d ABSTRACTFoot-and-mouth disease (FMD) virus (FMDV) circulates as multiple serotypes and strains in many regions of endemicity. In particular, the three Southern African Territories (SAT) serotypes are maintained effectively in their wildlife reservoir, the African buffalo, and individuals may harbor multiple SAT serotypes for extended periods in the pharyngeal region. However, the exact site and mechanism for persistence remain unclear. FMD in buffaloes offers a unique opportunity to study FMDV persistence, as transmission from carrier ruminants has convincingly been demonstrated for only this species. Following coinfection of naive African buffaloes with isolates of three SAT serotypes from field buffaloes, palatine tonsil swabs were the sample of choice for recovering infectious FMDV up to 400 days postinfection (dpi). Postmortem examination identified infectious virus for up to 185 dpi and viral genomes for up to 400 dpi in lymphoid tissues of the head and neck, focused mainly in germinal centers. Interestingly, viral persistence in vivo was not homogenous, and the SAT-1 isolate persisted longer than the SAT-2 and SAT-3 isolates. Coinfection and passage of these SAT isolates in goat and buffalo cell lines demonstrated a direct correlation between persistence and cell-killing capacity. These data suggest that FMDV persistence occurs in the germinal centers of lymphoid tissue but that the duration of persistence is related to virus replication and cell-killing capacity. IMPORTANCEFoot-and-mouth disease virus (FMDV) causes a highly contagious acute vesicular disease in domestic livestock and wildlife species. African buffaloes (Syncerus caffer) are the primary carrier hosts of FMDV in African savannah ecosystems, where the disease is endemic. We have shown that the virus persists for up to 400 days in buffaloes and that there is competition between viruses during mixed infections. There was similar competition in cell culture: viruses that killed cells quickly persisted more efficiently in passaged cell cultures. These results may provide a mechanism for the dominance of particular viruses in an ecosystem.

1. Quantifying movement and demographic events of free-ranging animals is fundamental to studying their ecology, evolution and conservation. Technological advances have led to an explosion in sensor-based methods for remotely observing these phenomena. This transition to big data creates new challenges for data management, analysis and collaboration.2. We present the Movebank ecosystem of tools used by thousands of researchers to collect, manage, share, visualize, analyse and archive their animal tracking and other animal-borne sensor data. Users add sensor data through file uploads or live data streams and further organize and complete quality control within the Movebank system. All data are harmonized to a data model and vocabulary. The public can discover, view and download data for which they have been given access to through the website, the Animal Tracker mobile app or by API. Advanced analysis tools are available through the EnvDATA System, the MoveApps platform and a variety of user-developed applications. Data owners can share studies with select users or the public, with options for embargos, licenses and formal archiving in a data repository.3. Movebank is used by over 3,100 data owners globally, who manage over 6 billion animal location and sensor measurements across more than 6,500 studies, with thousands of active tags sending over 3 million new data records daily. These data underlie >700 published papers and reports. We present a case

Background Fine-scale data on animal position are increasingly enabling us to understand the details of animal movement ecology and dead-reckoning, a technique integrating motion sensor-derived information on heading and speed, can be used to reconstruct fine-scale movement paths at sub-second resolution, irrespective of the environment. On its own however, the dead-reckoning process is prone to cumulative errors, so that position estimates quickly become uncoupled from true location. Periodic ground-truthing with aligned location data (e.g., from global positioning technology) can correct for this drift between Verified Positions (VPs). Yet relatively few bio-logging studies have adopted this approach due to an apparent inaccessibility of the complex analytical processes involved. We present step-by-step instructions for implementing Verified Position Correction (VPC) dead-reckoning in R using the tilt-compensated compass method, accompanied by the mathematical protocols underlying the code and improvements and extensions of this technique to reduce the trade-off between VPC rate and dead-reckoning accuracy. These protocols are all built into a user-friendly, fully-annotated VPC dead-reckoning R function; Gundog.Tracks, with multi-functionality to reconstruct animal movement paths across terrestrial, aquatic, and aerial systems, provided within the supplementary information as well as online (GitHub). Results The Gundog.Tracks function is demonstrated on three contrasting model species (the African lion Panthera leo, the Magellanic penguin Spheniscus magellanicus, and the Imperial cormorant Leucocarbo atriceps) moving on land, in water and in air, respectively. We show the effect of uncorrected errors in speed estimations, heading inaccuracies and infrequent VPC rate and demonstrate how these issues can be addressed. Conclusions The function provided will allow anyone familiar with R to dead-reckon animal tracks readily and accurately, as the key complex issues are dealt with by Gundog.Tracks. This will help the community to consider and implement a valuable, but often overlooked method of reconstructing high-resolution animal movement paths across diverse species and systems without requiring a bespoke application.