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This paper demonstrates the contribution of both genetic and environmental effects on cultured European sea bass shape. We used the progeny of five populations of sea bass, in a partly diallel design, to investigate the genetics of shape (estimated with geometric morphometrics) in European sea bass. This was done using a common garden experiment with microsatellite markers assignment to parents and populations to avoid confusion between genetic and environmental effects. Additionally, one of the populations was studied over four different aquaculture facilities to investigate the effects of environment on shape. For the first time in this species, shape-related traits were linked with genetic variation. The first relative warp analysis axis clearly differentiated rearing sites, demonstrating that the main shape/weight effects are related to culturing conditions, thereby accounting for ecomorphologically related differences. The second axis strongly differentiated groups by parental origins; there was a good correlation between shape differences and geographic distances between broodstock sampling locations. High heritabilities of axes scores (0.40–0.55) showed high genetic variation for shape within populations. This study shows that variation in shape has a high genetic component in sea bass, both at the population level and within populations

In the present study, we applied statistical methods to quantitative image analysis of the persistent and individual ventral colour pattern of Salamandrina salamanders, in order to discriminate between individuals of the two species belonging to this genus. Pictures of 238 individuals from three populations of S. perspicillata and pictures of 95 S. terdigitata from two populations were analysed. Partial least squares discriminant analysis (PLSDA) classified 98.78% of individuals into the correct species. PLSDA reaches lower percentages of correct classification when applied to discriminate individuals from different populations of the same species (74.14% for S. perspicillata, 78.26% for S. terdigitata). An ANOVA analysis of colour abundances in different body sectors reveals significant differences between species. The results show that colour pattern has a specific basis, the most discriminant areas being the head and the pectoral girdle. We discuss these results in the light of the proposed evolutionary scenarios of the species, and suggest that ventral colour patterns were driven by founder effect

Partial Least Square (PLS) regression is a recent soft-modelling technique that generalizes and combines features from principal component analysis (PCA) and multiple regression. It is particularly useful when predicting one or more dependent variables from a large set of independent variables, often collinear. The authors compared the potential of PLS regression and ordinary linear regression for accurate modelling of forest work, with special reference to wood chipping, wood extraction and the continuous harvesting of short rotation coppice. Compared to linear regression, PLS regression allowed producing models that better fit the original data. What is more, it allowed handling collinear variables, facilitating the extraction of sound models from large amounts of field data obtained from commercial forest operations. On the other hand, PLS regression analysis is not as easy to conduct, and produces models that are less user-friendly. By producing alternative models, PLS regression may provide additional -and not alternative -ways of reading the data. Ideally, a comprehensive data analysis could include both ordinary and PLS regression and proceed from their results in order to get a better understanding of the phenomenon under examination. Furthermore, the computational complexity of PLS regression may stimulate interdisciplinary team-building, to the greater benefit of scientific research within the field of forest operations.

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