Riparian forest corridors: A prioritization analysis to the Landscape Sample Units of the Brazilian National Forest Inventory (2018)
In addition to sampling biophysical data in field plots, the Brazilian National Forest Inventory (NFI-BR) has a component dedicated to the study of Brazilian rural landscapes. The Landscape Sample Units (LSUs) are square areas of 100 km2, established in a regular grid of 40 × 40 km over the entire national territory, where habitat quality and spatial structure are characterized and evaluated. The LSUs’ evaluation scheme measures the fragmentation and connectivity of remnant forest patches as well as the spatial configuration of riparian zones. As part of these analyses we propose the use of integrated indices based on the structural connectivity of the riparian environments as forest corridors, the degree of human pressure acting on them and the protection schemes defined by the new Brazilian forest legislation. These indices are then turned into scores to make a ranking allowing for the identification of riparian priority areas for conservation and landscape restoration. Basic processing steps included the application of Morphological Spatial Pattern Analysis (MSPA) to the LULC map of a pilot sample from the LSU dataset in the State of Paraná in southern Brazil. The following indices have been calculated for 20 LSUs: Structural Corridors Index (SCc), which reveals the proportion of core and bridge MSPA categories within the riparian zone, the Structural Corridors under Pressure Index (CPc), that allows the identification of areas where structural corridors coexist with areas subject to anthropogenic influences and, finally, the Structural Corridors under Pressure Protection Index (UCPc), which identifies areas that function as corridors, being under anthropogenic pressure as well but with little or no legal protection, thus corresponding to priority areas for conservation. Among the 20 pilot LSUs studied, three of them are representative of a critical situation regarding conservation issues as they presented high values for indices CPc and UCPc, which denote areas with high anthropogenic influences and no environmental protection schemes. An important aspect of the proposed methodology is the possibility to identify and prioritize areas at different spatial scales, further aggregating the indices for LSU or larger political regions, such as micro and mesoregions of federal states. © 2018 Elsevier Ltd