Bridging natural and social sciences: a framework for identify strategies and actions for the conservation of biodiversity.

The Atlantic Forest is one of the most diverse areas in the world and considered a hotspot. Several actions are needed for its preservation, among them the implementation of the Biodiversity Corridors. The Atlantic Forest has three biodiversity corridors and the Rio de Janeiro State, which harbors huge species diversity, is in the Serra do Mar Corridor. We developed socioeconomic, political and environmental indicators to present conservation strategies supported by a wide database. These indicators complemented the previous surveys of priority areas which emphasized biotic elements, and their integration allowed the elaboration of strategies for the conservation and management, regionally directed, to support actions to be implemented by the Government. The analysis was done considering three subjects: Anthropic Pressure, Physical and Biotic State, and Present Ability of Response. Data analysis followed a synthesis-aggregation schedule and the resulting database was taken to a workshop, where specialists proposed strategies and actions for the conservation. These strategies were discussed considering vegetation remnant distribution, biological relevance, environmental vulnerability, kind of anthropic pressure in the region and potential for success of the actions proposed, based on the ability of response. Rio de Janeiro State is very diverse in biotic, physical, political, socioeconomic and cultural aspects which demand specific actions for each region. So, depending on the present situation of the natural and anthropic environments and on the present and future sources of degradation, regionally directed actions are applicable. This specificity in conservation actions will enable that the State remnants will be more successfully protected.

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.