629 research outputs found

    Automated data analysis to rapidly derive and communicate ecological insights from satellite-tag data: A case study of reintroduced red kites

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    Analysis of satellite-telemetry data mostly occurs long after it has been collected, due to the time and effort needed to collate and interpret such material. Such delayed reporting does reduce the usefulness of such data for nature conservation when timely information about animal movements is required. To counter this problem we present a novel approach which combines automated analysis of satellite-telemetry data with rapid communication of insights derived from such data. A relatively simple algorithm (comprising speed of movement and turning angle calculated from fixes), allowed instantaneous detection of excursions away from settlement areas and automated calculation of home ranges on the remaining data Automating the detection of both excursions and home range calculations enabled us to disseminate ecological insights from satellite-tag data instantaneously through a dedicated web portal to inform conservationists and wider audiences. We recommend automated analysis, interpretation and communication of satellite tag and other ecological data to advance nature conservation research and practice

    Comparative cytogenetic analysis of two grasshopper species of the tribe Abracrini (Ommatolampinae, Acrididae)

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    The grasshopper species Orthoscapheus rufipes and Eujivarus fusiformis were analyzed using several cytogenetic techniques. The karyotype of O. rufipes, described here for the first time, had a diploid number of 2n = 23, whereas E. fusiformis had a karyotype with 2n = 21. The two species showed the same mechanism of sex determination (XO type) but differed in chromosome morphology. Pericentromeric blocks of constitutive heterochromatin (CH) were detected in the chromosome complement of both species. CMA3/DA/DAPI staining revealed CMA3-positive blocks in CH regions in four autosomal bivalents of O. rufipes and in two of E. fusiformis. The location of active NORs differed between the two species, occurring in bivalents M6 and S9 of O. rufipes and M6 and M7 of E. fusiformsi. The rDNA sites revealed by FISH coincided with the number and position of the active NORs detected by AgNO3 staining. The variability in chromosomal markers accounted for the karyotype differentiation observed in the tribe Abracrini

    Altruism in a volatile world

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    This is the author accepted manuscript. The final version is available from Springer Nature via the DOI in this record.The evolution of altruism – costly self-sacrifice in the service of others – has puzzled biologists since The Origin of Species. For half a century, attempts to understand altruism have been built on the insight that altruists may help relatives to have extra offspring in order to spread shared genes . This theory – known as inclusive fitness – is founded on a simple inequality termed ‘Hamilton’s rule’. However, explanations of altruism have typically ignored the stochasticity of natural environments, which will not necessarily favour genotypes that produce the greatest average reproductive success. Moreover, empirical data across many taxa reveal associations between altruism and environmental stochasticity, a pattern not predicted by standard interpretations of Hamilton’s rule. Here, we derive Hamilton’s rule with explicit stochasticity, leading to novel predictions about the evolution of altruism. We show that of offspring produced by relatives. Consequently, costly altruism can evolve even if it has a net negative effect on the average reproductive success of related recipients. The selective pressure on volatility suppressing altruism is proportional to the coefficient of variation in population fitness, and is therefore diminished by its own success. Our results formalise the hitherto elusive link between bet-hedging and altruism, and reveal missing fitness effects in the evolution of animal societies.PK was supported by the National Geographic Society (GEF-NE 145-15) and a University of Bristol Research Studentship; ADH was supported by the Natural Environment Research Council (NE/L011921/1); ANR was supported by a European Research Council Consolidator Grant (award no. 682253); and SS was supported by the Natural Environment Research Council (NE/M012913/2)

    A metabolomics cell-based approach for anticipating and investigating drug-induced liver injury

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    In preclinical stages of drug development, anticipating potential adverse drug effects such as toxicity is an important issue for both saving resources and preventing public health risks. Current in vitro cytotoxicity tests are restricted by their predictive potential and their ability to provide mechanistic information. This study aimed to develop a metabolomic mass spectrometry-based approach for the detection and classification of drug-induced hepatotoxicity. To this end, the metabolite profiles of human derived hepatic cells (i.e., HepG2) exposed to different well-known hepatotoxic compounds acting through different mechanisms (i.e., oxidative stress, steatosis, phospholipidosis, and controls) were compared by multivariate data analysis, thus allowing us to decipher both common and mechanism-specific altered biochemical pathways. Briefly, oxidative stress damage markers were found in the three mechanisms, mainly showing altered levels of metabolites associated with glutathione and γ-glutamyl cycle. Phospholipidosis was characterized by a decreased lysophospholipids to phospholipids ratio, suggestive of phospholipid degradation inhibition. Whereas, steatosis led to impaired fatty acids β-oxidation and a subsequent increase in triacylglycerides synthesis. The characteristic metabolomic profiles were used to develop a predictive model aimed not only to discriminate between non-toxic and hepatotoxic drugs, but also to propose potential drug toxicity mechanism(s)

    Phenotypic Variation and Bistable Switching in Bacteria

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    Microbial research generally focuses on clonal populations. However, bacterial cells with identical genotypes frequently display different phenotypes under identical conditions. This microbial cell individuality is receiving increasing attention in the literature because of its impact on cellular differentiation, survival under selective conditions, and the interaction of pathogens with their hosts. It is becoming clear that stochasticity in gene expression in conjunction with the architecture of the gene network that underlies the cellular processes can generate phenotypic variation. An important regulatory mechanism is the so-called positive feedback, in which a system reinforces its own response, for instance by stimulating the production of an activator. Bistability is an interesting and relevant phenomenon, in which two distinct subpopulations of cells showing discrete levels of gene expression coexist in a single culture. In this chapter, we address techniques and approaches used to establish phenotypic variation, and relate three well-characterized examples of bistability to the molecular mechanisms that govern these processes, with a focus on positive feedback.

    Post-depositional fracturing and subsidence of pumice flow deposits: Lascar Volcano, Chile

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    Unconsolidated pyroclastic flow deposits of the 1993 eruption of Lascar Volcano, Chile, have, with time, become increasingly dissected by a network of deeply penetrating fractures. The fracture network comprises orthogonal sets of decimeter-wide linear voids that form a pseudo-polygonal grid visible on the deposit surface. In this work, we combine shallow surface geophysical imaging tools with remote sensing observations and direct field measurements of the deposit to investigate these fractures and their underlying causal mechanisms. Based on ground penetrating radar images, the fractures are observed to have propagated to depths of up to 10 m. In addition, orbiting radar interferometry shows that deposit subsidence of up to 1 cm/year occurred between 1993 and 1996 with continued subsidence occurring at a slower rate thereafter. In situ measurements show that 1 m below the surface, the 1993 deposits remain 5°C to 15°C hotter, 18 years after emplacement, than adjacent deposits. Based on the observed subsidence as well as estimated cooling rates, the fractures are inferred to be the combined result of deaeration, thermal contraction, and sedimentary compaction in the months to years following deposition. Significant environmental factors, including regional earthquakes in 1995 and 2007, accelerated settling at punctuated moments in time. The spatially variable fracture pattern relates to surface slope and lithofacies variations as well as substrate lithology. Similar fractures have been reported in other ignimbrites but are generally exposed only in cross section and are often attributed to formation by external forces. Here we suggest that such interpretations should be invoked with caution, and deformation including post-emplacement subsidence and fracturing of loosely packed ash-rich deposits in the months to years postemplacement is a process inherent in the settling of pyroclastic material

    Metabolomic analyses of Leishmania reveal multiple species differences and large differences in amino acid metabolism

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    Comparative genomic analyses of Leishmania species have revealed relatively minor heterogeneity amongst recognised housekeeping genes and yet the species cause distinct infections and pathogenesis in their mammalian hosts. To gain greater information on the biochemical variation between species, and insights into possible metabolic mechanisms underpinning visceral and cutaneous leishmaniasis, we have undertaken in this study a comparative analysis of the metabolomes of promastigotes of L. donovani, L. major and L. mexicana. The analysis revealed 64 metabolites with confirmed identity differing 3-fold or more between the cell extracts of species, with 161 putatively identified metabolites differing similarly. Analysis of the media from cultures revealed an at least 3-fold difference in use or excretion of 43 metabolites of confirmed identity and 87 putatively identified metabolites that differed to a similar extent. Strikingly large differences were detected in their extent of amino acid use and metabolism, especially for tryptophan, aspartate, arginine and proline. Major pathways of tryptophan and arginine catabolism were shown to be to indole-3-lactate and arginic acid, respectively, which were excreted. The data presented provide clear evidence on the value of global metabolomic analyses in detecting species-specific metabolic features, thus application of this technology should be a major contributor to gaining greater understanding of how pathogens are adapted to infecting their hosts
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