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 above 520 m and below 2,965 m. Also a record in BioMap from Vaupes, which represents corrupted information in the database was deleted previously to modelling.
The habitat suitability model generated in Maxent showed areas suitable in climatic terms for this species along the Central and the Eastern Andes. except the slopes above the Cauca Valley, these 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 9,958 km2, which corresponds to a loss of 77 % of its potential original distribution due to deforestation. Nonetheless, this species occupies scrub and woodland edges in dry and semi-dry valleys (McMullan & Donegan, 2014; HBW Alive, 2017), secondary vegetation and plantations such as Eucalyptus (Hilty & Brown, 1986; McMullan & Donegan, 2014) and therefore possibly deforestation has not negatively affected greatly its populations.
BioMap Data shows a record in southern Huila in the Central Andes. This data seem suspicious and needs further confirmation.
Recent studies suggest that this species may be better placed within genus Amazilia (HBW Alive, 2017).
Regularized training gain is 2.981, training AUC is 0.986, unregularized training gain is 3.295.
Algorithm converged after 1720 iterations (95 seconds).
The follow settings were used during the run:
101 presence records used for training.
10101 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
'Fixed Cumulative Value 5%', 'Equal Training Sensitivity and Specificity' and 'Equate Entropy of Thresholded and Original Distributions' thresholds and omission rates:
0.081-0.055-0.051-Fractional predicted area
0.020-0.059-0.059-Training omission rate