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Both oxygen and temperature are fundamental factors determining metabolic performance, fitness, ecological niches, and responses of many aquatic organisms to climate change. Despite the importance of physical and physiological constraints on oxygen supply affecting aerobic metabolism of aquatic ectotherms, ecological theories such as the metabolic theory of ecology have focused on the effects of temperature rather than oxygen. This gap currently impedes mechanistic models from accurately predicting metabolic rates (i.e., oxygen consumption rates) of aquatic organisms and restricts predictions to resting metabolism, which is less affected by oxygen limitation. Here, we expand on models of metabolic scaling by accounting for the role of oxygen availability and temperature on both resting and active metabolic rates. Our model predicts that oxygen limitation is more likely to constrain metabolism in larger, warmer, and active fish. Consequently, active metabolic rates are less responsive to temperature than are resting metabolic rates, and metabolism scales to body size with a smaller exponent whenever temperatures or activity levels are higher. Results from a metaanalysis of fish metabolic rates are consistent with our model predictions. The observed interactive effects of temperature, oxygen availability, and body size predict that global warming will limit the aerobic scope of aquatic ectotherms and may place a greater metabolic burden on larger individuals, impairing their physiological performance in the future. Our model reconciles the metabolic theory with empirical observations of oxygen limitation and provides a formal, quantitative framework for predicting both resting and active metabolic rate and hence aerobic scope of aquatic ectotherms.

Considerable research is aimed at developing predictions of ecosystem responses to climate change, focusing on the spatial scale, such as range shifts and contractions, as well as activity restrictions to shaded microhabitats. On the other hand, the ability of species to shift their activity times during the diel cycle, and consequently to alter the environment in which activity occurs, has been largely neglected. Daily activity patterns are perceived as fairly fixed; however, natural changes in activity patterns have been reported in increasing numbers of species. Here, we present a framework that explores how shifts in activity patterns may buffer impacts of climate change. To demonstrate our framework, we simulated costs of activity of diurnal and nocturnal rodents and showed that future summers may decrease the energetic demands of nocturnal mammals while increasing water demands of diurnal mammals. Climate projections suggest that vegetation cover and water availability will decrease under future climate scenarios, especially in areas where water demands are expected to increase the most. These changes are expected to limit the ability of diurnal animals to restrict activity to shaded microhabitats and to keep a positive water balance. Our analysis shows that by shifting to nocturnality, diurnal mammals may mitigate the high water costs of future summers. We suggest that future research should explore the role of the diel time axis as an ecological resource when predicting the impacts of climate change.

The escalation in extreme weather events has raised concerns for agriculture. The quantification of the impacts of extreme events on crop yield has predominantly concentrated on individual events like drought or heat. Numerous instances have showcased the destructive effects of compound extreme events on crop yields, surpassing those of individual events. However, their influence extent is region‐specific and not fully understood in Australia's crop belt. Using a biophysical‐statistical modeling approach, we quantified the individual impacts of drought, heat, frost, and compound drought and extreme temperature (DET) events on wheat yield variations in Australia. We first developed indices for these different extreme events during the wheat reproductive period based on the APSIM (Agricultural Production System sIMulator) model and then used these indices in multiple linear regression models to quantify their impacts on wheat yield variations. We found that, during 1990–2021, drought, heat, and frost events explained 48% of yield variation, while the percentage increased to 54% after including DET events, with some regions even up to 86%. In extreme low‐yield years, the relative importance of DET events surpassed the sum importance of individual drought, heat, and frost events, reaching 52% in years with yields below the 10th percentiles, respectively. Our findings highlight the need to factor compound extreme weather events into climate risk management to inform the mitigation of yield losses or crop failure. Plain Language Summary Global warming has brought more extreme weather events like drought, heatwaves, frost, etc. These extreme events seriously threaten agricultural production and food security, especially multiple co‐occurring weather events, which usually cause far more destructive effects than individual ones. In this study, we used a combined modeling approach to precisely quantify the impacts of individual and co‐occurring extreme weather events on wheat yield variation over the past three decades in Australia. We found that these extreme weather events were responsible for more than half of the wheat yield variation, with multiple co‐occurring extreme weather events particularly responsible for severe wheat yield losses in Australia. These findings highlight the need to factor co‐occurring extreme weather events into climate risk management to inform the mitigation of yield losses or crop failure. Key Points We developed a combined modeling approach to quantify the effects of compound drought and extreme temperature (DET) on wheat yield Annual average DET intensity contributed an additional 6% of Australia's wheat yield variation beyond univariate drought, heat, and frost intensities In extreme low‐yield years, annual average DET intensity dominated wheat yield loss, with relative contribution exceeding 50%

Across all kingdoms of life, maintaining the correct cell shape is critical for behaviors such as sensing, motility, surface attachment, and nutrient acquisition. Maintaining proper shape requires cellular-scale coordination of proteins and feedback systems that enable responses that correct local morphological perturbations. Here, we demonstrate that the MreB cytoskeleton in Escherichia coli preferentially localizes to regions of negative curvature, directing growth away from the poles and actively straightening locally curved regions of the cell. Moreover, our biophysical simulations of curvature-biased growth suggest that cell wall insertion causes surface deformations that could be responsible for the circumferential motion of MreB. Taken together, our work demonstrates that MreB’s local orchestration of persistent, bursty growth enables robust, uniform growth at the cellular scale. Cells typically maintain characteristic shapes, but the mechanisms of self-organization for robust morphological maintenance remain unclear in most systems. Precise regulation of rod-like shape in Escherichia coli cells requires the MreB actin-like cytoskeleton, but the mechanism by which MreB maintains rod-like shape is unknown. Here, we use time-lapse and 3D imaging coupled with computational analysis to map the growth, geometry, and cytoskeletal organization of single bacterial cells at subcellular resolution. Our results demonstrate that feedback between cell geometry and MreB localization maintains rod-like cell shape by targeting cell wall growth to regions of negative cell wall curvature. Pulse-chase labeling indicates that growth is heterogeneous and correlates spatially and temporally with MreB localization, whereas MreB inhibition results in more homogeneous growth, including growth in polar regions previously thought to be inert. Biophysical simulations establish that curvature feedback on the localization of cell wall growth is an effective mechanism for cell straightening and suggest that surface deformations caused by cell wall insertion could direct circumferential motion of MreB. Our work shows that MreB orchestrates persistent, heterogeneous growth at the subcellular scale, enabling robust, uniform growth at the cellular scale without requiring global organization.

We developed a chemical cleavage method that releases single nucleosome dyad-containing fragments, allowing us to precisely map both single nucleosomes and linkers with high accuracy genome-wide in yeast. Our single nucleosome positioning data reveal that nucleosomes occupy preferred positions that differ by integral multiples of the DNA helical repeat. By comparing nucleosome dyad positioning maps to existing genomic and transcriptomic data, we evaluated the contributions of sequence, transcription, and histones H1 and H2A.Z in defining the chromatin landscape. We present a biophysical model that neglects DNA sequence and shows that steric occlusion suffices to explain the salient features of nucleosome positioning.

Sustaining ecosystem services (ES), mitigating their tradeoffs and avoiding unfavorable future trajectories are pressing social-environmental challenges that require enhanced understanding of their relationships across scales. Current knowledge of ES relationships is often constrained to one spatial scale or one snapshot in time. In this research, we integrated biophysical modeling with future scenarios to examine changes in relationships among eight ES indicators from 2001-2070 across three spatial scales-grid cell, subwatershed, and watershed. We focused on the Yahara Watershed (Wisconsin) in the Midwestern United States-an exemplar for many urbanizing agricultural landscapes. Relationships among ES indicators changed over time; some relationships exhibited high interannual variations (e.g. drainage vs. food production, nitrate leaching vs. net ecosystem exchange) and even reversed signs over time (e.g. perennial grass production vs. phosphorus yield). Robust patterns were detected for relationships among some regulating services (e.g. soil retention vs. water quality) across three spatial scales, but other relationships lacked simple scaling rules. This was especially true for relationships of food production vs. water quality, and drainage vs. number of days with runoff >10 mm, which differed substantially across spatial scales. Our results also showed that local tradeoffs between food production and water quality do not necessarily scale up, so reducing local tradeoffs may be insufficient to mitigate such tradeoffs at the watershed scale. We further synthesized these cross-scale patterns into a typology of factors that could drive changes in ES relationships across scales: (1) effects of biophysical connections, (2) effects of dominant drivers, (3) combined effects of biophysical linkages and dominant drivers, and (4) artificial scale effects, and concluded with management implications. Our study highlights the importance of taking a dynamic perspective and accounting for spatial scales in monitoring and management to sustain future ES.

The eelgrass Zostera marina is an important foundation species of coastal areas in the Northern Hemisphere, but is continuing to decline, despite management actions. The development of new management tools is therefore urgent in order to prioritize limited resources for protecting meadows most vulnerable to local extinctions and identifying most valuable present and historic meadows to protect and restore, respectively. We assessed 377 eelgrass meadows along the complex coastlines of two fjord regions on the Swedish west coast—one is currently healthy and the other is substantially degraded. Shoot dispersal for all meadows was assessed with Lagrangian biophysical modeling (scale: 100–1,000 m) and used for barrier analysis and clustering; a subset (n = 22) was also assessed with population genetic methods (20 microsatellites) including diversity, structure, and network connectivity. Both approaches were in very good agreement, resulting in seven subpopulation groupings or management units (MUs). The MUs correspond to a spatial scale appropriate for coastal management of “waterbodies” used in the European Water Framework Directive. Adding demographic modeling based on the genetic and biophysical data as a third approach, we are able to assess past, present, and future metapopulation dynamics to identify especially vulnerable and valuable meadows. In a further application, we show how the biophysical approach, using eigenvalue perturbation theory (EPT) and distribution records from the 1980s, can be used to identify lost meadows where restoration would best benefit the present metapopulation. The combination of methods, presented here as a toolbox, allows the assessment of different temporal and spatial scales at the same time, as well as ranking of specific meadows according to key genetic, demographic and ecological metrics. It could be applied to any species or region, and we exemplify its versatility as a management guide for eelgrass along the Swedish west coast.

Purpose Fluorescence imaging is critical for intraoperative intestinal perfusion assessment in colorectal surgery, yet its clinical adoption remains limited by subjective interpretation and lack of quantitative standards. This study introduces an integrated approach combining fluorescence curve analysis, biophysical modeling, and machine learning to improve intraoperative perfusion assessment. Methods Laparoscopic fluorescence videos from 68 low rectal cancer patients were analyzed, with 1,263 measurement points (15–20 per case) selected along colonic bands. Fluorescence intensity dynamics were extracted via color space transformation, video stabilization and image registration, then modeled using the Random Sample Consensus (RANSAC) algorithm and nonlinear least squares fitting to derive biophysical parameters. Three clinicians independently scored perfusion quality (0–100 scale) using morphological features and biophysical metrics. An XGBoost model was trained on these parameters to automate scoring. Results The model achieved superior test performance, with a root mean square error (RMSE) of 2.47, a mean absolute error (MAE) of 1.99, and an R 2 of 97.2%, outperforming conventional time-factor analyses. It demonstrated robust generalizability, showing no statistically significant prediction differences across age, diabetes, or smoking subgroups (P > 0.05). Clinically, low perfusion scores in distal anastomotic regions were significantly associated with postoperative complications (P < 0.001), validating the scoring system’s clinical relevance and discriminative capacity. The automated software we developed completed analyses within 2 min, enabling rapid intraoperative assessment. Conclusion This framework synergistically enhances surgical evaluation through three innovations: (1) Biophysical modeling quantifies perfusion dynamics beyond time-based parameters; (2) Machine learning integrates multimodal data for surgeon-level accuracy; (3) Automated workflow enables practical clinical translation. By addressing limitations of visual assessment through quantitative, rapid, and generalizable analysis, this method advances intraoperative perfusion monitoring and decision-making in colorectal surgery.

•Digital design and 3D printing of TES caps could allow for flexible positioning of stimulation electrodes.•We provide an in silico proof-of-concept that more flexible positioning significantly increases target engagement.•Personalized optimization with >64 available electrode positions outperformed other montages in terms of correlation of the electric field magnitude with the target and focality across all achievable target intensities.•Further gains are expected if design constraints are better integrated into the montage selection approach. Transcranial electric stimulation (TES) is a non-invasive neuromodulation technique with therapeutic potential for diverse neurological disorders including Alzheimer's disease. Conventional TES montages with stimulation electrodes in standardized positions suffer from highly varying electric fields across subjects due to variable anatomy. Biophysical modelling using individual's brain imaging has thus become popular for montage planning but may be limited by fixed scalp electrode locations. Here, we explore the potential benefits of flexible electrode positioning with 3D-printed neurostimulator caps. We modeled 10 healthy subjects and simulated montages targeting the left angular gyrus, which is relevant for restoring memory functions impaired by Alzheimer's disease. Using quantitative metrics and visual inspection, we benchmark montages with flexible electrode placement against well-established montage selection approaches. Personalized montages optimized with flexible electrode positioning provided tunable intensity and control over the focality-intensity trade-off, outperforming conventional montages across the range of achievable target intensities. Compared to montages optimized on a reference model, personalized optimization significantly reduced variance of the stimulation intensity in the target. Finally, increasing available electrode positions from 32 to around 86 significantly increased target engagement across a range of target intensities and current limits. In summary, we provide an in silico proof-of-concept that digitally designed and 3D-printed TES caps with flexible electrode positioning can increase target engagement with precise and tunable control of applied dose to a cortical target. This is of interest for stimulation of brain networks such as the default mode network with spatially proximate correlated and anti-correlated cortical nodes. [Display omitted]

Recent studies indicate that astrocytes show heterogeneity in morphology and physiological function. They integrate synaptic signals and release calcium in reaction to active neurons. These calcium signals are not yet fully understood as they are highly dependent on the cell's morphology, which can vary across and within brain regions. We found structural heterogeneity among mouse hippocampal CA1 astrocytes based on geometric features, clustering 741 cells into six classes. Of those, we selected 84 cells and reconstructed their morphology based on confocal microscope images and converted them into multi-compartment models with a high detailedness. We applied a computational biophysical model simulating the intracellular ion and IP 3 signaling and diffusion in those 3D cell geometries. The cells were stimulated with three different glutamate stimuli. Calcium mainly oscillated in the stimulated and the neighboring compartment but not in the soma. Significant differences were found in the peak width, mean prominence, and mean peak amplitude of the calcium signal when comparing the signals in the stimulated and neighboring compartments. Overall, this study highlights the influence of the complex morphology of astrocytes on intracellular ionic signaling.