Plausible Changes Research Articles

Exploring the Spatially Compounding Multi‐Sectoral Drought Vulnerabilities in Colorado's West Slope River Basins

AbstractThe state of Colorado's West Slope Basins are critical headwaters of the Colorado River and play a vital role in supporting Colorado's local economy and natural environment. However, balancing the multi‐sectoral water demands in the West Slope Basins while maintaining crucial downstream deliveries to Lake Powell is an increasing challenge for water managers. Internal variability of the hydroclimatic system and climate change complicate future vulnerability assessments. This work contributes a detailed accounting of multi‐sectoral drought vulnerability in the West Slope Basins and the impacts of drought on downstream deliveries. We first introduce a novel multi‐site Hidden Markov Model (HMM)‐based synthetic streamflow generator to create an ensemble of streamflows for all West Slope basins that better characterizes the region's drought extremes. We capture the effects of climate change by perturbing the HMM to generate an ensemble of streamflows reflecting plausible changes in climate. We then route both ensembles through StateMod, Colorado's water allocation model, to evaluate spatially compounding drought impacts across the West Slope Basins. Our results illustrate how drought events emerging from the system's stationary internal variability in the absence of climate change can significantly impact local water uses and deliveries to Lake Powell, exceeding extreme conditions in the historical record. Further, we find that even modest climate change can cause a regime shift where historically low downstream delivery volumes and extreme drought impacts become routine. These results can inform future Colorado River planning efforts, and our methodology can be expanded to other snow‐dominated regions that face persistent droughts.

How does running technique change with running speed? A quantitative analysis based on practice-informed principal components

Introduction & Purpose “Running technique is an important component of running economy and performance” (Folland et al., 2017). While economy and performance can directly be measured, no common measuring method exists for running technique. The aims of this study were twofold: (I) develop practice-informed running technique measures based on technique characterizations used by coaches (i.e. distinct variations of body segment movements instead of discrete kinematics); (II) investigate, how running technique changes with running speed. Methods Two independent kinematic data sets were recorded on a treadmill using a retro-reflective marker setup (“Plugin-Gait”) and a 10-camera system (Vicon Motion Systems Ltd., Oxford, UK). First, 20 experienced runners (age 25 ± 2 y; 10 females, 10 males) were tasked to vary their running according to 14 technique elements (vertical, horizontal, hip and upper body movement, foot strike, track width, ankle rotation, leg swing, back posture, elbow flexion/extension, arm swing amplitude and direction, gaze direction, cadence) into two opposing extreme forms per element. Measures for the 14 running technique elements were developed using principal component analyses (one PCA per two opposing technique element variations) and selecting principal components (PCs; Federolf, 2016) that aligned with the represented technique element. Second, an additional 19 experienced runners (age 30 ± 9 y, 3 females, 16 males) ran at different speeds (10-17 km/h with 1 km/h incremental steps) without any technique instructions. Their data were projected onto the selected PCs, resulting in averaged PC score waveforms of the different speeds along each technique element. Waveforms were analysed using statistical parametric mapping (SPM) with a repeated measures ANOVA design (Pataky et al., 2013). Results For all 14 technique elements, sections of significant differences between at least two different speeds were found within the cycle-normalized PC score waveforms. Figure 1 exemplifies the results for the foot track width, where the lateral range of motion of the feet decreased with speed. Post-hoc analyses revealed further differences, such as less vertical and greater horizontal movement, as well as smaller leg swing and greater arm swing amplitude at 17 km/h compared to 10 km/h. Discussion Firstly, practice-informed and data-driven running technique measures could be developed (I). Secondly, the measures could be applied on a group of runners and plausible changes in their technique due to running speed were identified (II). So far, the speed-dependent technique adaptations only reflect the specific techniques on a treadmill for a predominately male reference group, but the presented concept can be transferred to other runners and settings. Conclusion Running technique varies with speed, and the developed technique measures facilitate comparisons of these differences using practically relevant technique elements. Since the movement adaptations associated with running speed are directly quantifiable and visualizable, technique models for different speed ranges might be developed by researchers and then utilized by runners to train and assess their technique in alignment with these models.

Interval abstractions for robust counterfactual explanations

Counterfactual Explanations (CEs) have emerged as a major paradigm in explainable AI research, providing recourse recommendations for users affected by the decisions of machine learning models. However, CEs found by existing methods often become invalid when slight changes occur in the parameters of the model they were generated for. The literature lacks a way to provide exhaustive robustness guarantees for CEs under model changes, in that existing methods to improve CEs' robustness are mostly heuristic, and the robustness performances are evaluated empirically using only a limited number of retrained models. To bridge this gap, we propose a novel interval abstraction technique for parametric machine learning models, which allows us to obtain provable robustness guarantees for CEs under a possibly infinite set of plausible model changes Δ. Based on this idea, we formalise a robustness notion for CEs, which we call Δ-robustness, in both binary and multi-class classification settings. We present procedures to verify Δ-robustness based on Mixed Integer Linear Programming, using which we further propose algorithms to generate CEs that are Δ-robust. In an extensive empirical study involving neural networks and logistic regression models, we demonstrate the practical applicability of our approach. We discuss two strategies for determining the appropriate hyperparameters in our method, and we quantitatively benchmark CEs generated by eleven methods, highlighting the effectiveness of our algorithms in finding robust CEs.

Cost-consequence analysis of computer vision-based skin prick tests: implications for cost containment in Switzerland

BackgroundSkin prick tests (SPTs), or intraepidermal tests, are often the first diagnostic approach for people with a suspected allergy. Together with the clinical history, SPTs allow doctors to draw conclusions on allergies based on the sensitization pattern. The purpose of this study is to investigate the potential cost consequences that would accrue to a Swiss University hospital after the adoption of computer vision-based SPTs.MethodsWe conducted a cost-consequence analysis from a hospital’s perspective to evaluate the potential cost consequences of using a computer vision-based system to read SPT results. The patient population consisted of individuals who were referred to the allergology department of one of the five university hospitals in Switzerland, Inselspital, whose allergology department averages 100 SPTs a week. We developed an early cost-consequence model comparing two SPT techniques; computer vision-based SPTs conducted with the aid of Nexkin DSPT and standard fully manual SPTs. Probabilistic sensitivity analysis and additional univariate sensitivity analyses were used to account for uncertainty.ResultsThe difference in average cost between the two alternatives from a hospital’s perspective was estimated to be CHF 7 per SPT, in favour of the computer vison-based SPTs. Monte Carlo probabilistic simulation also indicated that SPTs conducted using the computer vision-based system were cost saving compared to standard fully manual SPTs. Sensitivity analyses additionally demonstrated the robustness of the base case result subject to plausible changes in all the input parameters, with parameters representing the costs associated with both SPT techniques having the largest influence on the incremental cost. However, higher sensitization prevalence rates seemed to favour the more accurate standard fully manual SPTs.ConclusionAgainst the backdrop of rising healthcare costs especially in Switzerland, using computer-aided or (semi) automated diagnostic systems could play an important role in healthcare cost containment efforts. However, results should be taken with caution because of the uncertainty associated with the early nature of our analysis and the specific Swiss context adopted in this study.

Critical Effects of Precipitation on Future Colorado River Flow

Abstract Of concern to Colorado River management, as operating guidelines post-2026 are being considered, is whether water resource recovery from low flows during 2000–20 is possible. Here, we analyze new simulations from phase 6 of the Coupled Model Intercomparison Project (CMIP6) to determine plausible climate impacts on Colorado River flows for 2026–50 when revised guidelines would operate. We constrain projected flows for Lees Ferry, the gauge through which 85% of the river flow passes, using its estimated sensitivity to meteorological variability together with CMIP6-projected precipitation and temperature changes. The critical importance of precipitation, especially its natural variability, is emphasized. Model projections indicate increased precipitation in the upper Colorado River basin due to climate change, which alone increases river flows by 5%–7% (relative to a 2000–20 climatology). Depending on the river’s temperature sensitivity, this wet signal compensates for some, if not all, of the depleting effects of basin warming. Considerable internal decadal precipitation variability (∼5% of the climatological mean) is demonstrated, driving a greater range of plausible Colorado River flow changes for 2026–50 than previously surmised from treatment of temperature impacts alone: the overall precipitation-induced Lees Ferry flow changes span from −25% to +40%, contrasting with a range from −30% to −5% from expected warming effects only. Consequently, extreme low and high flows are more likely. Lees Ferry flow projections, conditioned on initial drought states akin to 2000–20, reveal substantial recovery odds for water resources, albeit with elevated risks of even further flow declines than in recent decades. Significance Statement Increasing temperatures have led to concerns that Colorado River flows will be permanently reduced due to global warming. Here, we analyze precipitation, surface temperature, and streamflow (at Lees Ferry) in the upper Colorado River basin since 1895 revealing precipitation to be the largest contributor to runoff variability while temperature variability has been a much smaller contributor. New climate model projections indicate increased precipitation in the upper basin due to global warming, acting to increase river flows by 5%–7% during 2026–50. This wet signal compensates for some of the depleting effects from further basinwide warming. Critically, the large intrinsic variability in precipitation is demonstrated to yield a wider range of future Colorado River flows than previously foreseen based solely on considering temperature effects.

Testing MOND on Small Bodies in the Remote Solar System

Modified Newtonian dynamics (MOND), which postulates a breakdown of Newton's laws of gravity/dynamics below some critical acceleration threshold, can explain many otherwise puzzling observational phenomena on galactic scales. MOND competes with the hypothesis of dark matter, which successfully explains the cosmic microwave background and large-scale structure. Here we provide the first solar system test of MOND that probes the subcritical acceleration regime. Using the Bekenstein–Milgrom “aquadratic Lagrangian” (or AQUAL) formulation, we simulate the evolution of myriads of test particles (planetesimals or comets) born in the trans-Neptunian region and scattered by the giant planets over the lifetime of the Sun to heliocentric distances of 102–105 au. We include the effects of the Galactic tidal field and passing stars. While Newtonian simulations reproduce the distribution of binding energies of long-period and Oort-cloud comets detectable from Earth, MOND-based simulations do not. This conclusion is robust to plausible changes in the migration history of the planets, the migration history of the Sun, the MOND transition function, effects of the Sun's birth cluster, and the fading properties of long-period comets. For the most popular version of AQUAL, characterized by a gradual transition between the Newtonian and MOND regimes, our MOND-based simulations also fail to reproduce the orbital distribution of trans-Neptunian objects in the detached disk (perihelion q > 38 au). Our results do not rule out some MOND theories more elaborate than AQUAL, in which non-Newtonian effects are screened on small spatial scales, at small masses, or in external gravitational fields comparable in strength to the critical acceleration.

Debates on humanization of human-animal brain chimeras - are we putting the cart before the horses?

Research on human-animal chimeras have elicited alarms and prompted debates. Those involving the generation of chimeric brains, in which human brain cells become anatomically and functionally intertwined with their animal counterparts in varying ratios, either via xenografts or embryonic co-development, have been considered the most problematic. The moral issues stem from a potential for "humanization" of the animal brain, as well as speculative changes to the host animals' consciousness or sentience, with consequential alteration in the animal hosts' moral status. However, critical background knowledge appears to be missing to resolve these debates. Firstly, there is no consensus on animal sentience vis-à-vis that of humans, and no established methodology that would allow a wholesome and objective assessment of changes in animal sentience resulting from the introduction of human brain cells. Knowledge in interspecies comparative neuropsychology that could allow effective demarcation of a state of "humanization" is also lacking. Secondly, moral status as a philosophical construct has no scientific and objective points of reference. Either changes in sentience or humanization effects would remain unclear unless there are some neuroscientific research grounding. For a bioethical stance based on moral status of human-animal brain chimera to make meaningful contributions to regulatory policies, it might first need to be adequately informed by, and with its arguments constructed, in a manner that are factually in line with the science. In may be prudent for approved research projects involving the generation of human-animal brain chimera to have a mandatory component of assessing plausible changes in sentience.

The emergence of enhanced intelligence in a brain-inspired cognitive architecture.

The Causal Cognitive Architecture is a brain-inspired cognitive architecture developed from the hypothesis that the navigation circuits in the ancestors of mammals duplicated to eventually form the neocortex. Thus, millions of neocortical minicolumns are functionally modeled in the architecture as millions of "navigation maps." An investigation of a cognitive architecture based on these navigation maps has previously shown that modest changes in the architecture allow the ready emergence of human cognitive abilities such as grounded, full causal decision-making, full analogical reasoning, and near-full compositional language abilities. In this study, additional biologically plausible modest changes to the architecture are considered and show the emergence of super-human planning abilities. The architecture should be considered as a viable alternative pathway toward the development of more advanced artificial intelligence, as well as to give insight into the emergence of natural human intelligence.

Assessment of plausible changes in Climatic Impact-Drivers relevant for the viticulture sector: A storyline approach with a climate service perspective

Under the pressing warming of climate, interpretable and useful-for-adaptation information has become a need in society and has promoted rapid methodological advances in climate science. One such advance is the development of the dynamical-storyline approach, with which the spread in multi-model scenario projections can be represented as a set of physically plausible scenarios (storylines) defined by (a) a global warming level and (b) changes in large-scale dynamical conditions that arise from climate forcing. Moreover, if changes in regional climate are assessed in such a way that they can clearly inform societal systems or management of natural ecosystems, they can potentially aid decision-making in a practical manner. Such is the aim of the climatic impact-driver (CID) framework, proposed in the Sixth Assessment Report (AR6) from the Intergovernmental Panel on Climate Change. Here, we combine the dynamical-storyline approach with the CID framework and apply them to climate services. We focus on CIDs associated with the viticulture sector and the region of the South American Andes, where currently both Argentina and Chile produce wine. We explain the benefits of this approach from a communication and adaptation perspective. In particular, we found that the CIDs related to seasonally aggregated temperatures are mainly dependent on the global warming level although in some regions, but they can also be sensitive to changes in dynamical conditions. Meanwhile, CIDs related to extreme temperature values and precipitation depend strongly on the dynamical response. We show how adaptation to climate-related compound risks can be informed by a storyline approach, given that they can address compound uncertainty in multiple locations, variables and seasons.

A statewide, weather-regime based stochastic weather generator for process-based bottom-up climate risk assessments in California – Part II: Thermodynamic and dynamic climate change scenarios

This study is the second of a two-part series presenting a novel weather regime-based stochastic weather generator to support bottom-up climate vulnerability assessments of water systems in California. In Part 2 of this series, we present how the model is used to develop an ensemble of climate change scenarios based on both thermodynamic and dynamic signals of climate change. The ensemble includes a suite of 30 climate change scenarios, each consisting of 1000 years of simulated daily climate data (precipitation, maximum temperature, minimum temperature) at a 6 km resolution across the entire state of California. The 30 scenarios represent a range of plausible climate changes to temperature, average precipitation, and precipitation extremes that are reflective of thermodynamic responses of the atmosphere to warming. An additional two scenarios are also created that represent changes in the frequency of weather regimes (e.g., dynamic climate change). Results from these scenarios reveal that when the effects of anthropogenic climate change are combined with plausible realizations of natural climate variability, the severity of extremes in California is amplified significantly. In addition, recent changes in the frequency of large-scale patterns of atmospheric circulation can have impacts of similar magnitude to large (>10%) declines in average precipitation, particularly with respect to drought. The scenarios developed in this work are designed to allow water managers to systematically test the sensitivity of their water system to different combinations of climate change, so that key vulnerabilities can be discovered and then addressed through adaptation planning.

Assessment of land use/ land cover change derived catchment hydrologic response: An integrated parsimonious hydrological modeling and alteration analysis based approach

Land use/land cover (LULC) change, often a consequence of natural or anthropogenic drivers, plays a decisive role in governing global catchment dynamics, and subsequent impact on regional hydrology. Insight into the complex relationship between the drivers of LULC change and catchment hydrology is of utmost importance to decision makers. Contemplating the dynamic rainfall-runoff response of the Indian catchments, this study proposes an integrated modeling-based approach to identify the drivers and relative contribution to catchment hydrology. The proposed approach was evaluated in the tropical climate Nagavali River Basin (NRB) (9512 km2) of India. The Soil and Water Assessment Tool (SWAT) hydrological model, which uses daily-scale rainfall, temperature, wind speed, relative humidity, solar radiation, and streamflow information was integrated with the Indicators of Hydrologic Alteration (IHA) technique to characterize the plausible changes in the flow regime of the NRB. Subsequently, the Partial Least Squares Regression (PLSR) based modeling analysis was performed to quantify the relative contribution of individual LULC components on the catchment water balance. The outcomes of the study revealed that forest land has been significantly converted to agricultural land (45–59%) across the NRB resulting in mean annual streamflow increase of 3.57 m3/s during the monsoon season. The affinity between land use class and streamflow revealed that barren land (CN = 83–87) exhibits the maximum positive response to streamflow followed by the built-up land (CN = 89–91) and fallow land (CN = 88–93). The period 1985–1995 experienced an increased ET scenario (911–1050 mm), while the recent period (2005–2020) experienced reduced ET scenario owing to conversion of forest to agricultural land. Certainly, the study endorses adopting the developed methodology for understanding the complex land use and catchment-scale hydrologic interactions across global-scales for early watershed management planning.

Northwestern Mediterranean Heavy Precipitation Events in a Warmer Climate: Robust Versus Uncertain Changes With a Large Convection‐Permitting Model Ensemble

AbstractTaking advantage of a large ensemble of Convection Permitting‐Regional Climate Models on a pan‐Alpine domain and of an object‐oriented dedicated analysis, this study aims to investigate future changes in high‐impact fall Mediterranean Heavy Precipitation Events at high warming levels. We identify a robust multi‐model agreement for an increased frequency from central Italy to the northern Balkans combined with a substantial extension of the affected areas, for a dominant influence of the driving Global Climate Models for projecting changes in the frequency, and for an increase in intensity, area, volume and severity over the French Mediterranean. However, large quantitative uncertainties persist despite the use of convection‐permitting models, with no clear agreement in frequency changes over southeastern France and a large range of plausible changes in events' properties, including for the most intense events. Model diversity and international coordination are still needed to provide policy‐relevant climate information regarding precipitation extremes.

Inverse association between plasma chlordecone concentrations and progression of alcoholic liver fibrosis: the role of liver metabolism

Background and AimsChlordecone is a persistent organochlorinated insecticide, extensively used in the French West Indies and has been contaminating the population for more than thirty years. Its potentiation effect on hepatotoxic agents has been demonstrated in animal models. We investigated the relationship between environmental exposure to chlordecone and the progression of liver fibrosis.MethodsThis study included 182 consecutive patients with chronic alcoholic hepatitis whose liver fibrosis was assessed using non-invasive methods. Measured plasma chlordecone concentrations at inclusion were used as surrogate of long-term exposure under steady-state conditions. As the pharmacokinetic processing of chlordecone is largely determined by the liver, we used a human physiologically based pharmacokinetic model to predict plausible changes in the steady-state blood chlordecone concentrations induced by liver fibrosis.ResultsWith a median follow-up of 27.1 years after the onset of alcohol consumption, we found a significant decrease in the risk of advanced liver fibrosis with increasing plasma chlordecone concentration (adjusted hazard ratio = 0.56; 95% confidence interval: 0.34–0.95 for the highest vs. lowest tertile, p = 0.04). Changes induced by liver fibrosis influenced the pharmacokinetic processing of chlordecone, resulting in substantial modifications in its steady-state blood concentrations.ConclusionAccording to this human model of coexposure to alcohol, reverse causality is the most plausible explanation of this inverse association between plasma chlordecone concentrations and progression of liver fibrosis. This study underlines the importance of considering the pharmacokinetic of environmental contaminants in epidemiological studies when biomarkers of exposure are used to investigate their own impact on the liver.Trial registrationClinicalTrials.gov Identifier: NCT03373396.

Climate change effects on rainfall extreme value distribution: the role of skewness

Quantifying the potential effects of Climate Change (CC) on hydrological scales is a topic with a more and more increasing interest for the scientific community, given the CC impact on agriculture, industry, economy, human health, ecosystems, among the others. In this context, the paper focuses on the sub-daily Annual Maxima (AM) of rainfall height time series, and specifically on the crucial role played by initial skewness, i.e. the skewness of the observed rainfall series used to evaluate potential parametric trends. Here a quick and user-friendly methodology is proposed, that is aimed at quantifying plausible future changes in terms of probability distributions assumed at rain gauge scale, from projections of any climatic model. In detail, the Generalized Extreme Value (GEV) and the Two-Component Extreme Value (TCEV) distributions are adopted as probability functions suitable for modelling observed rainfall AM series, which could increase their frequency and magnitude into future horizons under CC. EURO-CORDEX projections for Europe are considered, under the hypothesis that the values of the change factor, i.e. the ratio between the values of a specific quantile at two specific time horizons, are invariant when moving from an areally-averaged scale (typical for any climate model) to a point rain gauge scale, which induces that future changes are provided (in terms of frequency and magnitude of extreme events) without the need of any spatial downscaling from the assumed projections. The proposed methodology can contribute to hazard quantification associated to potential climate changes, and thus it can play a crucial role in the assessment of hydraulic structures resilience; the obtained results, specific for the study area of Italy, but easily extendable on a global scale, showed that larger increases in frequency of future heavy events are expected for time series with “EV1 alike” values of initial skewness.

Atmospheres as a window to rocky exoplanet surfaces

ABSTRACT As the characterization of exoplanet atmospheres proceeds, providing insights into atmospheric chemistry and composition, a key question is how much deeper into the planet we might be able to see from its atmospheric properties alone. For small planets with modest atmospheres and equilibrium temperatures, the first layer below the atmosphere will be their rocky surface. For such warm rocky planets, broadly Venus-like planets, the high temperatures and moderate pressures at the base of their atmospheres may enable thermochemical equilibrium between rock and gas. This links the composition of the surface to that of the observable atmosphere. Using an equilibrium chemistry code, we find a boundary in surface pressure–temperature space which simultaneously separates distinct mineralogical regimes and atmospheric regimes, potentially enabling inference of surface mineralogy from spectroscopic observations of the atmosphere. Weak constraints on the surface pressure and temperature also emerge. This regime boundary corresponds to conditions under which SO2 is oxidized and absorbed by calcium-bearing minerals in the crust, thus the two regimes reflect the sulphidation of the crust. The existence of these atmospheric regimes for Venus-like planets is robust to plausible changes in the elemental composition. Our results pave the way to the prospect of characterizing exoplanetary surfaces as new data for short period rocky planet atmospheres emerge.

The effects of diachronous surface uplift of the European Alps on regional climate and the oxygen isotopic composition of precipitation

Abstract. This study presents the simulated response of regional climate and the oxygen isotopic composition of precipitation (δ18Op) to different along-strike topographic evolution scenarios. These simulations are conducted to determine if the previously hypothesized diachronous surface uplift in the Western and Eastern Alps would produce δ18Op signals in the geologic record that are sufficiently large and distinct to be detected using stable isotope paleoaltimetry. We present a series of topographic sensitivity experiments conducted with the water-isotope-tracking atmospheric general circulation model (GCM) ECHAM5-wiso. The topographic scenarios are created from the variation of two free parameters, (1) the elevation of the Western–Central Alps and (2) the elevation of the Eastern Alps. The results indicate Δδ18Op values (i.e., the difference between δ18Op values at the low- and high-elevation sites) of up to −8 ‰ along the strike of the Alps for the diachronous uplift scenarios, primarily due to changes in orographic precipitation and adiabatic lapse rate driven localized changes in near-surface variables. These simulated magnitudes of Δδ18Op values suggest that the expected isotopic signal would be significant enough to be preserved and measured in geologic archives. Moreover, the simulated slight δ18Op differences of 1 ‰–2 ‰ across the low-elevation sites support the use of the δ–δ paleoaltimetry approach and highlight the importance of sampling far-field low-elevation sites to differentiate between the different surface uplift scenarios. The elevation-dependent rate of change in δ18Op (“isotopic lapse rate”) varies depending on the topographic configuration and the extent of the surface uplift. Most of the changes are significant (e.g., −1.04 ‰ km−1 change with slope error of ±0.09 ‰ km−1), while others were within the range of the statistical uncertainties (e.g., −0.15 ‰ km−1 change with slope error of ±0.13 ‰ km−1). The results also highlight the plausible changes in atmospheric circulation patterns and associated changes in moisture transport pathways in response to changes in the topography of the Alps. These large-scale atmospheric dynamics changes can complicate the underlying assumption of stable isotope paleoaltimetry and therefore require integration with paleoclimate modeling to ensure accurate reconstruction of the paleoelevation of the Alps.

How much does issue salience matter? A model with applications to the UK elections

AbstractExtensive research applies counterfactual simulation methodology to study parties’ optimal policy positions in multiparty elections. In recent years, this methodology has been extended to the study of variation in issue salience. We employ this method to estimate the electoral effects of changes in the salience of specific positional issue dimensions on parties’ success. Applied to British Election Study survey data from 2017 and 2019, we find that plausible issue salience changes could have shifted the parties’ projected vote shares by several percentage points. Our approach implies that the governing Conservative Party had electoral incentives to downplay positional issues, to magnify the relative effects of its non‐policy advantage due to perceived competence and performance, among other factors. Labour would also have benefitted from reduced salience of Left‐Right ideology. By contrast, the Liberal Democrats had strong electoral incentives to emphasize their moderate Left‐Right position.

Perceptual learning deficits mediated by somatostatin releasing inhibitory interneurons of olfactory bulb in an early life stress mouse model

Early life adversity (ELA) causes aberrant functioning of neural circuits affecting the health of an individual. While ELA-induced behavioural disorders resulting from sensory and cognitive disabilities can be assessed clinically, the neural mechanisms need to be probed using animal models by employing multi-pronged experimental approaches. As ELA can alter sensory perception, we investigated the effect of early weaning on murine olfaction. By implementing go/no-go odour discrimination paradigm, we observed olfactory learning and memory impairments in early life stressed (ELS) male mice. As olfactory bulb (OB) circuitry plays a critical role in odour learning, we studied the plausible changes in the OB of ELS mice. Lowered c-Fos activity in the external plexiform layer and a reduction in the number of dendritic processes of somatostatin-releasing, GABAergic interneurons (SOM-INs) in the ELS mice led us to hypothesise the underlying circuit. We recorded reduced synaptic inhibitory feedback on mitral/tufted (M/T) cells, in the OB slices from ELS mice, explaining the learning deficiency caused by compromised refinement of OB output. The reduction in synaptic inhibition was nullified by the photo-activation of ChR2-expressing SOM-INs in ELS mice. The role of SOM-INs was revealed by learning-dependent refinement of Ca2+dynamics quantified by GCaMP6f signals, which was absent in ELS mice. Further, the causal role of SOM-INs involving circuitry was investigated by optogenetic modulation during the odour discrimination learning. Photo-activating these neurons rescued the ELA-induced learning deficits. Conversely, photo-inhibition caused learning deficiency in control animals, while it completely abolished the learning in ELS mice, confirming the adverse effects mediated by SOM-INs. Our results thus establish the role of specific inhibitory circuit in pre-cortical sensory area in orchestrating ELA-dependent changes.

Storylines of Sahel Precipitation Change: Roles of the North Atlantic and Euro‐Mediterranean Temperature

AbstractFuture changes in Sahel precipitation are uncertain because of large differences among projections from various models. In order to explore this uncertainty, we use a storyline approach which seeks to identify alternative plausible evolutions of Sahel precipitation and their driving factors. By analyzing projections from the CMIP6 climate models, we show that changes in North Atlantic and in Euro‐Mediterranean temperatures explain up to 60% of the central Sahel precipitation change uncertainty. We then construct several storylines of Sahel precipitation change based on future plausible changes in North Atlantic and Euro‐Mediterranean temperatures. In one storyline, an amplified warming of both the North Atlantic and the Euro‐Mediterranean areas promotes a northward shift of the West African monsoon, increasing precipitation over the central Sahel, while, in the opposite storyline, a moderate warming in both regions is associated with a small change in precipitation over the central Sahel and a decrease in precipitation over the western Sahel, at the end of the 21st century. These results indicate that Sahel precipitation uncertainty will not be substantially reduced unless the uncertainty in the future warming of the North Atlantic and the Euro‐Mediterranean areas is constrained.

Changes in streamflow statistical structure across the United States due to recent climate change

Changes in statistical structure (spectral properties) of streamflow across the USA due to climate change were studied for water years 1980–2013. The Fractionally differenced Autoregressive Integrated Moving Average (FARIMA) model was fit to the deseasonalized streamflow time series to model its statistical structure. FARIMA allows the separation of streamflow into low- (slowly varying) and high-frequency (fast varying) components. In this study, the changes in the contribution of various components to the total streamflow variance were analyzed. Further, the variables affecting these changes were identified using random forest and linear regression. Results show that in the snow-dominated watersheds, the contribution of low-frequency components to total streamflow variance decreased over the study period, and the contribution of high-frequency components increased. The changes in the snow-dominated watersheds were primarily driven by changes in precipitation statistics and changes in snowpack but also by changes in seasonal temperature statistics. Among the rain-driven watersheds, the contribution of high-frequency components generally increased in arid regions but decreased in humid regions. In both humid and arid rain-driven watersheds, increasing winter temperature appears to be responsible for the change in streamflow statistical structure. These results have consequences for the predictability of streamflow in the presence of climate change. Further, the analysis carried out in this study allowed us to understand the plausible changes in watershed hydrologic processes that affect streamflow without using process-based or conceptual models.