Feral Pigs In Australia Research Articles

First findings of Sarcocystis species in game deer and feral pigs in Australia

Several wild game meat species, including deer and feral pigs are hunted and consumed in Australia. Feral pigs and deer are not indigenous to Australia, but they have proliferated extensively and established their presence in every state and territory. Following the report of a sambar deer displaying Sarcocystis like white cysts in its rump muscles, the present study was conducted to explore the prevalence of Sarcocystis infections in wild deer and feral pigs in the southeastern regions of Australia. Oesophagus, diaphragm, and heart tissue from 90 deer and eight feral pigs were examined visually for sarcocysts. All results were negative. PCR testing of randomly selected deer and feral pigs yielded positive results, which were subsequently supported by histopathology. This is the first study to report the presence of Sarcocystis spp. in deer and feral pigs in Australia. As no visual cysts were found on the heart or oesophagus that came back positive with PCR, infected animals, particularly those reared free-range, could be passing through meat quality checks unidentified. If people consume this meat without cooking it properly, it may lead to a human infection of Sarcocystis. However, a more targeted study focused on determining the parasite's prevalence and assessing its risks is necessary to determine if it constitutes a food safety issue. As this species has been found not only in feral pigs but also in domestic pigs, the potential for infection spreading between feral pigs and pigs in free-range livestock systems is high, potentially posing a large problem for the Australian pork industry, particularly with the increased emphasis on free-range pig husbandry. Future studies should concentrate on determining the species of Sarcocystis in feral animals commonly consumed as game meat to determine potential zoonotic risks. This could also include a more in-depth look at the prevalence of Sarcocystis infections in other game animals. Identifying where these parasites are present and to what extent, are important areas for future studies.

Multiscale landscape genetic analysis identifies major waterways as a barrier to dispersal of feral pigs in north Queensland, Australia.

Feral pigs (Sus scrofa) are a destructive and widespread invasive pest in Australia. An understanding of feral pig movement is required to develop management strategies to control feral pigs in Australia. Because landscape structure can have a strong influence on animal movement, it is important to determine how landscape features facilitate or impede the movement of feral pigs. Consequently, we conducted a landscape genetic analysis of feral pig populations in the Herbert region of far north Queensland, Australia, to determine management units and provide recommendations to better inform feral pig population control strategies. Using microsatellite data obtained from 256 feral pig samples from 44 sites, we examined feral pig population structure at multiple spatial scales for univariate and multivariate landscape resistance surfaces to determine the optimal spatial scale and to identify which of the nine landscape features tested impede or facilitate feral pig gene flow. Only weak genetic structure was found among the 44 sampling sites, but major waterways were identified as a minor barrier to gene flow, and an isolation by distance model was supported. We also found that highways facilitated gene flow across the study area, and this suggests that they may act as movement corridors or indicate translocation of feral pigs. Additionally, incorporating a second spatial scale enhanced the ability of our landscape genetics analysis to detect the influence of landscape structure on gene flow. We identified three management units based on natural barriers to gene flow and future targeted control should be undertaken in these management units to deliver sustained reduction of feral pig populations in the Herbert region. This study demonstrates how a landscape genetic approach can be used to gain insight into the ecology of an invasive pest species and be used to develop population control strategies which utilise natural barriers to movement.

How many feral pigs in Australia? An update

The abundance of feral pigs in Australia has been estimated previously and been a topic of some debate. This study aims to update a previous estimate of abundance (13.5 million, 95% CI: 3.5 million to 23.5 million) of feral pigs in Australia. Abundance estimates for the 1970s, 1980s, 1990s, 2000s and 2010s were collated from published literature. Mean abundances in the middle decades were estimated using the ratio method. The average abundance of feral pigs varied from 4.4 million (95% CI: 2.4 million to 6.3 million) in the 1980s, to 3.0 million (95% CI: 2.3 million to 3.7 million) in the 1990s, to 3.2 million (95% CI: 2.4 million to 4.0 million) in the 2000s. Mean density across all 142 studies was 1.03 pigs km–2. The average abundance of feral pigs in Australia during the 1980s to 2000s was much lower and more precise than estimated previously, so scientists and managers should update their use of abundance estimates. Density estimates are above, and below, estimates of threshold host densities for infectious exotic disease establishment.

Proposed Surveillance for Influenza A in Feral Pigs

Pigs carry receptors for both avian- and human-adapted influenza viruses and have previously been proposed as a mixing and amplification vessel for influenza. Until now, there has been no investigation of influenza A viruses within feral pigs in Australia. We collected samples from feral pigs in Ramsar listed wetlands of South Australia and demonstrated positive antibodies to influenza A viruses. We propose feral pigs, and their control programs, as an available resource for future surveillance for influenza A viruses.

Applied Population and Community Ecology: The Case of Feral Pigs in Australia. Jim Hone. 2012. Wiley-Blackwell, West Sussex, United Kingdom. 200 pp. 133.95 hardcover; 107.99 E-book. ISBN:978-0-470-65864-2.

The Journal of Wildlife ManagementVolume 79, Issue 1 p. 167-168 Book Review Applied Population and Community Ecology: The Case of Feral Pigs in Australia. Hone, Jim. 2012. Wiley-Blackwell, West Sussex, United Kingdom. 200 pp. 133.95 hardcover; 107.99 E-book. ISBN:978-0-470-65864-2. Matthew N. Gentle, Corresponding Author Matthew N. Gentle Robert Wicks Pest Animal Research Centre, Biosecurity Queensland and Department of Agriculture, Fisheries and Forestry, Queensland, 4350 Australia E-mail: matthew.gentle@daff.qld.gov.auSearch for more papers by this author Matthew N. Gentle, Corresponding Author Matthew N. Gentle Robert Wicks Pest Animal Research Centre, Biosecurity Queensland and Department of Agriculture, Fisheries and Forestry, Queensland, 4350 Australia E-mail: matthew.gentle@daff.qld.gov.auSearch for more papers by this author First published: 19 November 2014 https://doi.org/10.1002/jwmg.808Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume79, Issue1January 2015Pages 167-168 RelatedInformation

Impacts on nontarget avian species from aerial meat baiting for feral pigs

SummaryBait containing sodium fluoroacetate (1080) is widely used for the routine control of feral pigs in Australia. In Queensland, meat baits are popular in western and northern pastoral areas where they are readily accepted by feral pigs and can be distributed aerially. Field studies have indicated some levels of interference and consumption of baits by nontarget species and, based on toxicity data and the 1080 content of baits, many nontarget species (particularly birds and varanids) are potentially at risk through primary poisoning. While occasional deaths of species have been recorded, it remains unclear whether the level of mortality is sufficient to threaten the viability or ecological function of species. A series of field trials at Culgoa National Park in south‐western Queensland was conducted to determine the effect of broadscale aerial baiting (1.7 baits per km2) on the density of nontarget avian species that may consume baits. Counts of susceptible bird species were conducted prior to and following aerial baiting, and on three nearby unbaited properties, in May and November 2011, and May 2012. A sample of baits was monitored with remote cameras in the November 2011 and May 2012 trials. Over the three baiting campaigns, there was no evidence of a population‐level decline among the seven avian nontarget species that were monitored. Thirty per cent and 15% of baits monitored by remote cameras in the November 2011 and May 2012 trials were sampled by birds, varanids or other reptiles. These results support the continued use of 1080 meat baits for feral pig management in western Queensland and similar environs.

How many are there? The use and misuse of continental-scale wildlife abundance estimates

The number of individuals in a wildlife population is often estimated and the estimates used for wildlife management. The scientific basis of published continental-scale estimates of individuals in Australia of feral cats and feral pigs is reviewed and contrasted with estimation of red kangaroo abundance and the usage of the estimates. We reviewed all papers on feral cats, feral pigs and red kangaroos found in a Web of Science search and in Australian Wildlife Research and Wildlife Research, and related Australian and overseas scientific and ‘grey’ literature. The estimated number of feral cats in Australia has often been repeated without rigorous evaluation of the origin of the estimate. We propose an origin. The number of feral pigs in Australia was estimated and since then has sometimes been quoted correctly and sometimes misquoted. In contrast, red kangaroo numbers in Australia have been estimated by more rigorous methods and the relevant literature demonstrates active refining and reviewing of estimation procedures and management usage. We propose four criteria for acceptable use of wildlife abundance estimates in wildlife management. The criteria are: use of appropriate statistical or mathematical analysis; precision estimated; original source cited; and age (current or out-of-date) of an estimate evaluated. The criteria are then used here to assess the strength of evidence of the abundance estimates and each has at least one deficiency (being out-of-date). We do know feral cats, feral pigs and red kangaroos occur in Australia but we do not know currently how many feral cats or feral pigs are in Australia. Our knowledge of red kangaroo abundance is stronger at the state than the continental scale, and is also out-of-date at the continental scale. We recommend greater consideration be given to whether abundance estimates at the continental scale are needed and to their use, and not misuse, in wildlife management.

Stochastic models of foot and mouth disease in feral pigs in the Australian semi‐arid rangelands

SummaryFoot and mouth disease (FMD) is one of the world's most important livestock diseases and pigsSus scrofaare highly susceptible. In countries with significant feral pig populations, such as Australia, the possibility that FMD may become established in these populations is a cause of considerable concern.Current models of FMD in feral pigs in Australia are based on deterministic population and behavioural parameters. However, the population dynamics of feral pigs in the semi‐arid regions of Australia vary stochastically, in concert with the biomass of rainfall‐driven pasture.This study explored how stochastic variation in the population dynamics of feral pigs in semi‐arid rangelands affected the probability of persistence of an FMD epizootic, and its impact on the density of feral pigs. A stochastic model of feral pig population dynamics, with death rate linked to vegetation and rainfall, was linked to a deterministic model of FMD in feral pigs.Unlike the fully deterministic model, the stochastic model predicted inevitable extinction of the disease. When the transmission coefficient for FMD (β) was set at the mean value of 9 km2pig−1 day−1, the mean persistence time of the epizootic (in 1000 simulations) was 3338 days, with a maximum persistence time of 8439 days.On average the FMD epizootic reduced the population density of feral pigs, compared with the density of uninfected pig populations, by between 54% and 43% for transmission coefficients (β) equal to the estimated likely mean and minimum values (9·0 km2pig−1 day−1and 2·5 km2pig−1 day−1), respectively. This compares with a suppression of 27% in density for the equivalent deterministic model.Further stochasticity was introduced to the linked population and disease model by making the transmission coefficient β stochastic with values based on radio‐telemetry of a population of feral pigs in the semi‐arid rangelands over an 18‐month period.The addition of a stochastically varying β lowered the mean persistence time of the simulated epizootic to 1037 days in 1000 simulations and reduced the maximum persistence time to 3907 days. Pig density was reduced by 45% compared with uninfected populations.Synthesis and applications.These simulations suggest that any control programme to suppress a FMD outbreak in feral pigs in the semi‐arid rangelands of Australia should take account of prevailing environmental conditions when aiming to reduce feral pig populations beneath a threshold density (NT) below which the disease cannot persist. As theNTis higher than for the equivalent deterministic model, the disease may be easier to control than such models suggest.

Assessing Lamb Predation by Feral Pigs in Australia's Semi-Arid Rangelands

Feral pigs prey upon newborn lambs in the semi-arid rangelands of eastern Australia. In this study. two experiments were used to investigate the relationship between feral pig density and the rate of lamb predation. The differential susceptibility of single and twin-born lambs to pig predation was also examined. In Experiment 1, the density of pig populations on four sites subjected to different levels of pig control was monitored quarterly (range: 0.7-6.4 pigs km -2 ) between 1989 and 1991. The rate of lamb loss was indexed by udder-scoring a sample of lambing ewes to estimate the proportion whose lambs had died. The index of lamb loss varied significantly with pig density, the relationship taking the form of an asymptotic increase in loss at progressively higher pig densities. Inclusion of a variable indicating whether pig density increased or decreased over the lambing season (summarizing the cumulative effects of recent seasonal conditions) explained no additional variation in lamb loss. This suggests that the availability of alternative foods did not influence the propensity of pigs to prey upon lambs. Experiment 2 was conducted on three sites with respective pig densities of 0.4, 2.4 and 5.8 pigs km -2 . On each site, two paddocks were established, one of which was electrically fenced to preclude pigs. Approximately 300 pregnant ewes at each site were ultrasonically scanned to determine whether they carried single or twin lambs, and then placed randomly in either the paddock to which pigs had access or the paddock from which they were excluded. The proportion of lambs born that survived was contrasted between the two paddocks at each site to provide a direct estimate of predation rate. The rate of lamb predation increased with feral pig density, reaching a maximum proportional rate of 0.29 on the site where pig density was highest. Comparison of predation rates indicated that twin lambs were on average 5-6 times more likely to be preyed upon by pigs than were single lambs. The relationship between pig density and the index of predation rate estimated in Experiment 1 was modified to predict actual predation rates by substituting the maximum rate measured in Experiment 2. The resulting relationship, in combination with a measure of stochastic year-to-year variation in predation rates, was used to construct distributions describing the probability of sustaining different rates of lamb predation at given feral pig densities. This information enables sheep farmers to contrast the risk of lamb predation with their lamb production objectives and the costs of holding feral pig density below levels corresponding to acceptable rates of lamb predation. By valuing the reduced risk of sustaining high levels of lamb predation and the costs associated with achieving it, a sheep farmer can incorporate reduction in costs and benefits of pig control directly into economic analyses used to manage their enterprise.

Simondsia paradoxa: newly recorded nematode parasite from feral pigs in Australia.

Australian Veterinary JournalVolume 74, Issue 5 p. 394-395 Simondsia paradoxa: newly recorded nematode parasite from feral pigs in Australia DM SPRATT, DM SPRATT CSIRO Division of Wildlife & Ecology, PO Box 84, Lyneham, Australian Capital Territory 2602Search for more papers by this authorPM PAVLOV, PM PAVLOV Pav Ecol PO Box 464, Mossman, Queensland 4873Search for more papers by this author DM SPRATT, DM SPRATT CSIRO Division of Wildlife & Ecology, PO Box 84, Lyneham, Australian Capital Territory 2602Search for more papers by this authorPM PAVLOV, PM PAVLOV Pav Ecol PO Box 464, Mossman, Queensland 4873Search for more papers by this author First published: November 1996 https://doi.org/10.1111/j.1751-0813.1996.tb15454.xCitations: 3AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat No abstract is available for this article.Citing Literature Volume74, Issue5November 1996Pages 394-395 RelatedInformation

Effect of Pasture Availability on Bait Uptake by Feral Pigs in Australia's Semi-Arid Rangelands.

Factors that influence bait uptake by feral pigs will determine the efficacy of poisoning and trapping programmes for the control of pigs and have the potential to introduce bias to indices of pig abundance requiring bait consumption. In this study, the influence of pasture availability on uptake of bait trails consisting of soaked wheat by pigs in the semi-arid rangelands of north-western New South Wales was investigated. Percentage uptake of bait trails, pig density and pasture biomass were estimated for six sites along the Paroo River on six occasions: two each when pasture biomass was relatively high, moderate and low. The influence of pasture biomass on the relationship between percentage uptake of bait trails and pig density was examined by linear regression analysis. The analysis demonstrated that increasing pasture biomass significantly reduced the density of pigs corresponding to a given percentage uptake of bait trails, suggesting that, as pasture biomass increased, fewer pigs consumed bait trails andlor the number of bait trails each pig consumed declined. Assuming the former, the effect of increasing pasture biomass on the relationship between percentage uptake of bait trails and pig density indicated that, for every increase in pasture biomass of 100 kg ha-1, the percentage of pigs consuming bait declined by about 10%. The implications of these results for pig control and bias associated with indices of pig abundance requiring bait consumption are discussed.

Assessing visibility bias associated with helicopter counts of feral pigs in Australia's semi-arid rangelands

Aerial survey is a rapid technique for obtaining information about the abundance and distribution of feral pigs. To obtain estimates of actual pig abundance from such surveys, visibility bias associated with counts of pig groups must be estimated and accounted for. A double-count survey technique was used to estimate habitat-specific visibility bias associated with counts of pigs obtained from standardised helicopter surveys conducted in the semi-arid rangelands. Visibility bias differed significantly between riverine black-soil floodplains and non-riverine habitats, suggesting that at least two visibility-bias correction factors (3.61 and 1.47,respectively) were needed to derive absolute estimates of abundance from observed counts. The density of pigs was reduced experimentally on six sites by helicopter shooting or trapping to (1) evaluate the effect of helicopter shooting on visibility bias during subsequent helicopter surveys, and (2) provide further information on visibility bias associated with black-soil floodplain habitat. The experiments indicated no effect of helicopter shooting on visibility bias. However, a significant positive relationship between percentage cover of black-soil floodplain and visibility bias on study sites used for removal experiments suggests that estimates of visibility bias for this habitat derived from double-count surveys may be underestimates.

Disease surveillance in wildlife with emphasis on detecting foot and mouth disease in feral pigs

Surveillance strategies for detecting disease in wildlife are reviewed. Opportunistic and structured surveillance schemes are examined, and the detection of foot and mouth disease (FMD) in feral pigs ( Sus scrofa ) in Australia discussed in more detail. The probability of detecting an individual case of FMD in feral pigs in Australia with the current opportunistic surveillance scheme is estimated to be less than 0·0015. A model derived from the binomial distribution and for sampling without replacement estimated that between 28 and 3077 FMD cases would occur before the disease outbreak is detected. The range depends on the level of certainty required for detection. A model of the dynamics of the disease and an equation for estimating sample sizes for sampling without replacement were combined. For a feral pig population occupying 100 km 2 at a population density of 15/km 2 , the estimated time to detection of an FMD outbreak, with opportunistic surveillance, was 23 to 358 days. Alternatively, with a fixed sample size of 200 feral pigs, the minimum time to detection was 29 days, and for 100 pigs, was 35 days. These results are for a 95% confidence level in detecting an outbreak. Methods for ranking areas according to the probability of disease occurrence or detection are discussed and presented as components of possible structured surveillance schemes.

How Many Feral Pigs in Australia

Wildlife Research provides an international forum for the publication of original and significant research and debate on the ecology and management of wild animals in natural and modified habitats. Readers can expect a broad range of high quality, internationally refereed papers that contribute conceptual and practical advances to our knowledge and understanding of wildlife ecology and management

A Model of the Dynamics and Control of an Outbreak of Foot and Mouth Disease in Feral Pigs in Australia

(1) A model of the progress of an outbreak of foot and mouth disease in a single population of feral pigs, Sus scrofa (Linnaeus), is described. The population was divided into categories according to disease status: susceptible, latent, infective or immune. Taking into account natural recruitment and mortality, and mortality due to foot and mouth disease, the number of animals in each of these categories is predicted over the duration of an outbreak. (2) Results suggest that, for floodplain habitat in semi-arid eastern Australia, the threshold feral pig density for the disease to persist is 2 3-14 km-2. The large uncertainty is due to limited data for estimating the disease transmission coefficient. (3) Very high culling rates (>95%) are required for rapid disease eradication in, for example, <21 days. Lower culling rates could be effective if a longer outbreak is acceptable.