The cabbage stem flea beetle (CSFB) is an economically important pest of oilseed rape crops that has increased in importance over recent years. Here we present the first attempt at a process-based model of this species using delay-differential equations (implemented in the R package stagePop) to simulate the abundance of each stage of the life cycle. We split the life cycle into 6 distinct stages: eggs, larvae, pupae-diapause (pupae, pre-aestivation adults and aestivating adults), pre-oviposition adults, reproductive adults and non-reproductive adults (past reproductive age), with temperature-dependent stage durations and death rates. We use adult trap data to inform on the initial conditions for the model and drive the model with a generic air temperature time series. To validate our model we compare the results with expected timings based on the scientific literature and field data on larval abundance. We use the model to investigate the effects of increasing the yearly average air temperature, and the effects of unusually warm seasons on CSFB population seasonal abundance patterns. Due to a lack of data there are key processes (e.g. temperature dependence of larval development) and parameter values that are uncertain. However, we believe the model, and its future iterations as more data are obtained, has the potential to be used as part of a decision support system for farmers and advisors, enabling more informed decisions on drilling and IPM strategies based on the within season weather conditions.

Different parasite challenge models have been used over many years in the development of novel vaccines against gastrointestinal nematodes of livestock. Typically, following vaccination with either native or recombinant proteins, the host animal is then given a bolus challenge of infective nematode larvae (iL3) or a trickle challenge where smaller numbers of iL3 are given at regular intervals over a period of time. The bolus method may be a robust test of whether high levels of vaccine-induced immunity translate to protection against a large pathogen insult, whereas the trickle infection method may be more appropriate to test the impacts of an exposure-induced anamnestic response. In the work presented here, three different models of testing gastrointestinal nematode vaccine efficacy were compared. Lambs (4-5 months old) were vaccinated with the excretory/secretory products collected from ex-vivo Teladorsagia circumcincta fourth stage larvae (L4ESP) and then challenged with a bolus of 5,000 iL3 or with a trickle infection where 2,000 iL3 were administered 3 times per week for 4 weeks (truncated trickle) or continuously challenged for 9 weeks (trickle) until post-mortem. Monitoring of faecal egg counts following challenge demonstrated that there was no significant impact of vaccination on cumulative faecal egg count (cFEC) following bolus challenge but, during the period of regular ingestion of iL3 in both trickle challenge models, statistically-significant reductions in the cFEC [(40-46% reduction in mean cFEC (P<0.05); 68-71% reduction in median cFEC)] were observed. Shortly after cessation of the iL3 challenge in the truncated trickle challenge group, this protective effect of the vaccine on cFEC was lost whereas vaccine efficacy was maintained in the model with continued regular ingestion of iL3 (trickle challenge model, which most accurately reflect the parasite challenge in a field situation). In conclusion, the choice of challenge model had a profound impact on the ability to measure vaccine efficacy.

Cabbage stem flea beetle (CSFB) is an economically important pest of oilseed rape crops responsible for substantial yield losses in recent years, particularly since the restrictions on neonicotinoid seed treatment use came into force in 2013. To effectively time sowing dates and target control measures, it is crucial that accurate estimates of when migratory adult CSFB will arrive at the crop can be made. A Bayesian hierarchical model was fitted to data from 19 sites containing adult CSFB traps over a period of three years to characterise the relationship between the day of year, temperature, rainfall, wind speed and solar radiation on beetle counts and to understand their relative importance. Day of the year was identified as the main driver of migration and temperature was the predominant environmental driver of CSFB migration. A hot day (based on the range of observed temperatures over the trapping window) resulted in approximately 300% of the expected CSFB migration relative to an average day during peak migration. The second most important environmental driver of migration was wind speed, but this resulted in a relatively negligible increase of approximately 15% from an average day to a still day. These findings suggest that efforts to predict timing of adult CSFB migration should focus on understanding how the phenology of CSFB and temperature interact to drive the timing of migration.

The incidence of vector-borne disease is on the rise globally, with burdens increasing in endemic countries and outbreaks occurring in new locations. Effective mitigation and intervention strategies require models that accurately predict both spatial and temporal changes in disease dynamics, but this remains challenging due to the complex and interactive relationships between environmental variation and the vector traits that govern the transmission of vector-borne diseases. Predictions of disease risk in the literature typically assume that vector traits vary instantaneously and independently of population density, and therefore do not capture the delayed response of these same traits to past biotic and abiotic environments. We argue here that to produce accurate predictions of disease risk it is necessary to account for environmentally driven and delayed instances of phenotypic plasticity. To show this, we develop a stage and phenotypically structured model for the invasive mosquito vector, Aedes albopictus, and dengue, the second most prevalent human vector-borne disease worldwide. We find that environmental variation drives a dynamic phenotypic structure in the mosquito population, which accurately predicts global patterns of mosquito trait-abundance dynamics. In turn, this interacts with disease transmission to capture historic dengue outbreaks. By comparing the model to a suite of simpler models, we reveal that it is the delayed phenotypic structure that is critical for accurate prediction. Consequently, the incorporation of vector trait relationships into transmission models is critical to improvement of early warning systems that inform mitigation and control strategies.

The enzootic abortion of ewes, caused by the bacterium Chlamydia abortus (C. abortus), is one of the main causes of abortion in sheep. There are multiple contributory factors, including chlamydial growth, host immune response, and hormonal balance, that result in different pregnancy outcomes, such as abortion, the birth of weak lambs that may die, or healthy lambs. This study aimed to determine the relationship between phenotypical patterns of immune cell infiltration and different pregnancy outcomes in twin-bearing sheep (both lambs born dead; one alive and one dead; both alive) when experimentally infected with C. abortus. Both the sheep uteri and placentae were collected after parturition. All samples were analysed for specific immune cell features, including cell surface antigens and the T-regulatory (Treg) cell-associated transcription factor and cytokines, by immunohistochemistry and in situ hybridisation. Some of these immunological antigens were evaluated in ovine reproductive tissues for the first time. Differential patterns of T helper/Treg cells revealed significant group effects in the placentae. It suggests the potential role that the balance of lymphocyte subsets may play in affecting different pregnancy outcomes in C. abortus-infected sheep. The present study provides novel detailed information about the immune responses observed at the maternofoetal interface in sheep at the time of pre-term abortion or lambing.

The bacterium Coxiella burnetii can cause the disease Q-fever in a wide range of animal hosts. Ruminants, including sheep, are thought to play a pivotal role in the transmission of C. burnetii to humans; however, the only existing livestock vaccine, namely, Coxevac® (Ceva Animal Health Ltd., Libourne, France), a killed bacterin vaccine based on phase I C. burnetii strain Nine-Mile, is only approved for use in goats and cattle. In this study, a pregnant ewe challenge model was used to determine the protective effects of Coxevac® and an experimental bacterin vaccine based on phase II C. burnetii against C. burnetii challenge. Prior to mating, ewes (n = 20 per group) were vaccinated subcutaneously with either Coxevac®, the phase II vaccine, or were unvaccinated. A subset of pregnant ewes (n = 6) from each group was then challenged 151 days later (~100 days of gestation) with 106 infectious mouse doses of C. burnetii, Nine-Mile strain RSA493. Both vaccines provided protection against C. burnetii challenge as measured by reductions in bacterial shedding in faeces, milk and vaginal mucus, and reduced abnormal pregnancies, compared to unvaccinated controls. This work highlights that the phase I vaccine Coxevac® can protect ewes against C. burnetii infection. Furthermore, the phase II vaccine provided comparable levels of protection and may offer a safer and cost-effective alternative to the currently licensed vaccine.

Background: To refine an on-hen mite feeding device, an ethogram was employed to measure the reactions of hens during a routine experimental procedure (feather plucking) and to assess effects of analgesic cream on those reactions. Methods: Three experimental groups were used; one treated with EMLA 5% before plucking (“EMLA group”); one with aqueous cream (“placebo group”) and a “no treatment” group. Behaviours were measured and compared on three days: ‘dummy handling day’ i.e. no plucking; ‘plucking day’, plucking the left thigh; and ‘treatment day’ i.e with right thighs plucked post-treatment. Poultry red mite feeding assays were performed to examine effect of creams on mite feeding rates, mortality and fecundity. All data were analysed using generalised linear (mixed) modelling approaches. Results: Use of the ethogram demonstrated no significant difference in hen behaviours in the EMLA group between dummy handling day and treatment day (p = 0.949) alongside a significant reduction in measured behaviours between plucking day and treatment day in the same group (p = 0.028). There was a statistically significant increase in measured behaviours from the dummy handling day to the plucking day in both placebo (p = 0.011) and no treatment group (p < 0.001). Effect sizes and directions were similar between dummy handling and treatment days in the ‘placebo’ and ‘no treatment’ groups, though not statistically significant (placebo, p = 0.064; no treatment p = 0.069). Mite feeding in the EMLA group was significantly lower than in the no treatment group in feeding assay 1 (p = 0.029) only. Mite mortality and fertility were unaffected. Conclusions: The ethogram successfully measured changes in observed behaviours between the dummy handling session and procedures. No adverse effects of EMLA cream on hens were demonstrated at 3mg/kg in hens. Use of analgesia for this routine procedure improves hens’ experiences during experimental trials.

Background: The aim of this study was to evaluate the efficacy of highthroughput on-farm transthoracic ultrasound (TUS) to screen for ovine pulmonary adenocarcinoma (OPA), an infectious ovine disease of increasing concern. No other routine diagnosis of preclinical OPA is available, or any vaccine or treatment. Methods: More than 80,000 rapid TUS scans were applied on farms with a history of OPA. The TUS results from a convenience sample of 171 TUSnegative and 269 TUS-positive sheep were compared with postmortem histology/immunohistochemistry results, the 'gold standard' reference test for OPA diagnosis. These results, together with new data on within-flock prevalence, allowed estimation of the efficacy of rapid TUS screening to identify OPA (defined as tumours of larger than 1 cm) on-farm. Results: The TUS screening had an estimated specificity of 0.998 (95% confidence interval [CI] : 0.998-0.999) and an estimated sensitivity of between 0.76 (95% CI: 0.72-0.79) and 0.99 (95% CI: 0.97-0.99) depending on the presumed false-negative rate applied to the calculation. Conclusion: High-throughput TUS should be considered for screening to identify individual sheep with OPA and has potential application to indicate flocks at low risk of OPA. However, lower efficacy is likely if conducted by less experienced persons.

Pathogens such as African swine fever virus (ASFV) are an increasing threat to global livestock production with implications for economic well-being and food security. Quantification of epidemiological parameters, such as transmission rates and latent and infectious periods, is critical to inform efficient disease control. Parameter estimation for livestock disease systems is often reliant upon transmission experiments, which provide valuable insights in the epidemiology of disease but which may also be unrepresentative of at-risk populations and incur economic and animal welfare costs. Routinely collected mortality data are a potential source of readily available and representative information regarding disease transmission early in outbreaks. We develop methodology to conduct exact Bayesian parameter inference from mortality data using reversible jump Markov chain Monte Carlo incorporating multiple routes of transmission (e.g. within-farm secondary and background transmission from external sources). We use this methodology to infer epidemiological parameters for ASFV using data from outbreaks on nine farms in the Russian Federation. This approach improves inference on transmission rates in comparison with previous methods based on approximate Bayesian computation, allows better estimation of time of introduction and could readily be applied to other outbreaks or pathogens.

ABSTRACT Potato cyst nematodes (PCN) are economically important pests of potato plants worldwide that can result in yield losses exceeding 80%, with an estimated cost of £50 million annually in the United Kingdom alone. The life cycle of PCN, and in particular the hatching of eggs and development and survival of juveniles, is sensitive to temperatures in the soil. Despite this fact, relatively little is known about temperatures inside potato drills and how these may differ to temperatures in the surrounding soil. We monitored the temperature inside potato drills at 19 sites across the United Kingdom and used a published temperature‐driven process‐based PCN life cycle model to compare predictions of PCN population dynamics driven by these temperatures to predictions based on modelled soil temperatures derived from the HadUK‐Grid climate. We found that mean soil temperatures derived from the climate model were lower than those observed inside potato drills; thus, using temperatures measured directly in potato drills resulted in increased estimates of population growth and shorter estimated generation times than when using modelled soil temperatures. This finding suggests that greater understanding of the temperature inside potato drills is required if we are to make accurate predictions about the effects of temperature on PCN populations.

BackgroundPremature death of livestock is a problem in all ruminant production systems. While the number of premature ruminant deaths in a country is a reasonable indicator for the nation's health, few data sources exist in a country like Ethiopia that can be used to generate valid estimates. The present study aimed to establish if three different data sets, each with imperfect information on ruminant mortality, including abortions, could be combined into improved estimates of nationwide mortality in Ethiopia.MethodsWe combined information from a recent survey of ruminant mortality with information from the Living Standards Measurement Study and the Disease Outbreak and Vaccination Reporting dataset. Generalized linear mixed and hurdle models were used for data analysis, with results summarized using predicted outcomes.ResultsAnalyses indicated that most herds experienced zero mortality and reproductive losses, with rare occasions of larger losses. Diseases causing deaths varied greatly both geographically and over time. There was little agreement between the different datasets. While the models aid the understanding of patterns of mortality and reproductive losses, the degree of variation observed limited the predictive scope.ConclusionsThe models revealed some insight into why mortality rates are variable over time and are therefore less useful in measuring production or health status, and it is suggested that alternative measures of productivity, such as number of offspring raised to 1 year old per dam, would be more stable over time and likely more indicative.

The importance given to minimising health issues and promoting natural behaviours is a polarising issue within farm animal welfare. It is predominantly thought that members of the public prioritise animals being able to behave naturally over other aspects of farm animal welfare, such as addressing health issues. However, public perspectives may be more multi-dimensional than is generally thought, with the importance given to these different elements of welfare dependent on the situation and state of the animals in question. To examine this, a factorial survey using vignettes, which experimentally manipulated the different levels of health (high health vs. low health) and natural behaviour provision (high behaviour vs. low behaviour), was completed by a sample (n = 810) representative of the UK population (on age, gender, ethnicity). Contrary to the predominant view, this study found animal health had the greatest effect on participants' judgements, explaining more of the variance in their assessments of animal welfare than any other factor. However, findings also indicated that participants considered animal welfare to be most positive when both health issues are minimised and natural behaviours are promoted. Attitudes to natural behaviours also varied more between participants, with females, individuals who do not (regularly) eat meat and those with a greater belief in animal mind giving greater priority to natural behaviours. In the context of public and private welfare standards seeking to meet public expectations, this study provides important insights into how public perspectives of animal welfare are more nuanced than previously thought, influenced by the context of the animal, the aspect of welfare in question and personal characteristics.

Vector-borne diseases (VBDs), such as dengue, Zika, West Nile virus (WNV) and tick-borne encephalitis, account for substantial human morbidity worldwide and have expanded their range into temperate regions in recent decades. Climate change has been proposed as a likely driver of past and future expansion, however, the complex ecology of host and vector populations and their interactions with each other, environmental variables and land-use changes makes understanding the likely impacts of climate change on VBDs challenging. We present an environmentally driven, stage-structured, host–vector mathematical modelling framework to address this challenge. We apply our framework to predict the risk of WNV outbreaks in current and future UK climates. WNV is a mosquito-borne arbovirus which has expanded its range in mainland Europe in recent years. We predict that, while risks will remain low in the coming two to three decades, the risk of WNV outbreaks in the UK will increase with projected temperature rises and outbreaks appear plausible in the latter half of this century. This risk will increase substantially if increased temperatures lead to increases in the length of the mosquito biting season or if European strains show higher replication at lower temperatures than North American strains.

Potato cyst nematodes (PCN) are responsible for large losses in potato yields in many of the world's potato-growing regions. As soil temperatures increase due to climate change, there is potential for faster growth rates of PCN, allowing development of multiple generations in a growing season. We develop a process-based temperature-dependent model representing the life cycle of Globodera pallida, comprising juvenile, adult and cyst/diapause stages. To incorporate variability in the amount of time spent in each stage caused by genetic/environmental variation, the model is based on a mix of ordinary differential equations (ODEs) with sub-stages, and delay differential equations (DDEs). The effect of climate change is incorporated through the influence of soil temperature on the rate of development and survival in the hatching and juvenile stages. The level of the plant resistance to PCN is incorporated via the proportion of juveniles which become adults. After comparing the model with field data we run simulations to explore the effects of temperature and resistance on PCN populations. We find that with higher temperatures and longer growing seasons multiple generations of PCN can develop within a season, provided any required diapause period is short. Despite this, we show that growing resistant potatoes is a very effective control strategy and planting potatoes with even moderate levels of resistance can counter the effects of climate change.

Predicting complex species-environment interactions is crucial for guiding conservation and mitigation strategies in a dynamically changing world. Phenotypic plasticity is a mechanism of trait variation that determines how individuals and populations adapt to changing and novel environments. For individuals, the effects of phenotypic plasticity can be quantified by measuring environment-trait relationships, but it is often difficult to predict how phenotypic plasticity affects populations. The assumption that environment-trait relationships validated for individuals indicate how populations respond to environmental change is commonly made without sufficient justification. Here we derive a novel general mathematical framework linking trait variation due to phenotypic plasticity to population dynamics. Applying the framework to the classical example of Nicholson's blowflies, we show how seemingly sensible predictions made from environment-trait relationships do not generalise to population responses. As a consequence, trait-based analyses that do not incorporate population feedbacks risk mischaracterising the effect of environmental change on populations.

Mastitis affects both dairy and meat/wool sheep industries with losses due to reductions in milk quality and quantity, increased treatment costs and restricted lamb growth. Effective vaccines would be important tools for mastitis control. However, the development of vaccines against mastitis has proved challenging due to the failure to target protective immunity to the mammary gland. In order to target responses to the mammary gland, this study tested whether local administration directly into the gland through the teat canal or in the udder skin confers protection against an intramammary infection. In this study, we tested a vaccine that confers protection against respiratory disease caused by Mannheimia haemolytica to determine if it also protects against intramammary infection by the same organism. No evidence of protection was observed in animals that received a subcutaneous immunisation in the udder skin, however, intramammary immunisation provided almost complete protection against an experimental challenge administered 7 days post immunisation but not if the challenge was delivered 14 days post immunisation. To investigate further the nature of this variation in response, the somatic cell count and concentration of cytokines Interleukin-1β, Interleukin-10 and Interleukin-17A was determined in milk over the course of each study. Intramammary immunisation induced an inflammatory response within the mammary gland, characterised by increases in SCC and in the production of cytokines IL-1β, IL-10, and IL-17A. This response was similar to that observed in un-vaccinated control animals post challenge. The SCC and cytokine levels had returned to levels comparable with un-vaccinated controls prior to challenge at both 7 and 14 days post immunisation. The transient nature of the protective effect is consistent with the priming of an innate antibacterial response within the mammary gland which provides protection against challenge at 7 days but is diminished by 14 days post-vaccination. Further studies are planned to determine the nature of the innate immune mechanisms associated with the protective effect described here to determine whether it may be exploited to improve ruminant udder health.

There is increasing interest in enabling positive experiences, not just minimizing negative experiences, to improve the welfare of farmed animals. This has influenced the growth of private agri-food standards and supported arguments to integrate animal welfare into policy on sustainability and climate change. However, much research finds that farmers predominantly focus on the minimization of negatives (i.e., health issues). This may impact the positioning of farmers within these wider societal debates, affecting their social license to farm. It is thus important to better understand farmers' priorities relating to the minimization of negative factors (e.g., health issues) and the promotion of positive experiences (i.e., natural behaviors). A novel 2 × 2 factorial survey using vignettes, which experimentally manipulated health (health issues minimized/not minimized) and natural behavior (natural behaviors promoted/not promoted) provision, was completed by livestock farmers (n = 169), mostly with extensive systems, in the UK and Republic of Ireland. The majority (88%) considered “minimizing health issues” to be the most important factor for animal well-being. However, the overall welfare of animals was judged to be highest when both health and natural behaviors were supported. Several individual characteristics, including farming sector, production system, gender, belief in animal mind and business type influenced how participants judged the welfare of animals and the level of importance they gave to health and natural behaviors. Findings suggest that although farmers prioritize the minimization of health issues they want animals to be both healthy and able to express natural behaviors, and individual characteristics are important for understanding farmers' welfare-related judgements.

BackgroundMany mosquito-borne diseases exhibit substantial seasonality, due to strong links between environmental variables and vector and pathogen life-cycles. Further, a range of density-dependent and density-independent biotic and abiotic processes affect the phenology of mosquito populations, with potentially large knock-on effects for vector dynamics and disease transmission. Whilst it is understood that density-independent and density-dependent processes affect seasonal population levels, it is not clear how these interact temporally to shape the population peaks and troughs. Due to this, the paucity of high-resolution data for validation, and the difficulty of parameterizing density-dependent processes, models of vector dynamics may poorly estimate abundances, which has knock-on effects for our ability predict vector-borne disease outbreaks.ResultsWe present a rich dataset describing seasonal abundance patterns of each life stage of Culex pipiens, a widespread vector of West Nile virus, at a field site in southern England in 2015. Abundance of immature stages was measured three times per week, whilst adult traps were run four nights each week. This dataset is integrated with an existing delay-differential equation model predicting Cx. pipiens seasonal abundance to improve understanding of observed seasonal abundance patterns. At our field site, the outcome of our model fitting suggests interspecific predation on mosquito larvae and temperature-dependent larval mortality combine to act as the main sources of population regulation throughout the active season, whilst competition for resources is a relatively small source of larval mortality.ConclusionsThe model suggests that density-independent mortality and interspecific predation interact to shape patterns of mosquito seasonal abundance in a permanent aquatic habitat and we propose that competition for resources is likely to be important where periods of high rainfall create transient habitats. Further, we highlight the importance of challenging population abundance models with data from across all life stages of the species of interest if reliable inferences are to be drawn from these models, particularly when considering mosquito control and vector-borne disease transmission.

Understanding the contributions from the environment to society is seen as increasingly important globally. In Scotland this is currently a high priority, as policymakers begin to shift attention away from traditional wellbeing indicators such as GDP. Although alternative natural capital accounting techniques exist, and are useful for creating commeasurable market values, they are unable to account for the full suite of benefits derived from the environment. Scotland's Natural Capital Asset Index (NCAI) is an attempt to create an account of Scotland's natural capital stock and how it's potential to contribute to wellbeing changes on an annual basis. This paper describes the inputs, calculation process and results of the NCAI. It also reports on sensitivity testing of the model, which found the model to be robust, credible to policy makers and meaningful, thus achieving the overall aims of the indicator.