Correlation between bioluminescent blinks and swimming behavior in the splitfin flashlight fish Anomalops katoptron.

BACKGROUND: The light organs of the splitfin flashlight fish Anomalops katoptron are necessary for schooling behavior, to determine nearest neighbor distance, and to feed on zooplankton under dim light conditions. Each behavior is coupled to context-dependent blink frequencies and can be regulated via mechanical occlusion of light organs. During shoaling in the laboratory individuals show moderate blink frequencies around 100 blinks per minute. In this study, we correlated bioluminescent blinks with the spatio-temporal dynamics of swimming profiles in three dimensions, using a stereoscopic, infrared camera system. RESULTS: Groups of flashlight fish showed intermediate levels of polarization and distances to the group centroid. Individuals showed higher swimming speeds and curved swimming profiles during light organ occlusion. The largest changes in swimming direction occurred when darkening the light organs. Before A. katoptron exposed light organs again, they adapted a nearly straight movement direction. CONCLUSIONS: We conclude that a change in movement direction coupled to light organ occlusion in A. katoptron is an important behavioral trait in shoaling of flashlight fish.

Carnivore space use behaviors reveal variation in responses to human land modification.

BACKGROUND: Spatial behavior, including home-ranging behaviors, habitat selection, and movement, can be extremely informative in estimating how animals respond to landscape heterogeneity. Responses in these spatial behaviors to features such as human land modification and resources can highlight a species' spatial strategy to maximize fitness and minimize mortality. These strategies can vary on spatial, temporal, and individual scales, and the combination of behaviors on these scales can lead to very different strategies among species. METHODS: Harnessing the variation present at these scales, we characterized how species may respond to stimuli in their environments ranging from broad- to fine-scale spatial responses to human modification in their environment. Using 15 bobcat-years and 31 coyote-years of GPS data from individuals inhabiting a landscape encompassing a range of human land modification, we evaluated the complexity of both species' responses to human modification on the landscape through their home range size, habitat selection, and functional response behaviors, accounting for annual, seasonal, and diel variation. RESULTS: Bobcats and coyotes used different strategies in response to human modification in their home ranges, with bobcats broadly expanding their home range with increases in human modification and displaying temporal consistency in functional response in habitat selection across both season and time of day. Meanwhile, coyotes did not expand their home ranges with increased human modification, but instead demonstrated fine-scale responses to human modification with habitat selection strategies that sometimes varied by time of day and season, paired with functional responses in selection behaviors. CONCLUSIONS: These differences in response to habitat, resources, and human modification between the two species highlighted the variation in spatial behaviors animals can use to exist in anthropogenic environments. Categorizing animal spatial behavior based on these spatiotemporal responses and individual variation can help in predicting how a species will respond to future change based on their current spatial behavior.

ExMove: An open-source toolkit for processing and exploring animal-tracking data in R.

Ongoing technological advances have led to a rapid increase in the number, type and scope of animal-tracking studies. In response, many software tools have been developed to analyse animal movement data. These tools generally focus on movement modelling, but the steps required to clean raw data files from different tracking devices have been largely ignored. Such pre-processing steps are often time-consuming and involve a steep learning curve but are crucial for the creation of high-quality, standardised and shareable data. Moreover, decisions made at this early stage can substantially influence subsequent analyses, and in the current age of reproducibility crisis, the transparency of this process is vital. Here we present an open-access, reproducible toolkit written in the programming language R for processing raw data files into a single cleaned data set for analyses and upload to online tracking databases (found here: https://github.com/ExMove/ExMove). The toolkit comprises well-documented and flexible code to facilitate data processing and user understanding, both of which can increase user confidence and improve the uptake of sharing open and reproducible code. Additionally, we provide an overview website (found here: https://exmove.github.io/) and a Shiny app to help users visualise tracking data and assist with parameter determination during data cleaning. The toolkit is generalisable to different data formats and device types, uses modern 'tidy coding' practices, and relies on a few well-maintained packages. Among these, we perform spatial manipulations using the package sf. Overall, by collating all required steps from data collection to archiving on open access databases into a single, robust pipeline, our toolkit provides a valuable resource for anyone conducting animal movement analyses and represents an important step towards increased standardisation and reproducibility in animal movement ecology.

Methods for implementing integrated step-selection functions with incomplete data.

Integrated step-selection analyses (iSSAs) are versatile and powerful frameworks for studying habitat and movement preferences of tracked animals. iSSAs utilize integrated step-selection functions (iSSFs) to model movements in discrete time, and thus, require animal location data that are regularly spaced in time. However, many real-world datasets are incomplete due to tracking devices failing to locate an individual at one or more scheduled times, leading to slight irregularities in the duration between consecutive animal locations. To address this issue, researchers typically only consider bursts of regular data (i.e., sequences of locations that are equally spaced in time), thereby reducing the number of observations used to model movement and habitat selection. We reassess this practice and explore four alternative approaches that account for temporal irregularity resulting from missing data. Using a simulation study, we compare these alternatives to a baseline approach where temporal irregularity is ignored and demonstrate the potential improvements in model performance that can be gained by leveraging these additional data. We also showcase these benefits using a case study on a spotted hyena (Crocuta crocuta).

Breeding phase and outcome determine space use in European rollers Coracias garrulus prior to migration.

The breeding period is a demanding and time-constrained phase for migratory bird species. Breeding outcome and duration can interact with the extent and duration of post-breeding movements, resulting in individual differences in space use ultimately influencing later stages of the annual cycle. We present space-use and home range estimates during the breeding season for 21 European rollers Coracias garrulus tracked between 2018 and 2022, in Italy and Croatia. Using high-resolution spatial GPS data coupled with regular nest-box monitoring, we analyzed differences in space use during the incubation/nestling period versus post-breeding period prior to migration, accounting for the breeding outcome (successful vs. failure). We found that adult movements were strongly reduced during the first phase, whereas increased in the post-breeding phase, especially for failed breeders. Successful breeders remained in the surroundings of the nest site, whereas unsuccessful ones tended to abandon the nest and visit distant areas (up to 500 km) for long periods (60.5 ±â€…6.2 days). Breeding outcome did not influence the departure date of autumn migration, suggesting that failed breeders used this period for exploratory movements but not for advancing the onset of migration. Such exploratory movements may be functional to prospect and inform settlement decisions in failed breeders in search of new breeding opportunities and may be particularly important in migratory species, which generally have a limited period to gather information prior to autumn migration. The study demonstrates the need to investigate seasonal movements in different populations and the potential importance of prospecting post-breeding movements for long-distance migratory species.

The role of memory-based movements in the formation of animal home ranges.

Most animals live in spatially-constrained home ranges. The prevalence of this space-use pattern in nature suggests that general biological mechanisms are likely to be responsible for their occurrence. Individual-based models of animal movement in both theoretical and empirical settings have demonstrated that the revisitation of familiar areas through memory can lead to the formation of stable home ranges. Here, we formulate a deterministic, mechanistic home range model that includes the interplay between a bi-component memory and resource preference, and evaluate resulting patterns of space-use. We show that a bi-component memory process can lead to the formation of stable home ranges and control its size, with greater spatial memory capabilities being associated with larger home range size. The interplay between memory and resource preferences gives rise to a continuum of space-use patterns-from spatially-restricted movements into a home range that is influenced by local resource heterogeneity, to diffusive-like movements dependent on larger-scale resource distributions, such as in nomadism. Future work could take advantage of this model formulation to evaluate the role of memory in shaping individual performance in response to varying spatio-temporal resource patterns.

Male mating season range expansion results from an increase in scale of daily movements for a polygynous-promiscuous bird.

Males of species with promiscuous mating systems are commonly observed to use larger ranges during the mating season relative to non-mating seasons, which is often attributed to a change in movements related to reproductive activities. However, few studies link seasonal range sizes to variation in daily space use patterns to provide insight into the behavioral mechanisms underlying mating season range expansion. We studied 20 GPS-tagged male wild turkeys (Meleagris gallopavo), a large upland gamebird, during the mating and summer non-mating seasons to test the hypothesis that larger mating season ranges resulted from male wild turkeys expanding the scale of daily movement activities to locate and court females. We delineated mating and non-mating seasons based on intensity of gobbling, a vocalization tied to courtship behavior, recorded by autonomous recording units distributed across the study area. Mating season ranges were significantly larger than non-mating season ranges. Daily ranges were larger in the mating season, as were distances between roost sites used on consecutive nights. Variance in daily range size was greater in the mating season, but low temporal autocorrelation suggested considerable daily variability in both seasons. We found no evidence that male wild turkeys changed how they distributed daily movements within seasonal ranges, or differences in habitat use, suggesting larger mating season ranges result from male wild turkeys increasing the scale of their daily movements, rather than a systematic shift to a nomadic movement strategy. Likely, the distribution of females is more dynamic and ephemeral compared to other resources, prompting males to traverse larger daily ranges during the mating season to locate and court females. Our work illustrates the utility of using daily movement to understand the behavioral process underlying larger space use patterns.

From little things big things grow: enhancement of an acoustic telemetry network to monitor broad-scale movements of marine species along Australia's east coast.

BACKGROUND: Acoustic telemetry has become a fundamental tool to monitor the movement of aquatic species. Advances in technology, in particular the development of batteries with lives of > 10 years, have increased our ability to track the long-term movement patterns of many species. However, logistics and financial constraints often dictate the locations and deployment duration of acoustic receivers. Consequently, there is often a compromise between optimal array design and affordability. Such constraints can hinder the ability to track marine animals over large spatial and temporal scales. Continental-scale receiver networks have increased the ability to study large-scale movements, but significant gaps in coverage often remain. METHODS: Since 2007, the Integrated Marine Observing System's Animal Tracking Facility (IMOS ATF) has maintained permanent receiver installations on the eastern Australian seaboard. In this study, we present the recent enhancement of the IMOS ATF acoustic tracking infrastructure in Queensland to collect data on large-scale movements of marine species in the northeast extent of the national array. Securing a relatively small initial investment for expanding receiver deployment and tagging activities in Queensland served as a catalyst, bringing together a diverse group of stakeholders (research institutes, universities, government departments, port corporations, industries, Indigenous ranger groups and tourism operators) to create an extensive collaborative network that could sustain the extended receiver coverage into the future. To fill gaps between existing installations and maximise the monitoring footprint, the new initiative has an atypical design, deploying many single receivers spread across 2,100 km of Queensland waters. RESULTS: The approach revealed previously unknown broad-scale movements for some species and highlights that clusters of receivers are not always required to enhance data collection. However, array designs using predominantly single receiver deployments are more vulnerable to data gaps when receivers are lost or fail, and therefore "redundancy" is a critical consideration when designing this type of array. CONCLUSION: Initial results suggest that our array enhancement, if sustained over many years, will uncover a range of previously unknown movements that will assist in addressing ecological, fisheries, and conservation questions for multiple species.

Animal migration in the Anthropocene: threats and mitigation options.

Animal migration has fascinated scientists and the public alike for centuries, yet migratory animals are facing diverse threats that could lead to their demise. The Anthropocene is characterised by the reality that humans are the dominant force on Earth, having manifold negative effects on biodiversity and ecosystem function. Considerable research focus has been given to assessing anthropogenic impacts on the numerical abundance of species/populations, whereas relatively less attention has been devoted to animal migration. However, there are clear linkages, for example, where human-driven impacts on migration behaviour can lead to population/species declines or even extinction. Here, we explore anthropogenic threats to migratory animals (in all domains - aquatic, terrestrial, and aerial) using International Union for the Conservation of Nature (IUCN) Threat Taxonomy classifications. We reveal the diverse threats (e.g. human development, disease, invasive species, climate change, exploitation, pollution) that impact migratory wildlife in varied ways spanning taxa, life stages and type of impact (e.g. from direct mortality to changes in behaviour, health, and physiology). Notably, these threats often interact in complex and unpredictable ways to the detriment of wildlife, further complicating management. Fortunately, we are beginning to identify strategies for conserving and managing migratory animals in the Anthropocene. We provide a set of strategies that, if embraced, have the potential to ensure that migratory animals, and the important ecological functions sustained by migration, persist.

How to account for behavioral states in step-selection analysis: a model comparison.

Step-selection models are widely used to study animals' fine-scale habitat selection based on movement data. Resource preferences and movement patterns, however, often depend on the animal's unobserved behavioral states, such as resting or foraging. As this is ignored in standard (integrated) step-selection analyses (SSA, iSSA), different approaches have emerged to account for such states in the analysis. The performance of these approaches and the consequences of ignoring the states in step-selection analysis, however, have rarely been quantified. We evaluate the recent idea of combining iSSAs with hidden Markov models (HMMs), which allows for a joint estimation of the unobserved behavioral states and the associated state-dependent habitat selection. Besides theoretical considerations, we use an extensive simulation study and a case study on fine-scale interactions of simultaneously tracked bank voles (Myodes glareolus) to compare this HMM-iSSA empirically to both the standard and a widely used classification-based iSSA (i.e., a two-step approach based on a separate prior state classification). Moreover, to facilitate its use, we implemented the basic HMM-iSSA approach in the R package HMMiSSA available on GitHub.

Association of size, climatic factors, and mercury body burdens with movement behavior in American alligators.

Animal movement behavior provides insight into organismal and ecological function. These functions are often disturbed by anthropogenic influences, such as urbanization and habitat fragmentation, yet the effects of long-term exposures to environmental contaminants on movement have yet to be examined. The long lifespans and broad diets of crocodilians often lead to bioaccumulation of persistent contaminants and confer a marked vulnerability to consequent physiological effects. In this study, we investigate the relationships between blood concentrations of mercury (Hg), a widespread contaminant with well characterized neurotoxicity, and movement patterns in free living, naturally exposed American alligators (Alligator mississippiensis). We sampled adult male alligators from two former nuclear cooling reservoirs with different Hg contamination histories and placed GPS transmitters on a subset of individuals from each reservoir (13 total). Data collected over the ensuing two years were analyzed using a linear mixed effects framework combined with AICc model selection to resolve the relationships linking seasonal alligator movement (daily activity (s) and daily distance (m)) and home range to climate conditions, individual traits, and blood Hg concentrations (mg/kg; wet weight). We found that climate conditions, alligator size (snout-vent-length), and blood Hg concentrations all influence alligator daily activity but do not contribute to alligator daily movement (distance). Furthermore, we found that blood Hg concentrations were strongly correlated with seasonal home range size where individuals with elevated Hg had larger home ranges in spring, fall, and winter. These findings provide insight into how climate, anthropogenic contaminants, and individual traits relate to alligator movement patterns across seasons.

Landscape connectivity for predicting the spread of ASF in the European wild boar population.

African swine fever (ASF) is an infectious and highly fatal disease affecting wild and domestic swine, which is unstoppably spreading worldwide. In Europe, wild boars are one of the main drivers of spread, transmission, and maintenance of the disease. Landscape connectivity studies are the main discipline to analyze wild-species dispersal networks, and it can be an essential tool to predict dispersal-wild boar movement routes and probabilities and therefore the associated potential ASF spread through the suitable habitat. We aimed to integrate wild boar habitat connectivity predictions with their occurrence, population abundance, and ASF notifications to calculate the impact (i.e., the capacity of a landscape feature to favor ASF spread) and the risk (i.e., the likelihood of a habitat patch becoming infected) of wild boar infection across Europe. Furthermore, we tested the accuracy of the risk of infection by comparing the results with the temporal distribution of ASF cases. Our findings identified the areas with the highest impact and risk factors within Europe's central and Eastern regions where ASF is currently distributed. Additionally, the impact factor was 31 times higher on habitat patches that were infected vs non-infected, proving the utility of the proposed approach and the key role of wild boar movements in ASF-spread. All data and resulting maps are openly accessible and usable.

A multistate Langevin diffusion for inferring behavior-specific habitat selection and utilization distributions.

The identification of important habitat and the behavior(s) associated with it is critical to conservation and place-based management decisions. Behavior also links life-history requirements and habitat use, which are key to understanding why animals use certain habitats. Animal population studies often use tracking data to quantify space use and habitat selection, but they typically either ignore movement behavior (e.g., foraging, migrating, nesting) or adopt a two-stage approach that can induce bias and fail to propagate uncertainty. We develop a habitat-driven Langevin diffusion for animals that exhibit distinct movement behavior states, thereby providing a novel single-stage statistical method for inferring behavior-specific habitat selection and utilization distributions in continuous time. Practitioners can customize, fit, assess, and simulate our integrated model using the provided R package. Simulation experiments demonstrated that the model worked well under a range of sampling scenarios as long as observations were of sufficient temporal resolution. Our simulations also demonstrated the importance of accounting for different behaviors and the misleading inferences that can result when these are ignored. We provide case studies using plains zebra (Equus quagga) and Steller sea lion (Eumetopias jubatus) telemetry data. In the zebra example, our model identified distinct "encamped" and "exploratory" states, where the encamped state was characterized by strong selection for grassland and avoidance of other vegetation types, which may represent selection for foraging resources. In the sea lion example, our model identified distinct movement behavior modes typically associated with this marine central-place forager and, unlike previous analyses, found foraging-type movements to be associated with steeper offshore slopes characteristic of the continental shelf, submarine canyons, and seamounts that are believed to enhance prey concentrations. This is the first single-stage approach for inferring behavior-specific habitat selection and utilization distributions from tracking data that can be readily implemented with user-friendly software. As certain behaviors are often more relevant to specific conservation or management objectives, practitioners can use our model to help inform the identification and prioritization of important habitats. Moreover, by linking individual-level movement behaviors to population-level spatial processes, the multistate Langevin diffusion can advance inferences at the intersection of population, movement, and landscape ecology.

Assessing the Efficiency of Local Rabies Vaccination Strategies for Raccoons (Procyon lotor) in an Urban Setting.

Raccoon rabies virus (RRV) has been managed using multiple vaccination strategies, including oral rabies vaccination and trap-vaccinate-release (TVR). Identifying a rabies vaccination strategy for an area is a nontrivial task. Vaccination strategies differ in the amount of effort and monetary costs required to achieve a particular level of vaccine seroprevalence (efficiency). Simulating host movement relative to different vaccination strategies in silico can provide a useful tool for exploring the efficiency of different vaccination strategies. We refined a previously developed individual-based model of raccoon movement to evaluate vaccination strategies for urban Hamilton, Ontario, Canada. We combined different oral rabies vaccination baiting (hand baiting, helicopter, and bait stations) with TVR strategies and used GPS data to parameterize and simulate raccoon movement in Hamilton. We developed a total of 560 vaccination strategies, in consultation with the Ontario Ministry of Natural Resources and Forestry, for RRV control in Hamilton. We documented the monetary costs of each vaccination strategy and estimated the population seroprevalence. Intervention costs and seroprevalence estimates were used to calculate the efficiency of each strategy to meet targets set for the purpose of RRV control. Estimated seroprevalence across different strategies varied widely, ranging from less than 5% to more than 70%. Increasing bait densities (distributed using by hand or helicopter) led to negligible increase in seroprevalence. Helicopter baiting was the most efficient and TVR was the least efficient, but helicopter-based strategies led to lower levels of seroprevalence (6-12%) than did TVR-based strategies (17-70%). Our simulations indicated that a mixed strategy including at least some TVR may be the most efficient strategy for a local urban RRV control program when seroprevalence levels >30% may be required. Our simulations provide information regarding the efficiency of different vaccination strategies for raccoon populations, to guide local RRV control in urban settings.

A global systematic review of frugivorous animal tracking studies and the estimation of seed dispersal distances.

Seed dispersal is one of the most important ecosystem functions globally. It shapes plant populations, enhances forest succession, and has multiple, indirect benefits for humans, yet it is one of the most threatened processes in plant regeneration, worldwide. Seed dispersal distances are determined by the diets, seed retention times and movements of frugivorous animals. Hence, understanding how we can most effectively describe frugivore movement and behaviour with rapidly developing animal tracking technology is key to quantifying seed dispersal. To assess the current use of animal tracking in frugivory studies and to provide a baseline for future studies, we provide a comprehensive review and synthesis on the existing primary literature of global tracking studies that monitor movement of frugivorous animals. Specifically, we identify studies that estimate dispersal distances and how they vary with body mass and environmental traits. We show that over the last two decades there has been a large increase in frugivore tracking studies that determine seed dispersal distances. However, some taxa (e.g. reptiles) and geographic locations (e.g. Africa and Central Asia) are poorly studied. Furthermore, we found that certain morphological and environmental traits can be used to predict seed dispersal distances. We demonstrate that flight ability and increased body mass both significantly increase estimated seed dispersal mean and maximum distances. Our results also suggest that protected areas have a positive effect on mean seed dispersal distances when compared to unprotected areas. We anticipate that this review will act as a reference for future frugivore tracking studies, specifically to target current taxonomic and geographic data gaps, and to further explore how seed dispersal relates to key frugivore and fruit traits.

Ponds as experimental arenas for studying animal movement: current research and future prospects.

Animal movement is a multifaceted process that occurs for multiple reasons with powerful consequences for food web and ecosystem dynamics. New paradigms and technical innovations have recently pervaded the field, providing increasingly powerful means to deliver fine-scale movement data, attracting renewed interest. Specifically in the aquatic environment, tracking with acoustic telemetry now provides integral spatiotemporal information to follow individual movements in the wild. Yet, this technology also holds great promise for experimental studies, enhancing our ability to truly establish cause-and-effect relationships. Here, we argue that ponds with well-defined borders (i.e. "islands in a sea of land") are particularly well suited for this purpose. To support our argument, we also discuss recent experiences from studies conducted in an innovative experimental infrastructure, composed of replicated ponds equipped with modern aquatic telemetry systems that allow for unparalleled insights into the movement patterns of individual animals.

Modeling the movement of Oecophylla smargandina on short-length scales in an unfamiliar environment.

The movement of individual weaver ants, of Oecophylla smargandina, was previously tracked within an unfamiliar arena. We develop an empirical model, based on Brownian motion with a linear drag and constant driving force, to explain the observed distribution of ants over position and velocity. Parameters are fixed according to the isotropic, homogeneous distribution observed near the middle of the arena. Then, with no adjustable parameters, the model accounts for all features of the measured population distribution. The tendency of ants to remain near arena edges is largely explained as a statistical property of bounded stochastic motion though evidence for active wall-following behavior appears in individual ant trajectories. Members of this ant species are capable of impressive feats of collective action and long-range navigation. But we argue that they use a simplistic algorithm, captured semi-quantitatively by the model provided, to navigate within the confined region.

Albatross movement suggests sensitivity to infrasound cues at sea.

The ways in which seabirds navigate over very large spatial scales remain poorly understood. While olfactory and visual information can provide guidance over short distances, their range is often limited to 100s km, far below the navigational capacity of wide-ranging animals such as albatrosses. Infrasound is a form of low-frequency sound that propagates for 1,000s km in the atmosphere. In marine habitats, its association with storms and ocean surface waves could in effect make it a useful cue for anticipating environmental conditions that favor or hinder flight or be associated with profitable foraging patches. However, behavioral responses of wild birds to infrasound remain untested. Here, we explored whether wandering albatrosses, Diomedea exulans, respond to microbarom infrasound at sea. We used Global Positioning System tracks of 89 free-ranging albatrosses in combination with acoustic modeling to investigate whether albatrosses preferentially orientate toward areas of 'loud' microbarom infrasound on their foraging trips. We found that in addition to responding to winds encountered in situ, albatrosses moved toward source regions associated with higher sound pressure levels. These findings suggest that albatrosses may be responding to long-range infrasonic cues. As albatrosses depend on winds and waves for soaring flight, infrasonic cues may help albatrosses to identify environmental conditions that allow them to energetically optimize flight over long distances. Our results shed light on one of the great unresolved mysteries in nature, navigation in seemingly featureless ocean environments.

Evaluation of foot and mouth disease control measures: Simulating two endemic areas of Thailand.

Foot and mouth disease (FMD) is an important livestock disease in Thailand, with outbreaks occurring every year. However, the effects of FMD control measures in Thailand have received little research attention. Epidemiological models have been widely used to evaluate FMD outbreak control, but such a model has never been developed for Thailand. We constructed a stochastic between-farm transmission model to evaluate FMD control measures. The epidemiological unit of the model was the farm, which could be in different states: susceptible, latent, undetected infectious, detected infectious and recovered. The between-farm transmission was calculated by the sum of distance-dependent transmission and trade network transmission using parameters derived from FMD outbreaks in 2016-2017. We used this model to simulate the outbreaks with and without the implementation of the following control measures: culling all animals on infected farms, ring vaccination, animal movement restrictions and isolation of infected farms. The control measures were evaluated by estimating the number of secondarily infected farms and the outbreak duration for each scenario. The model was simulated in two study areas located in the Lamphaya Klang subdistrict (high farm density) and the Bo Phloi district (low farm density). The effects of control measures differed between the two study areas. When farm density was high, rigid control measures were required to prevent a major outbreak. Among all options, culling the animals on infected farms resulted in the lowest number of infected farms and the shortest outbreak duration. In contrast, for an area with a low farm density, less stringent control measures were sufficient to control the usually minor outbreaks. The results indicate that different areas require a different approach to control an outbreak of FMD.