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 below 1,500 m and above 3,650 m.
The habitat suitability model generated in Maxent showed areas suitable in climatic terms for this species in the high Cauca Valley, the Central Andes, the low Magdalena Valley and the 'Alta Guajira'. Those areas are not known to be occupied by this species and were deleted from our final potential distribution map. Areas south of approximately Santander were left in our potential map as part of a possible extended range in case it is proven specimens from near Bogota are correctly identified as conradii.
Distribution of specimens according to BioMap suggest the species possibly goes south as far as Bogota. Nevertheless, this requires further studies to confirm it and clarify better the distribution of the species in Colombia.
Assuming that the distribution of the species may have filled the complete climatic model generated, its distribution today in remnants of forest is about 3,077 km2, which corresponds to a loss of 68 % of its potential original distribution due to deforestation.
Further taxonomic studies needed to clarify relationships between C. torquata, C. conradii, C. eisenmanni and C. inca.
C. conradii usually considered a subspecies of C. torquata.
The distribution of the species is small in Colombia and it needs some conservation attention if it is intended to conserve it in the country.
Regularized training gain is 2.730, training AUC is 0.988, unregularized training gain is 3.261.
Algorithm converged after 100 iterations (1 seconds).
The follow settings were used during the run:
3 presence records used for training.
10003 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: 1.000, categorical: 0.605, threshold: 1.970, hinge: 0.500
Feature types used: linear
'Equal Training Sensitivity and Specificity' and 'Equate Entropy of Thresholded and Original Distributions' thresholds and omission rates:
0.019-0.065-Fractional predicted area
0.000-0.000-Training omission rate