medians followed the order Zn > Fe > Mn > Cu > Cr > Cd in MMELC and Zn > Cu > Fe > Mn > Cr > Cd in Meirim River. It is concluded that the Crassostrea rhizophorae oysters from the studied environments presented concentrations of all the metals proposed in the research and demonstrates its accumulating and bioindicator character.

The mangrove forest is an important transitional ecosystem consisted of terrestrial and marine environment located in tropical and subtropical regions with average temperatures above 20 °C. In Alagoas, the mangrove forests are found on the entire coastline from Maragogi to Piaçabuçu. In the last 20 years, due to the pollution of water resources, studies of coastal aquatic ecosystems have been developed. The objective of this study was to analyze the physicochemical properties and determine the levels of heavy metals in mangrove sediments of the Mundaú-Manguaba estuary lagoon complex (MMELC) and Meirim River in Alagoas. Zinc, copper, lead, cadmium and chromium were chosen due to their relationship with sewer, agricultural, and industrial wastes. 22 soil samples were collected in the MMELC and in the Meirim River. The samples were submitted to soil routine analyses of Embrapa. The heavy metals were extracted by the Mehlich-1 method and analyzed by atomic absorption spectrometry. The mean concentrations of these metals in the sediment samples followed the order Mn > Zn >Pb > Cr> Cu >Cd in MMELC and Zn > Mn >Pb > Cr> Cu >Cd in Meirim River. All proposed heavy metals were found in sediments, however, the cadmium levels were above the normal levels proposed by Environment National Council (CONAMA) and Canadian Council of Ministers of the Environment. The study shows that the analysis of sediment can contribute to environmental monitoring actions and development of public policies aimed to controlling the sustainable use of natural resources of the studied areas.

O manguezal é um importante ecossistema de transição entre o ambiente marinho e terrestre, localizado em regiões tropicais e subtropicais com temperaturas médias acima de 20°C.Nos últimos 20 anos, a poluição dos recursos hídricos tem levado ao estudo dos ecossistemas costeiros, que são importantes para preservação e equilíbrio da vida. Dentre os contaminantes provenientes de descarga de efluentes industriais, urbanos e agrícolas, os metais pesados se destacam por não serem biodegradáveis. O objetivo deste trabalho foi avaliar as características físico-químicos e os níveis ambientalmente disponíveis dos metais pesados: Cobre, Zinco, Chumbo, Cádmio, Crômio, Ferro e Manganês no solo de mangue da foz do Estuário do Rio Meirim no estado de Alagoas. Foram coletadas 10 amostras de solo de mangue na foz rio Meirim. As amostras foram submetidas as análises

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<p>Environmental models often require soil maps to represent the spatial variability of soil attributes. However, mapping soils using conventional in-situ survey protocols is time-consuming and costly. As an alternative, digital soil mapping offers a fast-mapping approach that might be used to monitor soil attributes and their interrelationships over large areas. In Brazil, conventional survey methods are still widely used, and thus maps still in development are considered as the state-of-the-art products for decades. In this study, we address this lack of updated spatial information on many soil attributes by producing regional statistical soil models using an innovative framework. This new framework attempts to reduce prediction redundancies due to high multicollinearity, by implementing a Feature Selector algorithm. This is expected to improve a model’s strength by decreasing its unexplained variance. The framework’s core is composed of the Soil-Landscape Estimation and Evaluation Program (SLEEP) and a calibrated Gradient Boosting Model capable of modelling the spatial distribution of soil attributes at multiple soil depths. These models allowed us to explain the spatial distribution of some basic soil attributes (physical and chemical), and its environmental drivers. The model training and testing approach used 30 environmental attributes, and data from 223 soil profiles for the state of Pernambuco, Brazil. Our models demonstrated a consistent potential to perform spatial extrapolations with r<sup>2</sup> ranging from 0.8 to 0.97, and PBIAS from -0.51 to 2.03. The properties related to topographic and climatic conditions were dominating when estimating the number of horizons, percentage of silt and the sum of bases (a measure of soil fertility). We believe that our framework features high flexibility, while reducing capital investments when compared to <em>in situ</em> surveys and traditional mapping protocols. These findings also have implications for the improvement and testing of pedotransfer functions. We thank FACEPE for funding this through APQ 0646-9.25/16.</p>