Intensive versus Extensive Dairy Production Systems: Dairy States in the Eastern and Midwestern U.S. and Key Pasture Countries the E.U.: Determining the Competitive Edge

In recent years, significant structural and production system changes have been noted in the U.S. and European Union, as well as increased interest in pasture-based dairy systems. Technical efficiency, returns to scale, and farm characteristics are compared by size and production system in traditional U.S. dairy states and E.U. countries.U.S., EU Countries, Dairy Systems, Technical Efficiency, Returns To Scale, Size, Technology, Land Prices, Production Economics, Q12,

Economic Efficiency of U.S. Organic Versus Conventional Dairy Farms: Evidence from 2005 and 2010

We estimate an input distance function for U.S. dairy farming to examine the competitiveness of organic and non-organic dairy production by system and size. Across organic/non-organic systems and size classes, size is the major determinant of competitiveness based on various measures of productivity and returns to scale.Organic, Non-organic, Input Distance Function, Livestock Production/Industries, Production Economics,

Forage Outsourcing in the Dairy Sector: The Extent of Use and Impact on Farm Profitability

The extent of forage purchasing behavior in milk production and its impact on profitability are analyzed using data from the 2000 and 2005 dairy versions of the Agricultural Resource Management Survey. Forage outsourcing is more common with hay than with silage and haylage, and is more prevalent in the western United States. Though silage and haylage outsourcing is found to impact profitability, the major profitability drivers appear to be farm size and efficiency. Evidence of significant forage contracting is found in the western United States.forage, input purchasing, outsourcing, contracting, milk production, Farm Management, Industrial Organization, Livestock Production/Industries,

Small U.S. Dairy Farms: Can They Compete?

The U.S. dairy industry is undergoing rapid structural change, evolving from a structure including many small farmers in the Upper Midwest and Northeast to one that includes very large farms in new production regions. Small farms are struggling to retain competitiveness via improved management and low-input systems. Using data from USDA’s Agricultural Resource Management Survey, we determine the extent of U.S. conventional and pasture-based milk production during 2003-2007, and estimate net returns, scale efficiency, and technical efficiency associated with the systems across different operation sizes. We compare the financial performance of small conventional and pasture-based producers with one another and with largescale producers. A stochastic production frontier is used to analyze performance over the period for conventional and pasture technologies identified using a binomial logit model. Large conventional farms generally outperformed smaller farms using most economic measures – technical efficiency, various profitability measures, and returns to scale.Pasture-based system, technical efficiency, returns to scale, dairy, Livestock Production/Industries, Productivity Analysis,

Pasture-Based Dairy Systems: Who Are the Producers and Are Their Operations More Profitable than Conventional Dairies?

U.S. dairy operations are sorted via a multinomial logit model into three production systems: pasture-based, semi-pasture-based, and conventional. Region, farm size, financial situation, and production intensity measures impact system choice. Analysis follows to determine the impact of production system on enterprise profitability. Region, farm size, and demographic variables impact profitability, as does system choice: semi-pasture-based operations were less profitable than conventional operations on an enterprise, per hundredweight of milk produced basis. Significant differences were not found in the profitability of pasture-based operations versus those using other systems.dairy farm size, grazing, pasture-based dairying, Livestock Production/Industries,

Determining the Competitive Edge: Diversified Dairy Production Systems in the United States and the European Union

Agricultural and Food Policy, Farm Management, Livestock Production/Industries, Production Economics, Productivity Analysis,

Genomic signatures of population decline in the malaria mosquito Anopheles gambiae

Population genomic features such as nucleotide diversity and linkage disequilibrium are expected to be strongly shaped by changes in population size, and might therefore be useful for monitoring the success of a control campaign. In the Kilifi district of Kenya, there has been a marked decline in the abundance of the malaria vector Anopheles gambiae subsequent to the rollout of insecticide-treated bed nets. To investigate whether this decline left a detectable population genomic signature, simulations were performed to compare the effect of population crashes on nucleotide diversity, Tajima's D, and linkage disequilibrium (as measured by the population recombination parameter ρ). Linkage disequilibrium and ρ were estimated for An. gambiae from Kilifi, and compared them to values for Anopheles arabiensis and Anopheles merus at the same location, and for An. gambiae in a location 200 km from Kilifi. In the first simulations ρ changed more rapidly after a population crash than the other statistics, and therefore is a more sensitive indicator of recent population decline. In the empirical data, linkage disequilibrium extends 100-1000 times further, and ρ is 100-1000 times smaller, for the Kilifi population of An. gambiae than for any of the other populations. There were also significant runs of homozygosity in many of the individual An. gambiae mosquitoes from Kilifi. These results support the hypothesis that the recent decline in An. gambiae was driven by the rollout of bed nets. Measuring population genomic parameters in a small sample of individuals before, during and after vector or pest control may be a valuable method of tracking the effectiveness of interventions

Spontaneous allelic variant in deafness–blindness gene \u3ci\u3eUsh1g\u3c/i\u3e resulting in an expanded phenotype

Relationships between novel phenotypic behaviors and specific genetic alterations are often discovered using target-specific, directed mutagenesis or phenotypic selection following chemical mutagenesis. An alternative approach is to exploit deficiencies in DNA repair pathways that maintain genetic integrity in response to spontaneously induced damage. Mice deficient in the DNA glycosylase NEIL1 show elevated spontaneous mutations, which arise from translesion DNA synthesis past oxidatively induced base damage. Several litters of Neil1 knockout mice included animals that were distinguished by their backwards-walking behavior in open-field environments, while maintaining frantic forward movements in their home cage environment. Other phenotypic manifestations included swim test failures, head tilting and circling. Mapping of the mutation that conferred these behaviors showed the introduction of a stop codon at amino acid 4 of the Ush1g gene. Ush1gbw/bwnull mice displayed auditory and vestibular defects that are commonly seen with mutations affecting inner-ear hair-cell function, including a complete lack of auditory brainstem responses and vestibular-evoked potentials. As in other Usher syndrome type I mutant mouse lines, hair cell phenotypes included disorganized and split hair bundles, as well as altered distribution of proteins for stereocilia that localize to the tips of row 1 or row 2. Disruption to the bundle and kinocilium displacement suggested that USH1G is essential for forming the hair cell\u27s kinocilial links. Consistent with other Usher type 1 models, Ush1gbw/bw mice had no substantial retinal degeneration compared with Ush1gbw/+ controls. In contrast to previously described Ush1g alleles, this new allele provides the first knockout model for this gene

Homophily and Contagion Are Generically Confounded in Observational Social Network Studies

We consider processes on social networks that can potentially involve three factors: homophily, or the formation of social ties due to matching individual traits; social contagion, also known as social influence; and the causal effect of an individual's covariates on their behavior or other measurable responses. We show that, generically, all of these are confounded with each other. Distinguishing them from one another requires strong assumptions on the parametrization of the social process or on the adequacy of the covariates used (or both). In particular we demonstrate, with simple examples, that asymmetries in regression coefficients cannot identify causal effects, and that very simple models of imitation (a form of social contagion) can produce substantial correlations between an individual's enduring traits and their choices, even when there is no intrinsic affinity between them. We also suggest some possible constructive responses to these results.Comment: 27 pages, 9 figures. V2: Revised in response to referees. V3: Ditt

First measurement of the 34S(p,γ)35Cl reaction rate through indirect methods for presolar nova grains

Sulphur isotopic ratio measurements may help to establish the astrophysical sites in which certain presolar grains were formed. Nova model predictions of the 34S/32S ratio are, however, unreliable due to the lack of an experimental 34S(p,γ)35Cl reaction rate. To this end, we have measured the 34S(3He,d)35Cl reaction at 20 MeV using a high resolution quadrupole-dipole-dipole-dipole magnetic spectrograph. Twenty-two levels over 6.2 MeV<Ex(35Cl)<7.4 MeV were identified, ten of which were previously unobserved. Proton-transfer spectroscopic factors have been measured for the first time over the energy range relevant for novae. With this new spectroscopic information a new 34S(p,γ)35Cl reaction rate has been determined using a Monte Carlo method. Hydrodynamic nova model calculations have been performed using this new reaction rate. These models show that remaining uncertainties in the 34S(p,γ) rate affect  nucleosynthesis predictions by less than a factor of 1.4, and predict a 34S/32S isotopic ratio of 0.014–0.017. Since recent type II supernova models predict 34S/32S=0.026−0.053, the 34S/32S isotopic ratio may be used, in conjunction with other isotopic signatures, to distinguish presolar grains from oxygen-neon nova and type II supernova origin. Our results address a key nuclear physics uncertainty on which recent considerations discounting the nova origin of several grains depend