Diversity of free-living marine nematodes (Enoplida) from Baja California assessed by integrative taxonomy

We used morphological and molecular approaches to evaluate the diversity of free-living marine nematodes (order Enoplida) at four coastal sites in the Gulf of California and three on the Pacific coast of Baja California, Mexico. We identified 22 morphological species belonging to six families, of which Thoracostomopsidae and Oncholaimidae were the most diverse. The genus Mesacanthion (Thoracostomopsidae) was the most widespread and diverse. Five allopatric species, genetically and morphologically differentiated, were found in two localities in the Gulf of California (M. sp1 and M. sp2) and three in the Pacific coast (M. sp3, M. sp4 and M. sp5). Overall, we produced 19 and 20 sequences for the 18S and 28S genes, respectively. Neither gene displayed intraspecific polymorphisms, which allowed us to establish that some morphological variation was likely either ontogenetic or due to phenotypic plasticity. Although 18S and 28S phylogenies were topologically congruent (incongruence length difference test, P > 0.05), divergences between species were much higher in the 28S gene. Moreover, this gene possessed a stronger phylogenetic signal to resolve relationships involving Rhabdodemania and Bathylaimus. On the other hand, the close relationship of Pareurystomina (Enchilidiidae) with oncholaimids warrants further study. The 28S sequences (D2D3 domain) may be better suited for DNA barcoding of marine nematodes than those from the 18S rDNA, particularly for differentiating closely related or cryptic species. Finally, our results underline the relevance of adopting an integrative approach encompassing morphological and molecular analyses to improve the assessment of marine nematode diversity and advance their taxonomy.     

How unpredictable is the individual scanning process in socially foraging mammals?

In group-forming prey species, theory assumes that individuals within groups should scan independently of one another, with vigilance sequences being relatively unpredictable, making interscan durations highly variable. We attempted to detect any divergence from randomness in the scanning process in three mammalian prey species phylogenetically and geographically separated and exposed to different levels of predation: waterbuck, Kobus ellipsiprymnus defassa, under a high observed predation risk, eastern grey kangaroo, Macropus giganteus, still experiencing occasional predation and European roe deer, Capreolus capreolus, under a very low natural predation risk. Our results revealed that the focal interscan duration increased when the duration of the preceding interscan increased, whatever the studied species and the predation risk that its individuals experienced, and decreased with the preceding scan duration in two species under, respectively, occasional and low predation risks. The exponential distribution was the tested model that fitted the observed distributions of interscan durations least well. We discuss what can trigger non-randomness in scanning, through a non-homogenous Poisson process, at both intra-individual and inter-individual levels, particularly with regard to previous studies that have demonstrated synchronisation of vigilance in such mammals. Our results suggest the need to reconsider any assumption of randomness in scanning in the basic model predicting form and frequency of scanning behaviour by prey species.     

Nest desertion is not predicted by cuckoldry in the Eurasian penduline tit

Engagement in extra-pair copulations is an example of the abundant conflicting interests between males and females over reproduction. Potential benefits for females and the risk of cuckoldry for males are expected to have important implications on the evolution of parental care. However, whether parents adjust parental care in response to parentage remains unclear. In Eurasian penduline tits Remiz pendulinus, which are small polygamous songbirds, parental care is carried out either by the male or by the female. In addition, one third of clutches is deserted by both male and female. Desertion takes place during the egg-laying phase. Using genotypes of nine microsatellite loci of 443 offspring and 211 adults, we test whether extra-pair paternity predicts parental care. We expect males to be more likely to desert cuckolded broods, whereas we expect females, if they obtain benefits from having multiple sires, to be more likely to care for broods with multiple paternity. Our results suggest that parental care is not adjusted to parentage on an ecological timescale. Furthermore, we found that male attractiveness does not predict cuckoldry, and we found no evidence for indirect benefits for females (i.e., increased growth rates or heterozygosity of extra-pair offspring). We argue that male Eurasian penduline tits may not be able to assess the risk of cuckoldry; thus, a direct association with parental care is unlikely to evolve. However, timing of desertion (i.e., when to desert during the egg-laying phase) may be influenced by the risk of cuckoldry. Future work applying extensive gene sequencing and quantitative genetics is likely to further our understanding of how selection may influence the association between parentage and parental care.     

Comparison and ranking of different modelling techniques for prediction of site index in Mediterranean mountain forests

Forestry science has a long tradition of studying the relationship between stand productivity and abiotic and biotic site characteristics, such as climate, topography, soil and vegetation. Many of the early site quality modelling studies related site index to environmental variables using basic statistical methods such as linear regression. Because most ecological variables show a typical non-linear course and a non-constant variance distribution, a large fraction of the variation remained unexplained by these linear models. More recently, the development of more advanced non-parametric and machine learning methods provided opportunities to overcome these limitations. Nevertheless, these methods also have drawbacks. Due to their increasing complexity they are not only more difficult to implement and interpret, but also more vulnerable to overfitting. Especially in a context of regionalisation, this may prove to be problematic. Although many non-parametric and machine learning methods are increasingly used in applications related to forest site quality assessment, their predictive performance has only been assessed for a limited number of methods and ecosystems.In this study, five different modelling techniques are compared and evaluated, i.e. multiple linear regression (MLR), classification and regression trees (CART), boosted regression trees (BRT), generalized additive models (GAM), and artificial neural networks (ANN). Each method is used to model site index of homogeneous stands of three important tree species of the Taurus Mountains (Turkey): Pinus brutia, Pinus nigra and Cedrus libani. Site index is related to soil, vegetation and topographical variables, which are available for 167 sample plots covering all important environmental gradients in the research area. The five techniques are compared in a multi-criteria decision analysis in which different model performance measures, ecological interpretability and user-friendliness are considered as criteria.When combining these criteria, in most cases GAM is found to outperform all other techniques for modelling site index for the three species. BRT is a good alternative in case the ecological interpretability of the technique is of higher importance. When user-friendliness is more important MLR and CART are the preferred alternatives. Despite its good predictive performance, ANN is penalized for its complex, non-transparent models and big training effort.     

Differential effect of ultraviolet exposure (UVR) in the stress response of the Dinophycea Gymnodinium sp. and the Chlorophyta Dunaliella tertiolecta: mortality versus survival

Dunaliella tertiolecta (Chlorophyta) and Gymnodinium sp. (Dinophyceae) cells were exposed to ultraviolet radiation (UVR) (PAR, UVA and UVB: PAB) for 6 days either continuously or during a photoperiod. Both UVR treatments were harmful to Gymnodinium but exposure to continuous PAB had the most dramatic effects. Although a number of lesions/damage could have happened during the first few hours of exposure to UVR, in less than 24 h, Gymnodinium lost its ability to detoxify ROS efficiently, photoinhibition occurred, thymine dimers formed in the DNA, caspase-like enzymatic activities DEVDase sharply increased and cells died as determined by SYTOX-green staining. Superoxide dismutase activity did not significantly change with time, and although the catalase activity augmented in both treatments, cells still suffered from the UVR stress. Clearly, UVR was fatal to the dinoflagellate. For the chlorophyte, however, cell numbers increased regardless of the UVR treatment and mortality remained low (<20 %). F _v/F _m showed an initial decrease but then remained constant for both light treatments. After 6 days of continuous PAB exposure, however, signs of stress (thymine dimers, oxidative stress) paralleled a drop in catalase activity. Results obtained here demonstrate that the dinoflagellate Gymnodinium was much more sensitive and was harmed more rapidly by UVR exposure than the chlorophyte D. tertiolecta. The increased tolerance to UVR exposure of the chlorophyte may provide advantages over other more sensitive phytoplankton species within the photic zone. We provide strong support in the present study for repair being an important component of UV resistance in this species.     

In vitro evaluation of human liver cancer cells and the potential cytotoxicity of Tecoma stans (Bignoniaceae) and Brickellia cavanillesi (Asteraceae) both single and in combination

Medicinal herbs are steadily increasing in complementary use for chronic and alterative therapies. The health risks associated with herbal supplements have therefore been identified as a top research priority. Tecoma stans (Tronadora), a Bignoniaceae plant, is a herbal drug traditionally consumed as tea in South America for the control of diabetes. It contains the alkaloids of tecomine and tecostanine which were shown as functional compounds responsible for hypoglycemic activity. However, the side effects of aqueous extracts of this herbal tea have not been reported. In this study, studies sought to evaluate the cytotoxicity of water extracts from T. stans in human hepatoblastoma (HepG2). Toxic effects of T. stans were concentration- and time-dependent in the presence and absence of fetal bovine serum (FBS). Cells were incubated for up to 72-h with varying concentrations of herbal extracts (60–100%), cytotoxicity was determined spectrophotometrically by MTT and reported in terms of % cell viability. For IC₅₀ assay (24 h exposure), cytotoxicity was found at concentration of 60–100%. Evaluation of the effects of T. stans and Brickellia cavanillesi (Asteraceae) in combination revealed that extracts of both herbal extracts' nontoxic levels of T. stans significantly reduced cell viability in a time-dependent manner. Further studies are needed regarding the identification, toxicity, and molecular mechanism of action of active compounds, as well as their cytotoxicity to other cell lines following exposure to both single and combined herbal extracts of these plants with anti-diabetic properties.     

A proposal for environmental indicators towards industrial building sustainable assessment

The construction sector carries out a very important role in the development of society. It is a basic component of economic activity, having a great influence on employment generation and country growth. The sector generates appreciable environmental changes and effects throughout the planet, leading to gradual exhaustion of natural resources and contamination of basic elements, such as air, water and soil. Recently, there have been advances in favour of more environmentally friendly buildings. Basically, sustainable construction has centred on residential and office buildings. It could be said that there is a lack of sustainability in the construction of industrial buildings, as they present characteristics which differ from other building typologies. This article aims to assess and analyze industrial building environmental effects, and considers a set of green study criteria, such as: location, materials, energy and water consumption, construction and deconstruction characteristics, and waste management in industrial building. At the same time, the studies are hierarchically structured into different assessment elements, such as: criteria, subcriteria and, finally, indicators, comprising the assessment model.     

Evolution of self-organized division of labor in a response threshold model

Division of labor in social insects is determinant to their ecological success. Recent models emphasize that division of labor is an emergent property of the interactions among nestmates obeying to simple behavioral rules. However, the role of evolution in shaping these rules has been largely neglected. Here, we investigate a model that integrates the perspectives of self-organization and evolution. Our point of departure is the response threshold model, where we allow thresholds to evolve. We ask whether the thresholds will evolve to a state where division of labor emerges in a form that fits the needs of the colony. We find that division of labor can indeed evolve through the evolutionary branching of thresholds, leading to workers that differ in their tendency to take on a given task. However, the conditions under which division of labor evolves depend on the strength of selection on the two fitness components considered: amount of work performed and on worker distribution over tasks. When selection is strongest on the amount of work performed, division of labor evolves if switching tasks is costly. When selection is strongest on worker distribution, division of labor is less likely to evolve. Furthermore, we show that a biased distribution (like 3:1) of workers over tasks is not easily achievable by a threshold mechanism, even under strong selection. Contrary to expectation, multiple matings of colony foundresses impede the evolution of specialization. Overall, our model sheds light on the importance of considering the interaction between specific mechanisms and ecological requirements to better understand the evolutionary scenarios that lead to division of labor in complex systems. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00265-012-1343-2) contains supplementary material, which is available to authorized users.     

Habitat selection predicts genetic relatedness in an alpine ungulate

Landscape heterogeneity plays an integral role in shaping ecological and evolutionary processes. Despite links between the two disciplines, ecologists and population geneticists have taken different approaches to evaluating habitat selection, animal movement, and gene flow across the landscape. Ecologists commonly use statistical models such as resource selection functions (RSFs) to identify habitat features disproportionately selected by animals, whereas population genetic approaches model genetic differentiation according to the distribution of habitat variables. We combined ecological and genetic approaches by using RSFs to predict genetic relatedness across a heterogeneous landscape. We constructed sex- and season-specific resistance surfaces based on RSFs estimated using data from 102 GPS (global positioning system) radio-collared mountain goats (Oreamnos americanus) in southeast Alaska, USA. Based on mountain goat ecology, we hypothesized that summer and male surfaces would be the best predictors of relatedness. All individuals were genotyped at 22 microsatellite loci, which we used to estimate genetic relatedness. Summer resistance surfaces derived from RSFs were the best predictors of genetic relatedness, and winter models the poorest. Mountain goats generally selected for areas close to escape terrain and with a high heat load (a metric related to vegetative productivity and snow depth), while avoiding valleys. Male- and female-specific surfaces were similar, except for winter, for which male habitat selection better predicted genetic relatedness. The null models of isolation-by-distance and barrier only outperformed the winter models. This study merges high-resolution individual locations through GPS telemetry and genetic data, that can be used to validate and parameterize landscape genetics models, and further elucidates the relationship between landscape heterogeneity and genetic differentiation.