Amazilia fimbriata


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 1,838 m.

The habitat suitability model generated in Maxent showed areas suitable in climatic terms for this species west of the Andes. Except areas in the north Caribbean and the mid-high to high Magdalena Valley (from where there are newer collected study skins), these areas are not known to be occupied by the species and were excluded from the potential distribution map of this hummingbird. Also is important to note that some areas in the central Amazon region were not predicted as suitable by our model, these areas were noted as such in our maps.

In our databases most specimens collected from the Orinoco region, which must correspond to subspecies apicalis have been determined as fimbriata that is not known to occur in Colombia, whilst specimens determined as apicalis occupy the foothills of the eastern slope of the Andes. This raise questions regarding the subspecific identity of those specimens. At present time, the Orinoco region has been considered as part of the distribution of apicalis in our maps, but this needs further revision.

Assuming that the distribution of the species may have filled the complete climatic model generated in the Amazon region, its distribution today in remnants of forest is about 476,240 km2, which corresponds to a loss of 9 % of its potential original distribution due to deforestation in that region.


Regularized training gain is 1.061, training AUC is 0.900, unregularized training gain is 1.447.

Algorithm terminated after 2000 iterations (93 seconds).

The follow settings were used during the run:

311 presence records used for training.

10310 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 of 1%', 'Equal Training Sensitivity and Specificity' and 'Equate Entropy of Thresholded and Original Distributions' thresholds and omission rates:


1.000-31.208-14.868-Cumulative threshold

0.036-0.321-0.185-Logistic threshold

0.769-0.170-0.348-Fractional predicted area

0.006-0.170-0.077-Training omission rate