Gill disease of farmed Atlantic salmon (Salmo salar) in the marine environment has emerged as a significant problem for the salmon aquaculture industry. Different types of marine salmon gill disease reported include amoebic gill disease (AGD), parasitic gill disease, viral gill disease, bacterial gill disease, zooplankton (cnidarian nematocyst)‐associated gill disease, harmful algal gill disease and chemical/toxin‐associated gill disease. The term ‘multifactorial gill disease’ is used when multiple distinguishable types of disease (as opposed to an obvious single primary type) are present. When gill disease is non‐specific, it is referred to as ‘complex gill disease’ (CGD) or ‘complex gill disorder’. These two terms are often used interchangeably and are overlapping. The significance of many infectious and non‐infectious agents that may be associated with CGD is often unclear. In this review, we summarise aspects of the different types of gill disease that are relevant to the epidemiology of gill disease and of CGD in particular. We also tabulate simultaneously occurring putative pathogens to explore the multifactorial nature of gill disease.

We describe the development and utilization of a new imaging technology for plant biology, optical coherence microscopy (OCM), which allows true in vivo visualization of plants and plant cells. This novel technology allows the direct, in situ (e.g. plants in soil), three-dimensional visualization of cells and events in shoot tissues without causing damage. With OCM we can image cells or groups of cells that are up to 1 mm deep in living tissues, resolving structures less than 5 μm in size, with a typical collection time of 5 to 6 min. OCM measures the inherent light-scattering properties of biological tissues and cells. These optical properties vary and provide endogenous developmental markers. Singly scattered photons from small (e.g. 5 × 5 × 10 μm) volume elements (voxels) are collected, assembled, and quantitatively false-colored to form a three-dimensional image. These images can be cropped or sliced in any plane. Adjusting the colors and opacities assigned to voxels allows us to enhance different features within the tissues and cells. We show that light-scattering properties are the greatest in regions of the Arabidopsis shoot undergoing developmental processes. In large cells, high light scattering is produced from nuclei, intermediate light scatter is produced from cytoplasm, and little if any light scattering originates from the vacuole and cell wall. OCM allows the rapid, repetitive, non-destructive collection of quantitative data about inherent properties of cells, so it provides a means of continuously monitoring plants and plant cells during development and in response to exogenous stimuli.

Greater phylogenetic signal is often found in parsimony-based analyses of third codon positions of protein-coding genes relative to their corresponding first and second codon positions, even for early-derived (“basal”) clades. We used the Soltis et al. (2000; Bot. J. Linn. Soc. 133:381–461) data matrix of atpB and rbcL from 567 seed plants to quantify how each of six factors (observed character-state space, frequencies of observed character states, substitution probabilities among nucleotides, rate heterogeneity among sites, overall rate of evolution, and number of parsimony-informative characters) contributed to this phenomenon. Each of these six factors was estimated from the original data matrix for parsimony-informative third codon positions considered separately from first and second codon positions combined. One of the most parsimonious trees found was used as the constraint topology; branch lengths were estimated using likelihood-based distances, and characters were simulated on this tree. Differential frequencies of observed character states were found to be the most limiting of the factors simulated for all three codon positions. Differential frequencies of observed character states and differential substitution probabilities among states were relatively advantageous for first and second codon positions. In contrast, differential numbers of observed character states, differential rate heterogeneity among sites, the greater number of parsimony-informative characters, and the higher overall rate of evolution were relatively advantageous for third codon positions. The amount of possible synapomorphy was predictive of the overall success of resolution.

Modern epidemiological analyses to understand and combat the spread of disease depend critically on access to, and use of, data. Rapidly evolving data, such as data streams changing during a disease outbreak, are particularly challenging. Data management is further complicated by data being imprecisely identified when used. Public trust in policy decisions resulting from such analyses is easily damaged and is often low, with cynicism arising where claims of ‘following the science’ are made without accompanying evidence. Tracing the provenance of such decisions back through open software to primary data would clarify this evidence, enhancing the transparency of the decision-making process. Here, we demonstrate a Findable, Accessible, Interoperable and Reusable (FAIR) data pipeline. Although developed during the COVID-19 pandemic, it allows easy annotation of any data as they are consumed by analyses, or conversely traces the provenance of scientific outputs back through the analytical or modelling source code to primary data. Such a tool provides a mechanism for the public, and fellow scientists, to better assess scientific evidence by inspecting its provenance, while allowing scientists to support policymakers in openly justifying their decisions. We believe that such tools should be promoted for use across all areas of policy-facing research. This article is part of the theme issue ‘Technical challenges of modelling real-life epidemics and examples of overcoming these’.