To elaborate our model we removed uncertain localities such as those localities with no coordinates, 'Bogota skins' and all records with coordinates laying down in sites with estimated elevations below 3,075 m and above 4,500 m.
The habitat suitability model generated in Maxent showed a few areas suitable in climatic terms for this species in the southern Central Andes. Those areas are not known to be occupied by this hummingbird and were deleted from our final potential distribution map.
This species, sometimes considered a subspecies of the complex Oxypogon guerinii-stubelii-cyanolaemus has been catalogued as of Least Concern (LC) by BirdLife (2016). According to BirdLife (2016) it does not approach to the thresholds to be categorised as Vulnerable (VU), although they estimate its extent of occurrence in 19,700 km2. We do believe this evaluation is incorrect. Our maps suggest an extent of occurrence of 14,044 km2, which is well below the threshold of 20,000 km2 and this combined with the fact that the paramo areas in Colombia are extremely fragmented and continue being burned and transformed for crops or cattle breeding, suggests this species must be recategorised as Vulnerable (VU), or the very least Near Threatened (NT).
Regularized training gain is 3.969, training AUC is 0.994, unregularized training gain is 4.189.
Algorithm converged after 360 iterations (11 seconds).
The follow settings were used during the run:
38 presence records used for training.
10037 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: 0.227, categorical: 0.250, threshold: 1.620, 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:
0.013-0.019-Fractional predicted area
0.000-0.000-Training omission rate