highlighting the differential impacts of stereoscopic technologies on HRV, the findings offer guidance for optimising VR visualisation to balance immersive experience with user comfort and health. Full article

As land use performance undergoes abrupt shifts due to the transition from growth-centric to ecology-focused development, traditional evaluation methods often overlook the catastrophe characteristics of urban complex functions in the process of system evolution, resulting in land governance strategies being unable to adjust rapidly to adapt to regional transformation. To address this limitation, this study develops an ecological priority-oriented performance evaluation system for land use Production–Living–Ecological (PLE) Functions and introduces the Entropy–Catastrophe Progression model to conduct comprehensive measurement and obstacle diagnosis of land use PLE function performance in the Yangtze River Economic Belt of Hubei Province, a typical region, thereby proposing differentiated control strategies. The results show the following: (1) The Entropy–Catastrophe Progression Model can accurately measure the spatiotemporal evolution of land use PLE function performance during the development transition period. (2) The average value of land use PLE function performance presents a fluctuating upward trend, increasing from 0.812 (Poor level) in 2014 to 0.924 (Good level) in 2023. (3) Significant spatial disparities are observed, exhibiting a gradient decrease from provincial capital centers, provincial sub-centers, and ecological economic belts to metropolitan areas. (4) The key obstacles restricting performance improvement include a weak foundation for high-quality tertiary industries, insufficient intensity in environmental purification, and an inadequate supply of high-level living services. These can be addressed by dividing high-quality service optimization zones, green industry enhancement zones, and ecology–economy synergy zones, and establishing differentiated governance mechanisms to improve land use PLE function performance. This study provides theoretical guidance and empirical support for optimizing pathways for urban–rural land use and management. Full article

Plant-derived nanocellulose particles, such as cellulose nanofibrils (CNFs) and cellulose nanocrystals (CNCs), are becoming increasingly popular for a wide range of applications. In particular, when they are employed as rheology modifiers and/or fillers, a choice between CNFs and CNCs is often not obvious. Here, we present the results of a comparative study on the rheological properties of suspensions and gels of carboxymethylated CNFs and CNCs with the same surface chemistry, surface density of charged groups, and thickness. We demonstrate that, at the same weight concentration, CNF suspensions have much higher viscosity and storage modulus, which is due to their longer length providing many entanglements. However, when comparing at the same nanoparticle concentration relative to C*, the situation is reversed: viscosity and storage modulus of CNCs appear to be much higher. This may be due in particular to the higher rigidity and intrinsic strength of highly crystalline CNCs. The gel points for CNF and CNC suspensions (without crosslinker) were compared for the first time. It was found that in the case of CNFs, the gel point occurs at a 3.5-fold lower concentration compared to that of CNCs. Hydrogels were also obtained by crosslinking negatively charged nanocellulose particles of both types by divalent calcium cations. For the first time, the thermodynamic parameters of the crosslinking of carboxymethylated CNFs by calcium ions were determined. Isothermal titration calorimetry data revealed that, for both CNFs and CNCs, crosslinking is endothermic and driven by increasing entropy, which is most likely due to the release of water molecules surrounding the interacting nanoparticles and Ca²⁺ ions. The addition of CaCl₂ to suspensions of nanocellulose particles leads to an increase in the storage modulus; the increase being much more significant for CNCs. Physically crosslinked hydrogels of both CNFs and CNCs can be reversibly destroyed by increasing the shear rate and then quickly recover up to 85% of their original viscosity when the shear rate decreases. The recovery time for CFC networks is only 6 s, which is much shorter than that of CNC networks. This property is promising for various applications, where nanocellulose suspensions are subjected to high shear forces (e.g., mixing, stirring, extrusion, injection, coating) and then need to regain their original properties when at rest. Full article

Extreme droughts caused by current climate changes affect the diversity, composition and function of fish communities in lake ecosystems. Poyang Lake is the largest freshwater lake in China, and it is home to many important avian, fish and aquatic mammals. In 2022, Poyang Lake experienced one of the most severe droughts in recorded history. Understanding how fish communities responded to this event can offer key knowledge in developing strategies for coping with future climatic extremes, particularly given that the local government has been actively posting several middle- to long-term policies on managing the fish diversity of Poyang Lake, including fishery resource supplements and the well-known “ten-year fishing ban”. To understand how the fish diversity of Poyang Lake has been altered by climate change and human interventions, here, we analyzed the α- and β-taxonomic diversity (TD) and functional diversity (FD) of fish species using environmental DNA (eDNA), and we compared the fish diversity and community changes before and after the 2022 drought. In total, 77 native fish species and 4 invasive species were detected. The species richness and Shannon–Wiener index decreased significantly, and Simpson’s index had no significant difference post-drought. Rao’s Quadratic Entropy (Rao’sQE) index increased significantly, and the Functional Evenness (FEve) index decreased significantly. The differences in α- and β-TD and FD in the north part and south part of Poyang Lake also reflect the impact of drought. When calculating biodiversity contribution rates of the different species, we found that small-sized species were dominant pre-drought, while medium- and large-sized species were predominant post-drought. These patterns indicate that the fish community of Poyang Lake is undergoing a reestablishing process after the extreme drought. This fish community reestablishment post-drought does not correspond to the natural process of community recovery; instead, it is the result of human intervention while being affected by drought brought about by climate change. Full article