Growth of native trees in two agroforestry systems.

Agroforestry systems with eucalyptus prevail in Central and Southeast Brazil, and little information is available about systems using native trees. The aim of the present study was to evaluate the development of seven native tree species grown under two agroforestry systems. The experiment was conducted starting in 2007 in 12-hectare area in the municipality of São Carlos, São Paulo state, Brazil. The tree species planted in the two systems (a silvopastoral system and an agrisilvicultural system) were: 'capixingui' (Croton floribundus) and 'mutambo' (Guazuma ulmifolia) (tutors), 'jequitibá-branco' (Cariniana estrellensis), 'canafistula' (Peltophorum dubium) and 'ipê felpudo' (Zeyheria tuberculosa) (timber trees), and 'angico-branco' (Anadenanthera colubrina) and 'pau-jacaré' (Piptadenia gonoacantha) (N-fixing trees). Data were collected for 48 months. The results show differences among tree development, which was evaluated as growth in height and diameter, as well as sensitivity to insect and disease damage. The overall results show that the agrisilvicultural system allowed better tree development. The species with best performance in the two systems were capixingui, mutambo and canafístula. Ipê-felpudo and jequitibá-branco showed the worst results. The high variability among individuals of the same species indicates the possibility of high production advances with selective breeding of these species.

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.