01230nas a2200253   4500008004100000245010800041210006900149260003800218300001100256490000600267520048000273653000800753653001300761653001700774653001700791653001500808653000800823100001600831700002500847700002100872700001700893700001500910856005100925       2008                        eng d00aOil and Gas Projects in the Western Amazon: Threats to Wilderness, Biodiversity, and Indigenous Peoples0 aOil and Gas Projects in the Western Amazon Threats to Wilderness  bPublic Library of SciencecAugust  ae2932+0 v33 aThe western Amazon is the most biologically rich part of the Amazon basin and is home to a great diversity of indigenous ethnic groups, including some of the world's last uncontacted peoples living in voluntary isolation. Unlike the eastern Brazilian Amazon, it is still a largely intact ecosystem. Underlying this landscape are large reserves of oil and gas, many yet untapped. The growing global demand is leading to unprecedented exploration and development in the region.10aabs10aamazonia10abiodiversity10aconservation10aindigenous10aoil1 aFiner, Matt1 aJenkins, Clinton, N.1 aPimm, Stuart, L.1 aKeane, Brian1 aRoss, Carl  uhttp://dx.doi.org/10.1371/journal.pone.000293201997nas a2200229   4500008004100000245005400041210005400095260003700149300001100186490000600197520136000203653000701563653000801570653001501578653001901593100001901612700002401631700001901655700002201674700002001696856005101716       2008                        eng d00aAutomated 3D Phenotype Analysis Using Data Mining0 aAutomated 3D Phenotype Analysis Using Data Mining  bPublic Library of SciencecMarch  ae1742+0 v33 aThe ability to analyze and classify three-dimensional (3D) biological morphology has lagged behind the analysis of other biological data types such as gene sequences. Here, we introduce the techniques of data mining to the study of 3D biological shapes to bring the analyses of phenomes closer to the efficiency of studying genomes. We compiled five training sets of highly variable morphologies of mammalian teeth from the MorphoBrowser database. Samples were labeled either by dietary class or by conventional dental types (e.g. carnassial, selenodont). We automatically extracted a multitude of topological attributes using Geographic Information Systems (GIS)-like procedures that were then used in several combinations of feature selection schemes and probabilistic classification models to build and optimize classifiers for predicting the labels of the training sets. In terms of classification accuracy, computational time and size of the feature sets used, non-repeated best-first search combined with 1-nearest neighbor classifier was the best approach. However, several other classification models combined with the same searching scheme proved practical. The current study represents a first step in the automatic analysis of 3D phenotypes, which will be increasingly valuable with the future increase in 3D morphology and phenomics databases.10a3d10agis10amorphology10areconstruction1 aPlyusnin, Ilya1 aEvans, Alistair, R.1 aKarme, Aleksis1 aGionis, Aristides1 aJernvall, Jukka  uhttp://dx.doi.org/10.1371/journal.pone.000174202687nas a2200193   4500008004100000245008100041210006900122260004100191300001100232490000600243520207500249653001202324653001402336653002202350100001702372700002702389700002602416856005102442       2008                        eng d00aEnvironment, Migratory Tendency, Phylogeny and Basal Metabolic Rate in Birds0 aEnvironment Migratory Tendency Phylogeny and Basal Metabolic Rat  bPublic Library of SciencecSeptember  ae3261+0 v33 aBasal metabolic rate (BMR) represents the minimum maintenance energy requirement of an endotherm and has far-reaching consequences for interactions between animals and their environments. Avian BMR exhibits considerable variation that is independent of body mass. Some long-distance migrants have been found to exhibit particularly high BMR, traditionally interpreted as being related to the energetic demands of long-distance migration. Here we use a global dataset to evaluate differences in BMR between migrants and non-migrants, and to examine the effects of environmental variables. The BMR of migrant species is significantly higher than that of non-migrants. Intriguingly, while the elevated BMR of migrants on their breeding grounds may reflect the metabolic machinery required for long-distance movements, an alternative (and statistically stronger) explanation is their occupation of predominantly cold high-latitude breeding areas. Among several environmental predictors, average annual temperature has the strongest effect on BMR, with a 50% reduction associated with a 20Â°C gradient. The negative effects of temperature variables on BMR hold separately for migrants and non-migrants and are not due their different climatic associations. BMR in migrants shows a much lower degree of phylogenetic inertia. Our findings indicate that migratory tendency need not necessarily be invoked to explain the higher BMR of migrants. A weaker phylogenetic signal observed in migrants supports the notion of strong phenotypic flexibility in this group which facilitates migration-related BMR adjustments that occur above and beyond environmental conditions. In contrast to the findings of previous analyses of mammalian BMR, primary productivity, aridity or precipitation variability do not appear to be important environmental correlates of avian BMR. The strong effects of temperature-related variables and varying phylogenetic effects reiterate the importance of addressing both broad-scale and individual-scale variation for understanding the determinants of BMR.10aecology10amigration10amigratory-species1 aJetz, Walter1 aFreckleton, Robert, P.1 aMcKechnie, Andrew, E.  uhttp://dx.doi.org/10.1371/journal.pone.0003261