A New Metric for Quantifying the Relative Impact of Risk Factors on Loss of Working Life Illustrated in a Population of Working Dogs.

In a resource-limited world, organisations attempting to reduce the impact of health or behaviour issues need to choose carefully how to allocate resources for the highest overall impact. However, such choices may not always be obvious. Which has the biggest impact? A large change to a small number of individuals, or a small change to a large number of individuals? The challenge is identifying the issues that have the greatest impact on the population so potential interventions can be prioritised. We addressed this by developing a score to quantify the impact of health conditions and behaviour problems in a population of working guide dogs using data from Guide Dogs, UK. The cumulative incidence of different issues was combined with information about their impact, in terms of reduction in working life, to create a work score. The work score was created at population-level to illustrate issues with the greatest impact on the population and to understand contributions of breeds or crossbreeds to the workforce. An individual work deficit score was also created and means of this score used to illustrate the impact on working life within a subgroup of the population such as a breed, or crossbreed generation. The work deficit scores showed that those removed for behavioural issues had a greater impact on the overall workforce than those removed for health reasons. Additionally trends over time illustrated the positive influence of interventions Guide Dogs have made to improve their workforce. Information highlighted by these scores is pertinent to the effort of Guide Dogs to ensure partnerships are lasting. Recognising that the scores developed here could be transferable to a wide variety of contexts and species, most notably human work force decisions; we discuss possible uses and adaptations such as reduction in lifespan, quality of life and yield in production animals.

Using the incidence and impact of behavioural conditions in guide dogs to investigate patterns in undesirable behaviour in dogs.

The domestic dog is one of our most popular companions and longest relationships, occupying different roles, from pet to working guide dog for the blind. As dogs age different behavioural issues occur and in some cases dogs may be relinquished or removed from their working service. Here we analyse a dataset on working guide dogs that were removed from their service between 1994 and 2013. We use the withdrawal reasons as a proxy for the manifestation of undesirable behaviour. More than 7,500 dogs were in the dataset used, 83% of which were retired (due to old age) and 17% were withdrawn for behavioural issues. We found that the main reasons for behaviour withdrawal were environmental anxiety, training, and fear/aggression. Breed and sex had an effect on the odds of dogs being withdrawn under the different reasons. The age at withdrawal for the different withdrawal reasons suggested that dogs were more likely to develop fear/aggression related issues early on, whilst issues related to training could develop at almost any age. We found no evidence for heterosis effecting behaviour. We believe that this work is relevant to the pet dog population and had implications for understanding ageing and genetic influences on behaviour.

Negative cross resistance mediated by co-treated bed nets: a potential means of restoring pyrethroid-susceptibility to malaria vectors.

Insecticide-treated nets and indoor residual spray programs for malaria control are entirely dependent on pyrethroid insecticides. The ubiquitous exposure of Anopheles mosquitoes to this chemistry has selected for resistance in a number of populations. This threatens the sustainability of our most effective interventions but no operationally practicable way of resolving the problem currently exists. One innovative solution involves the co-application of a powerful chemosterilant (pyriproxyfen or PPF) to bed nets that are usually treated only with pyrethroids. Resistant mosquitoes that are unaffected by the pyrethroid component of a PPF/pyrethroid co-treatment remain vulnerable to PPF. There is a differential impact of PPF on pyrethroid-resistant and susceptible mosquitoes that is modulated by the mosquito's behavioural response at co-treated surfaces. This imposes a specific fitness cost on pyrethroid-resistant phenotypes and can reverse selection. The concept is demonstrated using a mathematical model.

Derivation and interpretation of hazard quotients to assess ecological risks from the cultivation of insect-resistant transgenic crops.

Cost-effective and rigorous risk assessments for chemicals may be based on hazard quotients (HQs): the ratio of a measure of exposure to a substance and a measure of the effect of that substance. HQs have been used for many years in ecological risk assessments for the use of synthetic pesticides in agriculture, and methods for calculating pesticide HQs have been adapted for use with transgenic crops. This paper describes how laboratory methods for assessing the ecotoxicological effects of synthetic pesticides have been modified for the measurement of effects of insecticidal proteins, and how these effect measures are combined with exposure estimates to derive HQs for assessing the ecological risks from the cultivation of insect-resistant transgenic crops. The potential for ecological modeling to inform the design of laboratory effects tests for insecticidal proteins is also discussed.

Automated discovery of food webs from ecological data using logic-based machine learning.

Networks of trophic links (food webs) are used to describe and understand mechanistic routes for translocation of energy (biomass) between species. However, a relatively low proportion of ecosystems have been studied using food web approaches due to difficulties in making observations on large numbers of species. In this paper we demonstrate that Machine Learning of food webs, using a logic-based approach called A/ILP, can generate plausible and testable food webs from field sample data. Our example data come from a national-scale Vortis suction sampling of invertebrates from arable fields in Great Britain. We found that 45 invertebrate species or taxa, representing approximately 25% of the sample and about 74% of the invertebrate individuals included in the learning, were hypothesized to be linked. As might be expected, detritivore Collembola were consistently the most important prey. Generalist and omnivorous carabid beetles were hypothesized to be the dominant predators of the system. We were, however, surprised by the importance of carabid larvae suggested by the machine learning as predators of a wide variety of prey. High probability links were hypothesized for widespread, potentially destabilizing, intra-guild predation; predictions that could be experimentally tested. Many of the high probability links in the model have already been observed or suggested for this system, supporting our contention that A/ILP learning can produce plausible food webs from sample data, independent of our preconceptions about "who eats whom." Well-characterised links in the literature correspond with links ascribed with high probability through A/ILP. We believe that this very general Machine Learning approach has great power and could be used to extend and test our current theories of agricultural ecosystem dynamics and function. In particular, we believe it could be used to support the development of a wider theory of ecosystem responses to environmental change.