title: Using Species Distribution Models to Predict Potential Landscape Restoration Effects on Puma Conservation.
abstract: A mosaic of intact native and human-modified vegetation use can provide important habitat for top predators such as the puma (Puma concolor), avoiding negative effects on other species and ecological processes due to cascade trophic interactions. This study investigates the effects of restoration scenarios on the puma's habitat suitability in the most developed Brazilian region (São Paulo State). Species Distribution Models incorporating restoration scenarios were developed using the species' occurrence information to (1) map habitat suitability of pumas in São Paulo State, Southeast, Brazil; (2) test the relative contribution of environmental variables ecologically relevant to the species habitat suitability and (3) project the predicted habitat suitability to future native vegetation restoration scenarios. The Maximum Entropy algorithm was used (Test AUC of 0.84 ± 0.0228) based on seven environmental non-correlated variables and non-autocorrelated presence-only records (n = 342). The percentage of native vegetation (positive influence), elevation (positive influence) and density of roads (negative influence) were considered the most important environmental variables to the model. Model projections to restoration scenarios reflected the high positive relationship between pumas and native vegetation. These projections identified new high suitability areas for pumas (probability of presence >0.5) in highly deforested regions. High suitability areas were increased from 5.3% to 8.5% of the total State extension when the landscapes were restored for ≥ the minimum native vegetation cover rule (20%) established by the Brazilian Forest Code in private lands. This study highlights the importance of a landscape planning approach to improve the conservation outlook for pumas and other species, including not only the establishment and management of protected areas, but also the habitat restoration on private lands. Importantly, the results may inform environmental policies and land use planning in São Paulo State, Brazil.
authors.affiliation: University of São Paulo, Water Resources and Environmental Studies Centre, São Carlos School of Engineering, São Carlos, SP, Brazil.|University of Queensland, School of Geography, Planning and Environmental Management, Brisbane, QLD, Australia.
authors.forename: Cintia Camila Silva
authors.initials: CC
authors.lastname: Angelieri
authors.affiliation: University of Queensland, School of Geography, Planning and Environmental Management, Brisbane, QLD, Australia.
authors.forename: Christine
authors.initials: C
authors.lastname: Adams-Hosking
authors.affiliation: University of São Paulo, Forest Science Department, Luiz de Queiroz College of Agriculture, Piracicaba, SP, Brazil.
authors.forename: Katia Maria Paschoaletto Micchi de Barros
authors.initials: KM
authors.lastname: Ferraz
authors.affiliation: University of São Paulo, Biology Department, Ribeirão Preto School of Philosophy, Science and Literature, Ribeirão Preto, SP, Brazil.
authors.forename: Marcelo Pereira
authors.initials: MP
authors.lastname: de Souza
authors.affiliation: University of Queensland, School of Geography, Planning and Environmental Management, Brisbane, QLD, Australia.
authors.forename: Clive Alexander
authors.initials: CA
authors.lastname: McAlpine
mesh_terms: D000818:Animals; D019540:Area Under Curve; D001938:Brazil; D003247:Conservation of Natural Resources; D017753:Ecosystem; D008954:Models, Biological; D046011:Puma / Q000502:physiology*; D012372:ROC Curve