Although individuals may exhibit both gradual and abrupt changes in their dynamic properties as shaped by both slowly accumulating influences and acute events, existing statistical frameworks offer limited capacity for the simultaneous detection and representation of these distinct change patterns. We propose a Bayesian regime-switching (RS) modelling framework and an entropy measure adapted from the frequentist framework to facilitate simultaneous representation and testing of postulates of gradual and abrupt changes. Results from Monte Carlo simulation studies indicated that using a combination of entropy and information criterion measures such as the Bayesian information criterion was consistently most effective at facilitating the selection of the best-fitting model across varying magnitudes of abrupt changes. We found that slight lower entropy thresholds may be helpful in facilitating the selection of longitudinal models with RS properties as this class of models tended to yield lower entropy values than conventional thresholds for reliable classification in cross-sectional mixture models-even under satisfactory parameter recovery and classification results. We fitted the proposed models and other candidate models to the data collected from an intervention study on the psychological well-being (PWB) of college-attending early adults. Results suggested abrupt, regime-related transitions in the intra-individual variability levels of PWB dynamics among some participants following the intervention period. Practical usage of the entropy measure in conjunction with other model selection measures, and guidelines to enhance simultaneous detection of true abrupt and gradual changes are discussed.

ABSTRACT Education agents are key players in the global higher education (HE) market. Yet thus far the accounts of agents and the students who engage their services have received relatively limited scholarly attention. Previous studies have largely been written from the host country perspective, and current accounts emphasise agents’ role as recruiters, how universities manage their agent relationships, and how governments regulate agents’ role in the HE sector. This study takes a different approach, seeking to explore the nature of the agent-student relationship as an interactionally constituted process. Understanding the nature of this relationship is vital in order to better comprehend the consequent influences it may have on students’ mobility decision-making as emerging through these relational connections. This exploratory study draws on semi-structured interviews incorporating visual methods with agents and Chinese international students who interacted with agents. The findings revealed both reciprocal relationships where agent-student mentorship was established with mutual trust and understanding as well as one-sided, transactional relationships. The study identifies high levels of complexity and variability, suggesting that agent-student dynamics are better understood as evolving relational configurations.

Computer-based assessments generate rich process data that captures examinees' interactions with test items. Using process data from the U.S. PISA 2012 computer-based mathematics assessment sample, this study applied recurrent neural networks to predict item-level correctness and assessment-level latent proficiency. The analysis also examines the impact of expert-engineered features, levels of architectural complexity, action variability, and score variability on model performance. At the item level, most models achieved AUC values around 0.80, indicating good predictive performance. Moderate correlations were observed between latent proficiency from 30 items and predictions based on process data from a subset of items (n = 10). For item-level models, adding expert-engineered features reduces training time and may improve predictive performance with low action variability. For the assessment-level models, adding expert-engineered features improved performance. Model complexity, including model type (i.e., standard RNN, GRU, and LSTM), number of nodes, and number of layers, had little effect on accuracy and efficiency. Moreover, items with greater action variability were associated with better model performance. The findings suggest that simple neural network architectures are sufficient for modeling process data with limited action variability and that combining action sequences with expert-engineered features improves accuracy, efficiency, and interpretability.

The COVID-19 pandemic exposed critical vulnerabilities in pharmaceutical supply chains, highlighting the urgent need for robust decision-making frameworks capable of accommodating demand uncertainty. This paper presents a data-driven two-stage stochastic programming model for pharmaceutical distribution optimization under demand uncertainty. Using a synthetic dataset that captures realistic pharmaceutical distribution operations, we develop a mathematical formulation that integrates first-stage inventory allocation decisions with second-stage recourse actions contingent on realized demand scenarios. The model incorporates key real-world constraints including lead time variability, capacity limitations, and service level requirements. Goodness-of-fit tests (Kolmogorov–Smirnov, Akaike Information Criterion) validate the use of negative binomial distributions for demand and lognormal distributions for lead times. We employ Monte Carlo simulation with scenario reduction and conduct extensive computational experiments comparing stochastic and deterministic approaches. Results demonstrate that the stochastic model achieves a 23.6% reduction in expected total costs (95% confidence interval: 21.4%–25.8%) and a 12.0 percentage point improvement in service level fulfilment compared to deterministic planning, with a paired t-test confirming statistical significance (p < 0.01). Sensitivity analysis reveals critical thresholds for inventory positioning and the value of incorporating demand uncertainty in pharmaceutical logistics. The proposed framework provides practical decision support for healthcare supply chain managers while contributing to the emerging literature on resilient pharmaceutical supply chains

Hydrogen/Deuterium Exchange Mass Spectrometry (HDX-MS) is a unique, rapidly evolving technique that has been widely adopted for the characterization of the higher-order structure of proteins. Numerous statistical tools are available in the literature that can be used to identify statistically significant differences in the deuterium uptake values. Biopharmaceutical comparability studies, however, require evidence that two protein samples are highly similar and therefore necessitate a different statistical approach. Hageman et al. recently introduced an innovative HDX-MS equivalence testing method utilizing univariate two one-sided tests (TOST). The acceptance limits were established by the randomized resampling of eight replicate measurements of a reference protein. However, this approach can introduce a non-negligible level of variability in the acceptance limits when the same data set is reanalyzed. In the present study, we enhance this method by replacing the randomized resampling process with the systematic enumeration of all possible combinations of the reference data set, thus eliminating the resampling-induced variation. Because this approach incorporates all measurements, including replicate combinations with markedly elevated variability, it leads to higher acceptance limits. Therefore, we evaluated three strategies: robust outlier detection, a percentile-based method, and a partitioning approach to establish more stringent criteria and reduce patient risk. By applying the enhanced methods to data sets of three approved infliximab biosimilars and a partially deglycosylated NIST mAb used as a mock candidate biosimilar, we demonstrated correct classification of equivalent and nonequivalent samples, making the enhanced evaluation strategy well suited for regulatory comparability assessment.

Studies over the past 3 decades have shown decreased motor adaptation with age. The most widely supported theory for this change proposes that older adults fail to successfully implement cognitive strategies to facilitate performance. However, increased movement variability may also affect adaptation with age, but this has to date remained unstudied. Here, we examine whether age-related increases in movement variability influence adaptation. Healthy older adults (N = 48) exhibited significantly higher levels of baseline movement variability than younger adults (N = 60) in a visuomotor adaptation task, with variability increasing modestly with advancing age. Across all participants, greater movement variability correlated with slower rates of adaptation and smaller aftereffects. In our study, we also manipulated perturbation magnitude and sensory feedback in the task: such manipulations should facilitate participants applying cognitive strategies to the larger, more identifiable perturbation. Altering perturbation magnitude and sensory feedback did not affect the relationship between age and measures of adaptation performance, suggesting that adaptive changes with age cannot be fully accounted for by changes in the generation or the application of cognitive strategies in this task. While our results are correlational, they suggest instead that increased movement variability may contribute to the age-related decline in visuomotor adaptation. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

The photopic negative response (PhNR) is a measure of generalised retinal ganglion cell function. There has been heterogenous methodology to record this, with varied electrode type, stimulus luminance, temporal frequency and measurement approach. This study aimed to empirically explore these features to identify an optimal PhNR luminance-response protocol which produces the lowest variance and maximal efficiency to guide clinical protocols. Twelve healthy participants were recruited (age range 27-51y). Flash ERGs were simultaneously recorded from infraorbital skin and corneal fibre electrodes to a range of red flash stimuli (-0.3-2.4 log cd.s/m2, incremented in 0.3 log units), whilst varying temporal frequency (1-5Hz), background blue luminance (1, 1.5, 2 log cd/m2), and PhNR measurement approach (from baseline or b-wave, as an amplitude or ratio). The luminance-response series data were analysed for changes according to these variables, alongside a calculation of variability. The PhNR luminance-response curves showed few significant differences with increasing temporal frequency, though inter-subject variability was highest for the slowest (1Hz) and highest flash (5Hz) stimulation rates. Background luminance reduced the relative sensitivity (K) but not maximal amplitude of the luminance-response curves (Vmax). With skin electrodes the b-PhNR amplitude and b-PhNR ratio showed the lowest levels of variability compared with other measurement approaches or electrodes. This study demonstrates that temporal frequency can be increased significantly, optimally at 4Hz, without compromising the PhNR. PhNR variance is lower with skin electrode recordings and PhNR amplitude measurements from the b-wave compared to corneal fibre electrodes and baseline-PhNR amplitudes.

Genetic variability is crucial for enhancing economically important traits and for developing effective conservation strategies in livestock populations. In this study, genome-wide genetic variability and population divergence were evaluated in four native Turkish sheep breeds, known as Dağlıç (DGL), Sakız (SKZ), Pırlak (PRL), and Pırıt (PRT), using 366,544 single nucleotide polymorphisms (SNPs) generated by double-digest restriction-site associated DNA sequencing (ddRADseq). Across the four populations, the mean minor allele frequency (MAF) and nucleotide diversity (π) were estimated at 0.320 and 0.295, respectively. Observed heterozygosity (HO) ranged from 0.314 in the DGL breed to 0.323 in the SKZ breed. Expected heterozygosity (HE) values were consistently higher than the observed values across all breeds, with an overall mean of 0.327. The inbreeding coefficient (FIS) was negative in all populations, varying from - 0.034 in PRL to - 0.019 in DGL. Population structure analyses based on discriminant analysis of principal components (DAPC), ADMIXTURE, and TreeMix revealed a high level of admixture between the PRL and PRT populations, whereas the DGL breed was genetically distinct. In addition, TreeMix inferred a migration edge from the SKZ breed to the PRL-PRT clade. The high level of genetic variability observed in native Anatolian sheep breeds should be conserved to support diverse breeding strategies and to mitigate potential future challenges, particularly genetic bottlenecks. Further studies employing improved sampling strategies are recommended to obtain more robust insights into the genetic structure of native Anatolian sheep, especially for the PRL and PRT populations.

BackgroundFacioscapulohumeral muscular dystrophy (FSHD) patients carrying borderline D4Z4 repeat units (DRUs) (8–10) represent a molecularly ambiguous group overlapping FSHD1 and FSHD2, characterized by pronounced phenotypic heterogeneity. This study aimed to determine the association between methylation levels and disease severity, progression in this undercharacterized cohort.MethodsThis single-center and retrospective cohort study (ClinicalTrials.gov: NCT04369209), was conducted at the Fujian Neuromedical Centre (FNMC), China. Methylation levels were quantified using bisulfite sequencing in all participants. Whole-exome sequencing (WES) was performed for all probands. Phenotypic classification followed the Comprehensive Clinical Evaluation Form (CCEF). Motor function was assessed using the FSHD clinical score, clinical severity scale (CSS), and age-corrected CSS. Key functional endpoints were defined as follows: (1) lower extremity involvement, CSS ≥ 3.0; and (2) independent ambulation loss, CSS 4.5–5.ResultsThe patients carrying borderline DRUs exhibited milder phenotypes, broader phenotypic variability and lower methylation levels compared to those carrying 4–7 DRUs. The mean methylation levels of the 10 CpG sites and CpG6 methylation levels showed significant negative correlations with FSHD clinical score, CSS, and age-corrected CSS. Those methylation thresholds effectively discriminated symptomatic from asymptomatic patients with borderline DRUs. Furthermore, patients with lower methylation levels exhibited higher disease penetrance and an increased risk of progressing to lower extremity involvement. In a multigenerational pedigree, cooccurrence of a pathogenic SMCHD1 variant exacerbated hypomethylation and clinical severity.ConclusionsHypomethylation of the distal D4Z4 array serves as a robust biomarker for phenotypic penetrance and disease progression in borderline-allele FSHD. The co-presence of mutations in epigenetic modulators (e.g., SMCHD1) and D4Z4 hypomethylation is correlated with more severe clinical phenotypes, underscoring a compound epigenetic-genetic disease mechanism.

Tolerance mechanisms to UV-B in olive pollen demonstrate cultivar-dependent biochemical responses.

Extreme weather events such as higher temperatures, droughts, and soil salinization are projected to increase as atmospheric CO2 concentrations rise and climate change progresses. These factors have a negative impact on global food security, the water supply, and ecosystem productivity. The focus of this review is on modern concepts, comparative studies, and our data on the mechanisms of adaptation of halophytes and glycophytes with different types of photosynthetic metabolism (C3, C4) to the individual and combined effects of climatic factors. The analysis revealed that C3 and C4 species and C4-NAD-ME and C4-NADP-ME species differ in terms of stability and photosynthetic plasticity. Under drought conditions, both individually and in combination with other factors, C4 halophytes demonstrate the advantages of efficient photosynthesis and salt tolerance. Halophytes with C4-NADP-ME are characterized by uniquely high levels of plasticity and variability in photosynthetic metabolism. This is reflected in their ability to mitigate the negative effects of elevated temperatures and drought through the use of elevated CO2 (eCO2). The mitigating effect of eCO2 on photosynthesis at elevated temperatures was not detected in halophytes, regardless of photosynthesis type. Halophytes possess an augmented capacity for heat tolerance. Integrating fundamental scientific knowledge with urgent practical needs will enable us to predict changes in ecosystems and create new, sustainable agricultural systems.

Myzus persicae (Sulzer), is a major global pest whose control is challenged by widespread insecticide resistance. This study assessed the resistance status of M. persicae populations collected in Greece (2021-2025), using diagnostic bioassays with insecticides (acetamiprid, flupyradifurone, flonicamid, sulfoxaflor and FliPPER) and a newly developed, highly sensitive droplet digital polymerase chain reaction (ddPCR) panel targeting seven key resistance mutations (vgsc: super-kdr M918T/L and kdr L1014F - pyrethroid resistance; acetyl-CoA carboxylase: A2666V - keto-enol resistance; AChE: MACE S431F - dimethyl carbamates resistance; nAChR: R81T and T74I linked to CYP6CY3 overexpression - resistance to nAChR competitive modulators). Bioassays revealed frequent cross-resistance cases. Notably, we report the first case of resistance to flonicamid. FliPPER (fatty acids potassium salts) showed the highest resistance frequency (50.0%) and sulfoxaflor the lowest (1.7%). The ddPCR analysis (on 634 aphids) confirmed the presence of six resistance mutations. The mutation T74I was almost fixed across all populations (mean resistant allele frequency of 99.9%). Other key mutations (MACE, kdr/super-kdr and R81T) were present at moderate-to-high frequencies, with the M918L super-kdr variant showing a notable increase. Myzus persicae in Greece exhibits a high level of genetic variability, leading to severe and dynamic resistance problems. The widespread metabolic resistance (CYP6CY3 overexpression) which has been found to compromise neonicotinoids and fluryradifurone and the emergence of flonicamid resistance complicate the implementation of integrated pest management. The ddPCR panel provides a valid, evidence-based tool for large-scale monitoring of resistance and decision-making, essential for managing this difficult to control pest. However, bioassays are also useful when molecular markers are not available. © 2026 Society of Chemical Industry.

This study addresses the moving heterogeneous worker assembly line balancing problem, a new variant of the classical problem that simultaneously considers worker-dependent task times and worker mobility between stations. In this setting, the processing time of each task differs according to the skills and efficiency of the assigned worker, while workers are allowed to move within a limited range to perform tasks at different stations. These features make the problem more realistic but also substantially more complex, as precedence relations, heterogeneous workloads, cycle time restrictions, and worker movements must all be satisfied simultaneously. To capture these interrelated aspects, mixed integer linear programming is proposed, which can provide exact solutions for small-sized instances. A dataset based on well-known precedence diagrams is generated to evaluate model performance across varying levels of task time variability and worker–station configurations. The results show that the formulation optimally solves small-sized instances, whereas medium and large instances remain computationally demanding, with increasing gaps and longer solving times. The findings further reveal that adding an extra workstation can improve efficiency, especially in larger-sized problem instances. Overall, this study contributes to assembly line literature with a novel mathematical model that integrates worker heterogeneity and mobility, highlighting future research opportunities for heuristic and metaheuristic approaches.

Short-term fluctuations in climate patterns (climate variability) often indicate long-term climate change (CC) trends, which are a global threat to our planet today. CC is speeding up the terrestrial water cycle and potentially affecting groundwater availability, a major component of that cycle. Considering that terrestrial water cycle intensity (WCI) and groundwater level (GWL) are indicators of CC and groundwater availability, respectively, this study explored the dynamic relationship between WCI and GWL anomalies (WCIAs and GWLAs, respectively) in an arid region, based on an innovative approach to statistical correlation and causation analysis. Pearson correlation (r) assessed the strength and direction of a contemporaneous linear relationship between both variables; a cross-correlation function (CCF) determined the dynamic nature of those relationships considering monthly lags up to a predetermined maximum of 12 months; and Granger causality (GC) tests assessed the statistical significance of past values of the lead variable in enhancing the prediction of future values of the lagged variable. A contemporaneous linear relationship between both variables was mostly absent but appeared at various lags. At these lags, the strongest correlations were dominantly negative, with GWLA leading WCIA, as supported by the GC tests. This trend suggests that the intensification of the water cycle reflects a decline in past groundwater levels, necessitating immediate water management actions in the affected areas.

Objective. To analyze severity of psychological maladjustment in military personnel with consequences of combat trauma and effectiveness of innovative rehabilitation technologies with neurofeedback based on acoustic stimulation for its correction. Material and methods. The study involved 100 military personnel with consequences of combat trauma. All patients received basic therapy (BT), including psychotropic medications, psychological counseling and physical exercises. All ones were randomized into 4 groups. The control group received BT alone. In the second group (comparison group 1), patients received a course of bioacoustic correction (BAC) in addition to BT. In the third group (comparison group 2), BT was supplemented with a course of binaural therapy. In the main group, patients received BAC and binaural stimulation in addition to BT. We assessed effectiveness of rehabilitation measures considering psychometric tests, heart rate variability and integral level of functional reserves. Results. BAC therapy was the most effective for chronic pain syndrome. The mechanism is based on modulation of pathological neural activity through EEG-dependent feedback. Binaural therapy demonstrated the greatest results in correcting the manifestations of post-traumatic stress reactions (according to the Mississippi scale), asthenic syndrome (reduced fatigue according to the MFI-20), and anxiety with autonomic dysfunction (lower PARS index). Its action is aimed at synchronizing brain rhythms, increasing parasympathetic tone, and restoring energy resources. Combined therapy (BAC+binaural stimulation) demonstrated the highest efficacy for complex anxiety-depressive disorders and comprehensive rehabilitation of posttraumatic stress disorders due to synergistic effect. Our results allowed for development and validation of methodology for a differentiated approach to selecting medical and psychological rehabilitation strategies based on strict principle of pathogenetic and symptomatic correspondence. According to this approach, maximum clinical and psychophysiological effectiveness is achieved when dominant mechanism of therapeutic factor precisely matches the leading pathogenetic component of certain clinical syndrome. Conclusion. We formulated and empirically substantiated methodology for differentiated use of neuroacoustic technologies in rehabilitation of military personnel with consequences of combat mental trauma. This methodology is based on a strict correspondence between the mechanism of action of physical factor and the leading pathogenetic component of syndrome. The proposed syndrome-oriented algorithm facilitates transition from universal protocols to personalized and diagnosis-guided rehabilitation.

Under pressures of health insurance cost containment and high-quality development, diagnosis-related groups (DRGs) and other case-based payment schemes have become a major direction of China’s inpatient payment reform, yet their impacts may extend beyond changes in mean costs. Using large-scale inpatient settlement data, we evaluate the cost-containment effects of DRG payment reform from a distributional perspective, testing whether the reform is reflected not only in a decline in mean standardized inpatient spending but also in reshaping spending variability and heavy tails (tail risk). The study covers six cities in China’s Province S from January 2019 to December 2021; three cities launched DRG reform in November 2020, January 2021, and June 2021, respectively. The individual-level sample includes 6,882,875 admissions from 172 healthcare institutions and is aggregated into a hospital–month panel; we construct individual standardized inpatient spending as “spending per admission divided by DRG weight,” and then compute the hospital–month mean, standard deviation, skewness, and kurtosis of standardized spending. Our identification strategy applies a two-stage difference-in-differences (DID) estimator suited to staggered adoption to estimate the average treatment effect, and uses the Sun & Abraham event-study approach to test parallel trends and trace dynamic effects; we control for patient composition and city-level covariates and include institution and month fixed effects; we further assess heterogeneity by hospital level and DRG design (point-based vs. rate-based). The two-stage DID results show that DRG implementation is associated with a significant reduction in the hospital–month mean of standardized spending (β = −705.7, p < 0.001) and a significant reduction in the standard deviation (β = −1,098.0, p < 0.001); meanwhile, distributional shape metrics increase, with higher skewness (β = 0.380, p < 0.05) and higher excess kurtosis (β = 18.3, p < 0.01). In the event-study analysis, most pre-reform lead coefficients fluctuate around zero and their confidence intervals largely cover zero, providing overall support for the parallel-trends assumption. Regarding heterogeneity, relative to secondary hospitals, the interaction term for tertiary hospitals is not statistically significant across all four outcomes. Relative to the rate-based design, the point-based design shows a significant mitigating effect on distributional shape metrics, reducing skewness (β = −0.941, p < 0.001) and excess kurtosis (β = −38.4, p < 0.001), while differences in the mean and standard deviation are not statistically significant. While DRG payment reform reduces the mean level of standardized inpatient spending and within-hospital spending variability, it may be accompanied by a strengthened right tail and heavier tails, indicating that “mean-based cost containment” is insufficient to characterize the reform’s structural consequences; distributional metrics and tail risk should be incorporated into routine performance assessment and regulatory frameworks. Compared with the rate-based approach, the point-based approach appears more advantageous in curbing heavy-tail indicators, underscoring the importance of settlement mechanisms and payment-parameter design for risk discipline.

BackgroundThis study investigated the effects of rapid weight-cutting on stress in elite kickboxers by analyzing Heart Rate Variability (HRV) and subjective stress levels using a Visual Analog Scale (VAS).MethodsData were collected across seven standardized time points: Weigh-in Morning, Pre-Weigh-in, Post-Weigh-in, Post–Weigh-in Meal, Match Day Morning, Pre-Match, and Post-Match. Participants were divided into a weight-cutting group (n = 12), who reduced at least 5% of their body weight within 48 h before competition, and a control group (n = 13), who maintained regular training and nutrition. HRV was measured using a chest-strap electrocardiography-based heart rate sensor (Polar H10) to obtain high-accuracy R–R interval data under real-world competition conditions.ResultsThe weight-cutting group showed consistently lower RMSSD values, indicating sustained physiological stress. Subjective stress levels were also higher in this group, peaking before the weigh-in and exceeding pre-match levels. A marked reduction in perceived stress was observed immediately after the weigh-in, suggesting psychological relief. However, despite post-weigh-in rehydration and feeding, RMSSD values remained suppressed on match day, indicating incomplete physiological recovery despite stabilized subjective stress. The control group demonstrated relatively stable HRV and VAS values across all time points.ConclusionsThese findings highlight the prolonged autonomic strain associated with rapid weight-cutting and demonstrate a dissociation between subjective and physiological recovery. Monitoring both autonomic and perceptual stress responses may be essential for safeguarding athlete health and optimizing performance in weight-category sports.Trial registrationClinicalTrials.gov, identifier: NCT06860204.

Variability in running plays a crucial role in distributing biomechanical loads and can be consequently associated with injury risk. This study aims to compare the level of variability between several biomechanical features at different scales of analysis, to investigate the correlations in amplitude and variability, between biomechanical features and the second metatarsal stress, and to explore the inter- and intra-individual variability of the stress distribution in the second metatarsal. Eight participants looped overground on a 45m circuit for 30 minutes, while kinematics, kinetics, and plantar pressure of a stance phase were recorded at each loop. A dynamic finite element model of the foot, driven by muscle forces estimated by a musculoskeletal model, was used to estimate internal loads in the foot. Each variable of interest was classified into a category (ground reaction force (GRF), angles, net joint moments, muscle forces, joint reaction forces and internal bone stress). Variability was quantified using the mean standard deviation over the stance phase and compared both within and between these categories. The study revealed that variability across biomechanical domains of analysis lacked a clear relationship, with GRF components showing the lowest variability and joint angles exhibiting the highest. Although second metatarsal stress amplitude correlated strongly with vertical GRF, joint moments, and muscle forces, its variability showed less consistent correlations and was more participant-dependent. Significant inter/intra-individual variations in second metatarsal von Mises stress amplitude and variability were observed. External ground reaction forces and joint kinematics related quantities, extracted directly from the experimental data, were found to inadequately represent the internal load variability, thus questioning the representativeness of these external features to assess internal stress/load variability.

Abstract Central Chile has undergone a steady shift from traditional annual crops to fruit orchards and vineyards, and a decline in the area dedicated to annual crops. This transition coincides with a decrease in precipitation and an increase in temperature. We compare regions experiencing different levels of variability with observed changes in crop patterns. Our findings suggest significant swings in seasonality and transitions between dry and wet months in certain regions and periods. The most impacted regions coincide with areas undergoing transitions toward water‐intensive crops, which require technical upgrades of irrigation systems. We suggest that farmers are increasingly turning to groundwater rather than surface water, which may pose longer term risks to the sustainability of Central Chile's agricultural systems.

The determinants of population variability across taxa, time, and space are not fully understood, particularly for insects, a group with recent reports of widespread abundance declines. We collated data from unpublished and published sources to calculate indices of interannual population variability for over 4500 unique insect time series, comprising data from nearly 1500 species. We evaluate whether insects exhibit greater population variability than other types of animals. Our results demonstrate that insects as a group indeed exhibit much greater population variability than birds, mammals, or fish, but that within Insecta, included orders show similar levels of population variability. We also find that population variability in insects is greater at higher latitudes, for species with smaller body sizes and for shorter, older time series and that it varies between biomes. Overall, our findings can inform the interpretation and prediction of insect population trends, fluctuations and extinction risk in an era of insect decline.