Ocreatus underwoodii


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 700 m and above 3,100 m.

The habitat suitability model generated in Maxent showed some areas suitable in climatic terms for this species in serrania del Baudo, serrania de San Lucas and Sierra Nevada de Santa Marta. Those areas are not known to be occupied by this species and were deleted from our final potential distribution map.

Distribution of specimens according to BioMap suggest two zones of intergradation. A first possible zone of intergradation of at least 3,146 km2 between subspecies incommodus and melanantherus from southern Valle del Cauca to central southern Cauca. A second possible zone of intergradation (2,772 km2) between subspecies discifer and underwoodii in Norte de Santander.

The southern portion of the Eastern Andes needs collections to clarify better the boundaries between subspecies underwoodii and incommodus. Equally, are necessary collections in the Southern Eastern Andes in Nariño/Putumayo to confirm the subspecies present in that area. It may be that subspecies peruanus enters Colombia in that zone as has been pointed by McMullan & Donegan (2014). Nonetheless, this is far from certain as those authors suggest and needs further research.

Assuming that the distribution of the species may have filled the complete climatic model generated, its distribution today in remnants of forest is about 73,532 km2, which corresponds to a loss of 61 % of its potential original distribution due to deforestation.


Regularized training gain is 1.691, training AUC is 0.941, unregularized training gain is 1.831.

Algorithm converged after 940 iterations (35 seconds).

The follow settings were used during the run:

586 presence records used for training.

10582 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

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

17.473-4.524-Cumulative threshold

0.366-0.195-Logistic threshold

0.125-0.184-Fractional predicted area

0.125-0.019-Training omission rate