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Journal articleZhao J, Paschalis A, Gentine P, et al., 2026,
Limited capability of current satellite solar-induced chlorophyll fluorescence reconstructions to capture stomatal responses to environmental stresses
, Communications Earth and Environment, Vol: 7Quantification of the impact of environmental stress on terrestrial vegetation photosynthesis is crucial for our understanding of the global carbon cycle, particularly under a changing climate. Vegetation responses to environmental stress manifest first as plant physiological changes, and at later stages through changes in canopy structure. Here we leverage CO<inf>2</inf> and water flux data from 103 eddy covariance towers and satellite thermal images to assess whether current satellite reconstructions of solar-induced chlorophyll fluorescence capture these plant mechanisms. After removing seasonality using standardized anomalies (z-scores), we found that the relationship between tower-observed gross primary productivity and fluorescence reconstructions considerably weakened across a wide range of biomes. This loss of correlation results from a decoupling between stomatal responses and the physiological emission yield (Φ<inf>F</inf>) of fluorescence reconstructions during soil and atmospheric dry periods. The consequence is that productivity derived from fluorescence reconstructions will be progressively overestimated as dry conditions persist.
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Journal articleAlmalki YR, Karmpadakis I, 2026,
Uncertainty analysis of oscillating water column experiments under regular and random wave conditions
, Renewable Energy, Vol: 271, Pages: 126002-126002, ISSN: 0960-1481 -
Journal articleKristoffersen JC, Kabel T, Georgakis CT, et al., 2026,
Spatio-temporal measurement of laboratory wave fields using LiDAR
, Coastal Engineering, Vol: 209, ISSN: 0378-3839Accurate spatio-temporal measurements of the free-surface elevation are essential for understanding wave evolution, wave breaking, and wave-structure interaction. In laboratory studies, conventional wave gauges provide reliable point measurements but become intrusive and impractical when extended to dense spatial arrays. This study evaluates the capability of a commercially available 3D LiDAR system to resolve the spatio-temporal evolution of regular and irregular waves in a wave flume, through direct comparison with high-resolution camera and wave-gauge measurements.The LiDAR is deployed non-intrusively to capture free-surface elevation over a spatial extent exceeding two wavelengths with high spatial and temporal resolution. Regular and irregular wave conditions are investigated over a sloping bathymetry, including breaking waves. Quantitative comparisons are conducted in the time, frequency, and spatial domains, as well as individual wave statistics. For irregular sea states, significant wave height, individual wave heights, periods, and crest heights derived from LiDAR measurements show close agreement with wave gauge estimates, with root-mean-square errors typically below 6% of the significant wave height and correlation coefficients exceeding 0.97 outside the immediate vicinity of the LiDAR.Systematic deviations are observed directly beneath the LiDAR. Under breaking conditions, the LiDAR preferentially captures the densest part of the overturning crest and aerated surface, revealing inherent differences between optical and probe-based definitions of the free surface. These effects are quantified, and practical guidance on sensor placement, data processing, and interpretation is provided. Overall, the results demonstrate that LiDAR offers a robust and efficient alternative to dense wave gauge arrays for laboratory studies requiring spatio-temporal resolution of wave fields.
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Journal articleWright W, Craske J, Karmpadakis I, 2026,
Real-time phase-resolved wave prediction over planar coastal bathymetries using U-Net convolutional neural networks
, Coastal Engineering, Vol: 209, ISSN: 0378-3839Real-time, phase-resolved forecasting of waves is essential for safe operations in the coastal zone, for example, by enabling early-warning systems to inform real-time decision-making. However, non-linear transformations, depth variations and wave breaking limit the accuracy of theoretical models. This study presents a data-driven alternative using convolutional neural networks to predict nearshore surface elevation time series. The proposed method is developed for long-crested waves over planar slopes, predicting surface elevations up to approximately 6 peak periods in advance. Specifically, a U-Net architecture with three encoding and three decoding stages and approximately 200,000 trainable parameters is used, with the prediction based on a short time window from a single offshore gauge. Laboratory experiments of long-crested waves propagating over sloping beds were used for training and testing, covering multiple bed slopes and a wide range of spectral shapes, peak periods, and steepnesses. Model performance was compared against predictions from linear and second-order wave theories with shoaling corrections. The neural network reproduced the measured wave evolution with consistently lower errors than the theoretical models, particularly in shallow water where nonlinearity and breaking become dominant. It also captured wave arrival times with higher accuracy than the theoretical models, and showed robustness when applied to unseen sea states or slightly noisy input signals. These results show that within this laboratory regime, neural networks can extend phase-resolved wave prediction into the coastal zone, complementing traditional theoretical approaches and offering a practical framework which, with further development, could provide real-time operational forecasting based on offshore wave data.
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Journal articleZhou Z, Chandresh R, Whittaker A, et al., 2026,
Sediment supply controls on channel morphological adjustments to tectonics and lithology
, Earth and Planetary Science Letters, Vol: 685, ISSN: 0012-821XIn nature, rivers not only incise bedrock but also transport sediment supplied to them; however, incision is often assumed to dominate over sediment transport in shaping channel geometry so as to exploit the simplicity of the stream power law. This likely flawed assumption raises fundamental concerns about inverting channel morphology to map external forcing, such as active deformation. Central to this issue is how relative sediment flux (i.e. sediment supply relative to transport capacity, Qs/Qt) modulates the efficacy of excess shear stress in incising bedrock, known as the relative sediment flux function. Two competing functions have been proposed, but resolving them in the field has proven challenging to date. Here, we address this issue by contrasting two rivers in the Gulf of Corinth, Greece that traverse comparable gradients in tectonics and lithology with distinct relative sediment fluxes. We show that the sediment-rich Phoenix river, with an estimated Qs/Qt value ∼0.8, has a much lower sensitivity of excess shear stress to tributary sediment input than the sediment-poor Sithas river. To our knowledge, this represents the first field evidence supporting the function with a markedly decreased sensitivity to Qs/Qt at high Qs/Qt values. This allows us to clarify the importance and mechanisms of channel slope versus width adjustment in reaching the excess shear stress required for equilibrium. As a result, we outline the conditions under which the widely used stream power law and its associated metrics, such as steepness and knickpoints, can (or cannot) be sensibly employed.
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Journal articleFeng H, Marini G, Barabás É, et al., 2026,
Modelling the risk of West Nile virus infection in seven European countries from published serological and case notification data, 2008 to 2022
, Eurosurveillance, Vol: 31<jats:sec> <jats:title>BACKGROUND</jats:title> <jats:p>West Nile virus (WNV) is a zoonotic mosquito-borne pathogen increasingly reported in Europe.</jats:p> </jats:sec> <jats:sec> <jats:title>AIM</jats:title> <jats:p>We aimed to characterise heterogeneities in the average annual human risk of WNV infection (force of infection, FOI) and in WNV surveillance across Europe.</jats:p> </jats:sec> <jats:sec> <jats:title>METHODS</jats:title> <jats:p>We conducted a systematic review following the PRISMA guidelines to identify serological studies on WNV in humans with IgG-based assays in Europe. We then used mathematical models fitted to both age-stratified serosurvey and case data to reconstruct spatially explicit FOI estimates, the sensitivity of syndromic surveillance and age-dependent trends in case reporting.</jats:p> </jats:sec> <jats:sec> <jats:title>RESULTS</jats:title> <jats:p>We extracted 92 serosurvey datasets from 21 countries. Based on 10 age-stratified serosurvey datasets from Greece, Hungary, Italy, Romania and Spain and case data from seven countries (Austria, Cyprus, Greece, Hungary, Italy, Romania and Spain), we estimated the WNV FOI for 119 European nomenclature of territorial units for statistics level (NUTS) 0-3 regions. We found evidence of spatial heterogeneities in transmission intensity and estimated that on average less than 0.2% of human WNV infections were notified, with country variability and age-dependent trends in the propensity of reporting WNV disease.</jats:p> </jats:sec> <jats:sec> <jats:t
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OtherM Jaison A, Ceppi P, Wilson Kemsley S, 2026,
Supplementary material to "The role of the QBO for tropical high-cloud variability in CMIP6 models and observations"
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Journal articleGan W, Alizadeh N, Best M, et al., 2026,
An eco-evolutionary optimality model explains the acclimated temperature response of photosynthesis
, New Phytologist, Vol: 250, Pages: 2884-2899, ISSN: 0028-646XThe optimal temperature of net photosynthesis (Topt) generally increases with plant growth temperature. Changes in Topt are associated with changes in the maximum carboxylation capacity at 25 °C (Vcmax25) and the maximum electron transport rate at 25 °C (Jmax25). The ratio between Jmax25 and Vcmax25 declines with warming. Accurate representation of leaf-level photosynthetic responses to temperature is essential for realistic projections of the terrestrial carbon cycle and its response to ongoing climate changes. However, many land-surface models incorporate thermal acclimation through empirical approaches and through assigning distinct but static parameter values to plant functional types (PFTs). Eco-evolutionary optimality approaches provide a simpler way of modelling photosynthesis without recourse to PFTs. Here we use the sub-daily P model, an eco-evolutionary optimality-based model of photosynthesis that explicitly separates the instantaneous and acclimated responses of photosynthetic parameters to temperature to investigate how optimal temperature changes with growth temperature, as represented by leaf or air temperature. We show that the simulated responses are consistent with observations from both controlled experiments and eddy-covariance flux tower data. We show that changes in Topt, and in the assimilation rate at Topt, are caused by changes in carboxylation capacity and electron transport rate that follow directly from the hypotheses underlying the model.
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Journal articleQuijada Rodriguez ML, Vicco A, Bajura F, et al., 2026,
Dengue epidemiology and transmission intensity across Panama during 2000-2024: a modelling study
, The Lancet Regional Health. Americas, Vol: 58, ISSN: 2667-193XBackgroundPanama is a dengue endemic country which experienced a large outbreak in 2024 with over 32,000 reported cases and an incidence rate exceeding 700 cases per 100,000 inhabitants. Despite decades of circulation, the epidemiology of dengue and its heterogeneity in transmission intensity across Panama have not yet been characterised.MethodsWe used 25 years of dengue case notification and population data from across Panama's 16 health regions and 82 districts to characterise dengue epidemiology and transmission intensity in the country. The analytic dataset comprised 128,890 dengue cases, of whom 52% were female and 48% were male; the mean age was 32.4 years (range 0–108 years). Ethnicity data are not collected in Panama's national dengue surveillance system and were therefore unavailable for this analysis. We characterised spatial heterogeneities in delay distributions by fitting parametric probability distributions to epidemiological delays, and demographic differences in the incidence risk ratio of dengue, and of dengue attributable hospitalisations and deaths. We also implemented catalytic models to infer the time-constant dengue force-of-infection (FOI) (i.e. the long-term average annual per capita risk of infection for a susceptible individual) from the age-stratified case notification data reported across Panama during 2000–2024 and explored age- and sex-related differences in dengue case reporting in sensitivity analyses.FindingsWe observed spatial variation in delay distributions across health regions. The mean of the regional average time from symptoms onset to (i) reporting was 4.78 days (95% CI: 4.72–4.84 days), (ii) hospitalisation was 4.49 days (95% CI: 4.22–4.76), and (iii) recovery was 7.82 days (95% CI: 6.47–8.85 days). The dengue transmission intensity also showed spatial heterogeneity, with a mean regional per-serotype FOI of 0.008 (95% CrI: 0.004–0.015). The mean regional probability of detecting a secondar
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Journal articleCeppi S, Mshanga N, Mkindi A, et al., 2026,
Hydro-climatic anomalies and livelihoods associated with thinness among children and adolescents in Mount Meru, Tanzania
, ISSN: 2055-0928BackgroundSchool-aged children and adolescents face significant nutritional challenges in sub-Saharan Africa yet remain understudied compared to under-five populations. Climate variability increasingly threatens food security in rural communities, but evidence on climate-nutrition relationships beyond early childhood is limited. We investigated associations between hydro-climatic anomalies, livelihood strategies, demographic characteristics, and thinness among school-aged children and adolescents on the slopes and surrounding plains of Mount Meru, northern Tanzania.MethodsWe analysed five waves of anthropometric data from 26,009 records of children and adolescents aged 6–18 years attending 18 public primary schools in the Mount Meru ecosystem between 2010 and 2015. Thinness was defined as BMI-for-age Z-score < -2 using the World Health Organisation (WHO) 2007 growth references. Bayesian logistic mixed-effects models were used with school-level and temporal random effects to examine associations of thinness with sex, age, dominant livelihood (farming, agropastoralism, pastoralism), and standardized anomalies in precipitation, evapotranspiration, and land-surface temperature.ResultsOverall thinness prevalence ranged from 61.2% in 2010 to 72.7% in 2015. Girls had lower odds of undernutrition than boys (odds ratio [OR]: 0.58, 95% credible interval [CrI]: 0.54–0.61), but age-sex interactions revealed complex developmental patterns. Girls showed peak vulnerability at age 12 years followed by sharp decline, while boys demonstrated more sustained risk through mid-adolescence. Children and adolescents from pastoralist communities had substantially higher undernutrition odds compared to farming communities (OR: 2.21, 95%CrI: 1.31–3.50). Above-normal precipitation was protective (OR: 0.34, 95% CrI: 0.20–0.54), while elevated evapotranspiration increased the odds of thinness (OR: 2.18, 95%CrI: 1.41–3.24).ConclusionsThe odds of thinness among sch
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