Soil attributes and grain yield of upland rice as affected by cover crops.

The aim of this study was to determine the effect of pearl millet intercropped with other cover crops on mineral forms of N and urease activity in soil, nitrate reductase activity in the leaves of the follow-up rice crop, as well as the yield components of this rice crop. The experiment was performed in the year 2012/2013 at two locations of the Brazilian Cerrado.

Rice affected by seed treatment, soil compaction and nitrogen at no-tillage and conventional tillage.

The objective of this study was to determine the best combination of management options for upland rice production: seed treatment, N management and soil compaction in zero and conventional tillage methods.

Rice grain yield as affected by grain-producing cover crops in Cabo Delgado, Mozambique.

The aim of this study was to evaluate the production of biomass and grain cover crops, yield components, and grain yield of rice in Mozambique. The study was conducted in two sites located in the province of Cabo Delgado, in Mozambique.

Transaction costs in an association of organic farmers in Goiania, Brazil.

This study aimed to analyse the transaction costs of an association of organic farmers located in Goiania, Goias state, Brazil. We analysed the marketing and organisation relations based on data collected at the Association for the Development of Organic Farming in Goias state (ADAO/GO).

Spatial scale effects of sampling on the interpolation of species distribution models in the southwestern Amazon.

Knowledge of the geographical distribution of timber tree species in the Amazon is still scarce. This is especially true at the local level, thereby limiting natural resource management actions. Forest inventories are key sources of information on the occurrence of such species. However, areas with approved forest management plans are mostly located near access roads and the main industrial centers. The present study aimed to assess the spatial scale effects of forest inventories used as sources of occurrence data in the interpolation of potential species distribution models. The occurrence data of a group of six forest tree species were divided into four geographical areas during the modeling process. Several sampling schemes were then tested applying the maximum entropy algorithm, using the following predictor variables: elevation, slope, exposure, normalized difference vegetation index (NDVI) and height above the nearest drainage (HAND). The results revealed that using occurrence data from only one geographical area with unique environmental characteristics increased both model overfitting to input data and omission error rates. The use of a diagonal systematic sampling scheme and lower threshold values led to improved model performance. Forest inventories may be used to predict areas with a high probability of species occurrence, provided they are located in forest management plan regions representative of the environmental range of the model projection area.