Chalcostigma herrani


To elaborate our model we removed uncertain localities such as those localities with no coordinates, 'Bogota skins' and all records with coordinates laying down in sites with estimated elevations below 2,700 m and above 4,200 m. Also four records in BioMap from Magdalena, which represent corrupted information in the database were deleted.

The habitat suitability model generated in Maxent showed areas suitable in climatic terms for this species in the southern Eastern Andes. Those areas are not known to be occupied by this hummingbird and were deleted from our final potential distribution map. Otherwise areas predicted as suitable in the northern Western Andes and the Central southern Central Andes were left in our maps although are not supported by records.


Regularized training gain is 3.589, training AUC is 0.992, unregularized training gain is 3.743.

Algorithm converged after 920 iterations (27 seconds).

The follow settings were used during the run:

70 presence records used for training.

10070 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: 0.136, categorical: 0.250, threshold: 1.300, 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:

5.985-8.219-Cumulative threshold

0.102-0.142-Logistic threshold

0.032-0.028-Fractional predicted area

0.029-0.057-Training omission rate