Investigating the effects of predator removal and habitat management on nest success and breeding population size of a farmland passerine: a case study

Passerines are especially vulnerable to predation at the pre-independence stage. Although the role of nest success in British farmland passerine declines is contentious, improvement in nest success through sympathetic management could play a role in their reversal. Because habitat is known to interact with predation, management options for mitigation will need to consider effects of nest predation. We present results from an observational study of a population of Common Blackbird Turdus merula on a farm which has experienced a range of agri-environment and game-management options, including a period with nest predator control, as a case study to address some of these issues. We used an information theoretic model comparison procedure to look for evidence of interactions between habitat and nest predation, and then asked whether habitat management and nest predator abundances could explain population trends at the site through their effects on nest success. Interactions were detected between measures of predator abundance and habitat variables, and these varied with nest stage - habitat within the vicinity of the nest appeared to be important at the egg stage, and nest-placement characteristics were important at the nestling stage. Although predator control appeared to have a positive influence on Blackbird breeding population size, the non-experimental set-up meant we could not eliminate other potential explanations. Variation in breeding population size did not appear to be influenced by variation in nest success alone. Our study demonstrates that observational data can only go so far in detection of such effects, and we discuss how it might be taken further. Agri-environment and game-management techniques are likely to influence nest predation pressure on farmland passerines, but the patterns, mechanisms and importance to population processes remain not wholly understood.

Investigating the effects of predator removal and habitat management on nest success and breeding population size of a farmland passerine: a case study

Passerines are especially vulnerable to predation at the pre-independence stage. Although the role of nest success in British farmland passerine declines is contentious, improvement in nest success through sympathetic management could play a role in their reversal. Because habitat is known to interact with predation, management options for mitigation will need to consider effects of nest predation. We present results from an observational study of a population of Common Blackbird Turdus merula on a farm which has experienced a range of agri-environment and game-management options, including a period with nest predator control, as a case study to address some of these issues. We used an information theoretic model comparison procedure to look for evidence of interactions between habitat and nest predation, and then asked whether habitat management and nest predator abundances could explain population trends at the site through their effects on nest success. Interactions were detected between measures of predator abundance and habitat variables, and these varied with nest stage - habitat within the vicinity of the nest appeared to be important at the egg stage, and nest-placement characteristics were important at the nestling stage. Although predator control appeared to have a positive influence on Blackbird breeding population size, the non-experimental set-up meant we could not eliminate other potential explanations. Variation in breeding population size did not appear to be influenced by variation in nest success alone. Our study demonstrates that observational data can only go so far in detection of such effects, and we discuss how it might be taken further. Agri-environment and game-management techniques are likely to influence nest predation pressure on farmland passerines, but the patterns, mechanisms and importance to population processes remain not wholly understood.

RAMI4PILPS: An intercomparison of formulations for the partitioning of solar radiation in land surface models

[1] Remotely sensed, multiannual data sets of shortwave radiative surface fluxes are now available for assimilation into land surface schemes (LSSs) of climate and/or numerical weather prediction models. The RAMI4PILPS suite of virtual experiments assesses the accuracy and consistency of the radiative transfer formulations that provide the magnitudes of absorbed, reflected, and transmitted shortwave radiative fluxes in LSSs. RAMI4PILPS evaluates models under perfectly controlled experimental conditions in order to eliminate uncertainties arising from an incomplete or erroneous knowledge of the structural, spectral and illumination related canopy characteristics typical for model comparison with in situ observations. More specifically, the shortwave radiation is separated into a visible and near-infrared spectral region, and the quality of the simulated radiative fluxes is evaluated by direct comparison with a 3-D Monte Carlo reference model identified during the third phase of the Radiation transfer Model Intercomparison (RAMI) exercise. The RAMI4PILPS setup thus allows to focus in particular on the numerical accuracy of shortwave radiative transfer formulations and to pinpoint to areas where future model improvements should concentrate. The impact of increasing degrees of structural and spectral subgrid variability on the simulated fluxes is documented and the relevance of any thus emerging biases with respect to gross primary production estimates and shortwave radiative forcings due to snow and fire events are investigated.

Hierarchical analysis of production efficiency in a coastal trawl fishery

We present, pedagogically, the Bayesian approach to composed error models under alternative, hierarchical characterizations; demonstrate, briefly, the Bayesian approach to model comparison using recent advances in Markov Chain Monte Carlo (MCMC) methods; and illustrate, empirically, the value of these techniques to natural resource economics and coastal fisheries management, in particular. The Bayesian approach to fisheries efficiency analysis is interesting for at least three reasons. First, it is a robust and highly flexible alternative to commonly applied, frequentist procedures, which dominate the literature. Second,the Bayesian approach is extremely simple to implement, requiring only a modest addition to most natural-resource economist tool-kits. Third, despite its attractions, applications of Bayesian methodology in coastal fisheries management are few.

Stated attribute non-attendance in successive choice experiments

Attribute non-attendance in choice experiments affects WTP estimates and therefore the validity of the method. A recent strand of literature uses attenuated estimates of marginal utilities of ignored attributes. Following this approach, we propose a generalisation of the mixed logit model whereby the distribution of marginal utility coefficients of a stated non-attender has a potentially lower mean and lower variance than those of a stated attender. Model comparison shows that our shrinkage approach fits the data better and produces more reliable WTP estimates. We further find that while reliability of stated attribute non-attendance increases in successive choice experiments, it does not increase when respondents report having ignored the same attribute twice.

Towards radiocarbon calibration beyond 28ka using speleothems from the Bahamas

We present a new speleothem record of atmospheric Δ14C between 28 and 44 ka that offers considerable promise for resolving some of the uncertainty associated with existing radiocarbon calibration curves for this time period. The record is based on a comprehensive suite of AMS 14C ages, using new low-blank protocols, and U–Th ages using high precision MC-ICPMS procedures. Atmospheric Δ14C was calculated by correcting 14C ages with a constant dead carbon fraction (DCF) of 22.7 ± 5.9%, based on a comparison of stalagmite 14C ages with the IntCal04 (Reimer et al., 2004) calibration curve between 15 and 11 ka. The new Δ14C speleothem record shows similar structure and amplitude to that derived from Cariaco Basin foraminifera (Hughen et al., 2004, 2006), and the match is further improved if the latter is tied to the most recent Greenland ice core chronology (Svensson et al., 2008). These data are however in conflict with a previously published 14C data set for a stalagmite record from the Bahamas — GB-89-24-1 (Beck et al., 2001), which likely suffered from 14C analytical blank subtraction issues in the older part of the record. The new Bahamas speleothem ∆14C data do not show the extreme shifts between 44 and 40 ka reported in the previous study (Beck et al., 2001). Causes for the observed structure in derived atmospheric Δ14C variation based on the new speleothem data are investigated with a suite of simulations using an earth system model of intermediate complexity. Data-model comparison indicates that major fluctuations in atmospheric ∆14C during marine isotope stage 3 is primarily a function of changes in geomagnetic field intensity, although ocean–atmosphere system reorganisation also played a supporting role.

Seasonal to interannual Arctic sea-ice predictability in current GCMs

We establish the first inter-model comparison of seasonal to interannual predictability of present-day Arctic climate by performing coordinated sets of idealized ensemble predictions with four state-of-the-art global climate models. For Arctic sea-ice extent and volume, there is potential predictive skill for lead times of up to three years, and potential prediction errors have similar growth rates and magnitudes across the models. Spatial patterns of potential prediction errors differ substantially between the models, but some features are robust. Sea-ice concentration errors are largest in the marginal ice zone, and in winter they are almost zero away from the ice edge. Sea-ice thickness errors are amplified along the coasts of the Arctic Ocean, an effect that is dominated by sea-ice advection. These results give an upper bound on the ability of current global climate models to predict important aspects of Arctic climate.

An Information Theory framework for two-stage binary image operator design

The design of translation invariant and locally defined binary image operators over large windows is made difficult by decreased statistical precision and increased training time. We present a complete framework for the application of stacked design, a recently proposed technique to create two-stage operators that circumvents that difficulty. We propose a novel algorithm, based on Information Theory, to find groups of pixels that should be used together to predict the Output Value. We employ this algorithm to automate the process of creating a set of first-level operators that are later combined in a global operator. We also propose a principled way to guide this combination, by using feature selection and model comparison. Experimental results Show that the proposed framework leads to better results than single stage design. (C) 2009 Elsevier B.V. All rights reserved.

Framework for Skew-Probit Links in Binary Regression

We review several asymmetrical links for binary regression models and present a unified approach for two skew-probit links proposed in the literature. Moreover, under skew-probit link, conditions for the existence of the ML estimators and the posterior distribution under improper priors are established. The framework proposed here considers two sets of latent variables which are helpful to implement the Bayesian MCMC approach. A simulation study to criteria for models comparison is conducted and two applications are made. Using different Bayesian criteria we show that, for these data sets, the skew-probit links are better than alternative links proposed in the literature.

Genetic parameter estimates for live weight and daily live weight gain obtained for Nellore bulls in a test station using different models

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Mini-implant and Nance button for initial retraction of maxillary canines: a prospective study in cast models

OBJETIVO: a ancoragem óssea é fundamental para o sucesso do tratamento de algumas más oclusões, pois permite a aplicação de forças contínuas, diminui o tempo de tratamento e independe da colaboração do paciente. MÉTODOS: o propósito desse trabalho foi comparar, por meio de modelos dentários, a perda de ancoragem após a retração inicial de caninos superiores entre dois grupos. O grupo A utilizou o mini-implante enquanto o grupo B utilizou o Botão de Nance. Para todos os pacientes foram realizados dois modelos (M1 e M2). Os primeiros modelos foram realizados ao início (M1), e os outros ao final da retração inicial de canino (M2). RESULTADOS: todas as medidas foram tabuladas e submetidas à análise estatística. Para verificar o erro sistemático intraexaminador foi utilizado o teste t pareado. Na determinação do erro casual utilizou-se o cálculo de erro proposto por Dahlberg. Para comparação entre as fases Início e Após, foi utilizado o teste t pareado. Para a comparação entre os grupos de mini-implante e Botão de Nance, foi utilizado o teste t de Student para medidas independentes. em todos os testes foi adotado nível de significância de 5% (p<0,05). CONCLUSÃO: ao se medir e comparar em modelos dentários a perda de ancoragem dos molares após a retração inicial de canino utilizando-se dois sistemas de ancoragem distintos (Mini-implante e Botão de Nance), pôde-se observar a inexistência de diferença estatisticamente significativa entre os dois grupos.

First-order decay models to describe soil C-CO2 Loss after rotary tillage

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A new three-phase transformer modeling for three-phase harmonic analysis in distribution systems

This work presents a new three-phase transformer modeling suitable for simulations in Pspice environment, which until now represents the electrical characteristics of a real transformer. It is proposed the model comparison to a three-phase transformer modeling present in EMTP - ATP program, which includes the electrical and magnetic characteristics. In addition, a set including non-linear loads and a real three-phase transformer was prepared in order to compare and validate the results of this new proposed model. The three-phase Pspice transformer modeling, different from the conventional one using inductance coupling, is remarkable for its simplicity and ease in simulation process, since it uses available voltage and current sources present in Pspice program, enabling simulations of three-phase network system including the most common configuration, three wires in the primary side and four wires in the secondary side (three-phases and neutral). Finally, the proposed modeling becomes a powerful tool for three-phase network simulations due to its simplicity and accuracy, able to simulate and analyze harmonic flow in three-phase systems under balanced and unbalanced conditions.

Random regression models using Legendre polynomials or linear splines for test-day milk yield of dairy Gyr (Bos indicus) cattle

Studies investigating the use of random regression models for genetic evaluation of milk production in Zebu cattle are scarce. In this study, 59,744 test-day milk yield records from 7,810 first lactations of purebred dairy Gyr (Bos indicus) and crossbred (dairy Gyr × Holstein) cows were used to compare random regression models in which additive genetic and permanent environmental effects were modeled using orthogonal Legendre polynomials or linear spline functions. Residual variances were modeled considering 1, 5, or 10 classes of days in milk. Five classes fitted the changes in residual variances over the lactation adequately and were used for model comparison. The model that fitted linear spline functions with 6 knots provided the lowest sum of residual variances across lactation. On the other hand, according to the deviance information criterion (DIC) and Bayesian information criterion (BIC), a model using third-order and fourth-order Legendre polynomials for additive genetic and permanent environmental effects, respectively, provided the best fit. However, the high rank correlation (0.998) between this model and that applying third-order Legendre polynomials for additive genetic and permanent environmental effects, indicates that, in practice, the same bulls would be selected by both models. The last model, which is less parameterized, is a parsimonious option for fitting dairy Gyr breed test-day milk yield records. © 2013 American Dairy Science Association.

Linear and Poisson models for genetic evaluation of tick resistance in cross-bred Hereford x Nellore cattle

Cattle resistance to ticks is measured by the number of ticks infesting the animal. The model used for the genetic analysis of cattle resistance to ticks frequently requires logarithmic transformation of the observations. The objective of this study was to evaluate the predictive ability and goodness of fit of different models for the analysis of this trait in cross-bred Hereford x Nellore cattle. Three models were tested: a linear model using logarithmic transformation of the observations (MLOG); a linear model without transformation of the observations (MLIN); and a generalized linear Poisson model with residual term (MPOI). All models included the classificatory effects of contemporary group and genetic group and the covariates age of animal at the time of recording and individual heterozygosis, as well as additive genetic effects as random effects. Heritability estimates were 0.08 ± 0.02, 0.10 ± 0.02 and 0.14 ± 0.04 for MLIN, MLOG and MPOI models, respectively. The model fit quality, verified by deviance information criterion (DIC) and residual mean square, indicated fit superiority of MPOI model. The predictive ability of the models was compared by validation test in independent sample. The MPOI model was slightly superior in terms of goodness of fit and predictive ability, whereas the correlations between observed and predicted tick counts were practically the same for all models. A higher rank correlation between breeding values was observed between models MLOG and MPOI. Poisson model can be used for the selection of tick-resistant animals. © 2013 Blackwell Verlag GmbH.