Explicit Predictions Research Articles

Negotiating failure: understanding the geopolitics of climate change

Negotiating failure: understanding the geopolitics of climate change

On Mordell–Weil groups and congruences between derivatives of twisted Hasse–Weil L-functions

Abstract Let A be an abelian variety defined over a number field k and let F be a finite Galois extension of k. Let p be a prime number. Then under certain not-too-stringent conditions on A and F we compute explicitly the algebraic part of the p-component of the equivariant Tamagawa number of the pair ( h 1 ⁢ ( A / F ) ⁢ ( 1 ) , ℤ ⁢ [ Gal ⁢ ( F / k ) ] ) (h^{1}(A_{/F})(1),\mathbb{Z}[{\rm Gal}(F/k)]) . By comparing the result of this computation with the theorem of Gross and Zagier we are able to give the first verification of the p-component of the equivariant Tamagawa number conjecture for an abelian variety in the technically most demanding case in which the relevant Mordell–Weil group has strictly positive rank and the relevant field extension is both non-abelian and of degree divisible by p. More generally, our approach leads us to the formulation of certain precise families of conjectural p-adic congruences between the values at s = 1 s=1 of derivatives of the Hasse–Weil L-functions associated to twists of A, normalised by a product of explicit equivariant regulators and periods, and to explicit predictions concerning the Galois structure of Tate–Shafarevich groups. In several interesting cases we provide theoretical and numerical evidence in support of these more general predictions.

Developmental stages in receptive grammar acquisition: A Processability Theory account

This study takes a new look at the topic of developmental stages in the second language (L2) acquisition of morphosyntax by analysing receptive learner data, a language mode that has hitherto received very little attention within this strand of research (for a recent and rare study, see Spinner, 2013). Looking at both the receptive and productive side of grammar acquisition, however, is necessary for a better understanding of developmental systematicity and of the relationship between receptive and productive grammar acquisition more widely, as well as for the construction of a comprehensive theory of second language acquisition (SLA). In the present exploratory study, the receptive acquisition of L2 English grammar knowledge is studied cross-sectionally within a Processability Theory (PT) framework (Pienemann, 1998, 2005b), a theory of L2 grammar acquisition which makes explicit predictions about the order in which L2 learners learn to productively process different morphosyntactic phenomena. Participants are 72 francophone beginning child L2 learners (age 6–9) acquiring English in an immersion program. The learners’ ability to process six morphosyntactic phenomena situated at extreme ends of the developmental hierarchy proposed by PT was tested by means of the ELIAS Grammar Test, a picture selection task. Overall, the developmental orders obtained through implicational scaling for the six target phenomena agreed with PT’s predictions, suggesting that similar mechanisms underlie the acquisition of receptive and productive L2 grammar processing skills.

T Cells Integrate Local and Global Cues to Discriminate between Structurally Similar Antigens.

T lymphocytes’ ability to discriminate between structurally related antigens has been attributed to the unique signaling properties of the T cell receptor. However, recent studies have suggested that the output of this discrimination process is conditioned by environmental cues. Here, we demonstrate how the IL-2 cytokine, collectively generated by strongly activated T cell clones, can induce weaker T cell clones to proliferate. We identify the PI3K pathway as being critical for integrating the antigen and cytokine responses and for controlling cell-cycle entry. We build a hybrid stochastic/deterministic computational model that accounts for such signal synergism and demonstrates quantitatively how T cells tune their cell-cycle entry according to environmental cytokine cues. Our findings indicate that antigen discrimination by T cells is not solely an intrinsic cellular property but rather a product of integration of multiple cues, including local cues such as antigen quality and quantity, to global ones like the extracellular concentration of inflammatory cytokines.

Model for Probing Membrane-Cortex Adhesion by Micropipette Aspiration and Fluctuation Spectroscopy

We propose a model for membrane-cortex adhesion that couples membrane deformations, hydrodynamics, and kinetics of membrane-cortex ligands. In its simplest form, the model gives explicit predictions for the critical pressure for membrane detachment and for the value of adhesion energy. We show that these quantities exhibit a significant dependence on the active acto-myosin stresses. The model provides a simple framework to access quantitative information on cortical activity by means of micropipette experiments. We also extend the model to incorporate fluctuations and show that detailed information on the stability of membrane-cortex coupling can be obtained by a combination of micropipette aspiration and fluctuation spectroscopy measurements.

Exploring the spatially explicit predictions of the Maximum Entropy Theory of Ecology

AbstractAimThe maximum entropy theory of ecology (METE) is a unified theory of biodiversity that attempts to simultaneously predict patterns of species abundance, size and spatial structure. The spatial predictions of this theory have repeatedly performed well at predicting diversity patterns across scales. However, the theoretical development and evaluation of METE has focused on predicting patterns that ignore intersite spatial correlations. As a result the theory has not been evaluated using one of the core components of spatial structure. We develop and test a semi‐recursive version of the spatially explicit predictions of METE for the distance–decay relationship of community similarity and compare its performance with the classic random placement model of completely random species distributions. This provides a better understanding and stronger test of the spatial community predictions of METE.LocationNew World tropical and temperate plant communities.MethodsWe analytically derived and simulated the spatially explicit expectations of METE for the Sørensen index of community similarity. We then compared the distance–decay of community similarity of 16 mapped plant communities with METE and the random placement model.ResultsThe version of METE we examined was successful at capturing the general functional form of the observed distance–decay relationships, a negative power function relationship between community similarity and distance. However, the semi‐recursive approach consistently predicted lower intercepts and higher slopes than observed in the empirical distance–decay relationships and yielded worse predictions than the random placement model.Main conclusionsOur results suggest that while the current spatial models of METE accurately predict the spatial scaling of species occupancy, and therefore core ecological patterns like the species–area relationship, its semi‐recursive form does not accurately characterize spatially explicit patterns of correlation. More generally, this suggests that tests of spatial theories based only on the species–area relationship may appear to support the underlying theory despite significant deviations in important aspects of spatial structure.

Ice formation on a smooth or rough cold surface due to the impact of a supercooled water droplet

Ice accretion is considered in the impact of a supercooled water droplet on a smooth or rough solid surface, the roughness accounting for earlier icing. In this theoretical investigation, the emphasis and novelty lie in the full nonlinear interplay of the droplet motion and the growth of the ice surface being addressed for relatively small times, over a realistic range of Reynolds numbers, Froude numbers, Weber numbers, Stefan numbers and capillary under-heating parameters. The Prandtl number and the kinetic under-heating parameter are taken to be order unity. The ice accretion brings inner layers into play forcibly, affecting the outer flow. (The work includes viscous effects in an isothermal impact without phase change, as a special case, and the differences between impacts with and without freezing.) There are four main findings. First, the icing dynamically can accelerate or decelerate the spreading of the droplet whereas roughness on its own tends to decelerate spreading. The interaction between the two and the implications for successive freezings are found to be subtle. Second, a focus on the dominant physical effects reveals a multi-structure within which restricted regions of turbulence are implied. The third main finding is an essentially parabolic shape for a single droplet freezing under certain conditions. Fourth is a connection with a body of experimental and engineering works and with practical findings to the extent that the explicit predictions here for ice-accretion rates are found to agree with the experimental range.

Invasion success of a global avian invader is explained by within‐taxon niche structure and association with humans in the native range

AbstractAimTo mitigate the threat invasive species pose to ecosystem functioning, reliable risk assessment is paramount. Spatially explicit predictions of invasion risk obtained through bioclimatic envelope models calibrated with native species distribution data can play a critical role in invasive species management. Forecasts of invasion risk to novel environments, however, remain controversial. Here, we assess how species’ association with human‐modified habitats in the native range and within‐taxon niche structure shape the distribution of invasive populations at biogeographical scales and influence the reliability of predictions of invasion risk.LocationAfrica, Asia and Europe.MethodsWe use ~1200 native and invasive ring‐necked parakeet (Psittacula krameri) occurrences and associated data on establishment success in combination with mtDNA‐based phylogeographic structure to assess niche dynamics during biological invasion and to generate predictions of invasion risk. Niche dynamics were quantified in a gridded environmental space while bioclimatic models were created using the biomod2 ensemble modelling framework.ResultsRing‐necked parakeets show considerable niche expansion into climates colder than their native range. Only when incorporating a measure of human modification of habitats within the native range do bioclimatic envelope models yield credible predictions of invasion risk for parakeets across Europe. Invasion risk derived from models that account for differing niche requirements of phylogeographic lineages and those that do not achieve similar statistical accuracy, but there are pronounced differences in areas predicted to be susceptible for invasion.Main conclusionsInformation on within‐taxon niche structure and especially association with humans in the native range can substantially improve predictive models of invasion risk. To provide policymakers with robust predictions of invasion risk, including these factors into bioclimatic envelope models is recommended.

Inferring cetacean population densities from the absolute dynamic topography of the ocean in a hierarchical Bayesian framework.

We inferred the population densities of blue whales (Balaenoptera musculus) and short-beaked common dolphins (Delphinus delphis) in the Northeast Pacific Ocean as functions of the water-column’s physical structure by implementing hierarchical models in a Bayesian framework. This approach allowed us to propagate the uncertainty of the field observations into the inference of species-habitat relationships and to generate spatially explicit population density predictions with reduced effects of sampling heterogeneity. Our hypothesis was that the large-scale spatial distributions of these two cetacean species respond primarily to ecological processes resulting from shoaling and outcropping of the pycnocline in regions of wind-forced upwelling and eddy-like circulation. Physically, these processes affect the thermodynamic balance of the water column, decreasing its volume and thus the height of the absolute dynamic topography (ADT). Biologically, they lead to elevated primary productivity and persistent aggregation of low-trophic-level prey. Unlike other remotely sensed variables, ADT provides information about the structure of the entire water column and it is also routinely measured at high spatial-temporal resolution by satellite altimeters with uniform global coverage. Our models provide spatially explicit population density predictions for both species, even in areas where the pycnocline shoals but does not outcrop (e.g. the Costa Rica Dome and the North Equatorial Countercurrent thermocline ridge). Interannual variations in distribution during El Niño anomalies suggest that the population density of both species decreases dramatically in the Equatorial Cold Tongue and the Costa Rica Dome, and that their distributions retract to particular areas that remain productive, such as the more oceanic waters in the central California Current System, the northern Gulf of California, the North Equatorial Countercurrent thermocline ridge, and the more southern portion of the Humboldt Current System. We posit that such reductions in available foraging habitats during climatic disturbances could incur high energetic costs on these populations, ultimately affecting individual fitness and survival.

Predictive modeling of subsurface shoreline oil encounter probability from the Exxon Valdez oil spill in Prince William Sound, Alaska.

To better understand the distribution of remaining lingering subsurface oil residues from the Exxon Valdez oil spill (EVOS) along the shorelines of Prince William Sound (PWS), AK, we revised previous modeling efforts to allow spatially explicit predictions of the distribution of subsurface oil. We used a set of pooled field data and predictor variables stored as Geographic Information Systems (GIS) data to generate calibrated boosted tree models predicting the encounter probability of different categories of subsurface oil. The models demonstrated excellent predictive performance as evaluated by cross-validated performance statistics. While the average encounter probabilities at most shoreline locations are low across western PWS, clusters of shoreline locations with elevated encounter probabilities remain in the northern parts of the PWS, as well as more isolated locations. These results can be applied to estimate the location and amount of remaining oil, evaluate potential ongoing impacts, and guide remediation. This is the first application of quantitative machine-learning based modeling techniques in estimating the likelihood of ongoing, long-term shoreline oil persistence after a major oil spill.

Applications of the Gaussian kinematic formula to CMB data analysis

The Gaussian Kinematic Formula (GKF, see Adler and Taylor (2007,2011)) is an extremely powerful tool allowing for explicit analytic predictions of expected values of Minkowski functionals under realistic experimental conditions for cosmological data collections. In this paper, we implement Minkowski functionals on multipoles and needlet components of CMB fields, thus allowing a better control of cosmic variance and extraction of information on both harmonic and real domains; we then exploit the GKF to provide their expected values on spherical maps, in the presence of arbitrary sky masks, and under nonGaussian circumstances. All our results are validated by numerical experiments, which show a perfect agreement between theoretical predictions and Monte Carlo simulations.

The eye in hand: predicting others' behavior by integrating multiple sources of information

The ability to predict the outcome of other beings' actions confers significant adaptive advantages. Experiments have assessed that human action observation can use multiple information sources, but it is currently unknown how they are integrated and how conflicts between them are resolved. To address this issue, we designed an action observation paradigm requiring the integration of multiple, potentially conflicting sources of evidence about the action target: the actor's gaze direction, hand preshape, and arm trajectory, and their availability and relative uncertainty in time. In two experiments, we analyzed participants' action prediction ability by using eye tracking and behavioral measures. The results show that the information provided by the actor's gaze affected participants' explicit predictions. However, results also show that gaze information was disregarded as soon as information on the actor's hand preshape was available, and this latter information source had widespread effects on participants' prediction ability. Furthermore, as the action unfolded in time, participants relied increasingly more on the arm movement source, showing sensitivity to its increasing informativeness. Therefore, the results suggest that the brain forms a robust estimate of the actor's motor intention by integrating multiple sources of information. However, when informative motor cues such as a preshaped hand with a given grip are available and might help in selecting action targets, people tend to capitalize on such motor cues, thus turning out to be more accurate and fast in inferring the object to be manipulated by the other's hand.

A Resource-Control Account of Sustained Attention

Staying attentive is challenging enough when carrying out everyday tasks, such as reading or sitting through a lecture, and failures to do so can be frustrating and inconvenient. However, such lapses may even be life threatening, for example, if a pilot fails to monitor an oil-pressure gauge or if a long-haul truck driver fails to notice a car in his or her blind spot. Here, we explore two explanations of sustained-attention lapses. By one account, task monotony leads to an increasing preoccupation with internal thought (i.e., mind wandering). By another, task demands result in the depletion of information-processing resources that are needed to perform the task. A review of the sustained-attention literature suggests that neither theory, on its own, adequately explains the full range of findings. We propose a novel framework to explain why attention lapses as a function of time-on-task by combining aspects of two different theories of mind wandering: attentional resource (Smallwood & Schooler, 2006) and control failure (McVay & Kane, 2010). We then use our “resource-control” theory to explain performance decrements in sustained-attention tasks. We end by making some explicit predictions regarding mind wandering in general and sustained-attention performance in particular.

Ocean acidification through the lens of ecological theory

Ocean acidification, chemical changes to the carbonate system of seawater, is emerging as a key environmental challenge accompanying global warming and other human-induced perturbations. Considerable research seeks to define the scope and character of potential outcomes from this phenomenon, but a crucial impediment persists. Ecological theory, despite its power and utility, has been only peripherally applied to the problem. Here we sketch in broad strokes several areas where fundamental principles of ecology have the capacity to generate insight into ocean acidification's consequences. We focus on conceptual models that, when considered in the context of acidification, yield explicit predictions regarding a spectrum of population- and community-level effects, from narrowing of species ranges and shifts in patterns of demographic connectivity, to modified consumer-resource relationships, to ascendance of weedy taxa and loss of species diversity. Although our coverage represents only a small fraction of the breadth of possible insights achievable from the application of theory, our hope is that this initial foray will spur expanded efforts to blend experiments with theoretical approaches. The result promises to be a deeper and more nuanced understanding of ocean acidification'and the ecological changes it portends.

Criteria for genuineN-partite continuous-variable entanglement and Einstein-Podolsky-Rosen steering

Following previous work, we distinguish between genuine $N$-partite entanglement and full $N$-partite inseparability. Accordingly, we derive criteria to detect genuine multipartite entanglement using continuous-variable (position and momentum) measurements. Our criteria are similar but different to those based on the van Loock--Furusawa inequalities, which detect full $N$-partite inseparability. We explain how the criteria can be used to detect the genuine $N$-partite entanglement of continuous variable states generated from squeezed and vacuum state inputs, including the continuous-variable Greenberger-Horne-Zeilinger state, with explicit predictions for up to $N=9$. This makes our work accessible to experiment. For $N=3$, we also present criteria for tripartite Einstein-Podolsky-Rosen (EPR) steering. These criteria provide a means to demonstrate a genuine three-party EPR paradox, in which any single party is steerable by the remaining two parties.

Predictability and Reasonableness of Discounts and Premiums on Closed-End Funds

This article presents a mathematical model for explaining the premiums and discounts to net asset value for closed-end funds. The model does not require (1) constraining assumptions about the underlying price, liquidity, and volatility paths of securities held in the funds, or (2) differential market knowledge between fund investors and fund managers. Our empirical tests show that the observed discounts and premiums for seasoned U.S. closed-end funds are consistent with the model’s explicit predictions regarding payout policy and the relative performance of underlying fund holdings. Consistent with the implicit predictions of the model, our results show that fund size, sentiment, and liquidity also affect how a closed-end fund trades.

Possibilities and Limitations of Spatially Explicit Site Index Modelling for Spruce Based on National Forest Inventory Data and Digital Maps of Soil and Climate in Bavaria (SE Germany)

Combining national forest inventory (NFI) data with digital site maps of high resolution enables spatially explicit predictions of site productivity. The aim of this study is to explore the possibilities and limitations of this database to analyze the environmental dependency of height-growth of Norway spruce and to predict site index (SI) on a scale that is relevant for local forest management. The study region is the German federal state of Bavaria. The exploratory methods comprise significance tests and hypervolume-analysis. SI is modeled with a Generalized Additive Model (GAM). In a second step the residuals are modeled using Boosted Regression Trees (BRT). The interaction between temperature regime and water supply strongly determined height growth. At sites with very similar temperature regime and water supply, greater heights were reached if the depth gradient of base saturation was favorable. Statistical model criteria (Double Penalty Selection, AIC) preferred composite variables for water supply and the supply of basic cations. The ability to predict SI on a local scale was limited due to the difficulty to integrate soil variables into the model.

All doctors are jackasses.

All doctors are jackasses.

Rapid Response Tools and Datasets for Post-fire Erosion Modeling: Linking Remote Sensing and Process-based Hydrological Models to support Post-fire Remediation

Abstract. Post-fire flooding and erosion can pose a serious threat to life, property, and municipal water supplies. Increased peak flows and sediment delivery due to the loss of surface cover and fire-induced changes in soil properties are of great concern to both resource managers and the public. To respond to this threat, interdisciplinary Burned Area Emergency Response (BAER) Teams are formed to assess potential erosion and flood risks. These teams are under tight deadlines as remediation plans and treatments must be developed and implemented before the first major storms in order to be effective. One of the primary sources of information for making these decisions is a burn severity map derived from remote sensing data (typically Landsat) that reflects fire induced changes in vegetative cover and soil properties. Slope, soils, land cover, and climate are also important parameters that need to be considered when accessing risk. Many modeling tools and datasets have been developed to assist BAER teams, but process-based and spatially explicit empirical models are currently under-utilized compared to simpler, lumped models because they are both more difficult to set up and require spatially explicit inputs such as digital elevation models, soils, and land cover. We are working to facilitate the use of models by preparing spatial datasets within a web-based tool that rapidly modifies model inputs using burn severity maps derived from earth observation data. Automating the creation of model inputs facilitates the wider use of more accurate, process-based models for spatially explicit predictions of post-fire erosion and runoff.

Exaggerated trait growth in insects.

Animal structures occasionally attain extreme proportions, eclipsing in size the surrounding body parts. We review insect examples of exaggerated traits, such as the mandibles of stag beetles (Lucanidae), the claspers of praying mantids (Mantidae), the elongated hindlimbs of grasshoppers (Orthoptera: Caelifera), and the giant heads of soldier ants (Formicidae) and termites (Isoptera). Developmentally, disproportionate growth can arise through trait-specific modifications to the activity of at least four pathways: the sex determination pathway, the appendage patterning pathway, the insulin/IGF signaling pathway, and the juvenile hormone/ecdysteroid pathway. Although most exaggerated traits have not been studied mechanistically, it is already apparent that distinct developmental mechanisms underlie the evolution of the different types of exaggerated traits. We suggest this reflects the nature of selection in each instance, revealing an exciting link between mechanism, form, and function. We use this information to make explicit predictions for the types of regulatory pathways likely to underlie each type of exaggerated trait.