The objective of this study was to evaluate the environmental performance and environmental licensing of aquaculture in Ariquemes, Rondônia, western Amazon in Brazil. Twenty farmers were interviewed. For data collection, structured interviews were conducted using a questionnaire. Data were organized into three main topics: a) social and legal standards, b) environmental standards, c) food safety and hygiene standards. Data showed that aquaculture in Ariquemes presents two fish production systems: extensive and semi-intensive. Both are characterized by using fish species Tambaqui omnivorous (Colossoma macropomum), Tilapia omnivorous (Oreochromis spp.), and Pirarucu carnivorous (Arapaima gigas). The first 13 properties showed critical environmental performance (less than 30.0%). Six properties had very bad environmental performance (between 30.0 and 50.0%), and one presented appropriate environmental performance (between 50.0 and 70.0%). The environmental performance index showed that aquaculture in northern Rondônia is environmentally unsustainable.

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The sampling grid density for georeferenced soil collection must be large enough to allow the identification of the spatial dependence of attributes with representative accuracy of the cultivated area, but not large enough to make fertility mapping unfeasible. The objective of this study was to define, from the evaluation of geostatistical parameters obtained from a super dense soil sampling, an efficient grid for detecting the spatial dependence of potassium (K+), calcium (Ca2+), and magnesium (Mg2+) in a sandy soil. The experiment was conducted in a 3.2 hectare annatto crop (Bixa orellana L.), in 2017. The geostatistical grid consisted of 31 points per hectare, totaling 101 georeferenced points in an 18x18 m spacing. Soil was sampled at the depths of 0-0.20 m and 0.20-0.40 m. A strong spatial dependence was found for all soil attributes in both depths, while the semivariograms fitted to the spherical model with good coefficients of determination (R²) indicating a spatial correlation between the attributes. The range of spatial dependence was close to 100 m for all attributes in both layers. In sandy soils, an efficient sampling grid to detect the spatial dependence of K+, Ca2+ and Mg2+ must consider a semivariogram range of approximately 100 meters.