The habitat suitability model generated in Maxent did not show areas that might be possibly occupied by this species in central and south Amazonia, from where there are very few records.
Distribution of specimens, according to BioMap, suggests a possible area (≈ 16,457 km2) of intergradation between subspecies zuliensis and saturatus from central Cordoba towards the east to northeastern Antioquia. Most specimens in this area have been collected well after the description of both subspecies involved and we believe it is unlikely they are erroneously identified. Similarly, there is one specimen of saturatus inside the northern portion of the range of latifrons, which may denote a greater individual variation in that area for that last subspecies or the possibility of a narrow zone (≈ 1,961 km2), 'possibly wider', of intergradation between both subspecies.
Assuming that the distribution of the species may have filled the complete climatic model generated, west of the Andes its distribution today in remnants of forest is about 126,622 km2, which corresponds to a loss of 63 % of its potential original distribution due to deforestation. Nevertheless, accounting for the possible areas that this species occupy in the Amazonia that were not predicted by the model, its distribution today in remnants of forest may be about 609,940 km2, which corresponds to a loss of 32 % of its potential suitable habitat in the country due to deforestation.
Regularized training gain is 0.825, training AUC is 0.893, unregularized training gain is 1.259.
Algorithm terminated after 2000 iterations (66 seconds).
The follow settings were used during the run:
98 presence records used for training.
10097 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: 0.064, categorical: 0.250, threshold: 1.020, hinge: 0.500
Feature types used: product linear quadratic hinge threshold
'Equal Training Sensitivity and Specificity' and 'Equate Entropy of Thresholded and Original Distributions' thresholds and omission rates:
0.198-0.441-Fractional predicted area
0.194-0.031-Training omission rate