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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 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 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 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 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 articleWarder SC, Piggott MD, 2026,
Wind farm wake losses under future build-out scenarios
, Wind Energy and Engineering Research, Vol: 5, Pages: 100025-100025, ISSN: 2950-3604 -
Journal articleHoward BC, Awuni C, Agyei-Mensah S, et al., 2026,
Coproduced assessments of climate change adaptation reveal equity challenges in locally led approaches.
, Environ Res Lett, Vol: 21, ISSN: 1748-9326Systematic assessments of climate change adaptation are critical for monitoring progress and planning effectively, but current approaches are limited in their scope, accuracy, and relevance to local contexts. Here, we present an improved approach using coproduction to quantitively assess adaptation based on local knowledge and priorities. This is applied to locally led adaptation (LLA) to flood risk in Tamale, Ghana, to provide the first quantitative assessments of this increasingly common adaptation practice. Through a multi-year process, including community marble distribution, focus groups, and household surveys, 11 LLA solutions were assessed. Assessments were based on adaptation success criteria that mattered most to local communities and included important considerations that are commonly missing from technical assessments, including multiple risk-reduction mechanisms, equity, sustainability, and co-impacts. Community-based and behavioural LLA solutions, such as collective action and tree planting, were deemed most effective, whilst structural and technical solutions were ranked lower. By integrating these assessments into a flood risk model, we show that LLA approaches significantly reduced flood risk overall but did not address existing inequalities. Our results showcase the potential of coproduction to increase the scope and robustness of adaptation assessments and highlight practical challenges of delivering on the LLA principles in real-world settings.
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Journal articleSandoval Calle D, Flo V, Morfopoulos C, et al., 2026,
Environmental influences on the maximum quantum yield of terrestrial primary production
, New Phytologist, ISSN: 0028-646XHistorically, terrestrial biosphere models (TBMs) have assigned the intrinsic (maximum) quantum yield of photosynthesis (π) a constant value for each plant functional type. However, experimental studies have shown that π – when measured on light adapted leaves – depends on temperature. It is unclear whether this dependence is universal or biome-specific; how it is manifested at the ecosystem level; and how it should be represented in TBMs. By fitting empirical light-response curves to a global set of eddy-covariance CO2 flux measurements and correcting for photorespiration, we inferred apparent, ecosystem level πvalues and their temperature responses across a wide range of environments. The temperature response of apparent ecosystem-level π follows a universal bell shaped curve. The shape of this curve does not markedly differ among biomes, but the maximum value of π decreases with increasing aridity, its temperature optimum increases with increasing growth temperature, and its sensitivity to temperature increases as growth temperature declines. Our model for π(π) aligns with recent theory highlighting the role of cytochrome b6f in regulating the light reactions of photosynthesis. If implemented in TBMs, this model should allow better predictions of the responses of terrestrial ecosystem function to a warming climate.
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Journal articleZhao J, Bai L, Zhan R, et al., 2026,
Distinct impacts of tropical North Atlantic warming flavors on cross-basin tropical cyclone activity.
, Sci Adv, Vol: 12Tropical North Atlantic (TNA) warming typically favors tropical cyclone (TC) genesis over the North Atlantic but suppresses TC formation over the Northwest Pacific during boreal summer. The TNA anomaly patterns can be classified into an eastern coastal and a western warm-pool type, but their respective impacts remain unclear. Here, we find a pronounced difference in the impact between the two TNA flavors. The warm-pool TNA warming suppresses Northwest Pacific TC genesis through a remote dynamical control, while the coastal warming promotes North Atlantic TC genesis via a local thermodynamic control. High-resolution modeling reveals that, compared with the canonical TNA warming, the warm-pool TNA warming suppresses Northwest Pacific TC genesis by 65.2%, while the coastal warming enhances North Atlantic TC genesis by 60.1%. Under greenhouse warming, increased coastal TNA warming is projected to intensify North Atlantic TC activity. Therefore, distinguishing TNA flavors is critical for improving seasonal prediction and future projections of cross-basin TC activity.
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