Accounting for Location Uncertainty in Azimuthal Telemetry Data Improves Ecological Inference

Background: Characterizing animal space use is critical for understanding ecological relationships. Animal telemetry technology has revolutionized the fields of ecology and conservation biology by providing high quality spatial data on animal movement. Radio-telemetry with very high frequency (VHF) radio signals continues to be a useful technology because of its low cost, miniaturization, and low battery requirements. Despite a number of statistical developments synthetically integrating animal location estimation and uncertainty with spatial process models using satellite telemetry data, we are unaware of similar developments for azimuthal telemetry data. As such, there are few statistical options to handle these unique data and no synthetic framework for modeling animal location uncertainty and accounting for it in ecological models. We developed a hierarchical modeling framework to provide robust animal location estimates from one or more intersecting or non-intersecting azimuths. We used our azimuthal telemetry model (ATM) to account for azimuthal uncertainty with covariates and propagate location uncertainty into spatial ecological models. We evaluate the ATM with commonly used estimators (Lenth (1981) maximum likelihood and M-Estimators) using simulation. We also provide illustrative empirical examples, demonstrating the impact of ignoring location uncertainty within home range and resource selection analyses. We further use simulation to better understand the relationship among location uncertainty, spatial covariate autocorrelation, and resource selection inference. Results: We found the ATM to have good performance in estimating locations and the only model that has appropriate measures of coverage. Ignoring animal location uncertainty when estimating resource selection or home ranges can have pernicious effects on ecological inference. Home range estimates can be overly confident and conservative when ignoring location uncertainty and resource selection coefficients can lead to incorrect inference and over confidence in the magnitude of selection. Furthermore, our simulation study clarified that incorporating location uncertainty helps reduce bias in resource selection coefficients across all levels of covariate spatial autocorrelation. Conclusion: The ATM can accommodate one or more azimuths when estimating animal locations, regardless of how they intersect; this ensures that all data collected are used for ecological inference. Our findings and model development have important implications for interpreting historical analyses using this type of data and the future design of radio-telemetry studies

Influenza A Viruses from Wild Birds in Guatemala Belong to the North American Lineage

The role wild bird species play in the transmission and ecology of avian influenza virus (AIV) is well established; however, there are significant gaps in our understanding of the worldwide distribution of these viruses, specifically about the prevalence and/or significance of AIV in Central and South America. As part of an assessment of the ecology of AIV in Guatemala, we conducted active surveillance in wild birds on the Pacific and Atlantic coasts. Cloacal and tracheal swab samples taken from resident and migratory wild birds were collected from February 2007 to January 2010.1913 samples were collected and virus was detected by real time RT-PCR (rRT-PCR) in 28 swab samples from ducks (Anas discors). Virus isolation was attempted for these positive samples, and 15 isolates were obtained from the migratory duck species Blue-winged teal. The subtypes identified included H7N9, H11N2, H3N8, H5N3, H8N4, and H5N4. Phylogenetic analysis of the viral sequences revealed that AIV isolates are highly similar to viruses from the North American lineage suggesting that bird migration dictates the ecology of these viruses in the Guatemalan bird population

Beyond Study Abroad: A Human Rights Delegation to Teach Policy Advocacy

Advancement of human rights is a core competency in the social work curriculum. Presented is a model to teach policy practice from a human rights perspective based on a violence-against-women delegation visit to Guatemala. Postdelegation policy advocacy responses included White House and State Department briefings on the problems, including femicide. Case examples of witnessed testimony about human rights violations, including rape, femicide, and human trafficking, reflect the unique and dynamic nature of social work practice in a global context. We link Council on Social Work Education core competencies in policy practice and human rights to experiential learning strategies used by the delegation and derive lessons learned to advance human rights education for the profession. © 2013 Council on Social Work Education

Human Rights and the Social Work Curriculum: Integrating Human Rights into Skill-Based Education Regarding Policy Practice Behaviors

This article provides a model for social work educators seeking to integrate human rights content in the policy course. Each of the four policy-related practice behaviors (e.g., policy formulation, policy analysis, policy advocacy, and collaboration in policy practice) is examined with respect to the traditional methods used in social welfare policy courses and the ways in which these methods can be expanded to include human rights content. Available literature and multimedia resources are noted and practical human rights applications are presented with the goal of supporting efforts to achieve this integration