Risk of disease from wildlife reservoirs: Badgers, cattle, and bovine tuberculosis

Livestock face complex foraging options associated with optimizing nutrient intake while being able to avoid areas posing risk of parasites or disease. Areas of tall nutrient-rich swards around fecal deposits may be attractive for grazing, but might incur fitness costs from parasites. We use the example of dairy cattle and the risks of tuberculosis transmission posed to them by pastures contaminated with badger excreta to examine this trade-off. A risk may be posed either by aerosolized inhalation through investigation or by ingestion via grazing contaminated swards. We quantified the levels of investigation and grazing of 150 dairy cows at badger latrines (accumulations of feces and urine) and crossing points (urination-only sites). Grazing behavior was compared between strip-grazed and rotation-grazed fields. Strip grazing had fields subdivided for grazing periods of

Wildlife tracking data management: a new vision

To date, the processing of wildlife location data has relied on a diversity of software and file formats. Data management and the following spatial and statistical analyses were undertaken in multiple steps, involving many time-consuming importing/exporting phases. Recent technological advancements in tracking systems have made large, continuous, high-frequency datasets of wildlife behavioral data available, such as those derived from the global positioning system (GPS) and other animal-attached sensor devices. These data can be further complemented by a wide range of other information about the animals’ environment. Management of these large and diverse datasets for modelling animal behaviour and ecology can prove challenging, slowing down analysis and increasing the probability of mistakes in data handling. We address these issues by critically evaluating the requirements for good management of GPS data for wildlife biology. We highlight that dedicated data management tools and expertise are needed. We explore current research in wildlife data management. We suggest a general direction of development, based on a modular software architecture with a spatial database at its core, where interoperability, data model design and integration with remote-sensing data sources play an important role in successful GPS data handling.