Aim The geographic clinal variation of traits in organisms can indicate the possible causes of phenotypic evolution. We studied the correlates of flower trait variation in populations of a style-dimorphic plant, Narcissus papyraceus Ker-Gawl., within a region of high biogeographical significance, the Strait of Gibraltar. This species shows a geographic gradient in the style-morph ratio, suggested to be driven by pollinator shifts. We tested whether parallel geographic variation of perianth traits also exists, concomitant with vegetative trait variation or genetic similarity of plant populations.Location The Strait of Gibraltar region (SG hereafter, including both southwestern Iberian Peninsula and north-western Morocco).Methods We used univariate and multivariate analyses of flower and vegetative traits in 23 populations. We applied Mantel tests and partial Mantel correlations on vegetative and flower traits and geographic locations of populations to test for spatial effects. We used Moran's autocorrelation analyses to explore the spatial structure within the range, and performed the analyses with and without the Moroccan samples to test for the effects of the SG on spatial patterns. Amplified fragment length polymorphism data were used to estimate the genetic distance between populations and to ascertain its relationship with morphometric distance. ResultsThere was high variation between and within populations in both flower and vegetative traits. Mantel correlations between geographic and morphometric distances were not significant, but the exclusion of Moroccan populations revealed some distance effect. Partial Mantel correlation did not detect a significant correlation between flower and vegetative morphometric distances after controlling for geographic distance. There were opposite trends in spatial autocorrelograms of flower and vegetative traits. The genetic distance between pairs of populations was directly correlated with geographic distance; however, flower morphometric and genetic distances were not significantly correlated. Main conclusionsThe SG had some influence on phenotypes, although the causes remain to be determined. The opposite trend of variation in flower and vegetative traits, and the lack of correlation between genetic distance and dissimilarity of flower phenotypes favour the hypothesis of pollinator-mediated selection on flower morphology, although this may affect only particular traits and populations rather than overall phenotypes. Although stochastic population processes may have a small effect, other factors may account for the high flower variation within and between populations.

There is a long history of exploitation of the South American river turtle Podocnemis expansa. Conservation efforts for this species started in the 1960s but best practices were not established, and population trends and the number of nesting females protected remained unknown. In 2014 we formed a working group to discuss conservation strategies and to compile population data across the species’ range. We analysed the spatial pattern of its abundance in relation to human and natural factors using multiple regression analyses. We found that > 85 conservation programmes are protecting 147,000 nesting females, primarily in Brazil. The top six sites harbour > 100,000 females and should be prioritized for conservation action. Abundance declines with latitude and we found no evidence of human pressure on current turtle abundance patterns. It is presently not possible to estimate the global population trend because the species is not monitored continuously across the Amazon basin. The number of females is increasing at some localities and decreasing at others. However, the current size of the protected population is well below the historical population size estimated from past levels of human consumption, which demonstrates the need for concerted global conservation action. The data and management recommendations compiled here provide the basis for a regional monitoring programme among South American countries.

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Within the field of soft computing, intelligent optimization modelling techniques include various major techniques in artificial intelligence. These techniques pretend to generate new business knowledge transforming sets of "raw data" into business value. One of the principal applications of these techniques is related to the design of predictive analytics for the improvement of advanced CBM (condition-based maintenance) strategies and energy production forecasting. These advanced techniques can be used to transform control system data, operational data and maintenance event data to failure diagnostic and prognostic knowledge and, ultimately, to derive expected energy generation. One of the systems where these techniques can be applied with massive potential impact are the legacy monitoring systems existing in solar PV energy generation plants. These systems produce a great amount of data over time, while at the same time they demand an important effort in order to increase their performance through the use of more accurate predictive analytics to reduce production losses having a direct impact on ROI. How to choose the most suitable techniques to apply is one of the problems to address. This paper presents a review and a comparative analysis of six intelligent optimization modelling techniques, which have been applied on a PV plant case study, using the energy production forecast as the decision variable. The methodology proposed not only pretends to elicit the most accurate solution but also validates the results, in comparison with the different outputs for the different techniques.

We analysed how replacing cereal concentrates with dehydrated orange pulp (DOP) in the diet of mother goats affects the meat quality of suckling kids. Three experimental diets for mother goats were designed. The DOP-0 diet contained commercial concentrates and alfalfa hay. In the DOP-40 and DOP-80 diets, 40% and 80% (respectively) of the cereal in the concentrate was replaced with pellets of DOP (the alfalfa hay component was unchanged). We evaluated the chemical composition, texture, water holding capacity, colour, fatty acids (FAs) profile, volatile compounds, and sensorial appraisal of the meat from 30 male suckling kids (cold carcass weight 4.74 kg, 4.82 kg, and 4.65 kg for DOP-0, DOP-40, and DOP-80, respectively) of the Payoya breed (n = 10 for each diet). Meat from kids in the DOP-40 and DOP-80 groups exhibited characteristics favourable for human health, including the meat’s thrombogenicity index, PUFA/SFA ratio (0.60 index), and n-6 PUFA/n-3 PUFA ratio (approximately 7.50). The meat also exhibited reduced MUFA content (around 460 mg/100 g fresh meat). An increase in ethyl furan, dimethyl disulphide and heptane was observed in grilled meat from goats that were fed using DOP. The inclusion of DOP in goat feed improved consumers’ sensory appreciation of the kid’s meat.