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Red lists are a crucial tool for the management of threatened species and ecosystems. Among the information red lists provide, the threats affecting the listed species or ecosystem, such as pollution or hunting, are of special relevance. This information can be used to quantify the relative contribution of different threat factors to biodiversity loss by disaggregating the cumulative extinction risk across species into components that can be attributed to certain threats. We devised and compared 3 metrics that accomplish this and may be used as indicators. The first metric calculates the portion of the temporal change in red list index (RLI) values that is caused by each threat. The second metric attributes the deviation of an RLI value from its reference value to different threats. The third metric uses extinction probabilities that are inferred from red list categories to estimate the contribution of a threat to the expected loss of species or ecosystems within 50 years. We used data from Norwegian Red Lists to test and evaluate these metrics. The first metric captured only a minor portion of the biodiversity loss caused by threats because it ignores species whose red list category does not change. Management authorities will often be interested in the contribution of a given threat to the total deviation from the optimal state. This was measured by the remaining metrics. The second metric was best suited for comparisons across countries or taxonomic groups. The third metric conveyed the same information but uses numbers of species or ecosystem as its unit, which is likely more intuitive to lay people and may be preferred when communicating with stakeholders or the general public.

Medidas para cuantificar la contribución de las diferentes amenazas a las listas rojas de especies y ecosistemas Resumen Las listas rojas son una herramienta crucial para la gestión de los ecosistemas y las especies bajo amenaza. Entre la información que proporcionan estas listas, son de mucha relevancia las amenazas que afectan a los ecosistemas o especies en la lista, como la contaminación o la cacería. Esta información puede usarse para cuantificar la contribución relativa que tienen los diferentes factores de amenaza para la pérdida de la biodiversidad mediante la disgregación del riesgo de extinción acumulado de varias especies en componentes que pueden atribuirse a ciertas amenazas. Diseñamos y comparamos tres medidas que logran esto y que pueden usarse como indicadores. La primera medida calcula la porción del cambio temporal en los valores del índice de listas rojas (ILR) causado por cada amenaza. La segunda medida les atribuye a las diferentes amenazas la desviación de un valor del ILR de su valor de referencia. La tercera medida usa probabilidades de extinción inferidas a partir de las categorías de las listas rojas para estimar la contribución de una amenaza a la pérdida esperada de especies o ecosistemas dentro de 50 años. Usamos datos de las Listas Rojas de Noruega para probar y evaluar estas medidas. La primera medida sólo capturó una porción menor de la pérdida de la biodiversidad causada por amenazas porque ignora las especies cuya categorías no cambia. Las autoridades gestoras se interesan con frecuencia en la contribución de una amenaza a la desviación total del estado óptimo. Medimos lo anterior con las medidas restantes. La segunda medida fue la mejor para comparar entre países y grupo taxonómicos. La tercera medida comunicó la misma información, pero con los números de especies o ecosistemas como su unidad, lo cual probablemente sea más intuitivo en términos sencillos y pueda preferirse para comunicarse con los actores o el público en general.

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BACKGROUND: Respiratory viruses often have been studied in children with respiratory tract infection (RTI), but less knowledge exists about viruses in asymptomatic children. We have studied the occurrence of a broad panel of respiratory viruses in apparently healthy children attending day care, taking into account the influence of possible confounding factors, such as age, clinical signs of respiratory tract infection (RTI), location (day-care section) and season. METHODS: We have studied 161 children in two day-care centers, each with separate sections for younger and older children, during four autumn and winter visits over a two-year period. A total of 355 clinical examinations were performed, and 343 nasopharyngeal samples (NPS) were analyzed by semi-quantitative, real-time, polymerase chain reaction (PCR) tests for 19 respiratory pathogens. RESULT: Forty-three percent of all NPS were PCR-positive for ≥ 1 of 13 virus species, with high species variation during visits. Rhinovirus 26% (88/343 NPS), enterovirus 12% (40/343) and parechovirus 9% (30/343) were detected in every visit, and the rates varied in relation to age, day-care section and season. Ten other viruses were detected in ≤ 3% of the NPS. Generally, viruses occurred together in the NPS. In 24% (79/331) of the clinical examinations with available NPS, the children had clear signs of RTI, while in 41% (135/331) they had mild signs, and in 35% (117/331) the children had no signs of RTI. Moreover, viruses were found in 70% (55/79) of children with clear signs of RTI, in 41% (55/135) with mild signs and in 30% (35/117) without any signs of RTI (p < 0.001). CONCLUSIONS: Positive PCR tests for respiratory viruses, particularly picornaviruses, were frequently detected in apparently healthy children attending day care. Virus detection rates were related to age, presence of clinical signs of RTI, location in day care and season.

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Epigenetic differentiation is the potentially heritable changes in levels of gene expression not caused by DNA sequence changes. Here, a classification scheme of mutations and epimutations is introduced, enabling a simple analysis of mutation and epimutation load in haploid and diploid organisms. It is found that the deleterious effect of epimutations is mainly determined by epimutation rate and degree of reversibility. Inherited epimutations have the same fitness consequences as inherited mutations. With complete reversibility and no inheritance, then epimutations have the same fitness consequences as somatic mutations. It is argued that organisms with somatic inheritance may experience more genetic load than organisms without somatic inheritance due to inherited epimutations in the former. This may partly explain the maintenance of soma/germ differentiation in many life forms. It is also argued that masking of deleterious somatic mutations may not necessarily explain the evolution of diploidy in life forms with inherited epimutations.

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