Filters
Availability
Publication Year
Resource Type
Faculty
School/Institute
Publication Search Results
Sort
Results per page
1 - 10 of 555
-
(2007)Journal ArticleSimulation models are important for investigating foot-and-mouth disease (FMD) introduction scenarios and testing the potential effectiveness of control programs. To incorporate disease spread via domestic livestock and wildlife populations, a multi-model approach has been used to simulate potential FMD outbreaks in a region of Texas. Within the study region - a 9-county area (24,525 sq.km) of southern Texas, bordering Mexico - the distribution of cattle and feral pigs was estimated based on land use and vegetation characteristics. A geographic automata model of FMD spread between feral pig herds (1 km2 grid) was used to initiate the outbreak. During each simulated day of spread, we identified cattle herds (represented as either points or polygons) that may have been infected. We then used, separately, two spread models of FMD in domestic species to simulate an FMD outbreak in cattle herds in the study region. Initial simulations of this multi-model system based on introduction of infection into five randomly selected feral pig herds as input to the two spread models resulted in a typical outbreak that lasted 1-2 R. Sanson / Preventive Veterinary Medicine 81 (2007) 213-223 221 months and could affect about 100 cattle herds. The multi-epidemiologic modeling framework is currently being integrated with livestock transportation, carcass disposal and economic models to create a scalable and generic decision support system.
-
(2008)Journal ArticleModeling potential disease spread in wildlife populations is important for predicting, responding to and recovering from a foreign animal disease incursion. To make spatial epidemic predictions, the target animal species of interest must first be represented in space. We conducted a series of simulation experiments to determine how estimates of the spatial distribution of white-tailed deer impact the predicted magnitude and distribution of foot-and-mouth disease (FMD) outbreaks. Outbreaks were simulated using a susceptible-infected-recovered geographic automata model. The study region was a 9-county area ( 24 000 km(2)) of southern Texas. Methods used for creating deer distributions included dasymetric mapping, kriging and remotely sensed image analysis. The magnitudes and distributions of the predicted outbreaks were evaluated by comparing the median number of deer infected and median area affected ( km2), respectively. The methods were further evaluated for similar predictive power by comparing the model predicted outputs with unweighted pair group method with arithmetic mean (UPGMA) clustering. There were significant differences in the estimated number of deer in the study region, based on the geostatistical estimation procedure used ( range: 385 939 - 768 493). There were also substantial differences in the predicted magnitude of the FMD outbreaks ( range: 1 563 - 8 896) and land area affected ( range: 56 - 447 km2) for the different estimated animal distributions. UPGMA clustering indicated there were two main groups of distributions, and one outlier. We recommend that one distribution from each of these two groups be used to model the range of possible outbreaks. Methods included in cluster 1 ( such as county-level disaggregation) could be used in conjunction with any of the methods in cluster 2, which included kriging, NDVI split by ecoregion, or disaggregation at the regional level, to represent the variability in the model predicted outbreak distributions.
-
(2007)Conference PaperManagement response to contagious disease outbreaks requires rapid application of appropriate control measures (for example, quarantine and vaccination), but with little current or empirical data about how the disease may spread. This means that modelling is one of the few available options for making important decisions, and geographical modelling is a key approach. While there are many models that deal with disease spread within livestock populations, there are few that deal explicitly with widely dispersed animal populations such as unfenced livestock and wild and feral animals. It is for this purpose that we have developed a geographic automata model, Sirca, to simulate possible outbreaks of disease in wild and unfenced animal populations.
-
(2007)Journal ArticleThe construction of habitat models is a repeatable technique for describing and mapping species distributions, the utility of which lies in enabling management to predict where a species is likely to occur within a landscape. Typically, habitat models have been used to establish habitat requirements for threatened species; however they have equal applicability for modelling local populations of common species. Often, few data exist on local populations of common species, and issues of abundance and habitat selection at varying scales are rarely addressed. We provide a habitat suitability model for the common wombat (Vombatus ursinus) in southern New South Wales. This species is currently perceived as abundant throughout its extensive range across temperate regions of eastern Australia, yet little factual survey data exist and populations appear under threat. We use wombat burrows to reflect habitat selection and as our basis for ecological modelling. We found that environmental variables representing proximity to cover, measures of vegetation and proximity to watercourses are important predictors of burrow presence. Extrapolation of habitat models identified an abundance of habitat suitable for burrows. However, burrows in many suitable areas were abandoned. Our estimate of the population size was similar to the total annual mortality associated with road-kill. Theoretically, given the availability of suitable habitat, common wombat populations in the region should be thriving. It seems likely that this area once supported a much higher number of wombats; however limiting factors such as road mortality and disease have reduced the populations. The persistence of wombats in the study region must be supported by migration from other populations. Our findings challenge the perception that wombats are currently common and not in need of monitoring, suggesting that perceptions of abundance are often clouded by socio-political motives rather than informed by biological and ecological factors.
-
(2007)Journal ArticleWe investigated the potential role of feral pigs and wild deer as FMD reservoirs with a susceptible-latent-infected-recovered geographic-automata model, using spatially referenced data from southern Texas, USA. An uncontrolled FMD outbreak initiated in feral pigs and in wild deer might infect up to 698 (90% prediction interval 181, 1387) and 1557 (823, 2118) cattle and affect an area of 166 km(2) (53, 306) and 455 km(2) (301, 588), respectively. The predicted spread of FMD virus infection was influenced by assumptions we made regarding the number of incursion sites and the number of neighborhood interactions between herds. Our approach explicitly incorporates the spatial relationships between domesticated and non-domesticated animal populations, providing a new framework to explore the impacts, costs, and strategies for the control of foreign animal diseases with a potential wildlife reservoir. (c) 2007 Elsevier B.V. All rights reserved.
-
-
(2006)Journal ArticleThe preferred habitats, home range and activity patterns of sub-adult mulloway Argyrosomus japonicus (Sciaenidae) in the Georges River, New South Wales, Australia, were investigated using ultrasonic telemetry. Tags were surgically implanted in 9 hatchery-reared and 12 wild-caught mulloway (330 to 730 mm total length, TL). Fish were tracked for 2 periods of continuous tracking over 72 h in a 15 km section of river, once daily for a 20 d period, and up to 3 times mo–1 for 11 mo. Key habitats were identified as discrete holes or basins up to 20 m deep. Mulloway preferred this deep hole habitat as small fish (hatchery-reared, 300 to 500 mm TL) remained in these deep holes both day and night, while large fish (wild, 500 to 800 mm TL) ventured outside the holes at night. Maximum home range of small and large mulloway was 6000 and 17710 m2, respectively, and home range correlated significantly with length. Small fish moved up to 7 km d-1 while large fish moved up to 16 km d-1. Small fish released in shallow water initially had significantly greater movements than those released directly over deep holes, with movement up to 10 km in 3 d. Activity patterns varied between small and large fish, with significantly larger movements by large fish during the night and early morning than daytime. Five wild-caught mulloway tracked over 11 mo showed strong fidelity to holes within their particular home range. Mulloway should be stocked directly into their deep holes to minimise movements. The use of key habitats by mulloway indicate that their survival will be sensitive to stocking density. Optimal stocking density could be estimated from the area of key habitat in the target estuary.
-
-
(2006)Journal ArticleAim To determine the relationship between the distribution of climate, climatic heterogeneity and pteridophyte species richness gradients in Australia, using an approach that does not assume potential relationships are spatially invariant and allows for scale effects (extent of analysis) to be explicitly examined. Location Australia, extending from 10 degrees S to 43 degrees S and 112 degrees E to 153 degrees E. Method Species richness within 50 x 50 km grid cells was determined using point distribution data. Climatic surfaces representing the distribution and availability of water and energy at 1 km and 5 km cell resolutions were obtained. Climate at the 50 km resolution of analysis was represented by their mean and standard deviation in that area. Relationships were assessed using geographically weighted linear regression at a range of spatial bandwidths to investigate scale effects. Results The parameters and the predictive strength of all models varied across space at all extents of analysis. Overall, climatic variables representing water availability were more highly correlated to pteridophyte richness gradients in Australia than those representing energy. Their variance in cells further increased the strength of the relationships in topographically heterogeneous regions. Relationships with water were strong across all extents of analysis, particularly in the tropical and subtropical parts of the continent. Water availability explained less of the variation in richness at higher latitudes. Main conclusions This study brings into question the ability of aspatial and single-extent models, searching for a unified explanation of macro-scaled patterns in gradients of diversity, to adequately represent reality. It showed that, across Australia, there is a positive relationship between pteridophyte species richness and water availability but the strength and nature of the relationship varies spatially with scale in a highly complex manner. The spatial variance, or act
-
(2006)Journal ArticleKnowledge of the spatial distribution of weed infestations over regional scales is essential for effective management of source populations and to assess future threats. To this end, the distributions of Nassella trichotoma across a study area in south-east New South Wales, Australia, were analysed using the geographically local Getis-Ord G(i)* spatial hotspot clustering statistic. The clustering of N. trichotoma observations was analysed at three infestation levels: presence (at any density), patch level and the occasional plant level. The results indicate that there are c. 578 km(2) of cells containing N. trichotoma in strongly clustered infestations, 11.2 km(2) within weakly clustered infestations distinct from the main clusters, and 55 km(2) that are not clustered. There are 117 km(2) of strongly clustered patch level cells, 3 km(2) in distinct but weak clusters, and none outside of a cluster area. Of the occasional plant level cells, 329 km(2) are strongly clustered, 6.2 km(2) are in distinct but weak clusters, and 19 km(2) are not clustered. These results provide a mechanism by which control efforts can be prioritized. The analysis approach described in this paper provides a consistent, quantitative and repeatable approach to assess weed infestations across regional scales and can be applied to any weed species for which spatial distribution data are available.