In 1992 we began an investigation into incidents of unusual and mass mortalities of the common frog (Rana temporaria) in Britain which were being reported unsolicited to us in increasing numbers by members of the public. Investigations conducted at ten sites of unusual mortality resulted in two main disease syndromes being found: one characterized by skin ulceration and one characterized by systemic haemorrhages. However, frogs also were found with lesions common to both of these syndromes and microscopic skin lesions common to both syndromes were seen. The bacterium Aeromonas hydrophila, which has been described previously as causing similar lesions, was isolated significantly more frequently from haemorrhagic frogs than from those with skin ulceration only. However, as many of the latter were euthanased, this may have been due to differences in post mortem bacterial invasion. An iridovirus-like particle has been identified on electron microscopical examination of skin lesions from frogs with each syndrome and iridovirus-like inclusions have been detected in the livers of frogs with systemic haemorrhages. Also, an adenovirus-like particle has been cultured from one haemorrhagic frog. A poxvirus-like particle described previously from diseased frogs has now been found also in control animals and has been identified as a melanosome. Both the prevalence of the iridovirus-like particle and its association with lesions indicate that it may be implicated in the aetiology of the disease syndromes observed. Specifically, we hypothesize that primary iridovirus infection, with or without secondary infection with opportunistic pathogens such as A. hydrophila, may cause natural outbreaks of 'red-leg', a disease considered previously to be due to bacterial infection only.

There have been few reconstructions of wildlife disease emergences, despite their extensive impact on biodiversity and human health. This is in large part attributable to the lack of structured and robust spatio-temporal datasets. We overcame logistical problems of obtaining suitable information by using data from a citizen science project and formulating spatio-temporal models of the spread of a wildlife pathogen (genus Ranavirus, infecting amphibians). We evaluated three main hypotheses for the rapid increase in disease reports in the UK: that outbreaks were being reported more frequently, that climate change had altered the interaction between hosts and a previously widespread pathogen, and that disease was emerging due to spatial spread of a novel pathogen. Our analysis characterized localized spread from nearby ponds, consistent with amphibian dispersal, but also revealed a highly significant trend for elevated rates of additional outbreaks in localities with higher human population density—pointing to human activities in also spreading the virus. Phylogenetic analyses of pathogen genomes support the inference of at least two independent introductions into the UK. Together these results point strongly to humans repeatedly translocating ranaviruses into the UK from other countries and between UK ponds, and therefore suggest potential control measures.

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The crested or great crested newt (Triturus cristatus spp) is declining and now considered threatened in many of the countries where it is present. This has resulted in the four members of the superspecies being afforded protection under local, national and international law. This study looks at a possible threat to T. cristatus in southern England through hybridization, by the introduction of a related alien species (T. carnifex). The study used multivariate morphometries to discriminate closely related species, and their hybrids. The character set involved both continuous and meristic data, collected through body measurements and colour pattern. The identification of the species and/or hybrids at the introduction site and surrounding areas was mapped. From the results it can be inferred that hybridization has taken place at the introduction site, but there is no morphological evidence for the spread of hybrids/aliens in to the surrounding areas.

Abstract. Aerosol radiative forcing uncertainty affects estimates of climate sensitivity and limits model skill at making climate projections. Efforts to improve the representations of physical processes in climate models, including extensive comparisons with observations, have not significantly constrained the range of possible aerosol forcing values. A far stronger constraint, in particular for the lower (most-negative) bound, can be achieved using global mean energy-balance arguments based on observed changes in historical temperature. Here, we show that structural deficiencies in a climate model, revealed as inconsistencies among observationally constrained cloud properties in the model, limit the effectiveness of observational constraint of the uncertain physical processes. We sample uncertainty in 37 model parameters related to aerosols, clouds and radiation in a perturbed parameter ensemble of the UK Earth System Model and evaluate 1 million model variants (different parameter settings from Gaussian Process emulators) against satellite-derived observations over several cloudy regions. We show that it is possible to reduce the parametric uncertainty in global mean aerosol forcing by more than 50 %, constraining it to a range in close agreement with energy-balance constraints (around −1.3 to −0.1 W m−2). However, our analysis of a very large set of model variants exposes model internal inconsistencies that would not be apparent in a small set of model simulations. Incorporating observations associated with these inconsistencies weakens the forcing constraint because they require a wider range of parameter values to accommodate conflicting information. Our estimated aerosol forcing range is the maximum feasible constraint using our structurally imperfect model and the chosen observations. Structural model developments targeted at the identified inconsistencies would enable a larger set of observations to be used for constraint, which would then narrow the uncertainty further. Such an approach provides a rigorous pathway to improved model realism and reduced uncertainty that has so far not been achieved through the normal model development approach.