1,938 research outputs found

    Integration of temporal environmental variation by the marine plankton community

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    Theory and observations suggest that low frequency variation in marine plankton populations, or red noise, may arise through cumulative integration of white noise atmospheric forcing by the ocean and its amplification within food webs. Here, we revisit evidence for the integration of stochastic atmospheric variations by comparing the power spectra of time series of atmospheric and oceanographic conditions to the population dynamics of 150 plankton taxa at Station L4 in the Western English Channel. The power spectra of oceanographic conditions (sea surface temperature, surface nitrate) are redder than those of atmospheric forcing (surface wind stress, net heat fluxes) at Station L4. However, plankton populations have power spectral slopes across trophic levels and body sizes that are redder than atmospheric forcing but whiter than oceanographic conditions. While zooplankton have redder spectral slopes than phytoplankton, there is no significant relationship between power spectral slope and body size or generation length. Using a predator−prey model, we show that the whitening of plankton time series relative to oceanographic conditions arises from noisy plankton bloom dynamics in this strongly seasonal system. The model indicates that, for typical predator−prey interactions, where the predator is on average 10 times longer than the prey, grazing leads to a modest reddening of phytoplankton variability by their larger and longer lived zooplankton consumers. Our findings suggest that, beyond extrinsic forcing by the environment, predator–prey interactions play a role in influencing the power spectra of time series of plankton populations

    A new species of cosmocercoides (Nematoda; cosmocercidae) and other helminths in leptodactylus latrans (anura; leptodactylidae) from Argentina

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    Cosmocercoides latrans n. sp. (Cosmocercidae) from the small intestine of Leptodactylus latrans (Anura: Leptodactylidae) from Northeastern Province of Buenos Aires, Argentina is described. The new species can be distinguished from their congeners by a combination of the characters, among which stands out the number of rosette papillae, the lack of gubernaculum and the presence of lateral alae in both sexes. There are over 20 species in the genus Cosmocercoides, and Cosmocercoides latrans n. sp. represents the third species from the Neotropical realm and the second for Argentina. Additionally, seven previously known taxa are reported; Pseudoacanthocephalus cf. lutzi, Catadiscus uruguayensis, Rauschiella palmipedis, Aplectana hylambatis, Cosmocerca parva, Schrankiana sp. and Rhabdias elegans; providing literature records and information on distribution and host-parasite relationships.Fil: Draghi, Regina. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. DivisiĂłn ZoologĂ­a Invertebrados; Argentina. Consejo Nacional de Investigaciones CientĂ­ficas y TĂŠcnicas. Centro CientĂ­fico TecnolĂłgico Conicet - La Plata; ArgentinaFil: Drago, Fabiana Beatriz. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. DivisiĂłn ZoologĂ­a Invertebrados; Argentina. Provincia de Buenos Aires. GobernaciĂłn. ComisiĂłn de Investigaciones CientĂ­ficas; ArgentinaFil: Lunaschi, LĂ­a InĂŠs. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. DivisiĂłn ZoologĂ­a Invertebrados; Argentin

    Effect of Biodiversity Changes in Disease Risk: Exploring Disease Emergence in a Plant-Virus System

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    The effect of biodiversity on the ability of parasites to infect their host and cause disease (i.e. disease risk) is a major question in pathology, which is central to understand the emergence of infectious diseases, and to develop strategies for their management. Two hypotheses, which can be considered as extremes of a continuum, relate biodiversity to disease risk: One states that biodiversity is positively correlated with disease risk (Amplification Effect), and the second predicts a negative correlation between biodiversity and disease risk (Dilution Effect). Which of them applies better to different host-parasite systems is still a source of debate, due to limited experimental or empirical data. This is especially the case for viral diseases of plants. To address this subject, we have monitored for three years the prevalence of several viruses, and virus-associated symptoms, in populations of wild pepper (chiltepin) under different levels of human management. For each population, we also measured the habitat species diversity, host plant genetic diversity and host plant density. Results indicate that disease and infection risk increased with the level of human management, which was associated with decreased species diversity and host genetic diversity, and with increased host plant density. Importantly, species diversity of the habitat was the primary predictor of disease risk for wild chiltepin populations. This changed in managed populations where host genetic diversity was the primary predictor. Host density was generally a poorer predictor of disease and infection risk. These results support the dilution effect hypothesis, and underline the relevance of different ecological factors in determining disease/infection risk in host plant populations under different levels of anthropic influence. These results are relevant for managing plant diseases and for establishing conservation policies for endangered plant species

    Predicting spatial distribution patterns and hotspots of fish assemblage in a coastal basin of the central-south of Chile, by geostatistical techniques

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    Currently the application of geographic information systems in the subjects of biology and ecology has facilitated the study patterns of distribution, richness y diversity of species. However, in freshwater ecosystems the application of geostatistical analysis are scarcely used in the worldwide, including Chile. Therefore, in our study we developed predictive maps using simple Kriging (resolution 12.5 x 12.5 m), based on richness and Shannon-Weaver diversity, and we analyzed spatial autocorrelation of fish assemblages (Moran and Getis-Ord index) present in the AndaliĂŠn River basin. Our results established a fish assemblage composition of 24 species, most of them native (79%) and with endanger conservation status. Predictive maps showed highest values of richness and diversity of fish species in the potamon zone of the AndaliĂŠn and NonguĂŠn streams, while the low values were described in the Chaimavida sub-basin and the transition zone of AndaliĂŠn River. The Moran and Getis-Ord index determined a cluster pattern of the data and define hotspot and coldspot zones, concordant with the predictive maps of richness and Shannon-Weaver diversity. The geostatistical and spatial techniques showed to be relevant tools for the determination of distribution patterns of freshwater species and conservation issues

    Changes in timber haul emissions in the context of shifting forest management and infrastructure

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    <p>Abstract</p> <p>Background</p> <p>Although significant amounts of carbon may be stored in harvested wood products, the extraction of that carbon from the forest generally entails combustion of fossil fuels. The transport of timber from the forest to primary milling facilities may in particular create emissions that reduce the net sequestration value of product carbon storage. However, attempts to quantify the effects of transport on the net effects of forest management typically use relatively sparse survey data to determine transportation emission factors. We developed an approach for systematically determining transport emissions using: 1) -remotely sensed maps to estimate the spatial distribution of harvests, and 2) - industry data to determine landscape-level harvest volumes as well as the location and processing totals of individual mills. These data support spatial network analysis that can produce estimates of fossil carbon released in timber transport.</p> <p>Results</p> <p>Transport-related emissions, evaluated as a fraction of transported wood carbon at 4 points in time on a landscape in western Montana (USA), rose from 0.5% in 1988 to 1.7% in 2004 as local mills closed and spatial patterns of harvest shifted due to decreased logging on federal lands.</p> <p>Conclusion</p> <p>The apparent sensitivity of transport emissions to harvest and infrastructure patterns suggests that timber haul is a dynamic component of forest carbon management that bears further study both across regions and over time. The monitoring approach used here, which draws only from widely available monitoring data, could readily be adapted to provide current and historical estimates of transport emissions in a consistent way across large areas.</p

    An entropy test for single-locus genetic association analysis

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    <p>Abstract</p> <p>Background</p> <p>The etiology of complex diseases is due to the combination of genetic and environmental factors, usually many of them, and each with a small effect. The identification of these small-effect contributing factors is still a demanding task. Clearly, there is a need for more powerful tests of genetic association, and especially for the identification of rare effects</p> <p>Results</p> <p>We introduce a new genetic association test based on symbolic dynamics and symbolic entropy. Using a freely available software, we have applied this entropy test, and a conventional test, to simulated and real datasets, to illustrate the method and estimate type I error and power. We have also compared this new entropy test to the Fisher exact test for assessment of association with low-frequency SNPs. The entropy test is generally more powerful than the conventional test, and can be significantly more powerful when the genotypic test is applied to low allele-frequency markers. We have also shown that both the Fisher and Entropy methods are optimal to test for association with low-frequency SNPs (MAF around 1-5%), and both are conservative for very rare SNPs (MAF<1%)</p> <p>Conclusions</p> <p>We have developed a new, simple, consistent and powerful test to detect genetic association of biallelic/SNP markers in case-control data, by using symbolic dynamics and symbolic entropy as a measure of gene dependence. We also provide a standard asymptotic distribution of this test statistic. Given that the test is based on entropy measures, it avoids smoothed nonparametric estimation. The entropy test is generally as good or even more powerful than the conventional and Fisher tests. Furthermore, the entropy test is more computationally efficient than the Fisher's Exact test, especially for large number of markers. Therefore, this entropy-based test has the advantage of being optimal for most SNPs, regardless of their allele frequency (Minor Allele Frequency (MAF) between 1-50%). This property is quite beneficial, since many researchers tend to discard low allele-frequency SNPs from their analysis. Now they can apply the same statistical test of association to all SNPs in a single analysis., which can be especially helpful to detect rare effects.</p

    Classical kinetic energy, quantum fluctuation terms and kinetic-energy functionals

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    We employ a recently formulated dequantization procedure to obtain an exact expression for the kinetic energy which is applicable to all kinetic-energy functionals. We express the kinetic energy of an N-electron system as the sum of an N-electron classical kinetic energy and an N-electron purely quantum kinetic energy arising from the quantum fluctuations that turn the classical momentum into the quantum momentum. This leads to an interesting analogy with Nelson's stochastic approach to quantum mechanics, which we use to conceptually clarify the physical nature of part of the kinetic-energy functional in terms of statistical fluctuations and in direct correspondence with Fisher Information Theory. We show that the N-electron purely quantum kinetic energy can be written as the sum of the (one-electron) Weizsacker term and an (N-1)-electron kinetic correlation term. We further show that the Weizsacker term results from local fluctuations while the kinetic correlation term results from the nonlocal fluctuations. For one-electron orbitals (where kinetic correlation is neglected) we obtain an exact (albeit impractical) expression for the noninteracting kinetic energy as the sum of the classical kinetic energy and the Weizsacker term. The classical kinetic energy is seen to be explicitly dependent on the electron phase and this has implications for the development of accurate orbital-free kinetic-energy functionals. Also, there is a direct connection between the classical kinetic energy and the angular momentum and, across a row of the periodic table, the classical kinetic energy component of the noninteracting kinetic energy generally increases as Z increases.Comment: 10 pages, 1 figure. To appear in Theor Chem Ac
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