Early environment influences later performance in fishes

Conditions fish encounter during embryogenesis and early life history can leave lasting effects not only on morphology, but also on growth rate, life‐history and behavioural traits. The ecology of offspring can be affected by conditions experienced by their parents and mother in particular. This review summarizes such early impacts and their ecological influences for a variety of teleost species, but with special reference to salmonids. Growth and adult body size, sex ratio, egg size, lifespan and tendency to migrate can all be affected by early influences. Mechanisms behind such phenotypically plastic impacts are not well known, but epigenetic change appears to be one central mechanism. The thermal regime during development and incubation is particularly important, but also early food consumption and intraspecific density can all be responsible for later life‐history variation. For behavioural traits, early experiences with effects on brain, sensory development and cognition appear essential. This may also influence boldness and other social behaviours such as mate choice. At the end of the review, several issues and questions for future studies are given.     

Biodiversity on the brink: Evaluating a transdisciplinary research collaboration

Global biodiversity is facing an extinction crisis. Australia has one of the highest terrestrial species extinction rates in the world. Scientists, policy advisors and governments have recommended that the issue be addressed at a landscape-scale, while noting that there are significant knowledge gaps that are hampering implementation of such an approach. From 2011–2015, the Australian Government funded a transdisciplinary research program, the Landscapes and Policy Hub, to meet this need. Transdisciplinary research is widely acknowledged as essential to address the complexity of contemporary environmental problems. Given that such research programs are in their infancy, it is important to evaluate their efficacy and provide an empirical basis for improving their design. This paper presents an evaluation of the strategies fostering transdisciplinarity adopted by the Landscapes and Policy Hub. A heavy emphasis on communication, with skilled knowledge brokering, regular face-to-face meetings using participatory activities and shared field engagements enhanced transdisciplinary interaction between researchers and research users. However, establishing a fully integrated interdisciplinary research program remained a challenge. Efforts to enable shared conceptual frameworks to emerge through adaptive application of theory in practice could have been balanced with increased effort at the outset for researchers and research users to collaboratively formulate shared research questions, leading to the establishment of teams that could address these questions through cross-mobilisation of interdisciplinary expertise.     

Accuracy of predicting genomic breeding values for carcass merit traits in Angus and Charolais beef cattle

Accuracy of predicting genomic breeding values for carcass merit traits including hot carcass weight, longissimus muscle area (REA), carcass average backfat thickness (AFAT), lean meat yield (LMY) and carcass marbling score (CMAR) was evaluated based on 543 Angus and 400 Charolais steers genotyped on the Illumina BovineSNP50 Beadchip. For the genomic prediction within Angus, the average accuracy was 0.35 with a range from 0.32 (LMY) to 0.37 (CMAR) across different training/validation data‐splitting strategies and statistical methods. The within‐breed genomic prediction for Charolais yielded an average accuracy of 0.36 with a range from 0.24 (REA) to 0.46 (AFAT). The across‐breed prediction had the lowest accuracy, which was on average near zero. When the data from the two breeds were combined to predict the breeding values of either breed, the prediction accuracy averaged 0.35 for Angus with a range from 0.33 (REA) to 0.39 (CMAR) and averaged 0.33 for Charolais with a range from 0.18 (REA) to 0.46 (AFAT). The prediction accuracy was slightly higher on average when the data were split by animal's birth year than when the data were split by sire family. These results demonstrate that the genetic relationship or relatedness of selection candidates with the training population has a great impact on the accuracy of predicting genomic breeding values under the density of the marker panel used in this study.     

CyberKnife beam output factor measurements: A multi-site and multi-detector study

PurposeNew promising detectors are available for measuring small field size output factors (OFs). This study focused on a multicenter evaluation of two new generation detectors for OF measurements on CyberKnife systems.MethodsPTW-60019 microDiamond and W1 plastic scintillation detector (PSD) were used to measure OFs on eight CyberKnife units of various generations for 5–60 mm fixed cones. MicroDiamond and PSD OF were compared to routinely used silicon diodes data corrected applying published Monte Carlo (MC) factors. PSD data were corrected for Čerenkov Light Ratio (CLR). The uncertainties related to CLR determination were estimated.ResultsConsidering OF values averaged over all centers, the differences between MC corrected diode and the other two detectors were within 1.5%. MicroDiamond exhibited an over-response of 1.3% at 7.5 mm and a trend inversion at 5 mm with a difference of 0.2%. This behavior was consistent among the different units. OFs measured by PSD slightly under-responded compared to MC corrected diode for the smaller cones and the differences were within 1%. The observed CLR variability was 2.5% and the related variation in OF values was 1.9%.ConclusionThis study indicates that CyberKnife microDiamond OF require corrections below 2%. The results are enhanced by the consistency observed among different units. Scintillator shows a good agreement to MC corrected diode but CLR determination remains critical requiring further investigations. The results emphasized the value of a multi-center validation over a single center approach.     

Rare species habitat suitability assessment and reliability evaluation of an expert-based model: A case study of the insectivorous plant Pinguicula crystallina Sibth. et Smith subsp. hirtiflora (Ten.) Strid (Lentibulariaceae)

The development of habitat suitability models requires a large amount of data which are rarely available. In this case, researchers need to get information on the ecological features of the studied species, based on the opinion of experts or on the literature, to construct a qualitative model. However, such models cannot be rigorously evaluated, as in most cases absence points are not available. In this paper, we assess the habitat suitability for a vulnerable insectivorous plant, Pinguicula crystallina Sibth. et Smith subsp. hirtiflora (Ten.) Strid (Lentibulariaceae) in the Campania region. Our aim was to develop an expert-based, presence-only model in support of possible conservation actions. Topographic and geological features of this species suggested by the literature were used in our model. Both the Boyce index and field surveys were chosen to evaluate the model's reliability. During field surveys, 31 absence sites and 1 new presence site were identified, and differences between sites with regard to water chemistry and quality were investigated, water being an element in the species habitat. Factors that affect reliability of the model, such as the lack of a large amount of information on the species and the limited spatial resolution of geographical information system data, are discussed.