207 research outputs found

    Genética de la conservación para la recuperación de especies animales en peligro de extinción: revisión de los planes de recuperación de especies en peligro de extinción de Estados Unidos (1977–1998)

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    The utility of genetic data in conservation efforts, particularly in comparison to demographic information, is the subject of ongoing debate. Using a database of information surveyed from 181 US endangered and threatened species recovery plans, we addressed the following questions concerning the use of genetic information in animal recovery plans: I. What is the relative prominence of genetic vs. demographic data in recovery plan development? and, II. When are genetic factors viewed as a threat, and how do plans respond to genetic threats? In general, genetics appear to play a minor and relatively ill–defined part in the recovery planning process; demographic data are both more abundant and more requested in recovery plans, and tasks are more frequently assigned to the collection / monitoring of demographic rather than genetic information. Nonetheless, genetic threats to species persistence and recovery are identified in a substantial minority (22 %) of recovery plans, although there is little uniform response to these perceived threats in the form of specific proposed recovery or management tasks. Results indicate that better guidelines are needed to identify how and when genetic information is most useful for species recovery; we highlight specific contexts in which genetics may provide unique management information, beyond that provided by other kinds of data.La utilidad de los datos genéticos en los esfuerzos conservacionistas, en particular en comparación con la información demográfica, es objeto de un continuo debate. Utilizando una base de datos con información sobre los 181 planes de recuperación de especies amenazadas y en peligro de extinción de Estados Unidos, hemos estudiado las siguientes cuestiones referentes al uso de la información genética en los planes de recuperación de especies animales: I ¿Cuál es la importancia relativa de los datos genéticos en comparación con los demográficos en el desarrollo de los planes de recuperación? y II ¿Cuándo se considera que los factores genéticos constituyen una amenaza, y cómo responden los planes a esas amenazas genéticas? En general, parece que la genética sólo desempeña un papel menor y relativamente mal definido en el proceso de planificación de la recuperación de especies; los datos demográficos son más abundantes y más solicitados para la elaboración de planes de recuperación, y las acciones que se llevan a cabo con frecuencia se enfocan más a las recopilación/observación de los datos demográficos que a la obtención de información genética. No obstante, las amenazas genéticas para la supervivencia y recuperación de especies se indican como un importante factor minoritario (22 %) en los planes de recuperación, si bien la respuesta a esas amenazas mediante medidas de gestión o recuperación específicas es poco uniforme. Los resultados apuntan a que se necesitan unas directrices más claras para determinar cómo y cuándo resulta más útil la información genética para la recuperación de especies; hemos resaltado contextos concretos en los que la genética puede proporcionar una valiosísima fuente de información para la gestión de esas cuestiones, superior a la que se pueda obtener a partir de otros datos

    Inference with interference between units in an fMRI experiment of motor inhibition

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    An experimental unit is an opportunity to randomly apply or withhold a treatment. There is interference between units if the application of the treatment to one unit may also affect other units. In cognitive neuroscience, a common form of experiment presents a sequence of stimuli or requests for cognitive activity at random to each experimental subject and measures biological aspects of brain activity that follow these requests. Each subject is then many experimental units, and interference between units within an experimental subject is likely, in part because the stimuli follow one another quickly and in part because human subjects learn or become experienced or primed or bored as the experiment proceeds. We use a recent fMRI experiment concerned with the inhibition of motor activity to illustrate and further develop recently proposed methodology for inference in the presence of interference. A simulation evaluates the power of competing procedures.Comment: Published by Journal of the American Statistical Association at http://www.tandfonline.com/doi/full/10.1080/01621459.2012.655954 . R package cin (Causal Inference for Neuroscience) implementing the proposed method is freely available on CRAN at https://CRAN.R-project.org/package=ci

    How complex do models need to be to predict dispersal of threatened species through matrix habitats?

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    Persistence of species in fragmented landscapes depends on dispersal among suitable breeding sites, and dispersal is often influenced by the "matrix" habitats that lie between breeding sites. However, measuring effects of different matrix habitats on movement and incorporating those differences into spatially explicit models to predict dispersal is costly in terms of time and financial resources. Hence a key question for conservation managers is: Do more costly, complex movement models yield more accurate dispersal predictions? We compared the abilities of a range of movement models, from simple to complex, to predict the dispersal of an endangered butterfly, the Saint Francis' satyr (Neonympha mitchellii francisci). The value of more complex models differed depending on how value was assessed. Although the most complex model, based on detailed movement behaviors, best predicted observed dispersal rates, it was only slightly better than the simplest model, which was based solely on distance between sites. Consequently, a parsimony approach using information criteria favors the simplest model we examined. However, when we applied the models to a larger landscape that included proposed habitat restoration sites, in which the composition of the matrix was different than the matrix surrounding extant breeding sites, the simplest model failed to identify a potentially important dispersal barrier, open habitat that butterflies rarely enter, which may completely isolate some of the proposed restoration sites from other breeding sites. Finally, we found that, although the gain in predicting dispersal with increasing model complexity was small, so was the increase in financial cost. Furthermore, a greater fit continued to accrue with greater financial cost, and more complex models made substantially different predictions than simple models when applied to a novel landscape in which butterflies are to be reintroduced to bolster their populations. This suggests that more complex models might be justifiable on financial grounds. Our results caution against a pure parsimony approach to deciding how complex movement models need to be to accurately predict dispersal through the matrix, especially if the models are to be applied to novel or modified landscapes

    A Halomethane thermochemical network from iPEPICO experiments and quantum chemical calculations

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    Internal energy selected halomethane cations CH3Cl+, CH2Cl2+, CHCl3+, CH3F+, CH2F2+, CHClF2+ and CBrClF2+ were prepared by vacuum ultraviolet photoionization, and their lowest energy dissociation channel studied using imaging photoelectron photoion coincidence spectroscopy (iPEPICO). This channel involves hydrogen atom loss for CH3F+, CH2F2+ and CH3Cl+, chlorine atom loss for CH2Cl2+, CHCl3+ and CHClF2+, and bromine atom loss for CBrClF2+. Accurate 0 K appearance energies, in conjunction with ab initio isodesmic and halogen exchange reaction energies, establish a thermochemical network, which is optimized to update and confirm the enthalpies of formation of the sample molecules and their dissociative photoionization products. The ground electronic states of CHCl3+, CHClF2+ and CBrClF2+ do not confirm to the deep well assumption, and the experimental breakdown curve deviates from the deep well model at low energies. Breakdown curve analysis of such shallow well systems supplies a satisfactorily succinct route to the adiabatic ionization energy of the parent molecule, particularly if the threshold photoelectron spectrum is not resolved and a purely computational route is unfeasible. The ionization energies have been found to be 11.47 ± 0.01 eV, 12.30 ± 0.02 eV and 11.23 ± 0.03 eV for CHCl3, CHClF2 and CBrClF2, respectively. The updated 0 K enthalpies of formation, ∆fHo0K(g) for the ions CH2F+, CHF2+, CHCl2+, CCl3+, CCl2F+ and CClF2+ have been derived to be 844.4 ± 2.1, 601.6 ± 2.7, 890.3 ± 2.2, 849.8 ± 3.2, 701.2 ± 3.3 and 552.2 ± 3.4 kJ mol–1, respectively. The ∆fHo0K(g) values for the neutrals CCl4, CBrClF2, CClF3, CCl2F2 and CCl3F and have been determined to be –94.0 ± 3.2, –446.6 ± 2.7, –702.1 ± 3.5, –487.8 ± 3.4 and –285.2 ± 3.2 kJ mol–1, respectively

    Rectal Transmission of Transmitted/Founder HIV-1 Is Efficiently Prevented by Topical 1% Tenofovir in BLT Humanized Mice

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    Rectal microbicides are being developed to prevent new HIV infections in both men and women. We focused our in vivo preclinical efficacy study on rectally-applied tenofovir. BLT humanized mice (n = 43) were rectally inoculated with either the primary isolate HIV-1(JRCSF) or the MSM-derived transmitted/founder (T/F) virus HIV-1(THRO) within 30 minutes following treatment with topical 1% tenofovir or vehicle. Under our experimental conditions, in the absence of drug treatment we observed 50% and 60% rectal transmission by HIV-1(JRCSF) and HIV-1(THRO), respectively. Topical tenofovir reduced rectal transmission to 8% (1/12; log rank p = 0.03) for HIV-1(JRCSF) and 0% (0/6; log rank p = 0.02) for HIV-1(THRO). This is the first demonstration that any human T/F HIV-1 rectally infects humanized mice and that transmission of the T/F virus can be efficiently blocked by rectally applied 1% tenofovir. These results obtained in BLT mice, along with recent ex vivo, Phase 1 trial and non-human primate reports, provide a critically important step forward in the development of tenofovir-based rectal microbicides

    Semiparametric theory and empirical processes in causal inference

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    In this paper we review important aspects of semiparametric theory and empirical processes that arise in causal inference problems. We begin with a brief introduction to the general problem of causal inference, and go on to discuss estimation and inference for causal effects under semiparametric models, which allow parts of the data-generating process to be unrestricted if they are not of particular interest (i.e., nuisance functions). These models are very useful in causal problems because the outcome process is often complex and difficult to model, and there may only be information available about the treatment process (at best). Semiparametric theory gives a framework for benchmarking efficiency and constructing estimators in such settings. In the second part of the paper we discuss empirical process theory, which provides powerful tools for understanding the asymptotic behavior of semiparametric estimators that depend on flexible nonparametric estimators of nuisance functions. These tools are crucial for incorporating machine learning and other modern methods into causal inference analyses. We conclude by examining related extensions and future directions for work in semiparametric causal inference

    State and local governments plan for development of most land vulnerable to rising sea level along the US Atlantic coast

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    Author Posting. © The Author(s), 2009. This is the author's version of the work. It is posted here by permission of IOP Publishing for personal use, not for redistribution. The definitive version was published in Environmental Research Letters 4 (2009): 044008, doi:10.1088/1748-9326/4/4/044008.Rising sea level threatens existing coastal wetlands. Overall ecosystems could often survive by migrating inland, if adjacent lands remained vacant. On the basis of 131 state and local land use plans, we estimate that almost 60% of the land below 1 m along the US Atlantic coast is expected to be developed and thus unavailable for the inland migration of wetlands. Less than 10% of the land below 1 m has been set aside for conservation. Environmental regulators routinely grant permits for shore protection structures (which block wetland migration) on the basis of a federal finding that these structures have no cumulative environmental impact. Our results suggest that shore protection does have a cumulative impact. If sea level rise is taken into account, wetland policies that previously seemed to comply with federal law probably violate the Clean Water Act

    Hepatitis C Virus (HCV) NS3 Sequence Diversity and Antiviral Resistance-Associated Variant Frequency in HCV/HIV Coinfection

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    ABSTRACT HIV coinfection accelerates disease progression in chronic hepatitis C and reduces sustained antiviral responses (SVR) to interferon-based therapy. New direct-acting antivirals (DAAs) promise higher SVR rates, but the selection of preexisting resistance-associated variants (RAVs) may lead to virologic breakthrough or relapse. Thus, pretreatment frequencies of RAVs are likely determinants of treatment outcome but typically are below levels at which the viral sequence can be accurately resolved. Moreover, it is not known how HIV coinfection influences RAV frequency. We adopted an accurate high-throughput sequencing strategy to compare nucleotide diversity in HCV NS3 protease-coding sequences in 20 monoinfected and 20 coinfected subjects with well-controlled HIV infection. Differences in mean pairwise nucleotide diversity (π), Tajima's D statistic, and Shannon entropy index suggested that the genetic diversity of HCV is reduced in coinfection. Among coinfected subjects, diversity correlated positively with increases in CD4 + T cells on antiretroviral therapy, suggesting T cell responses are important determinants of diversity. At a median sequencing depth of 0.084%, preexisting RAVs were readily identified. Q80K, which negatively impacts clinical responses to simeprevir, was encoded by more than 99% of viral RNAs in 17 of the 40 subjects. RAVs other than Q80K were identified in 39 of 40 subjects, mostly at frequencies near 0.1%. RAV frequency did not differ significantly between monoinfected and coinfected subjects. We conclude that HCV genetic diversity is reduced in patients with well-controlled HIV infection, likely reflecting impaired T cell immunity. However, RAV frequency is not increased and should not adversely influence the outcome of DAA therapy
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