To elaborate our model we removed uncertain localities such as 'Bogota skins', those localities with no coordinates and all records with coordinates laying down in sites with estimated elevations below 2,400 m and above 3,870 m. Also four records in DatAves one from Cundinamarca and three from Amazonas, which represent corrupted data in the database were deleted.
The habitat suitability model generated in Maxent showed extensive areas suitable in climatic terms for this species in the southern half of the Eastern Andes. Those areas are not known to be occupied by this species and were deleted from our final 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 10,402 km2, which corresponds to a loss of 66 % of its potential original distribution due to deforestation.
Regularized training gain is 3.300, training AUC is 0.991, unregularized training gain is 3.576.
Algorithm converged after 1420 iterations (45 seconds).
The follow settings were used during the run:
82 presence records used for training.
10082 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: 0.179, categorical: 0.250, threshold: 1.180, hinge: 0.500
Feature types used: hinge product linear threshold quadratic
'Equal Training Sensitivity and Specificity' and 'Equate Entropy of Thresholded and Original Distributions' thresholds and omission rates:
0.029-0.037-Fractional predicted area
0.024-0.024-Training omission rate