Fig 1.
Land use and pumas’ occurrence records (2001–2012) in São Paulo State, Southeast, Brazil. This figure was elaborated by the first author using software ArcGIS 10.1 and IrfanView 4.37.
Table 1.
Environmental variables used to develop the models for pumas in São Paulo State, Brazil (See S4 Table for the environmental variables not used to develop the models).
Fig 2.
The puma habitat suitability in São Paulo State, Brazil and its projection in three restoration scenarios: (a) original Maxent distribution model average, (b) ≥10% percentage of native vegetation restoration scenario, (c) ≥20% percentage of native vegetation restoration scenario, and ≥30% percentage of native vegetation restoration scenario (d).
This figure was elaborated by the first author using softwares ArcGIS 10.1 and IrfanView 4.37.
Table 2.
Cross-tabulated areas between the four classes of Puma concolor habitat suitability (HS) (i.e. low HS (values ≤ 0.17), medium HS (0.17 ≤ values ≤ 0.31), medium-high HS (0.31 ≤ values ≤ 0.50) and high HS (values > 0.50) and four land cover zones (i.e. native vegetation, exotic forest crops, agriculture and others—urban areas and water bodies pixels) calculated using ArcGIS 10.1 Spatial Analyst Zonal tool.
Fig 3.
Marginal response curves showing how the logistic prediction changed as each of the three environmental variables that contributed the most to the models were varied: native vegetation (a), elevation (b) and density of roads (c).
Table 3.
Environmental variable importance to the modeling process evaluated by percent contribution, permutation importance and training gain (Jackknife test).
Three highest values are indicated in bold.
Fig 4.
High probability of puma presence (original) in São Paulo State, Brazil and high probability of puma presence projected in three restoration scenarios (≥10% percentage of native vegetation, ≥20% percentage of native vegetation, and ≥30% percentage of native vegetation) zoomed in for a close-up of three different landscape regions: (a) Northwestern region, (b) Central region and (c) Southeastern region.
This figure was elaborated by the first author using softwares ArcGIS 10.1 and IrfanView 4.37.