2 resultados para Product Ecosystems
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:
When different markers are responsive to different aspects of a disease, combination of multiple markers could provide a better screening test for early detection. It is also resonable to assume that the risk of disease changes smoothly as the biomarker values change and the change in risk is monotone with respect to each biomarker. In this paper, we propose a boundary constrained tensor-product B-spline method to estimate the risk of disease by maximizing a penalized likelihood. To choose the optimal amount of smoothing, two scores are proposed which are extensions of the GCV score (O'Sullivan et al. (1986)) and the GACV score (Ziang and Wahba (1996)) to incorporate linear constraints. Simulation studies are carried out to investigate the performance of the proposed estimator and the selection scores. In addidtion, sensitivities and specificities based ona pproximate leave-one-out estimates are proposed to generate more realisitc ROC curves. Data from a pancreatic cancer study is used for illustration.