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Uses of Gold and silver coins Nanoparticles inside the Management of Acne Vulgaris: An organized Assessment.
In addition, ancient sea otters at the most southerly sites occupied an isotopic niche that was more than twice as large as ancient otters from northerly regions. This likely reflects greater invertebrate prey diversity in southern California relative to northern California. Thus, we suggest the potential dietary niche of sea otters in southern California could be larger than in central and northern California. At two sites, Año Nuevo and Monterey Bay, ancient otters had significantly higher δ15N values than modern populations. Amino acid δ15N data indicated this resulted from shifting baseline isotope values, rather than a change in sea otter trophic ecology. Our results help in better understanding the contemporary ecological role of sea otters and exemplify the strength of combing zooarchaeological and biological information to provide baseline data for conservation efforts. © 2020 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.Aim Insects are the most species-rich clade in the world, but the broad-scale diversity pattern and the potential drivers have not been well documented for the clade as a whole. We aimed to examine the relative roles of contemporary and historical climate, niche conservatism, range overlapping, and other environmental factors on geographic patterns of species richness and phylogenetic structure, for insects across China. Location China. Methods We collected insect data from 184 nature reserves and examined geographic patterns of species richness and mean root distance (MRD, a metric of the evolutionary development of assemblages) for different biogeographic affinities (Palearctic, Oriental, and widespread species) and for clades originated during the warm and cold geohistorical periods ("warm clades" and "cold clades," respectively). We related richness and MRD to contemporary and historical climate, area, habitat heterogeneity, and human disturbance to evaluate their relative importance. Results Total specieay have been overlooked if only total species richness was analyzed, suggesting the importance of examining different evolutionary groups separately. © 2020 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.Designing an effective conservation strategy requires understanding where rare species are located. Because rare species can be difficult to find, ecologists often identify other species called conservation surrogates that can help inform the distribution of rare species. Species distribution models typically rely on environmental data when predicting the occurrence of species, neglecting the effect of species' co-occurrences and biotic interactions. Here, we present a new approach that uses Bayesian networks to improve predictions by modeling environmental co-responses among species. For species from a European peat bog community, our approach consistently performs better than single-species models and better than conventional multi-species approaches that include the presence of nontarget species as additional independent variables in regression models. Our approach performs particularly well with rare species and when calibration data are limited. Furthermore, we identify a group of "predictor species" that are relatively common, insensitive to the presence of other species, and can be used to improve occurrence predictions of rare species. Predictor species are distinct from other categories of conservation surrogates such as umbrella or indicator species, which motivates focused data collection of predictor species to enhance conservation practices. © 2020 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.Apex carnivores are wide-ranging, low-density, hard to detect, and declining throughout most of their range, making population monitoring both critical and challenging. Rapid and inexpensive index calibration survey (ICS) methods have been developed to monitor large African carnivores. ICS methods assume constant detection probability and a predictable relationship between the index and the actual population of interest. The precision and utility of the resulting estimates from ICS methods have been questioned. We assessed the performance of one ICS method for large carnivores-track counts-with data from two long-term studies of African lion populations. We conducted Monte Carlo simulation of intersections between transects (road segments) and lion movement paths (from GPS collar data) at varying survey intensities. Then, using the track count method we estimated population size and its confidence limits. We found that estimates either overstate precision or are too imprecise to be meaningful. Overstated preccommended. © 2020 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.Geometric morphometric analyses are frequently employed to quantify biological shape and shape variation. Despite the popularity of this technique, quantification of measurement error in geometric morphometric datasets and its impact on statistical results is seldom assessed in the literature. Here, we evaluate error on 2D landmark coordinate configurations of the lower first molar of five North American Microtus (vole) species. We acquired data from the same specimens several times to quantify error from four data acquisition sources specimen presentation, imaging devices, interobserver variation, and intraobserver variation. We then evaluated the impact of those errors on linear discriminant analysis-based classifications of the five species using recent specimens of known species affinity and fossil specimens of unknown species affinity. Results indicate that data acquisition error can be substantial, sometimes explaining >30% of the total variation among datasets. Comparisons of datasets digitized by different individuals exhibit the greatest discrepancies in landmark precision, and comparison of datasets photographed from different presentation angles yields the greatest discrepancies in species classification results. selleck chemical All error sources impact statistical classification to some extent. For example, no two landmark dataset replicates exhibit the same predicted group memberships of recent or fossil specimens. Our findings emphasize the need to mitigate error as much as possible during geometric morphometric data collection. Though the impact of measurement error on statistical fidelity is likely analysis-specific, we recommend that all geometric morphometric studies standardize specimen imaging equipment, specimen presentations (if analyses are 2D), and landmark digitizers to reduce error and subsequent analytical misinterpretations. © 2020 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.
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