To elaborate our model we removed uncertain localities such as 'Bogota skins' and all records with coordinates laying down in sites with estimated elevations below 107 m and above 1,786 m. Also one records in BioMap from west Cundinamarca, which likely represent corrupted data, was removed previously to modelling.
The habitat suitability model generated in Maxent showed areas suitable in climatic terms for this species west of the Andes in the adjacent areas north of the Central Andes, the high Magdalena and Cauca valleys, and east of the andes near the Rio Negro zone . These areas are not known to be occupied by the species and were excluded from the potential distribution map.
Assuming that the distribution of the species may have filled the complete climatic model generated, its distribution today in remnants of forest is about 36,903 km2, which corresponds to a loss of 63 % of its potential original distribution due to deforestation in Colombia.
Conservation attention is drawn to the subspecies curiosus; endemic of the Sierra Nevada de Santa Marta. Assuming that the distribution of the subspecies may have filled the complete climatic model generated, its distribution today in remnants of forest is about 5,319 km2, which corresponds to a loss of 78 % of its potential original distribution due to deforestation in Colombia. Although good part of this range is covered by the parks Sierra Nevada de Santa Marta and Tayrona it is not clear if the subspecies is present in the northwestern slopes of the Sierra Nevada (McMullan & Donegan 2014), which can make its range even smaller than what has been formerly stated. Conservation of this subspecies in Colombia depend completely on measures taken for it in the country.
Regularized training gain is 1.831, training AUC is 0.979, unregularized training gain is 2.725.
Algorithm converged after 1040 iterations (28 seconds).
The follow settings were used during the run:
24 presence records used for training.
10024 points used to determine the Maxent distribution (background points and presence points).
Environmental layers used (all continuous): bio10co bio11co bio12co bio13co bio14co bio15co bio16co bio17co bio18co bio19co bio1co bio2co bio3co bio4co bio5co bio6co bio7co bio8co bio9co
Regularization values: linear/quadratic/product: 0.365, categorical: 0.250, threshold: 1.760, hinge: 0.500
Feature types used: hinge linear quadratic
'Equal Training Sensitivity and Specificity' and 'Equate Entropy of Thresholded and Original Distributions' thresholds and omission rates:
0.064-0.161-Fractional predicted area
0.083-0.000-Training omission rate