White-tailed deer (Odocoileus virginianus) are a host for cattle fever ticks (Rhipicephalus (Boophilus) sp.), which are vectors of the pathogens causing bovine babesiosis and anaplasmosis in cattle. Tick eradication efforts focused on cattle along the U.S.-Mexico border are high priority and the potential role of white-tailed deer in compromising these efforts is of great concern. We developed a spatially-explicit,
Zoonoses from wildlife threaten global public health. Hendra virus is one of several zoonotic viral diseases that have recently emerged from Pteropus species fruit-bats (flying-foxes). Most hypotheses regarding persistence of Hendra virus within flying-fox populations emphasize horizontal transmission within local populations (colonies) via urine and other secretions, and transmission among colonies via migration. As an alternative hypothesis, we explore the role of recrudescence in persistence of Hendra virus in flying-fox populations via computer simulation using a model that integrates published information on the ecology of flying-foxes, and the ecology and epidemiology of Hendra virus. Simulated infection patterns agree with infection patterns observed in the field and suggest that Hendra virus could be maintained in an isolated flying-fox population indefinitely via periodic recrudescence in a manner indistinguishable from maintenance via periodic immigration of infected individuals. Further, post-recrudescence pulses of infectious flying-foxes provide a plausible basis for the observed seasonal clustering of equine cases. Correct understanding of the infection dynamics of Hendra virus in flying-foxes is fundamental to effectively managing risk of infection in horses and humans. Given the lack of clear empirical evidence on how the virus is maintained within populations, the role of recrudescence merits increased attention.
Aim We present an integrated approach for predicting future range expansion of an invasive species (Chinese tallow tree) that incorporates statistical forecasting and analytical techniques within a spatially explicit, agent‐based, simulation framework.
Location East Texas and Louisiana, USA.
Methods We drew upon extensive field data from the US Forest Service and the US Geological Survey to calculate spread rate from 2003 to 2008 and to parameterize logistic regression models estimating habitat quality for Chinese tallow within individual habitat cells. We applied the regression analyses to represent population spread rate as a function of habitat quality, integrated this function into a logistic model representing local spread, and coupled this model with a dispersal model based on a lognormal kernel within the simulation framework. We simulated invasions beginning in 2003 based on several different dispersal velocities and compared the resulting spatial patterns to those observed in 2008 using cross Mantel’s tests. We then used the best dispersal velocity to predict range expansion to the year 2023.
Results Chinese tallow invasion is more likely in low and flat areas adjacent to water bodies and roads, and less likely in mature forest stands and in pine plantations where artificial regeneration by planting seedlings is used. Forecasted invasions resulted in a distribution that extended from the Gulf Coast of Texas and Louisiana northward and westward as much as 300 km, representing approximately 1.58 million ha.
Main conclusions Our new approach of calculating time series projections of annual range expansion should assist land managers and restoration practitioners plan proactive management strategies and treatments. Also, as field sampling continues on the national array of FIA plots, these new data can be incorporated easily into the present model, as well as being used to develop and/or improve models of other invasive plant species.
BackgroundVisceral leishmaniasis (VL) is a disease caused by two known vector-borne parasite species (Leishmania donovani, L. infantum), transmitted to man by phlebotomine sand flies (species: Phlebotomus and Lutzomyia), resulting in ≈50,000 human fatalities annually, ≈67% occurring on the Indian subcontinent. Indoor residual spraying is the current method of sand fly control in India, but alternative means of vector control, such as the treatment of livestock with systemic insecticide-based drugs, are being evaluated. We describe an individual-based, stochastic, life-stage-structured model that represents a sand fly vector population within a village in India and simulates the effects of vector control via fipronil-based drugs orally administered to cattle, which target both blood-feeding adults and larvae that feed on host feces.Principle findingsSimulation results indicated efficacy of fipronil-based control schemes in reducing sand fly abundance depended on timing of drug applications relative to seasonality of the sand fly life cycle. Taking into account cost-effectiveness and logistical feasibility, two of the most efficacious treatment schemes reduced population peaks occurring from April through August by ≈90% (applications 3 times per year at 2-month intervals initiated in March) and >95% (applications 6 times per year at 2-month intervals initiated in January) relative to no control, with the cumulative number of sand fly days occurring April-August reduced by ≈83% and ≈97%, respectively, and more specifically during the summer months of peak human exposure (June-August) by ≈85% and ≈97%, respectively.ConclusionsOur model should prove useful in a priori evaluation of the efficacy of fipronil-based drugs in controlling leishmaniasis on the Indian subcontinent and beyond.
System-of-systems approaches for integrated assessments have become prevalent in recent years. Such approaches integrate a variety of models from different disciplines and modeling paradigms to represent a socio-environmental (or social-ecological) system aiming to holistically inform policy and decision-making processes. Central to the system-of-systems approaches is the representation of systems in a multi-tier framework with nested scales. Current modeling paradigms, however, have disciplinary-specific lineage, leading to inconsistencies in the conceptualization and integration of socio-environmental systems. In this paper, a multidisciplinary team of researchers, from engineering, natural and social sciences, have come together to detail socio-technical practices and challenges that arise in the consideration of scale throughout the socio-environmental modeling process. We identify key paths forward, focused on explicit consideration of scale and uncertainty, strengthening interdisciplinary communication, and improvement of the documentation process. We call for a grand vision (and commensurate funding) for holistic system-of-systems research that engages researchers, stakeholders, and policy makers in a multi-tiered process for the co-creation of knowledge and solutions to major socio-environmental problems.
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