NOTES
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 150 m and above 2,455 m. Also five records in BioMap from Valle del Cauca and Atlantico, which represent corrupted or accidental (Atlantico records) information in the database were deleted previous to modelling.
The habitat suitability model generated in Maxent showed areas suitable in climatic terms for this species in the western slope of the Central Andes, and the most northern areas in the eastern slope of the Eastern Andes, equally areas in between records in the western Andes and the southern Andes, south of the Colombian Massif. 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 28,762 km2, which corresponds to a loss of 67 % of its potential original distribution due to deforestation. Despite this species occupies edges, secondary vegetation and plantations it is not clear if deforestation has or not negatively affected its populations. The species is considered uncommon to locally common (Hilty & Brown, 1986). Although the species has a relatively large extent of occurrence, estimated in our maps as 87,530 km2, given the massive destruction of habitat within its potencial distribution, which still continues we believe this species must be uplisted as Near Threatened (NT). This species needs urgently more research of its ecology, particularly to define its dependence from forest fragments.
Subspecies alfaroana from Costa Rica has been considered to belong to this species but its taxonomic status has not conclusively resolved (HBW Alive, 2017). In any case, it has not been recorded since 1895 and it is considered possibly extinct, which makes the species technically 'endemic' to Colombia.
MODEL METADATA
Regularized training gain is 2.460, training AUC is 0.977, unregularized training gain is 2.777.
Algorithm terminated after 2000 iterations (81 seconds).
The follow settings were used during the run:
159 presence records used for training.
10157 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
responsecurves: true
jackknife: true
maximumiterations: 2000
'Fixed Cumulative Value 5%', 'Equal Training Sensitivity and Specificity' and 'Equate Entropy of Thresholded and Original Distributions' thresholds and omission rates:
FCV5-ETSS-EETOD-Description
5.000-12.582-9.808-Cumulative threshold
0.055-0.182-0.135-Logistic threshold
0.127-0.073-0.085-Fractional predicted area
0.019-0.075-0.057-Training omission rate