Digital Commons Network^™

Deterring Non-Target Birds From Toxic Bait Sites For Wild Pigs, Nathan P. Snow, Joseph M. Halseth, Justin A. Foster, Michael J. Lavelle, Justin W. Fischer, Michael P. Glow, Ingrid A. Messer, Seth M. Cook, Kurt C. Vercauteren

United States Department of Agriculture Wildlife Services: Staff Publications

Toxic baiting of wild pigs (Sus scrofa) is a potential new tool for population control and damage reduction in the US. Field trials testing a prototype toxic bait (HOGGONE 2 containing 5% sodium nitrite [SN]), though, revealed that wild pigs spilled small particles of toxic bait outside of bait stations which subsequently created hazards for non-target species that consumed those particles, primarily passerine birds. To deter non-target birds from consuming particles of spilled bait, we tested four deterrents at mock bait sites (i.e., baited with bird seed) in north-central Colorado, USA during April–May 2020. We found a programable, inflatable deterrent …

Towards A More Comprehensive Understanding Of Wild Pig (Sus Scrofa) Impacts On Agricultural Producers: Insights From A Texas Case Study, Keith M. Carlisle, Nicole Didero, Sophie Mckee, Julie Elser, Stephanie A. Shwiff

United States Department of Agriculture Wildlife Services: Staff Publications

This research investigates the impacts of invasive wild pigs (Sus scrofa Linneaus) on agricultural producers in Texas, with the aim of identifying and describing all categories of wild pig impacts and quantifying the extent of producers’ over- or underestimation of their total wild pig-related costs in 2018, as compared to calculations based upon data subsequently provided by the producers about individual wild pig-related costs and losses. Based on interviews with 23 producers in 16 Texas counties, we identified more than 20 discrete categories of negative impacts and negligible positive impacts associated with wild pigs. Among them were categories that have …

Landscape Transformations Produce Favorable Roosting Conditions For Turkey Vultures And Black Vultures, Jacob E. Hill, Kenneth F. Kellner, Bryan M. Kluever, Michael L. Avery, John S. Humphrey, Eric A. Tillman, Travis L. Devault, Jerrold L. Belant

United States Department of Agriculture Wildlife Services: Staff Publications

Recent increases in turkey vulture (Cathartes aura) and black vulture (Coragyps atratus) populations in North America have been attributed in part to their success adapting to human-modified landscapes. However, the capacity for such landscapes to generate favorable roosting conditions for these species has not been thoroughly investigated. We assessed the role of anthropogenic and natural landscape elements on roosting habitat selection of 11 black and 7 turkey vultures in coastal South Carolina, USA using a GPS satellite transmitter dataset derived from previous research. Our dataset spanned 2006–2012 and contained data from 7916 nights of roosting. Landscape …

Reproductive Success Of Captive-Reared Allegheny Woodrats (Neotoma Magister) Released Into Genetically Depauperate Populations, Miracle M. Davis, Timothy J. Smyser, Scott A. Johnson, Joseph Duchamp, Jeffery L. Larkin, Robert K. Swihart, Jacqueline M. Doyle

United States Department of Agriculture Wildlife Services: Staff Publications

Habitat fragmentation and degradation have led to a proliferation of small and isolated populations that are vulnerable to genetic erosion. Reduction in habitat and concomitant declines in population connectivity can expediate the collapse of species that exist as natural metapopulations. In recent years, Allegheny woodrats (Neotoma magister) have experienced local extirpations and declines in genetic diversity across their range due to disease-related mortality, reduced food availability, and disruption of connectivity among subpopulations. In response, we developed a captive-breeding program to facilitate genetic management of isolated woodrat populations in Indiana. Between 2010 and 2012, 27 captive-reared individuals were released to four …

Economic Estimates Of Wild Hog (Sus Scrofa) Damage And Control Among Young Forest Plantations In Alabama, Micah Fern, Rebecca Barlow, Chris Slootmaker, John Kush, Stephanie Shwiff, Larry Teeter, Jim Armstrong

United States Department of Agriculture Wildlife Services: Staff Publications

Operating as ecological engineers, the increased distribution and abundance of wild hogs (Sus scrofa) has caused considerable socio-economic impacts. The international scope of economic research providing wild hog damage estimates are often confined to agricultural crops, while damage estimates among forest plantations are lacking. In Alabama, private landowners hold the majority of timberland acreage and are less equipped to absorb financial losses from wild hog damage than their industrial counterparts. A survey was conducted to estimate the economic impact of wild hogs, namely costs of damage and control, to privately owned forestlands. The survey was distributed in the …

Sex And Nest Type Influence Avian Blood Parasite Prevalence In A High-Elevation Bird Community, Marina D. Rodriguez, Paul F. Doherty, Antoinette J. Piaggio, Kathryn P. Huyvaert

United States Department of Agriculture Wildlife Services: Staff Publications

Background: The prevalence of avian haemosporidian parasites and the factors influencing infection in the Colorado Rocky Mountains are largely unknown. With climate change expected to promote the expansion of vector and avian blood parasite distributions, baseline knowledge and continued monitoring of the prevalence and diversity of these parasites is needed.

Methods: Using an occupancy modeling framework, we conducted a survey of haemosporidian parasite species infecting an avian community in the Colorado Rocky Mountains in order to estimate the prevalence and diversity of blood parasites and to investigate species-level and individual-level characteristics that may influence infection.

Results: We estimated the prevalence …

Responses Of Turkey Vultures To Unmanned Aircraft Systems Vary By Platform, Morgan B. Pfeiffer, Bradley F. Blackwell, Thomas W. Seamans, Bruce N. Buckingham, Joshua L. Hoblet, Patrice E. Baumhardt

United States Department of Agriculture Wildlife Services: Staff Publications

A challenge that conservation practitioners face is manipulating behavior of nuisance species. The turkey vulture (Cathartes aura) can cause substantial damage to aircraft if struck. The goal of this study was to assess vulture responses to unmanned aircraft systems (UAS) for use as a possible dispersal tool. Our treatments included three platforms (fixed-wing, multirotor, and a predator-like ornithopter [powered by flapping flight]) and two approach types (30 m overhead or targeted towards a vulture) in an operational context. We evaluated perceived risk as probability of reaction, reaction time, flight-initiation distance (FID), vulture remaining index, and latency to return. …

Reintegrating Biology Through The Nexus Of Energy, Information, And Matter, Kim L. Hoke, Sara L. Zimmer, Adam B. Roddy, Mary Jo Ondrechen, Craig E. Williamson, Nicole R. Buan

Department of Biochemistry: Faculty Publications

Information, energy, and matter are fundamental properties of all levels of biological organization, and life emerges from the continuous flux of matter, energy, and information. This perspective piece defines and explains each of the three pillars of this nexus. We propose that a quantitative characterization of the complex interconversions between matter, energy, and information that compose this nexus will help us derive biological insights that connect phenomena across different levels of biological organization. We articulate examples from multiple biological scales that highlight how this nexus approach leads to a more complete understanding of the biological system. Metrics of energy, information, …

Preferential Flow In Riparian Buffers: Current Research And Future Needs., Derek M. Heeren, Lucie Guertault, Kyle Mankin

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Preferential flow in riparian buffers can substantially compromise their effectiveness in reducing contaminants from overland runoff. The objective of this article is to introduce a collection of five articles on current research into subsurface preferential flow measurement, visualization, modeling, and impacts on contaminant fate and transport at scales ranging from the subsurface pore scale to the plot scale to the watershed scale. This collection presents selected works from a broader invited session on “Preferential flow and piping in riparian buffers” at the 2020 ASABE Annual International Meeting. Major findings include: new methodologies, such as light transmission and geophysics, to characterize …

Potential Use For Serosurveillance Of Feral Swine To Map Risk For Anthrax Exposure, Texas, Usa, Rachel M. Maison, Courtney F. Pierce, Izabela K. Ragan, Vienna R. Brown, Michael J. Bodenchuk, Richard A. Bowen, Angela M. Bosco-Lauth

United States Department of Agriculture Wildlife Services: Staff Publications

Anthrax is a disease of concern in many mammals, including humans. Management primarily consists of prevention through vaccination and tracking clinical-level observations because environmental isolation is laborious and bacterial distribution across large geographic areas diffi cult to confi rm. Feral swine (Sus scrofa) are an invasive species with an extensive range in the southern United States that rarely succumbs to anthrax. We present evidence that feral swine might serve as biosentinels based on comparative seroprevalence in swine from historically defi ned anthrax-endemic and non–anthraxendemic regions of Texas. Overall seropositivity was 43.7% (n = 478), and logistic regression revealed county endemicity …

Complete Modeling Of The Chondrogenic Environment Under Continuous Low-Intensity Ultrasound, Heather Newell

Department of Chemical and Biomolecular Engineering: Dissertations, Theses, and Student Research

Articular cartilage is an avascular tissue that requires therapeutic intervention methods. This work answers the following: determine transducer operation to optimize the bioeffects; calculate the magnitude of pressure exerted on chondrocytes at an injury site; and confirm the theoretical findings by an animal model.

Earlier work has shown that cellular response to US is maximized at the resonance frequency of the cells. Resonance frequencies were calculated for chondrocytes in various layers. The latter configuration closest resembles in vivo conditions and the resonance occurred at 3.8±0.3 ������. The 3D model of US propagation in a rabbit knee was constructed from MRIs …

News From The Bioconductor Project, Bioconductor Core Team

The R Journal

Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data. Bioconductor 3.14 was released on 27 October, 2021. It is compatible with R 4.1.0 and consists of 2083 software packages, 408 experiment data packages, 904 up-to-date annotation packages, and 29 workflows.

Rpese: Risk And Performance Estimators Standard Errors With Serially Dependent Data, Anthony-Alexander Christidis, R Douglas Martin

The R Journal

The R package RPESE (Risk and Performance Estimators Standard Errors) implements a new method for computing accurate standard errors of risk and performance estimators when returns are serially dependent. The new method makes use of the representation of a risk or performance estimator as a summation of a time series of influence-function (IF) transformed returns, and computes estimator standard errors using a sophisticated method of estimating the spectral density at frequency zero of the time series of IF-transformed returns. Two additional packages used by RPESE are introduced, namely RPEIF which computes and provides graphical displays of the IF of risk …

Visual Diagnostics For Constrained Optimisation With Application To Guided Tours, H Sherry Zhang, Dianne Cook, Ursula Laa, Nicolas Langrené, Patricia Menéndez

The R Journal

A guided tour helps to visualise high-dimensional data by showing low-dimensional projections along a projection pursuit optimisation path. Projection pursuit is a generalisation of principal component analysis in the sense that different indexes are used to define the interestingness of the projected data. While much work has been done in developing new indexes in the literature, less has been done on understanding the optimisation. Index functions can be noisy, might have multiple local maxima as well as an optimal maximum, and are constrained to generate orthonormal projection frames, which complicates the optimization. In addition, projection pursuit is primarily used for …

Bssm: Bayesian Inference Of Non-Linear And Non-Gaussian State Space Models In R, Jouni Helske, Matti Vihola

The R Journal

We present an R package bssm for Bayesian non-linear/non-Gaussian state space modeling. Unlike the existing packages, bssm allows for easy-to-use approximate inference based on Gaussian approximations such as the Laplace approximation and the extended Kalman filter. The package also accommodates discretely observed latent diffusion processes. The inference is based on fully automatic, adaptive Markov chain Monte Carlo (MCMC) on the hyperparameters, with optional importance sampling post-correction to eliminate any approximation bias. The package also implements a direct pseudo-marginal MCMC and a delayed acceptance pseudo-marginal MCMC using intermediate approximations. The package offers an easy-to-use interface to define models with linear-Gaussian state …

Passed: Calculate Power And Sample Size For Two Sample Tests, Jinpu Li, Ryan .. Knigge, Kaiyi Chen, Emily V. Leary

The R Journal

Power and sample size estimation are critical aspects of study design to demonstrate minimized risk for subjects and justify the allocation of time, money, and other resources. Researchers often work with response variables that take the form of various distributions. Here, we present an R package, PASSED, that allows flexibility with seven common distributions and multiple options to accommodate sample size or power analysis. The relevant statistical theory, calculations, and examples for each distribution using PASSED are discussed in this paper.

Automatic Time Series Forecasting With Ata Method In R: Ataforecasting Package, Ali Sabri Taylan, Güçkan Yapar, Hanife Taylan Selamlar

The R Journal

Ata method is a new univariate time series forecasting method that provides innovative solutions to issues faced during the initialization and optimization stages of existing methods. The Ata method’s forecasting performance is superior to existing methods in terms of easy implementation and accurate forecasting. It can be applied to non-seasonal or deseasonalized time series, where the deseasonalization can be performed via any preferred decomposition method. The R package ATAforecasting was developed as a comprehensive toolkit for automatic time series forecasting. It focuses on modeling all types of time series components with any preferred Ata methods and handling seasonality patterns by …

Robustbf: An R Package For Robust Solution To The Behrens-Fisher Problem, Gamze Güven, ŞÜkrü Acıtaş, Hatice ŞAmkar, Birdal ŞEnoğLu

The R Journal

Welch’s two-sample t-test based on least squares (LS) estimators is generally used to test the equality of two normal means when the variances are not equal. However, this test loses its power when the underlying distribution is not normal. In this paper, two different tests are proposed to test the equality of two long-tailed symmetric (LTS) means under heterogeneous variances. Adaptive modified maximum likelihood (AMML) estimators are used in developing the proposed tests since they are highly efficient under LTS distribution. An R package called RobustBF is given to show the implementation of these tests. Simulated Type I error rates …

Volesti: Volume Approximation And Sampling For Convex Polytopes In R, Apostolos Chalkis, Vissarion Fisikopoulos

The R Journal

Sampling from high-dimensional distributions and volume approximation of convex bodies are fundamental operations that appear in optimization, finance, engineering, artificial intelligence, and machine learning. In this paper, we present volesti, an R package that provides efficient, scalable algorithms for volume estimation, uniform, and Gaussian sampling from convex polytopes. volesti scales to hundreds of dimensions, handles efficiently three different types of polyhedra and provides non existing sampling routines to R. We demonstrate the power of volesti by solving several challenging problems using the R language.

Drhotnet: An R Package For Detecting Differential Risk Hotspots On A Linear Network, Álvaro Briz-Redón, Francisco Martínez-Ruiz, Francisco Montes

The R Journal

One of the most common applications of spatial data analysis is detecting zones, at a certain scale, where a point-referenced event under study is especially concentrated. The detection of such zones, which are usually referred to as hotspots, is essential in certain fields such as criminology, epidemiology, or traffic safety. Traditionally, hotspot detection procedures have been developed over areal units of analysis. Although working at this spatial scale can be suitable enough for many research or practical purposes, detecting hotspots at a more accurate level (for instance, at the road segment level) may be more convenient sometimes. Furthermore, it is …

Maint.Data: Modelling And Analysing Interval Data In R, A Pedro Duarte Silva, Paula Brito, Peter Filzmoser, José G. Dias

The R Journal

We present the CRAN R package MAINT.Data for the modelling and analysis of multivariate interval data, i.e., where units are described by variables whose values are intervals of R, representing intrinsic variability. Parametric inference methodologies based on probabilistic models for interval variables have been developed, where each interval is represented by its midpoint and log-range, for which multivariate Normal and Skew-Normal distributions are assumed. The intrinsic nature of the interval variables leads to special structures of the variance-covariance matrix, which are represented by four different possible configurations. MAINT.Data implements the proposed methodologies in the S4 object system, introducing a …

Matchthem: Matching And Weighting After Multiple Imputation, Farhad Pishgar, Noah Greifer, Clémence Leyrat, Elizabeth Stuart

The R Journal

Balancing the distributions of the confounders across the exposure levels in an observational study through matching or weighting is an accepted method to control for confounding due to these variables when estimating the association between an exposure and outcome and reducing the degree of dependence on certain modeling assumptions. Despite the increasing popularity in practice, these procedures cannot be immediately applied to datasets with missing values. Multiple imputation of the missing data is a popular approach to account for missing values while preserving the number of units in the dataset and accounting for the uncertainty in the missing values. However, …

Diproperm: An R Package For The Diproperm Test, Andrew G. Allmon, J.S. Marron, Michael G. Hudgens

The R Journal

High-dimensional low sample size (HDLSS) data sets frequently emerge in many biomedical applications. The direction-projection-permutation (DiProPerm) test is a two-sample hypothesis test for comparing two high-dimensional distributions. The DiProPerm test is exact, i.e., the type I error is guaranteed to be controlled at the nominal level for any sample size, and thus is applicable in the HDLSS setting. This paper discusses the key components of the DiProPerm test, introduces the diproperm R package, and demonstrates the package on a real-world data set

Bayessenmc: An R Package For Bayesian Sensitivity Analysis Of Misclassification, Jinhui Yang, Lifeng Lin, Haitao Chu

The R Journal

In case–control studies, the odds ratio is commonly used to summarize the association between a binary exposure and a dichotomous outcome. However, exposure misclassification frequently appears in case–control studies due to inaccurate data reporting, which can produce bias in measures of association. In this article, we implement a Bayesian sensitivity analysis of misclassification to provide a full posterior inference on the corrected odds ratio under both non-differential and differential misclassification. We present an R (R Core Team, 2018) package BayesSenMC, which provides user-friendly functions for its implementation. The usage is illustrated by a real data analysis on the association between …

Passo: An R Package For Assessing Partial Association Between Ordinal Variables, Shaobo Li, Xiaorui Zhu, Yuejie Chen, Dungang Liu

The R Journal

Partial association, the dependency between variables after adjusting for a set of covariates, is an important statistical notion for scientific research. However, if the variables of interest are ordered categorical data, the development of statistical methods and software for assessing their partial association is limited. Following the framework established by Liu et al. (2021), we develop an R package PAsso for assessing Partial Associations between ordinal variables. The package provides various functions that allow users to perform a wide spectrum of assessments, including quantification, visualization, and hypothesis testing. In this paper, we discuss the implementation of PAsso in …

Ngsseml: Non-Gaussian State Space With Exact Marginal Likelihood, Thiago R. Santos, Glaura C. Franco, Dani Gamerman

The R Journal

The number of packages/software for Gaussian State Space models has increased over recent decades. However, there are very few codes available for non-Gaussian State Space (NGSS) models due to analytical intractability that prevents exact calculations. One of the few tractable exceptions is the family of NGSS with exact marginal likelihood, named NGSSEML. In this work, we present the wide range of data formats and distributions handled by NGSSEML and a package in the R language to perform classical and Bayesian inference for them. Special functions for filtering, forecasting, and smoothing procedures and the exact calculation of the marginal likelihood function …

Dad: An R Package For Visualisation, Classification And Discrimination Of Multivariate Groups Modelled By Their Densities, Rachid Boumaza, Pierre Santagostini, Smail Yousfi, Sabine Demotes-Mainard

The R Journal

Multidimensional scaling (MDS), hierarchical cluster analysis (HCA), and discriminant analysis (DA) are classical techniques which deal with data made of n individuals and p variables. When the individuals are divided into T groups, the R package dad associates with each group a multivariate probability density function and then carries out these techniques on the densities, which are estimated by the data under consideration. These techniques are based on distance measures between densities: chi-square, Hellinger, Jeffreys, Jensen-Shannon, and L^p for discrete densities, Hellinger , Jeffreys, L² , and 2-Wasserstein for Gaussian densities, and L² for numeric non-Gaussian densities …

Estimating Social Influence Effects In Networks Using A Latent Space Adjusted Approach In R, Ran Xu

The R Journal

Social influence effects have been extensively studied in various empirical network research. However, many challenges remain in estimating social influence effects in networks, as influence effects are often entangled with other factors, such as homophily in the selection process and the common social-environmental factors that individuals are embedded in. Methods currently available either do not solve these problems or require stringent assumptions. Recent works by Xu (2018) and others have shown that a latent space adjusted approach based on the latent space model has the potential to disentangle the influence effects from other processes, and the simulation evidence has shown …

G2f As A Novel Tool To Find And Fill Gaps In Metabolic Networks, Daniel Osorio, Kelly Botero, Andrés Pinzón Velasco, Nicolás Mendoza-Mejía, Felipe Rojas-Rodríguez, George Barreto, Janneth González

The R Journal

During the building of a genome-scale metabolic model, there are several dead-end metabolites and substrates which cannot be imported, produced, nor used by any reaction incorporated in the network. The presence of these dead-end metabolites can block out the net flux of the objective function when it is evaluated through Flux Balance Analysis (FBA), and when it is not blocked, bias in the biological conclusions increase. In this aspect, the refinement to restore the connectivity of the network can be carried out manually or using computational algorithms. The g2f package was designed as a tool to find the gaps from …

Rejoinder: Software Engineering And R Programming, Melina Vidoni

The R Journal

It is a pleasure to take part in such fruitful discussion about the relationship between Software Engineering and R programming, and what could be gain by allowing each to look more closely at the other. Several discussants make valuable arguments that ought to be further discussed