Stability Models

Peruvian plantcutter

The maps used in this example was built for Peruviant plantcutter.

Peruvian plantcutter is a bird species endemic to the northern coast of Peru. It’s considerated to be tied closely to dry forests (see Atauchi et al., 2018).

In our case, we used maximum entropy approaches implemented in Maxent 3.3.3k (Phillips et al., 2006) for calibration models. The best models was transferred to 2050 based on three global circulation models: HagGem2-ES, MIROC5 and ACCESS1-0 (RCP 8.5).

Stability Models

Load current and future distribution of species

library(sdStaf)

# We read current distribution of Peruvian Plantcutter
current_list <- list.files(path=paste(system.file(package="sdStaf"),
                                      '/pre', sep=''), pattern='asc', full.names=TRUE)

current <- raster::stack(current_list)

# We read future distribution of Peruvian Plantcutter
future_list <- list.files(path=paste(system.file(package="sdStaf"),
                                     '/fut', sep=''), pattern='asc', full.names=TRUE)

future <- raster::stack(future_list)

We calculate stability values of Peruvian plantcutter

stabSpecies <- stability(current = current, project = future, thr.value=0.34)

Details of Stability Models. Realize that upper values to 100 show stability and lower values show areas with colonize potential.

Besides, It has built a stability maps that can be plotter with plot(stabSpecies)

print(stabSpecies)
#> *** Class Trajectories, method Print *** 
#> * Times =  Models nPixel
#> 1      0  11754
#> 2      1    141
#> 3      2    171
#> 4      3    483
#> 5    100   1262
#> 6    101     35
#> 7    102    202
#> 8    103    881
#> ******* End Print (trajectories) *******