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1. According to their geographical distribution, most Drosophila species may be classified as either temperate or tropical, and this pattern is assumed to reflect differences in their thermal adaptation, especially in their cold tolerance. We investigated cold tolerance in a global collection of D. melanogaster by monitoring the time adults take to recover from chill coma after a treatment at 0degreesC.2. Flies grown at an intermediate temperature (21degreesC) showed a significant linear latitudinal cline: recovery was faster in populations living in colder climates.3. The role of growth temperature was analysed in a subset of tropical and temperate populations. In all cases, recovery time decreased when growth temperature was lowered, and linear reaction norms were observed. This adaptive phenotypic plasticity explained more than 80% of the total variation, while genetic latitudinal differences accounted for less than 4%.4. The beneficial effect observed in adults grown at a low temperature contrasts with other phenotypic effects which, like male sterility, appear as harmful and pathological. Our results point to the difficulty of finding a general interpretation to the diversity of plastic responses that are induced by growth temperature variations.

Background Domestication of Atlantic salmon for commercial aquaculture has resulted in farmed salmon displaying substantially higher growth rates than wild salmon under farming conditions. In contrast, growth differences between farmed and wild salmon are much smaller when compared in the wild. The mechanisms underlying this contrast between environments remain largely unknown. It is possible that farmed salmon have adapted to the high-energy pellets developed specifically for aquaculture, contributing to inflated growth differences when fed on this diet. We studied growth and survival of 15 families of farmed, wild and F1 hybrid salmon fed three contrasting diets under hatchery conditions; a commercial salmon pellet diet, a commercial carp pellet diet, and a mixed natural diet consisting of preserved invertebrates commonly found in Norwegian rivers. Results For all groups, despite equal numbers of calories presented by all diets, overall growth reductions as high 68 and 83%, relative to the salmon diet was observed in the carp and natural diet treatments, respectively. Farmed salmon outgrew hybrid (intermediate) and wild salmon in all treatments. The relative growth difference between wild and farmed fish was highest in the carp diet (1: 2.1), intermediate in the salmon diet (1:1.9) and lowest in the natural diet (1:1.6). However, this trend was non-significant, and all groups displayed similar growth reaction norms and plasticity towards differing diets across the treatments. Conclusions No indication of genetic-based adaptation to the form or nutritional content of commercial salmon diets was detected in the farmed salmon. Therefore, we conclude that diet alone, at least in the absence of other environmental stressors, is not the primary cause for the large contrast in growth differences between farmed and wild salmon in the hatchery and wild. Additionally, we conclude that genetically-increased appetite is likely to be the primary reason why farmed salmon display higher growth rates than wild salmon when fed ad lib rations under hatchery conditions. Our results contribute towards an understanding of the potential genetic changes that have occurred in farmed salmon in response to domestication, and the potential mechanisms underpinning genetic and ecological interactions between farmed escapees and wild salmonids. Electronic supplementary material The online version of this article (doi:10.1186/s12862-016-0841-7) contains supplementary material, which is available to authorized users.

Background: Genetic variation for environmental sensitivity indicates that animals are genetically different in their response to environmental factors. Environmental factors are either identifiable (e.g. temperature) and called macro-environmental or unknown and called micro-environmental. The objectives of this study were to develop a statistical method to estimate genetic parameters for macro- and micro-environmental sensitivities simultaneously, to investigate bias and precision of resulting estimates of genetic parameters and to develop and evaluate use of Akaike’s information criterion using h-likelihood to select the best fitting model. Methods: We assumed that genetic variation in macro- and micro-environmental sensitivities is expressed as genetic variance in the slope of a linear reaction norm and environmental variance, respectively. A reaction norm model to estimate genetic variance for macro-environmental sensitivity was combined with a structural model for residual variance to estimate genetic variance for micro-environmental sensitivity using a double hierarchical generalized linear model in ASReml. Akaike’s information criterion was constructed as model selection criterion using approximated h-likelihood. Populations of sires with large half-sib offspring groups were simulated to investigate bias and precision of estimated genetic parameters. Results: Designs with 100 sires, each with at least 100 offspring, are required to have standard deviations of estimated variances lower than 50% of the true value. When the number of offspring increased, standard deviations of estimates across replicates decreased substantially, especially for genetic variances of macro- and micro-environmental sensitivities. Standard deviations of estimated genetic correlations across replicates were quite large (between 0.1 and 0.4), especially when sires had few offspring. Practically, no bias was observed for estimates of any of the parameters. Using Akaike’s information criterion the true genetic model was selected as the best statistical model in at least 90% of 100 replicates when the number of offspring per sire was 100. Application of the model to lactation milk yield in dairy cattle showed that genetic variance for micro- and macro-environmental sensitivities existed. Conclusion: The algorithm and model selection criterion presented here can contribute to better understand genetic control of macro- and micro-environmental sensitivities. Designs or datasets should have at least 100 sires each with 100 offspring. Open Access