283 research outputs found
CLUES TO THE MEDIEVAL DESTABILIZATION OF THE NEBRASKA SAND HILLS, USA, FROM ANCIENT POCKET GOPHER BURROWS
The Nebraska Sand Hills are a stabilized dune field in the central United States that reflect past conditions of drought. The most recent drought, known as the Medieval Climatic Anomaly, occurred from A.D. 900 to A.D. 1300 and had an enormous effect on the thriving prairie ecosystem, which included large populations of the plains pocket gopher (Geomys bursarius). Burrows of these organisms across a paleosol-eolian sand boundary in the Sand Hills indicate abrupt climate change during the transition from stabilized to active dune field and from humid to arid conditions. Medieval gophers tunneled at greater depths below the surface than do modern gophers, indicating the behavioral changes these animals underwent to survive during the transition. The gophers were likely surviving on roots remaining in the underlying soil as it was buried by sand; they tunneled .1 m up to the surface to deposit mounds of excavated soil and sand. Most of the burrows occur in areas of low-angle bedding, suggesting loss of vegetation occurred first on the crests of the newly formed dunes while vegetation persisted in the interdunes. Optically stimulated luminescence dates from a dune containing ancient gopher burrows are nearly identical throughout the height of the dune, indicating rapid accumulation of sand. As accumulation of sand was rapid, vegetative loss must also have occurred quickly, though not in a uniform pattern across the region. Pocket gophers were apparently able to survive in areas of remaining vegetation for a short time, but in a relatively short period of time, they were unable to reach their food sources and were forced ultimately to abandon the uplands in the region
Smoothed Analysis of Tensor Decompositions
Low rank tensor decompositions are a powerful tool for learning generative
models, and uniqueness results give them a significant advantage over matrix
decomposition methods. However, tensors pose significant algorithmic challenges
and tensors analogs of much of the matrix algebra toolkit are unlikely to exist
because of hardness results. Efficient decomposition in the overcomplete case
(where rank exceeds dimension) is particularly challenging. We introduce a
smoothed analysis model for studying these questions and develop an efficient
algorithm for tensor decomposition in the highly overcomplete case (rank
polynomial in the dimension). In this setting, we show that our algorithm is
robust to inverse polynomial error -- a crucial property for applications in
learning since we are only allowed a polynomial number of samples. While
algorithms are known for exact tensor decomposition in some overcomplete
settings, our main contribution is in analyzing their stability in the
framework of smoothed analysis.
Our main technical contribution is to show that tensor products of perturbed
vectors are linearly independent in a robust sense (i.e. the associated matrix
has singular values that are at least an inverse polynomial). This key result
paves the way for applying tensor methods to learning problems in the smoothed
setting. In particular, we use it to obtain results for learning multi-view
models and mixtures of axis-aligned Gaussians where there are many more
"components" than dimensions. The assumption here is that the model is not
adversarially chosen, formalized by a perturbation of model parameters. We
believe this an appealing way to analyze realistic instances of learning
problems, since this framework allows us to overcome many of the usual
limitations of using tensor methods.Comment: 32 pages (including appendix
Diversity and Productivity in a Long-Term Grassland Experiment
Plant diversity and niche complementarity had progressively stronger effects on ecosystem functioning during a 7-year experiment, with 16-species plots attaining 2.7 times greater biomass than monocultures. Diversity effects were neither transients nor explained solely by a few productive or unviable species. Rather, many higher-diversity plots outperformed the best monoculture. These results help resolve debate over biodiversity and ecosystem functioning, show effects at higher than expected diversity levels, and demonstrate, for these ecosystems, that even the best-chosen monocultures cannot achieve greater productivity or carbon stores than higher-diversity sites.
Includes Supplementary Material
The Scandinavian Sarcoma Group skeletal metastasis register: Survival after surgery for bone metastases in the pelvis and extremities
How does flow in a pipe become turbulent?
The transition to turbulence in pipe flow does not follow the scenario
familiar from Rayleigh-Benard or Taylor-Couette flow since the laminar profile
is stable against infinitesimal perturbations for all Reynolds numbers.
Moreover, even when the flow speed is high enough and the perturbation
sufficiently strong such that turbulent flow is established, it can return to
the laminar state without any indication of the imminent decay. In this
parameter range, the lifetimes of perturbations show a sensitive dependence on
initial conditions and an exponential distribution. The turbulence seems to be
supported by three-dimensional travelling waves which appear transiently in the
flow field. The boundary between laminar and turbulent dynamics is formed by
the stable manifold of an invariant chaotic state. We will also discuss the
relation between observations in short, periodically continued domains, and the
dynamics in fully extended puffs.Comment: for the proceedings of statphys 2
Invasive Andropogon gayanus (gamba grass) is an ecosystem transformer of nitrogen relations in Australian savanna
The African grass Andropogon gayanus Kunth. is invading Australian savannas, altering their ecological and biogeochemical function. To assess impacts on nitrogen (N) cycling, we quantified litter decomposition and N dynamics of grass litter in native grass and A. gayanus invaded savanna using destructive in situ grass litter harvests and litterbag incubations (soil surface and aerial position). Only 30% of the A. gayanus in situ litter decomposed, compared to 61% of the native grass litter, due to the former being largely comprised of highly resistant A. gayanus stem. In contrast to the stem, A. gayanus leaf decomposition was approximately 3- and 2-times higher than the dominant native grass, Alloteropsis semilata at the surface and aerial position, respectively. Lower initial lignin concentrations, and higher consumption by termites, accounted for the greater surface decomposition rate of A. gayanus. N flux estimates suggest the N release of A. gayanus litter is insufficient to compensate for increased N uptake and N loss via fire in invaded plots. Annually burnt invaded savanna may lose up to 8.2% of the upper soil N pool over a decade. Without additional inputs via biological N fixation, A. gayanus invasion is likely to diminish the N capital of Australia's frequently burnt savannas
Developing a National Alfalfa Information System
Using state-of-the-art telecommunication technologies, this project is developing a comprehensive knowledge resource for alfalfa (Medicago sativa L.); the National Alfalfa Information System (NAIS). This project will serve as an improved model for Extension educational programs. Alfalfa is the most important forage crop in the USA and grown worldwide for feeding millions of livestock and in many cropping systems. As a legume, it is important in sustaining the environment and the productivity of agriculture. Information needs are present in every state and internationally. The NAIS is being developed through national and international cooperation, putting the best science-based alfalfa information and expertise at the fingertips of producers, consultants, extension workers, instructors, researchers, and users. Collaboratively developed materials will reduce duplication of effort. To make the knowledge easy-to-use, educational design, communication, and information science professionals are working with alfalfa experts in creating a WWW system and Web-aware CD-ROM. To ensure content quality, peer-review by members of multiple professional societies is included. A significant result will be around-the-clock availability of up-to-date, easy-to-use, and peerreviewed information. Shared workload and the peer-review process can influence faculty morale, efficiency, and effectiveness, an adjunct to maximizing the utilization of alfalfa worldwide by making the best information readily available
A restricted curriculum for second language learners – a self-fulfilling teacher strategy?
Order-of-magnitude speedup for steady states and traveling waves via Stokes preconditioning in Channelflow and Openpipeflow
Steady states and traveling waves play a fundamental role in understanding
hydrodynamic problems. Even when unstable, these states provide the
bifurcation-theoretic explanation for the origin of the observed states. In
turbulent wall-bounded shear flows, these states have been hypothesized to be
saddle points organizing the trajectories within a chaotic attractor. These
states must be computed with Newton's method or one of its generalizations,
since time-integration cannot converge to unstable equilibria. The bottleneck
is the solution of linear systems involving the Jacobian of the Navier-Stokes
or Boussinesq equations. Originally such computations were carried out by
constructing and directly inverting the Jacobian, but this is unfeasible for
the matrices arising from three-dimensional hydrodynamic configurations in
large domains. A popular method is to seek states that are invariant under
numerical time integration. Surprisingly, equilibria may also be found by
seeking flows that are invariant under a single very large Backwards-Euler
Forwards-Euler timestep. We show that this method, called Stokes
preconditioning, is 10 to 50 times faster at computing steady states in plane
Couette flow and traveling waves in pipe flow. Moreover, it can be carried out
using Channelflow (by Gibson) and Openpipeflow (by Willis) without any changes
to these popular spectral codes. We explain the convergence rate as a function
of the integration period and Reynolds number by computing the full spectra of
the operators corresponding to the Jacobians of both methods.Comment: in Computational Modelling of Bifurcations and Instabilities in Fluid
Dynamics, ed. Alexander Gelfgat (Springer, 2018
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