2 resultados para ecological genomics
em Collection Of Biostatistics Research Archive
Resumo:
Despite a growing awareness that the herbaceous layer serves a special role in maintaining the structure and function of forests, this stratum remainsan underappreciated aspect of forest ecosystems. In this article I review and synthesize information concerning the herb layer’s structure,composition, and dynamics to emphasize its role as an integral component of forest ecosystems. Because species diversity is highest in the herb layeramong all forest strata, forest biodiversity is largely a function of the herb-layer community. Competitive interactions within the herb layer candetermine the initial success of plants occupying higher strata, including the regeneration of dominant overstory tree species. Furthermore, the herblayer and the overstory can become linked through parallel responses to similar environmental gradients. These relationships between strata varyboth spatially and temporally. Because the herb layer responds sensitively to disturbance across broad spatial and temporal scales, its dynamics canprovide important information regarding the site characteristics of forests, including patterns of past land-use practices. Thus, the herb layer has asignificance that belies its diminutive stature.
Resumo:
In the simultaneous estimation of a large number of related quantities, multilevel models provide a formal mechanism for efficiently making use of the ensemble of information for deriving individual estimates. In this article we investigate the ability of the likelihood to identify the relationship between signal and noise in multilevel linear mixed models. Specifically, we consider the ability of the likelihood to diagnose conjugacy or independence between the signals and noises. Our work was motivated by the analysis of data from high-throughput experiments in genomics. The proposed model leads to a more flexible family. However, we further demonstrate that adequately capitalizing on the benefits of a well fitting fully-specified likelihood in the terms of gene ranking is difficult.