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 2,668 m and above 3,633 m. There were several records placed at elevations as low as ≈ 2,000 m, several near El Tambo (Cauca). Those are of particular interest since the type locality of this species is Popayan. This might indicate that the species is present at lower elevations than what it is known at present time. Nonetheless, this needs further confirmation. Also, previous to modelling we deleted two records in BioMap from Guasca and La Calera (Cundinamarca), which likely represent corrupted information in the database.
The habitat suitability model generated in Maxent showed extensively areas suitable in climatic terms for this species across the Western and Eastern Andes, also a few areas in the northern end of the Central Andes and Sierra Nevada de Santa Marta. Those areas are not known to be occupied by the species and were excluded from the potential distribution map of 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 6,374 km2, which corresponds to a loss of 69 % of its potential original distribution due to deforestation. Despite being in Ecuador and Peru, this species is restricted just to the Central Andes in Colombia and its habitat has been severely fragmented. The extent of occurrence is ≈ 20,000 km2 and therefore in the country its category may be Near Threatened (NT) and may need revision.
Regularized training gain is 2.701, training AUC is 0.989, unregularized training gain is 3.286.
Algorithm converged after 220 iterations (1 seconds).
The follow settings were used during the run:
6 presence records used for training.
10006 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: 1.000, categorical: 0.560, threshold: 1.940, hinge: 0.500
Feature types used: linear
'Equal Training Sensitivity and Specificity' and 'Equate Entropy of Thresholded and Original Distributions' thresholds and omission rates:
0.022-0.067-Fractional predicted area
0.000-0.000-Training omission rate