To elaborate our model we removed uncertain localities such as those localities with no coordinates and all records with coordinates laying down in sites with estimated elevations below 1,740 m and above 3,988 m. Also one record in BioMap from 'rio Patia' (Cauca), which represents a highly imprecise locality was deleted; usually, this kind of localities recibe the coordinates of the mouth of the river, which can be kilometres away from the actual locality of actual collection.
The habitat suitability model generated in Maxent made excellent predictions, not showing any areas suitable in climatic terms for this species out of the main Andean ranges. Areas in the southern portion of the Eastern Andes are not supported by any records. Nonetheless, those areas were left in our final potential map since were predicted as suitable and are very likely to be occupied by this hummingbird.
Assuming that the distribution of the species may have filled the complete climatic model generated, its distribution today in remnants of forest is about 26,319 km2, which corresponds to a loss of 69 % of its potential original distribution due to deforestation. This proportion may be slightly overestimated since in some areas of its distribution this species includes Paramo.
Regularized training gain is 2.552, training AUC is 0.978, unregularized training gain is 2.780.
Algorithm converged after 1820 iterations (60 seconds).
The follow settings were used during the run:
168 presence records used for training.
10168 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: 0.050, categorical: 0.250, threshold: 1.000, 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:
0.069-0.078-Fractional predicted area
0.071-0.048-Training omission rate