Ortalis columbiana


To elaborate the habitat suitability model we removed all records with coordinates laying down in sites with estimated elevations above 2,300 m; among those a few 'Bogota skins'. Records uploaded in the map were kept with an old taxonomy, retaining O. columbiana as a subspecies of O. guttata, as a reference to keep the information on those specimens in BioMap determined to subspecies. It is important to note that there is one record from Villavicencio in BioMap that possibly has not been properly identified and it is O. guttata; however, this needs confirmation. Finally, coordinates from the record 302220, a sighting from Sanquianga, in DatAves were moved south a few centecimals of a degree to make them fit in the continental mask of Colombia.

The habitat suitability model generated in Maxent showed several areas that are suitable in climatic terms for this species in Sierra Nevada de Santa Marta, Perija, the Catatumbo and the eastern slope of the Eastern Andes. These areas are not known to be occupied by this chachalaca and were excluded from its potential distribution map.

Assuming that the distribution of the species may have filled the complete climatic model generated, its potential distribution today in remnants of forest is about 62,836 km2, which corresponds to a loss of 68 % of its potential original distribution due to deforestation. However, this species is relatively resilient and uses borders and secondary forest, which must increase the amount of possible remnant habitat for this chachalaca in Colombia.


Regularized training gain is 1.687, training AUC is 0.959, unregularized training gain is 2.171.

Algorithm terminated after 2000 iterations (64 seconds).

The follow settings were used during the run:

126 presence records used for training.

10124 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: product linear quadratic hinge threshold

responsecurves: true

jackknife: true

maximumiterations: 2000

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


21.914-8.801-Cumulative threshold

0.329-0.154-Logistic threshold

0.107-0.184-Fractional predicted area

0.111-0.024-Training omission rate