Estradas e conectividade na Mata Atlântica: identificando áreas prioritárias para aplicação de medidas de mitigação

Abstract

Roads may represent an important factor in fragmentation of habitat for wild species adapted to habitats of high structural complexity as rainforests. Roads reduce landscape connectivity and the capacity of the regional population live in all suitable areas and these effects are most significant in species that avoid the road, which are often species dependent on forests. The magnitude of the barrier effects depend on the behavior and mobility of these species. When roads represent "sinkers" or barriers for populations due, respectively, trampling or avoidance, mitigation measures are indicated to increase connectivity between habitat patches separated by these roads. The habitat quality is a factor that must be considered, even at low frequencies of road kill there. The goal of this study was to propose two methods of selecting priority areas for implementation of mitigation measures of roads effects on forest vertebrate species: Multivariate Hierarchical Selection and Bivariate Selection. The study area was the Atlantic Forest biome, being cut into hexagonal landscapes at three different scales (10,000, 1,000 and 100 km²), using the extension "Repeating Shapes" program in ArcGIS 9.3. In each hexagon was calculated: area of forest, protected areas, density of roads and hydrograph. Only hexagons covered by at least 45% by the Atlantic Forest, with over 50% forest cover and more than 1% of protected areas were included in the analyzes. After this using the Multivariate Hierarchical selection method, we performed a principal component analysis (PCA) with the four variables measured for each scale separately. The hexagons were then ordered according to their position in the first axis of PCA, using a hierarchical manner and the smaller scale of hexagons. For the Bivariate selection method we did a dot plot for each scale hexagon, with the variables forest cover and rivers. We selected hexagons that were located in the quadrant of the graph that represented higher density of rivers and larger percentage of forest cover. After that, we made a simulation to evaluate if the two methods were able to retrieve scores as high as the ordination following only the positioning of the hexagons on Axis 1 of the PCA, without a hierarchical analysis. For the study site, the Multivariate Hierarchical selection was more efficient for choosing priority areas than Bivariate Selection for both the intermediate scale (1000 km²) and to a lesser extent (100 km²). The five hexagons of 100 km² of highest priorities are located in São Paulo and Paraná, covering four protected areas (PARES of Jacupiranga, Guaraqueçaba APA, and APA Cananéia-Jacuípe and PARES Ilha do Cardoso). Due to simplicity and easy applicability of the method, we believe this may be an interesting option for selecting priority areas for implementation of mitigation measures of the effects of roads