Leucippus fallax


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 above 749 m.

The habitat suitability model generated in Maxent showed a few pixels suitable in climatic terms for this species in far east Amazon region in the Rio Negro valley. These areas are not known to be occupied by the species and were excluded from the potential distribution map of this hummingbird. The model predicted a few pixels south of 'Cienaga Grande de Santa Marta' that were left to inform, although it is unlikely the species reaches that area.


Regularized training gain is 3.980, training AUC is 0.995, unregularized training gain is 4.243.

Algorithm converged after 860 iterations (38 seconds).

The follow settings were used during the run:

54 presence records used for training.

10054 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: 0.181, categorical: 0.250, threshold: 1.460, hinge: 0.500

Feature types used: hinge linear quadratic

responsecurves: true

jackknife: true

maximumiterations: 2000

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


6.938-7.821-Cumulative threshold

0.106-0.123-Logistic threshold

0.020-0.019-Fractional predicted area

0.019-0.037-Training omission rate