Uplift histories of Africa and Australia from linear inverse modeling of drainage inventories

We describe and apply a linear inverse model which calculates spatial and temporal patterns of uplift rate by minimizing the misfit between inventories of observed and predicted longitudinal river profiles. Our approach builds upon a more general, non-linear, optimization model, which suggests that shapes of river profiles are dominantly controlled by upstream advec- tion of kinematic waves of incision produced by spatial and temporal changes in regional uplift rate. Here, we use the method of characteristics to solve a version of this problem. A damped, non-negative, least squares approach is developed that permits river profiles to be inverted as a function of up- lift rate. An important benefit of a linearized treatment is low computational cost. We have tested our algorithm by inverting 957 river profiles from both Africa and Australia. For each continent, the drainage network was constructed from a digital elevation model. The fidelity of river profiles extracted from this network was carefully checked using satellite imagery. River profiles were inverted many times to systematically investigate the trade-off between model misfit and smoothness. Spatial and temporal patterns of both uplift rate and cumulative uplift were calibrated using independent geologic and geophys- ical observations. Uplift patterns suggest that the topography of Africa and Australia grew in Cenozoic times. Inverse modeling of large inventories of river profiles demonstrates that drainage networks contain coherent signals that record the regional growth of elevation.This is the final version. It first appeared at http://onlinelibrary.wiley.com/wol1/doi/10.1002/2014JF003297/abstract

A neogene history of mantle convective support beneath Borneo

Most, but not all, geodynamic models predict 1–2 km of mantle convective draw-down of the Earth's surface in a region centered on Borneo within southeast Asia. Nevertheless, there is geomorphic, geologic and geophysical evidence which suggests that convective uplift might have played some role in sculpting Bornean physiography. For example, a long wavelength free-air gravity anomaly of +60 mGal centered on Borneo coincides with the distribution of Neogene basaltic magmatism and with the locus of sub-plate slow shear wave velocity anomalies. Global positioning system measurements, an estimate of elastic thickness, and crustal isostatic considerations suggest that regional shortening does not entirely account for kilometer-scale regional elevation. Here, we explore the possible evolution of the Bornean landscape by extracting and modeling an inventory of 90 longitudinal river profiles. Misfit between observed and calculated river profiles is minimized by smoothly varying uplift rate as a function of space and time. Erosional parameters are chosen by assuming that regional uplift post-dates Eocene deposition of marine carbonate rocks. The robustness of this calibration is tested against independent geologic observations such as thermochronometric measurements, offshore sedimentary flux calculations, and the history of volcanism. A calculated cumulative uplift history suggests that kilometer-scale Bornean topography grew rapidly during Neogene times. This suggestion is corroborated by an offshore Miocene transition from carbonate to clastic deposition. Co-location of regional uplift and slow shear wave velocity anomalies immediately beneath the lithospheric plate implies that regional uplift could have been at least partly generated and maintained by temperature anomalies within an asthenospheric channel

Large-Scale Tectonic Forcing of the African Landscape

Abstract: Successful inverse modeling of observed longitudinal river profiles suggests that fluvial landscapes are responsive to continent‐wide tectonic forcing. However, inversion algorithms make simplifying assumptions about landscape erodibility and drainage planform stability that require careful justification. For example, precipitation rate and drainage catchment area are usually assumed to be invariant. Here, we exploit a closed‐loop modeling strategy by inverting drainage networks generated by dynamic landscape simulations in order to investigate the validity of these assumptions. First, we invert 4,018 African river profiles to determine an uplift history that is independently calibrated, and subsequently validated, using separate suites of geologic observations. Second, we use this tectonic forcing to drive landscape simulations that permit divide migration, interfluvial erosion and changes in catchment size. These simulations reproduce large‐scale features of the African landscape, including growth of deltaic deposits. Third, the influence of variable precipitation is investigated by carrying out a series of increasingly severe tests. Inverse modeling of drainage inventories extracted from simulated landscapes can largely recover tectonic forcing. Our closed‐loop modeling strategy suggests that large‐scale tectonic forcing plays the primary role in landscape evolution. One corollary of the integrative solution of the stream‐power equation is that precipitation rate becomes influential only if it varies on time scales longer than ∼1 Ma. We conclude that calibrated inverse modeling of river profiles is a fruitful method for investigating landscape evolution and for testing source‐to‐sink models

Sodium and Potassium Ion Selective Conjugated Polymers for Optical Ion Detection in Solution and Solid State

EPSRC. Grant Number: EP/G037515/1; EC FP7 Project SC2. Grant Number: 610115; EC FP7 Project ArtESun. Grant Number: 604397; EC FP7 POLYMED. Grant Number: 61253

Scale-Dependent Contributors to River Profile Geometry

Abstract: A range of complex hydraulic and geomorphic processes shape terrestrial landscapes. It remains unclear how these processes act to generate observed drainage networks across scales of interest. To address this issue, we transform observed and synthetic longitudinal river profiles into the spectral domain with a view to interrogating the different scales at which fluvial landscapes are generated. North American river profiles are characterized by red noise (i.e., spectral power, ϕ ∝ k−2, where k is wave number) at wavelengths >100 km and pink noise (ϕ ∝ k−1) at shorter wavelengths. This observation suggests that river profile geometries are scale‐dependent and using small‐scale observations to develop a general understanding of large‐scale landscape evolution is not straightforward. At wavelengths >100 km, river profile geometries appear to be controlled by smoothly varying patterns of regional uplift and slope‐dependent incision. Landscape simulations, based upon stream power that are externally forced by regional uplift do not exhibit a spectral transition from red to pink noise because these simulations do not incorporate heterogeneous erodibility. Spectral analysis of erodibility extracted from patterns of lithologic variation along river profiles suggests that the missing spectral transition is accounted for by heterogeneous substrates, which are characterized by white or blue noise (ϕ ∝ k0 or k1). Our results have implications for the way by which rivers record large‐scale tectonic forcing while incising through complex lithologic patterns

Mechanisms Underlying Hypoxia Tolerance in Drosophila melanogaster: hairy as a Metabolic Switch

Hypoxia-induced cell injury has been related to multiple pathological conditions. In order to render hypoxia-sensitive cells and tissues resistant to low O2 environment, in this current study, we used Drosophila melanogaster as a model to dissect the mechanisms underlying hypoxia-tolerance. A D. melanogaster strain that lives perpetually in an extremely low-oxygen environment (4% O2, an oxygen level that is equivalent to that over about 4,000 m above Mt. Everest) was generated through laboratory selection pressure using a continuing reduction of O2 over many generations. This phenotype is genetically stable since selected flies, after several generations in room air, survive at this low O2 level. Gene expression profiling showed striking differences between tolerant and naïve flies, in larvae and adults, both quantitatively and qualitatively. Up-regulated genes in the tolerant flies included signal transduction pathways (e.g., Notch and Toll/Imd pathways), but metabolic genes were remarkably down-regulated in the larvae. Furthermore, a different allelic frequency and enzymatic activity of the triose phosphate isomerase (TPI) was present in the tolerant versus naïve flies. The transcriptional suppressor, hairy, was up-regulated in the microarrays and its binding elements were present in the regulatory region of the specifically down-regulated metabolic genes but not others, and mutations in hairy significantly reduced hypoxia tolerance. We conclude that, the hypoxia-selected flies: (a) altered their gene expression and genetic code, and (b) coordinated their metabolic suppression, especially during development, with hairy acting as a metabolic switch, thus playing a crucial role in hypoxia-tolerance

Coordinated optimization of visual cortical maps (I) Symmetry-based analysis

In the primary visual cortex of primates and carnivores, functional architecture can be characterized by maps of various stimulus features such as orientation preference (OP), ocular dominance (OD), and spatial frequency. It is a long-standing question in theoretical neuroscience whether the observed maps should be interpreted as optima of a specific energy functional that summarizes the design principles of cortical functional architecture. A rigorous evaluation of this optimization hypothesis is particularly demanded by recent evidence that the functional architecture of OP columns precisely follows species invariant quantitative laws. Because it would be desirable to infer the form of such an optimization principle from the biological data, the optimization approach to explain cortical functional architecture raises the following questions: i) What are the genuine ground states of candidate energy functionals and how can they be calculated with precision and rigor? ii) How do differences in candidate optimization principles impact on the predicted map structure and conversely what can be learned about an hypothetical underlying optimization principle from observations on map structure? iii) Is there a way to analyze the coordinated organization of cortical maps predicted by optimization principles in general? To answer these questions we developed a general dynamical systems approach to the combined optimization of visual cortical maps of OP and another scalar feature such as OD or spatial frequency preference.Comment: 90 pages, 16 figure

Coordinated optimization of visual cortical maps (II) Numerical studies

It is an attractive hypothesis that the spatial structure of visual cortical architecture can be explained by the coordinated optimization of multiple visual cortical maps representing orientation preference (OP), ocular dominance (OD), spatial frequency, or direction preference. In part (I) of this study we defined a class of analytically tractable coordinated optimization models and solved representative examples in which a spatially complex organization of the orientation preference map is induced by inter-map interactions. We found that attractor solutions near symmetry breaking threshold predict a highly ordered map layout and require a substantial OD bias for OP pinwheel stabilization. Here we examine in numerical simulations whether such models exhibit biologically more realistic spatially irregular solutions at a finite distance from threshold and when transients towards attractor states are considered. We also examine whether model behavior qualitatively changes when the spatial periodicities of the two maps are detuned and when considering more than 2 feature dimensions. Our numerical results support the view that neither minimal energy states nor intermediate transient states of our coordinated optimization models successfully explain the spatially irregular architecture of the visual cortex. We discuss several alternative scenarios and additional factors that may improve the agreement between model solutions and biological observations.Comment: 55 pages, 11 figures. arXiv admin note: substantial text overlap with arXiv:1102.335

Consequences of converting graded to action potentials upon neural information coding and energy efficiency

Information is encoded in neural circuits using both graded and action potentials, converting between them within single neurons and successive processing layers. This conversion is accompanied by information loss and a drop in energy efficiency. We investigate the biophysical causes of this loss of information and efficiency by comparing spiking neuron models, containing stochastic voltage-gated Na+ and K+ channels, with generator potential and graded potential models lacking voltage-gated Na+ channels. We identify three causes of information loss in the generator potential that are the by-product of action potential generation: (1) the voltage-gated Na+ channels necessary for action potential generation increase intrinsic noise and (2) introduce non-linearities, and (3) the finite duration of the action potential creates a ‘footprint’ in the generator potential that obscures incoming signals. These three processes reduce information rates by ~50% in generator potentials, to ~3 times that of spike trains. Both generator potentials and graded potentials consume almost an order of magnitude less energy per second than spike trains. Because of the lower information rates of generator potentials they are substantially less energy efficient than graded potentials. However, both are an order of magnitude more efficient than spike trains due to the higher energy costs and low information content of spikes, emphasizing that there is a two-fold cost of converting analogue to digital; information loss and cost inflation

Coverage, Continuity and Visual Cortical Architecture

The primary visual cortex of many mammals contains a continuous representation of visual space, with a roughly repetitive aperiodic map of orientation preferences superimposed. It was recently found that orientation preference maps (OPMs) obey statistical laws which are apparently invariant among species widely separated in eutherian evolution. Here, we examine whether one of the most prominent models for the optimization of cortical maps, the elastic net (EN) model, can reproduce this common design. The EN model generates representations which optimally trade of stimulus space coverage and map continuity. While this model has been used in numerous studies, no analytical results about the precise layout of the predicted OPMs have been obtained so far. We present a mathematical approach to analytically calculate the cortical representations predicted by the EN model for the joint mapping of stimulus position and orientation. We find that in all previously studied regimes, predicted OPM layouts are perfectly periodic. An unbiased search through the EN parameter space identifies a novel regime of aperiodic OPMs with pinwheel densities lower than found in experiments. In an extreme limit, aperiodic OPMs quantitatively resembling experimental observations emerge. Stabilization of these layouts results from strong nonlocal interactions rather than from a coverage-continuity-compromise. Our results demonstrate that optimization models for stimulus representations dominated by nonlocal suppressive interactions are in principle capable of correctly predicting the common OPM design. They question that visual cortical feature representations can be explained by a coverage-continuity-compromise.Comment: 100 pages, including an Appendix, 21 + 7 figure