Mangrove ecosystem dynamics and diverse human activities have led to a need for studies that give us a better understanding of the peculiarities of their soils. The objective of this study was to evaluate the physical and chemical soil attributes of mangrove forests located in the São Francisco River estuary, related to local ecological conditions. Two stations, divided into three forest types (fringe, basin and transition) were selected and five composite soil samples were collected from each forest type. Soil samples were submitted for chemical and physical analysis. The soil presented a sandy texture, with high organic matter and element content in the following order: Mg 2+ >Na + >Ca 2+ >H + >K + >P>Al 3+ and Fe 2+ >Zn 2+ >Cu 2+ >Mn 2+ , respectively, with variations between the forests and stations. In general, the mangrove forests presented high fertility, especially in the basin forest, provided by vegetation development, showing a zoning trend for species in relation to soil fertility.

Santos et al.: Models for estimating the biomass of mangroves 44Allometric models for estimating the aboveground biomass of the mangrove Rhizophora mangleThe development of species-specific allometric models is critical to the improvement of aboveground biomass estimates, as well as to the estimation of carbon stock and sequestration in mangrove forests. This study developed allometric equations for estimating aboveground biomass of Rhizophora mangle in the mangroves of the estuary of the São Francisco River, in northeastern Brazil. Using a sample of 74 trees, simple linear regression analysis was used to test the dependence of biomass (total and per plant part) on size, considering both transformed (ln) and not-transformed data. Best equations were considered as those with the lowest standard error of estimation (SEE) and highest adjusted coefficient of determination (R values, probably attributed to the seasonal nature of this compartment. "Basal Area² × Height" showed to be the best predictor, present in most of the bestfitted equations. The models presented here can be considered reliable predictors of the aboveground biomass of R. mangle in the NE-Brazilian mangroves as well as in any site were this widely distributed species present similar architecture to the trees used in the present study. , o que pode ser atribuído ao caráter sazonal deste compartimento. "Área basal²×Altura" demonstrou ser o melhor preditor, presente na maioria das equações melhor ajustadas. Os modelos aqui apresentados podem ser considerados preditores confiáveis da biomassa aérea de R. mangle no manguezal do Nordeste brasileiro, bem como em qualquer local onde esta espécie de ampla distribuição assemelhe-se à arquitetura das árvores utilizadas no presente estudo. AbstrAct resumoDescritores: Equações alométricas, Biomassa aérea, Manguezal, Análises de regressão, Rhizophora mangle.