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      Persistent anthrax as a major driver of wildlife mortality in a tropical rainforest

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          Abstract

          Anthrax is a globally important animal disease and zoonosis. Despite this, our current knowledge of anthrax ecology is largely limited to arid ecosystems, where outbreaks are most commonly reported. Here we show that the dynamics of an anthrax-causing agent, Bacillus cereus biovar anthracis, in a tropical rainforest have severe consequences for local wildlife communities. Using data and samples collected over three decades, we show that rainforest anthrax is a persistent and widespread cause of death for a broad range of mammalian hosts. We predict that this pathogen will accelerate the decline and possibly result in the extirpation of local chimpanzee (Pan troglodytes verus) populations. We present the epidemiology of a cryptic pathogen and show that its presence has important implications for conservation.

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          Conclusions beyond support: overconfident estimates in mixed models

          Mixed-effect models are frequently used to control for the nonindependence of data points, for example, when repeated measures from the same individuals are available. The aim of these models is often to estimate fixed effects and to test their significance. This is usually done by including random intercepts, that is, intercepts that are allowed to vary between individuals. The widespread belief is that this controls for all types of pseudoreplication within individuals. Here we show that this is not the case, if the aim is to estimate effects that vary within individuals and individuals differ in their response to these effects. In these cases, random intercept models give overconfident estimates leading to conclusions that are not supported by the data. By allowing individuals to differ in the slopes of their responses, it is possible to account for the nonindependence of data points that pseudoreplicate slope information. Such random slope models give appropriate standard errors and are easily implemented in standard statistical software. Because random slope models are not always used where they are essential, we suspect that many published findings have too narrow confidence intervals and a substantially inflated type I error rate. Besides reducing type I errors, random slope models have the potential to reduce residual variance by accounting for between-individual variation in slopes, which makes it easier to detect treatment effects that are applied between individuals, hence reducing type II errors as well.
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            Pandemic human viruses cause decline of endangered great apes.

            Commercial hunting and habitat loss are major drivers of the rapid decline of great apes [1]. Ecotourism and research have been widely promoted as a means of providing alternative value for apes and their habitats [2]. However, close contact between humans and habituated apes during ape tourism and research has raised concerns that disease transmission risks might outweigh benefits [3-7]. To date only bacterial and parasitic infections of typically low virulence have been shown to move from humans to wild apes [8, 9]. Here, we present the first direct evidence of virus transmission from humans to wild apes. Tissue samples from habituated chimpanzees that died during three respiratory-disease outbreaks at our research site, Côte d'Ivoire, contained two common human paramyxoviruses. Viral strains sampled from chimpanzees were closely related to strains circulating in contemporaneous, worldwide human epidemics. Twenty-four years of mortality data from observed chimpanzees reveal that such respiratory outbreaks could have a long history. In contrast, survey data show that research presence has had a strong positive effect in suppressing poaching around the research site. These observations illustrate the challenge of maximizing the benefit of research and tourism to great apes while minimizing the negative side effects.
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              Ancient DNA extraction from bones and teeth.

              This method is designed to maximize recovery of PCR-amplifiable DNA from ancient bone and teeth specimens and at the same time to minimize co-extraction of substances that inhibit PCR. This is achieved by a combination of DNA extraction from bone powder using a buffer consisting solely of EDTA and proteinase K, and purification of the DNA by binding to silica in the presence of high concentrations of guanidinium thiocyanate. All steps are performed at room temperature (20-23 degrees C), thereby reducing further degradation of the already damaged and fragile ancient DNA and providing an optimal trade-off between DNA release and degradation. Furthermore, the purification step removes most of the various types of PCR inhibitors present in ancient bone samples, thereby optimizing the amount of ancient DNA available for subsequent enzymatic manipulation, such as PCR amplification. The protocol presented here allows DNA extraction from ancient bone and teeth with a minimum of working steps and equipment and yields DNA extracts within 2 working days.
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                Author and article information

                Journal
                Nature
                Nature
                Springer Nature
                0028-0836
                1476-4687
                August 2 2017
                August 2 2017
                : 548
                : 7665
                : 82-86
                Article
                10.1038/nature23309
                28770842
                51216279-1b30-4b11-aae3-873fc0bff73b
                © 2017
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