Extinctions of aculeate pollinators in Britain and the role of large-scale agricultural changes

Pollinators are fundamental to maintaining both biodiversity and agricultural productivity, but habitat destruction, loss of flower resources, and increased use of pesticides are causing declines in their abundance and diversity. Using historical records we assessed the rate of extinction of bee and flower-visiting wasp species in Britain, from the mid 19th century to the present. The most rapid phase of extinction appears to be related to changes in agricultural policy and practice beginning in the 1920s, before the agricultural intensification prompted by the Second World War, often cited as the most important driver of biodiversity loss in Britain. Slowing of the extinction rate from the 1960s onwards may be due to prior loss of the most sensitive species and/or effective conservation programs

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

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

BIRDSFOOT TREFOIL - Brings New Life to Pastures

Thereare over 3 million acres of low yielding open land pastures in Iowa. Birdsfoot trefoil, a high quality, bloat-free forage with persistent stand and ability to withstand continuous grazing might be the answer to developing these low yield pastures

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

Side effects of analgesia may significantly reduce quality of life in symptomatic multiple myeloma: a cross-sectional prevalence study

Background Pain is a common symptom in patients with multiple myeloma (MM). Many patients are dependent on analgesics and in particular opioids, but there is limited information on the impact of these drugs and their side effects on health-related quality of life (HRQoL). Method In a cross-sectional study, semi-structured interviews were performed in 21 patients attending the hospital with symptomatic MM on pain medications. HRQoL was measured using items 29 and 30 of the European Organisation for Research and Treatment of Cancer (EORTC) QLQ-C30. Results Patients were able to recall a median of two (range 0–4) analgesics. They spontaneously identified a median of two (range 1–5) side effects attributable to their analgesic medications. Patients’ assessment of HRQoL based on the EORTC QLQ-C30 questions 29/30 was mean 48.3 (95 % CI; 38.7–57.9) out of 100. Patients’ assessment of their HRQoL in the hypothetical situation, in which they would not experience any side effects from analgesics, was significantly higher: 62.6 (53.5–71.7) (t test, p=0.001). Conclusion This study provides, for the first time, evidence that side effects of analgesics are common in symptomatic MM and may result in a statistically and clinically significant reduction of self-reported HRQoL

Influence of Richness and Seeding Density on Invasion Resistance in Experimental Tallgrass Prairie Restorations

In recent years, agricultural producers and non-governmental organizations and agencies have restored thousands of hectares of cropland to grassland in the Great Plains of the United States. However, little is known about the relationships between richness and seeding density in these restorations and resistance to invasive plant species. We assessed the effects of richness and seeding density on resistance to invasive and other unseeded plant species in experimental tallgrass prairie plots in central Nebraska. In 2006, twenty-four 55 m × 55 m plots were planted with six replicates in each of four treatments: high richness (97 species typically planted by The Nature Conservancy), at low and high seeding densities, and low richness (15 species representing a typical Conservation Reserve Program mix, CP25), at low and high seeding densities. There was a significant negative relationship between richness and basal cover of unseeded perennial forbs/legumes and unseeded perennial/annual grasses, abundance of bull thistle (Cirsium vulgare), and the number of inflorescences removed from smooth brome (Bromus inermis) transplants. Invasion resistance may have been higher in the high richness treatments because of the characteristics of the dominant species in these plots or because of greater interspecific competition for limiting resources among forbs/legumes with neighboring plants belonging to the same functional group. Seeding density was not important in affecting invasion resistance, except in the cover of unseeded grasses. Increasing seed mix richness may be more effective than increasing the seeding density for decreasing invasion by unseeded perennial species, bull thistle, and smooth brome

Coupling dendroecological and remote sensing techniques to assess the biophysical traits of \u3ci\u3eJuniperus virginiana\u3c/i\u3e and \u3ci\u3ePinus ponderosa\u3c/i\u3e within the Semi-Arid grasslands of the Nebraska Sandhills

Woody species encroachment is occurring within the semi-arid grasslands of the Nebraska Sandhills U.S., primarily driven by native Juniperus virginiana and Pinus ponderosa, altering ecosystems and the services they provide. Effective, low cost, and cross-scale monitoring of woody species growth and performance is necessary for integrated grassland and forest management in the face of climate variability and change. In this study, we sought to establish a relationship between remote sensing-derived vegetation indices (VIs), tree dendrochronological (raw and standardized tree ring width) measurements, and the abiotic environment [(precipitation, temperature, Palmer Drought Severity Index (PDSI), and soil water content (0–300 cm depth)], over a 30-year period (1984–2013), to assess the performance of encroaching woody J. virginiana and P. ponderosa within the Nebraska Sandhills. We also investigated whether VIs can be used as an effective alternative tool to replace or complement ground measurements. Our results indicate that precipitation, temperature, and PDSI were significant (p \u3c 0.05) predictors of J. virginiana and P. ponderosa growth based on dendrochronological measurements and VIs, while soil water content from 40 to 300 cm depth was a significant predictor of J. virginiana performance. Out of the six VIs that were investigated, four were significant predictors of tree ring growth. R2 values between grassland VIs and growing season climate were greater than those of J. virginiana or P. ponderosa, while grassland performance was decoupled from soil water content. Additionally, climatic conditions in the previous year were significant determinants of current year growth of tree species but did not affect current year grassland performance. This study provides evidence for the efficacy of remote sensing-based VIs in monitoring interannual variation in the growth of woody species, while determining abiotic factors impacting the growth of grassland vegetation, J. virginiana, and P. ponderosa in the Nebraska Sandhills

Integrated Dairy Waste Management, Water Quality and Crop Utilization System

Livestock-crop farmers have very limited opportunities to efficiently utilize manure in an environmentally safe manner during the cropgrowing season. In this study, dairy manure slurry was surfaceapplied over a two year period on reed canarygrass (Phalaris arundinacea L.), a perennial grass cover (living filter) at one location each in Iowa, Minnesota, and Wisconsin. Public and private (University and Cenex/Land O’Lakes) research and development capabilities were coupled to request and receive funding from a nationally-mandated program on water quality (United States Department of Agriculture). The primary objective was to study factors which impinge upon acceptable ground water quality using a living filter. Contrasting soil types were included to evaluate slurry application methods, timing, and rates; RC response to manure or fertilizer N; and herbage, soil, and soil solution N levels. We suggest our effort as an example of cooperation between private and public agriculturalists in seeking funding for research addressing important issues