KANSAS WHEAT YIELD RISK MEASURES AND AGGREGATION: A META- ANALYSIS APPROACH

A meta-analysis approach to prediction of farm level yield risk from county level yield series is applied to Kansas wheat yields. A nonlinear relationship between county level and farm level yield risk is found, which indicates that yield risk increases at an increasing rate as the number of acres in the risk measure decreases. County level yield variability should be adjusted upward by approximately .1% for each percent difference in county acreage and average farm acreage within the county. The meta-analysis approach is shown to be promising for the prediction of farm level yield risk when farm level information is difficult to obtain.Risk and Uncertainty,

Seeding supermassive black holes with a nonvortical dark-matter subcomponent

Article / Letter to editorLeids Instituut Onderzoek Natuurkund

Groundwater seepage landscapes from distant and local sources in experiments and on Mars

© 2014 Author(s). Valleys with theater-shaped heads can form due to the seepage of groundwater and as a result of knickpoint (waterfall) erosion generated by overland flow. This ambiguity in the mechanism of formation hampers the interpretation of such valleys on Mars, particularly since there is limited knowledge of material properties. Moreover, the hydrological implications of a groundwater or surface water origin are important for our understanding of the evolution of surface features on Mars, and a quantification of valley morphologies at the landscape scale may provide diagnostic insights on the formative hydrological conditions. However, flow patterns and the resulting landscapes produced by different sources of groundwater are poorly understood. We aim to improve the understanding of the formation of entire valley landscapes through seepage processes from different groundwater sources that will provide a framework of landscape metrics for the interpretation of such systems. We study groundwater seepage from a distant source of groundwater and from infiltration of local precipitation in a series of sandbox experiments and combine our results with previous experiments and observations of the Martian surface. Key results are that groundwater flow piracy acts on valleys fed by a distant groundwater source and results in a sparsely dissected landscape of many small and a few large valleys. In contrast, valleys fed by a local groundwater source, i.e., nearby infiltration, result in a densely dissected landscape. In addition, valleys fed by a distant groundwater source grow towards that source, while valleys with a local source grow in a broad range of directions and have a strong tendency to bifurcate, particularly on flatter surfaces. We consider these results with respect to two Martian cases: Louros Valles shows properties of seepage by a local source of groundwater and Nirgal Vallis shows evidence of a distant source, which we interpret as groundwater flow from Tharsis

On cosmological observables in a swiss-cheese universe

Photon geodesics are calculated in a swiss-cheese model, where the cheese is made of the usual Friedmann-Robertson-Walker solution and the holes are constructed from a Lemaitre-Tolman-Bondi solution of Einstein's equations. The observables on which we focus are the changes in the redshift, in the angular-diameter--distance relation, in the luminosity-distance--redshift relation, and in the corresponding distance modulus. We find that redshift effects are suppressed when the hole is small because of a compensation effect acting on the scale of half a hole resulting from the special case of spherical symmetry. However, we find interesting effects in the calculation of the angular distance: strong evolution of the inhomogeneities (as in the approach to caustic formation) causes the photon path to deviate from that of the FRW case. Therefore, the inhomogeneities are able to partly mimic the effects of a dark-energy component. Our results also suggest that the nonlinear effects of caustic formation in cold dark matter models may lead to interesting effects on photon trajectories.Comment: 25 pages, 21 figures; replaced to fit the version accepted for publication in Phys. Rev.

Phytoplankton growth at the shelf-break front in the Middle Atlantic Bight

The summertime front near the shelf break in the Middle Atlantic Bight is both thermohaline and baroclinic. Near the surface, large gradients of temperature (T) and salinity (S) exist with little cross-frontal variation in density. At depths \u3e50 m, an isopycnal boundary separates Slope Water from colder, fresher shelf water. Higher concentrations of chlorophyll are found in the upper part of the front, between water types of shelf and Slope Water origin. Calculations show also that the front is a region of enhanced phytoplankton growth. It is proposed that the relative fertility of the front is the result of large-scale deformations of the T/S boundary between shelf and Slope Water. The entrainment of deep shelf water along the shallowing, seaward-sloping, isopycnals in the deeper part of the front by these large-scale perturbations bring turbid, nutrient-rich water into clearer water that is also nutrient poor. The combination of this nutrient enrichment and a well-lighted water column makes the front more productive than elsewhere

Light-cone averages in a swiss-cheese universe

We analyze a toy swiss-cheese cosmological model to study the averaging problem. In our model, the cheese is the EdS model and the holes are constructed from a LTB solution. We study the propagation of photons in the swiss-cheese model, and find a phenomenological homogeneous model to describe observables. Following a fitting procedure based on light-cone averages, we find that the the expansion scalar is unaffected by the inhomogeneities. This is because of spherical symmetry. However, the light-cone average of the density as a function of redshift is affected by inhomogeneities. The effect arises because, as the universe evolves, a photon spends more and more time in the (large) voids than in the (thin) high-density structures. The phenomenological homogeneous model describing the light-cone average of the density is similar to the concordance model. Although the sole source in the swiss-cheese model is matter, the phenomenological homogeneous model behaves as if it has a dark-energy component. Finally, we study how the equation of state of the phenomenological model depends on the size of the inhomogeneities, and find that the equation-of-state parameters w_0 and w_a follow a power-law dependence with a scaling exponent equal to unity. That is, the equation of state depends linearly on the distance the photon travels through voids. We conclude that within our toy model, the holes must have a present size of about 250 Mpc to be able to mimic the concordance model.Comment: 20 pages, 14 figures; replaced to fit the version accepted for publication in Phys. Rev.

Robust fitting for generalized additive models for location, scale and shape

The validity of estimation and smoothing parameter selection for the wide class of generalized additive models for location, scale and shape (GAMLSS) relies on the correct specification of a likelihood function. Deviations from such assumption are known to mislead any likelihood-based inference and can hinder penalization schemes meant to ensure some degree of smoothness for nonlinear effects. We propose a general approach to achieve robustness in fitting GAMLSSs by limiting the contribution of observations with low log-likelihood values. Robust selection of the smoothing parameters can be carried out either by minimizing information criteria that naturally arise from the robustified likelihood or via an extended Fellner–Schall method. The latter allows for automatic smoothing parameter selection and is particularly advantageous in applications with multiple smoothing parameters. We also address the challenge of tuning robust estimators for models with nonlinear effects by proposing a novel median downweighting proportion criterion. This enables a fair comparison with existing robust estimators for the special case of generalized additive models, where our estimator competes favorably. The overall good performance of our proposal is illustrated by further simulations in the GAMLSS setting and by an application to functional magnetic resonance brain imaging using bivariate smoothing splines

Changes in Producers’ Perceptions of Within-field Yield Variability Following Adoption of Cotton Yield Monitors

Precision Farming, Risk, Yield Monitor, Yield Variability, Yield Perceptions, Spatial Yield Distributions, Within Field Variability, Farm Management, Production Economics, Risk and Uncertainty, Q12, Q16,