RESUMO
BACKGROUND: Companion animal behaviour problems significantly impact companion animal (and owner) welfare. Veterinary behavioural medicine (VBM) is an emerging discipline and aims to provide evidence-based advice to owners and veterinary professionals to support normal behaviour in companion animals through appropriate socialisation and training and to address behaviour problems in a constructive and welfare-friendly manner. The approach to problem behaviours in dogs has changed in recent years; previously a mis-understanding of the biological theory of dominance has been used to explain certain behavioural problems in dogs which has led to the use of punishment-based treatment methods. Current research advocates the benefits of reward-based methods and highlights the risks of implementing positive punishment-based training techniques to both dogs and owners. Golden and Hanlon (Ir Vet J 71: 12, 2018) have reported that veterinary professionals in Ireland are frequently asked to advise on dog behaviour problems. This study aimed to explore veterinary professionals' understanding of training and treatment options for frequently encountered dog behaviour problems, and to help support the development of competences in VBM in Ireland. METHODS: An online survey was developed, including a pre-test evaluation by a pilot group of veterinary professionals, on SurveyMonkey®. The link to the online survey was distributed via third-party professional associations and social media. The survey contained twelve vignettes illustrating advice from veterinary professionals on common behaviour scenarios. Using a Likert Scale, respondents were asked to assess the likelihood of the advice to support best outcome for the dog. Best outcome was defined as one which provides a resolution to the behavioural problem while not compromising the animal's welfare. RESULTS: 84 private veterinary practitioners (PVP) and 133 veterinary nurses (VN) completed the survey. In the majority of vignettes, most veterinary professionals agreed with our classification of best outcome, but several areas of uncertainty were identified. Marked variations in response were found for PVPs in vignettes depicting advice recommending citronella collars, invisible radio fences, trainers utilising dominance language, and another dog for separation anxiety. For VNs, variations in response were found in vignettes depicting dominance-based training and advice on separation anxiety. Significant differences were found in the responses of VNs and PVPs for the vignettes recommending the use of citronella collars (p < 0.01) and invisible radio fences (p < 0.05), where VNs agreed with their recommendation less often than PVPs. PVPs graduating since 2013 agreed with the recommendation of invisible radio fences less often than PVPs graduating before 2013 (p < 0.05). VNs graduating before 2013 agreed with the recommendation of an accredited trainer (p < 0.05) and disagreed with the use of flooding to treat fear (p < 0.05) more often than VNs graduating since 2013. CONCLUSIONS: Our findings have identified specific areas of uncertainty with regards knowledge of positive punishment-based training and the treatment of common dog behaviour problems, highlighted the demand for continuing professional education in VBM and provided further evidence of the need to develop day one competences in VBM for veterinary medicine and nursing programmes at university level.
RESUMO
Wetlands are one of the major contributors of methane (CH4) emissions to the atmosphere and the intensity of emissions is driven by local environmental variables and spatial heterogeneity. Peatlands are a major wetland class and there are numerous studies that provide estimates of methane emissions at chamber or eddy covariance scales, but these are not often aggregated to the site/ecosystem scale. This study provides a robust approach to map dominant vegetation communities and to use these areas to upscale methane fluxes from chamber to site scale using a simple weighted-area approach. The proposed methodology was tested at three peatlands in Ireland over a duration of 2 years. The annual vegetation maps showed an accuracy ranging from 83 to 99% for near-natural to degraded sites respectively. The upscaled fluxes were highest (2.25 and 3.80 gC m-2 y-1) at the near-natural site and the rehabilitation (0.17 and 0.31 gC m-2 y-1), degraded (0.15 and 0.27 gC m-2 y-1) site emissions were close to net-zero throughout the study duration. Overall, the easy to implement methodology proposed in this study can be applied across various landuse types to assess the impact of peatland rehabilitation on methane emissions by mapping ecological change.