Animal-side serologic assay for rapid detection of Mycobacterium Bovis infection in multiple species of free-ranging wildlife

Numerous species of mammals are susceptible to Mycobacterium bovis, the causative agent of bovine tuberculosis (TB). Several wildlife hosts have emerged as reservoirs of M. bovis infection for domestic livestock in different countries. In the present study, blood samples were collected from Eurasian badgers (n = 1532), white-tailed deer (n = 463), brushtail possums (n = 129), and wild boar (n = 177) for evaluation of antibody responses to M. bovis infection by a lateral-flow rapid test (RT) and multiantigen print immunoassay (MAPIA). Magnitude of the antibody responses and antigen recognition patterns varied among the animals as determined by MAPIA; however, MPB83 was the most commonly recognized antigen for each host studied. Other seroreactive antigens included ESAT-6, CFP10, and MPB70. The agreement of the RT with culture results varied from 74% for possums to 81% for badgers to 90% for wild boar to 97% for white-tailed deer. Small numbers of wild boar and deer exposed to M. avium infection or paratuberculosis, respectively, did not cross-react in the RT, supporting the high specificity of the assay. In deer, whole blood samples reacted similarly to corresponding serum specimens (97% concordance), demonstrating the potential for field application. As previously demonstrated for badgers and deer, antibody responses to M. bovis infection in wild boar were positively associated with advanced disease. Together, these findings suggest that a rapid TB assay such as the RT may provide a useful screening tool for certain wildlife species that may be implicated in the maintenance and transmission of M. bovis infection to domestic livestock.

An animal movement model incorporating home range and habitat selection

Wildlife biologists are often interested in how an animal uses space and the habitat resources within that space. We propose a single model that estimates an animal’s home range and habitat selection parameters within that range while accounting for the inherent autocorrelation in frequently sampled telemetry data. The model is applied to brown bear telemetry data in southeast Alaska.

A General Framework for the Analysis of Animal Resource Selection from Telemetry Data

We propose a general framework for the analysis of animal telemetry data through the use of weighted distributions. It is shown that several interpretations of resource selection functions arise when constructed from the ratio of a use and availability distribution. Through the proposed general framework, several popular resource selection models are shown to be special cases of the general model by making assumptions about animal movement and behavior. The weighted distribution framework is shown to be easily extended to readily account for telemetry data that are highly auto-correlated; as is typical with use of new technology such as global positioning systems animal relocations. An analysis of simulated data using several models constructed within the proposed framework is also presented to illustrate the possible gains from the flexible modeling framework. The proposed model is applied to a brown bear data set from southeast Alaska.