Context Poison baits are often used to control both foxes and feral cats but success varies considerably.
Aims This study investigated the influence of bait type, placement and lures on bait uptake by the feral cat, red fox and non-target species to improve baiting success and reduce non-target uptake.
Methods Six short field trials were implemented during autumn and winter over a five-year period in northern South Australia.
Key results Results suggest that poison baiting with Eradicat or dried kangaroo meat baits was inefficient for feral cats due to both low rates of bait detection and poor ingestion rates for baits that were encountered. Cats consumed more baits on dunes than swales and uptake was higher under bushes than in open areas. The use of auditory or olfactory lures adjacent to baits did not increase ingestion rates. Foxes consumed more baits encountered than cats and exhibited no preference between Eradicat and kangaroo meat baits. Bait uptake by native non-target species averaged between 14 and 57% of baits during the six trials, accounting for up to 90% of total bait uptake. Corvid species were primarily responsible for non-target uptake. Threatened mammal species investigated and nibbled baits but rarely consumed them; however, corvids and some common rodent species ingested enough poison to potentially receive a lethal dose.
Conclusions It is likely that several factors contributed to poor bait uptake by cats including the presence of alternative prey, a preference for live prey, an aversion to scavenging or eating unfamiliar foods and a stronger reliance on visual rather than olfactory cues for locating food.
Implications Further trials for control of feral cats should concentrate on increasing ingestion rates without the requirement for hunger through either involuntary ingestion via grooming or development of a highly palatable bait.
Cigarette smoking among nurses remains a public health concern despite a recent decline in current smoking prevalence. We recruited 149 registered nurses into a no-cost, targeted, self-help smoking cessation program supplemented by a supportive worksite environmental module. The study was designed to expand understanding of nurses' smoking and to measure program effectiveness. Follow-ups were conducted at one, six and 12 months post-intervention to assess self-reported smoking status (92% objectively validated) and predictors of cessation. Point prevalence abstinence at these time points (22.5%, 21.5% and 19.5%), continuous abstinence (12. 7%), and an ever-quit rate of 57% (i.e., quit for at least 48 hours), compare favorably to population quit rates and to rates reported for other self-help programs. Logistic regression analyses were utilized to identify predictors of short-term cessation [time before needing a cigarette, concern regarding the health hazards of smoking, working in a critical care setting, use of targeted weight manual] and long-term cessation [dosage (inverse relationship), use of standard American Lung Association maintenance manual, working with dying patients, and M. D. s' opposition to upgrading nursing service (inverse relationship)].
Context Feral cats (Felis catus) impact the health and welfare of wildlife, livestock and humans worldwide. They are particularly damaging where they have been introduced into island countries such as Australia and New Zealand, where native prey species evolved without feline predators. Kangaroo Island, in South Australia, is Australia's third largest island and supports several threatened and endemic species. Cat densities on Kangaroo Island are thought to be greater than those on the adjacent South Australian mainland, based on one cat density estimate on the island that is higher than most estimates from the mainland. The prevalence of cat-borne disease in cats and sheep is also higher on Kangaroo Island than the mainland, suggesting higher cat densities. A recent continental-scale spatial model of cat density predicted that cat density on Kangaroo Island should be about double that of the adjacent mainland. However, although cats are believed to have severe impacts on some native species on the island, other species that are generally considered vulnerable to cat predation have relatively secure populations on the island compared with the mainland.
Aims The present study aimed to compare feral cat abundance between Kangaroo Island and the adjacent South Australian mainland using simultaneous standardised methods. Based on previous findings, we predicted that the relative abundance of feral cats on Kangaroo Island would be approximately double that on the South Australian mainland.
Methods Standardised camera trap surveys were used to simultaneously estimate the relative abundance of feral cats on Kangaroo Island and the adjacent South Australian mainland. Survey data were analysed using the Royle–Nichols abundance-induced heterogeneity model to estimate feral cat relative abundance at each site.
Key results Cat abundance on the island was estimated to be over 10 times greater than that on the adjacent mainland.
Conclusions Consistent with predictions, cat abundance on the island was greater than on the adjacent mainland. However, the magnitude of this difference was much greater than expected.
Implications The findings show that the actual densities of cats at local sites can vary substantially from predictions generated by continental-scale models. The study also demonstrates the value of estimating abundance or density simultaneously across sites using standardised methods.
Context The Felixer grooming device ('Felixer') is a lethal method of feral cat control designed to be cost-effective and target specific. Aims This study aims to test the target specificity of the Felixer in Tasmania, with a particular focus on Tasmanian devil and quoll species due to the overlap in size, habitats and behaviour between these native carnivores and feral cats. Methods Our study deployed Felixer devices set in a non-lethal mode in nine field sites in Tasmania, one field site in New South Wales and two Tasmanian wildlife sanctuaries. Key results Our study recorded 4376 passes by identifiable vertebrate species including 528 Tasmanian devil passes, 507 spotted-tailed quoll passes and 154 eastern quoll passes. Our data showed that the Felixer can successfully differentiate quoll species from feral cats with spotted-tailed quolls and eastern quolls targeted in 0.19% and 0% of passes, respectively. However, Tasmanian devils and common wombats were targeted in 23.10% and 12% of passes, respectively, although sample size was low for common wombats (n = 25). Conclusions The Felixer could not reliably identify Tasmanian devils and possibly common wombats as non-target species. Further data is needed to confirm the potential for impacts on the common wombat and other potential non-target species in Tasmania, and the likelihood of the toxin being ingested by falsely targeted individuals. Implications Our study suggest that the Felixer device is safe for use in the presence of two species of conservation concern, the eastern and spotted-tailed quoll. It also supports evidence from previous studies that the Felixer is unlikely to impact bettongs and potoroos. Use of Felixer devices across much of Tasmania would have to balance the conservation or economic benefits of cat control against potential impacts on Tasmanian devils. We suggest that active Felixer deployments be preceded by surveys to establish the range of species present at the control site, and the season of control considered carefully to minimise potential impacts on more susceptible juvenile animals. In addition, modifications to the Felixer device such as the proposed incorporation of AI technology should be tested against the Tasmanian devil and other non-target species.
Context Feral cats (Felis catus) are a threat to biodiversity globally, but their impacts upon continental reptile faunas have been poorly resolved. Aims To estimate the number of reptiles killed annually in Australia by cats and to list Australian reptile species known to be killed by cats. Methods We used (1) data from >80 Australian studies of cat diet (collectively >10 000 samples), and (2) estimates of the feral cat population size, to model and map the number of reptiles killed by feral cats. Key results Feral cats in Australia's natural environments kill 466 million reptiles yr–1 (95% CI; 271–1006 million). The tally varies substantially among years, depending on changes in the cat population driven by rainfall in inland Australia. The number of reptiles killed by cats is highest in arid regions. On average, feral cats kill 61 reptiles km–2 year–1, and an individual feral cat kills 225 reptiles year–1. The take of reptiles per cat is higher than reported for other continents. Reptiles occur at a higher incidence in cat diet than in the diet of Australia's other main introduced predator, the European red fox (Vulpes vulpes). Based on a smaller sample size, we estimate 130 million reptiles year–1 are killed by feral cats in highly modified landscapes, and 53 million reptiles year–1 by pet cats, summing to 649 million reptiles year–1 killed by all cats. Predation by cats is reported for 258 Australian reptile species (about one-quarter of described species), including 11 threatened species. Conclusions Cat predation exerts a considerable ongoing toll on Australian reptiles. However, it remains challenging to interpret the impact of this predation in terms of population viability or conservation concern for Australian reptiles, because population size is unknown for most Australian reptile species, mortality rates due to cats will vary across reptile species and because there is likely to be marked variation among reptile species in their capability to sustain any particular predation rate. Implications This study provides a well grounded estimate of the numbers of reptiles killed by cats, but intensive studies of individual reptile species are required to contextualise the conservation consequences of such predation.
Acknowledgements The authors gratefully acknowledge the assistance of volunteers from the Galician (CEMMA) and Portuguese (SPVS) stranding networks. They also thank E. Dalgarno, L. Phillips, I. Hussy and J. A. Scurfield for their help with the organochlorine analysis. We would like to thank R. Gallois and C. Trichet, for their participation in the determination of total lipid content. This work was supported through the PhD grant of PMF from the Portuguese Foundation for Science and Technology of the Government of Portugal (SFRH/BD/36766/2007). GJP acknowledges support from the EU under the ANIMATE project (MEXC-CT-2006-042337). MBS was supported by the Spanish Ministry of Education, Programa Nacional de Movilidad de Recursos Humanos de Investigación (PR-2010-0518) and the LOTOFPEL project (Plan Nacional de I + D + I, CTM 2010–16053). Two anonymous reviewers and the associate editor F. Riget are thanked for helpful suggestions and comments on an earlier form of this manuscript. ; Peer reviewed ; Postprint
The authors gratefully acknowledge the assistance of volunteers from the Galician (CEMMA) and Portuguese (SPVS) stranding networks. The authors would like to thank R. Gallois and C. Trichet for their participation on total lipid content analysis. P. Méndez-Fernandez was supported during the research period through a PhD grant from the Fundação do Ministério de Ciência e Tecnologia de Portugal and ANIMATE project (SFRH/BD/36766/2007) and through a Science Without Borders (CSF) young talent postdoctoral grant of the Brazilian government. G. J. Pierce acknowledges support from the EU ANIMATE project (MEXC-CT-2006-042337), University of Aveiro and Caixa Geral de Depósitos (Portugal). ; Peer reviewed ; Postprint
The authors gratefully acknowledge the assistance of volunteers from the Galician (CEMMA) and Portuguese (SPVS) stranding networks. The authors would like to thank R. Gallois and C. Trichet for their participation on total lipid content analysis. P. Méndez-Fernandez was supported during the research period through a PhD grant from the Fundação do Ministério de Ciência e Tecnologia de Portugal and ANIMATE project (SFRH/BD/36766/2007) and through a Science Without Borders (CSF) young talent postdoctoral grant of the Brazilian government. G. J. Pierce acknowledges support from the EU ANIMATE project (MEXC-CT-2006-042337), University of Aveiro and Caixa Geral de Depósitos (Portugal). ; Peer reviewed ; Postprint
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Sloan Foundation ; Alexander von Humboldt Foundation ; Belgian Federal Science Policy Office ; Fonds pour la Formation a la Recherche dans l'Industrie et dans l'Agriculture (FRIA-Belgium) ; Agentschap voor Innovatie door Wetenschap en Technologie (IWT-Belgium) ; F.R.S.-FNRS (Belgium) ; Beijing Municipal Science & Technology Commission ; Ministry of Education, Youth and Sports (MEYS) of the Czech Republic ; Hungarian Academy of Sciences (Hungary) ; New National Excellence Program UNKP (Hungary) ; Council of Science and Industrial Research, India ; HOMING PLUS programme of the Foundation for Polish Science ; European Union, Regional Development Fund ; Mobility Plus programme of the Ministry of Science and Higher Education ; National Science Center (Poland) ; National Priorities Research Program by Qatar National Research Fund ; Programa Estatal de Fomento de la Investigacion Cientfica y Tecnica de Excelencia Maria de Maeztu ; Programa Severo Ochoa del Principado de Asturias ; EU-ESF ; Greek NSRF ; Rachadapisek Sompot Fund for Postdoctoral Fellowship, Chulalongkorn University (Thailand) ; Chulalongkorn Academic into Its 2nd Century Project Advancement Project (Thailand) ; Welch Foundation ; Weston Havens Foundation (U.S.A.) ; Canton of Geneva, Switzerland ; Herakleitos programme ; Thales programme ; Aristeia programme ; European Research Council (European Union) ; Horizon 2020 Grant (European Union): 675440 ; FWO (Belgium): 30820817 ; Beijing Municipal Science & Technology Commission: Z181100004218003 ; NKFIA (Hungary): 123842 ; NKFIA (Hungary): 123959 ; NKFIA (Hungary): 124845 ; NKFIA (Hungary): 124850 ; NKFIA (Hungary): 125105 ; National Science Center (Poland): Harmonia 2014/14/M/ST2/00428 ; National Science Center (Poland): Opus 2014/13/B/ST2/02543 ; National Science Center (Poland): 2014/15/B/ST2/03998 ; National Science Center (Poland): 2015/19/B/ST2/02861 ; National Science Center (Poland): Sonata-bis 2012/07/E/ST2/01406 ; Programa Estatal de Fomento de la Investigacion Cientfica y Tecnica de Excelencia Maria de Maeztu: MDM-2015-0509 ; Welch Foundation: C-1845 ; This paper presents the combinations of single-top-quark production cross-section measurements by the ATLAS and CMS Collaborations, using data from LHC proton-proton collisions at = 7 and 8 TeV corresponding to integrated luminosities of 1.17 to 5.1 fb(-1) at = 7 TeV and 12.2 to 20.3 fb(-1) at = 8 TeV. These combinations are performed per centre-of-mass energy and for each production mode: t-channel, tW, and s-channel. The combined t-channel cross-sections are 67.5 +/- 5.7 pb and 87.7 +/- 5.8 pb at = 7 and 8 TeV respectively. The combined tW cross-sections are 16.3 +/- 4.1 pb and 23.1 +/- 3.6 pb at = 7 and 8 TeV respectively. For the s-channel cross-section, the combination yields 4.9 +/- 1.4 pb at = 8 TeV. The square of the magnitude of the CKM matrix element V-tb multiplied by a form factor f(LV) is determined for each production mode and centre-of-mass energy, using the ratio of the measured cross-section to its theoretical prediction. It is assumed that the top-quark-related CKM matrix elements obey the relation |V-td|, |V-ts| « |V-tb|. All the |f(LV)V(tb)|(2) determinations, extracted from individual ratios at = 7 and 8 TeV, are combined, resulting in |f(LV)V(tb)| = 1.02 +/- 0.04 (meas.) +/- 0.02 (theo.). All combined measurements are consistent with their corresponding Standard Model predictions.