An evaluation of contemporary savanna fire regimes in the Canastra National Park, Brazil: Outcomes of fire suppression policies.

Fire has shaped plant evolution and biogeochemical cycles for millions of years in savanna ecosystems, but changes in natural fire regimes promoted by human land use threaten contemporary conservation efforts. In protected areas in the Brazilian savannas (Cerrado), the predominant management policy is fire suppression, reflecting a cultural heritage which considers that fire always has a negative impact on biodiversity. Here we compare resultant fire-regimes in Canastra National Park (CNP), southeast Brazil, associated with areas under and without fire suppression management, based on a 16-year Landsat imagery record. In open grasslands of the Canastra plateau (CP), firefighting is undertaken under government-sanctioned regulation, whereas in the Babilonia sector, non-sanctioned fire management is undertaken by small farmers to promote cattle grazing and cropping. Fire regimes in the Canastra sector are characterized by few, very large, late dry season wildfires recurring at intervals of two years. Fire regimes in lowlands of the Babilonia sector are characterized by many small-scale, starting at the beginning of the dry season (EDS). In Babilonia uplands fire regimes are characterized by higher frequencies of large fires. The study illustrates major challenges for managing fire-prone areas in conflict-of-interest regions. We suggest that management planning in CNP needs to effectively address: i) managing conflicts between CNP managers and local communities; and ii) fire management practices in order to achieve more ecologically sustainable fire regimes. The study has broader implications for conservation management in fire-prone savannas in South America generally.

Predictive Models of Primary Tropical Forest Structure from Geomorphometric Variables Based on SRTM in the Tapajós Region, Brazilian Amazon.

Surveying primary tropical forest over large regions is challenging. Indirect methods of relating terrain information or other external spatial datasets to forest biophysical parameters can provide forest structural maps at large scales but the inherent uncertainties need to be evaluated fully. The goal of the present study was to evaluate relief characteristics, measured through geomorphometric variables, as predictors of forest structural characteristics such as average tree basal area (BA) and height (H) and average percentage canopy openness (CO). Our hypothesis is that geomorphometric variables are good predictors of the structure of primary tropical forest, even in areas, with low altitude variation. The study was performed at the Tapajós National Forest, located in the Western State of Pará, Brazil. Forty-three plots were sampled. Predictive models for BA, H and CO were parameterized based on geomorphometric variables using multiple linear regression. Validation of the models with nine independent sample plots revealed a Root Mean Square Error (RMSE) of 3.73 m2/ha (20%) for BA, 1.70 m (12%) for H, and 1.78% (21%) for CO. The coefficient of determination between observed and predicted values were r2 = 0.32 for CO, r2 = 0.26 for H and r2 = 0.52 for BA. The models obtained were able to adequately estimate BA and CO. In summary, it can be concluded that relief variables are good predictors of vegetation structure and enable the creation of forest structure maps in primary tropical rainforest with an acceptable uncertainty.