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2 resultados encontrados para: AUTOR: Ryan, Casey M
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Resumen en: Inglés |
Resumen en inglés

Since its founding, the Monterey Bay Aquarium Research Institute (MBARI) has pioneered unique capabilities for accessing the deep ocean and its inhabitants through focused peer relationships between scientists and engineers. This focus has enabled breakthroughs in our understanding of life in the sea, leading to fundamental advances in describing the biology and the ecology of open-ocean and deep-sea animals. David Packard’s founding principle was the application of technological advances to studying the deep ocean, in part because he recognized the critical importance of this habitat in a global context. Among other fields, MBARI’s science has benefited from applying novel methodologies in molecular biology and genetics, imaging systems, and in situ observations. These technologies have allowed MBARI’s bioluminescence and biodiversity laboratory and worldwide collaborators to address centuries-old questions related to the biodiversity, behavior, and bio-optical properties of organisms living in the water column, from the surface into the deep sea. Many of the most interesting of these phenomena are in the midwater domain—the vast region of ocean between the sunlit surface waters and the deep seafloor.


Resumen en: Inglés |
Resumen en inglés

We combined two existing datasets of vegetation aboveground biomass (AGB) (Proceedings of the National Academy of Sciences of the United States of America, 108, 2011, 9899; Nature Climate Change, 2, 2012, 182) into a pan-tropical AGB map at 1- km resolution using an independent reference dataset of field observations and locally calibrated high-resolution biomass maps, harmonized and upscaled to 14 477 1-km AGB estimates. Our data fusion approach uses bias removal and weighted linear averaging that incorporates and spatializes the biomass patterns indicated by the reference data. The method was applied independently in areas (strata) with homogeneous error patterns of the input (Saatchi and Baccini) maps, which were estimated from the reference data and additional covariates. Based on the fused map, we estimated AGB stock for the tropics (23.4 N–23.4 S) of 375 Pg dry mass, 9–18% lower than the Saatchi and Baccini estimates. The fused map also showed differing spatial patterns of AGB over large areas, with higher AGB density in the dense forest areas in the Congo basin, Eastern Amazon and South-East Asia, and lower values in Central America and in most dry vegetation areas of Africa than either of the input maps. The validation exercise, based on 2118 estimates from the reference dataset not used in the fusion process, showed that the fused map had a RMSE 15–21% lower than that of the input maps and, most importantly, nearly unbiased estimates (mean bias 5 Mg dry mass ha 1 vs. 21 and 28 Mg ha 1 for the input maps). The fusion method can be applied at any scale including the policy-relevant national level, where it can provide improved biomass estimates by integrating existing regional biomass maps as input maps and additional, country-specific reference datasets.