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1.
Glob Chang Biol ; 27(4): 793-803, 2021 Feb.
Article in English | MEDLINE | ID: mdl-33249693

ABSTRACT

Land-use change is a significant cause of anthropogenic extinctions, which are likely to continue and accelerate as habitat conversion proceeds in most biomes. One way to understand the effects of habitat loss on biodiversity is through improved tools for predicting the number and identity of species losses in response to habitat loss. There are relatively few methods for predicting extinctions and even fewer opportunities for rigorously assessing the quality of these predictions. In this paper, we address these issues by applying a new method based on rarefaction to predict species losses after random, but aggregated, habitat loss. We compare predictions from three rarefaction models, individual-based, sample-based, and spatially clustered, to those derived from a commonly used extinction estimation method, the species-area relationship (SAR). We apply each method to a mesocosm experiment, in which we aim to predict species richness and extinctions of arthropods immediately following 50% habitat loss. While each model produced strikingly accurate predictions of species richness immediately after the habitat loss disturbance, each model significantly underestimated the number of extinctions occurring at both the local (within-mesocosm) and regional (treatment-wide) scales. Despite the stochastic nature of our small-scale, short-term, and randomly applied habitat loss experiment, we found surprisingly clear evidence for extinction selectivity, for example, when abundant species with low extinction probabilities were extirpated following habitat loss. The important role played by selective extinction even in this contrived experimental system suggests that ecologically driven, trait-based extinctions play an equally important role to stochastic extinction, even when the disturbance itself has no clear selectivity. As a result, neutrally stochastic null models such as the SAR and rarefaction are likely to underestimate extinctions caused by habitat loss. Nevertheless, given the difficulty of predicting extinctions, null models provide useful benchmarks for conservation planning by providing minimum estimates and probabilities of species extinctions.


Subject(s)
Biodiversity , Ecosystem , Conservation of Natural Resources , Extinction, Biological , Probability , Research Design
2.
Article in Spanish | LILACS | ID: lil-327315

ABSTRACT

El metabolismo lipídico postprandial se ha asociado al desarrollo de aterogénesis, por lo que se considera un factor de riesgo independiente para enfermedad cardiovascular. El objetivo de este estudio, de tipo descriptivo transversal, es determinar lipemia postprandial en dos grupos de adolescentes, uno con hipertensión arterial y otro normotenso. Participando en el mismo 65 individuos de 12 a 18 años de ambos sexos (34 hipertensos y 31 normotensos). Se practican exámenes de laboratorio determinando el perfil lipídico en ayunas y posterior a una carga grasa (60 gr/m² SC) se determinan a las 2, 4 y 6 horas postprandiales niveles de triglicéridos y de HDL-c, además se realizan mediciones del índice de masa corporal y del índice cintura cadera. Encontrándose una prevalencia de obesidad en la población del 40 por ciento, con una distribución de la grasa de tipo central en un 23.08 por ciento. Las dislipidemias se encontraron en un 35.38 por ciento de la población, siendo la más frecuente la tipo IV (65.22 por ciento); tipo II a (17.39 por ciento) y tipo II b (17.39 por ciento). En relación a la lipemia postprandial se observa el pico de trigliceridemia a las 4 horas en ambos grupos, mostrando los hipertensos una media de 233 mg/dl y el grupo control de 160 mg/dl, con una diferencia estadísticamente significativa de P: 0,02 entre ambos grupos. La fracción HDL-c muestra su mayor disminución a las 4 horas en ambos grupos con una media en los hipertensos de 35.47 mg/dl y el grupo control de 34.77 mg/dl


Subject(s)
Humans , Male , Adolescent , Female , Adolescent , Hyperlipidemias , Hypertension , Lipids , Lipoprotein Lipase , Obesity , Venezuela
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