Coeligena wilsoni


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 897 m and above 2,362 m. Also three records in BioMap possibly misplaced and assigned to Ricaurte (Cundinamarca) instead of Ricaurte (Nariño), those were deleted previous to modelling.

The habitat suitability model generated in Maxent showed extensive areas suitable in climatic terms for this species in the three Andean ranges and in serrania del Baudo. Except areas in the Pacific slope and a few in the eastern slope of the Western Andes and the western slope of the Central Andes those areas are not known to be occupied by this species and were deleted from our final potential distribution map.

The northern portion of the western slope of the Central Andes needs further collections to confirm if the species is continuously distributed in that section of the cordillera from Alto Pisones (Antioquia) to Park Ucumari (Risaralda).

Assuming that the distribution of the species may have filled the complete climatic model generated, its distribution today in remnants of forest is about 8,832 km2, which corresponds to a loss of 62 % of its potential original distribution due to deforestation.

Despite this species has a restricted range to Colombia and Ecuador is has been catalogued by BirdLife International (2016) as of Low Concern (LC); possibly this classification is not correct. The species has a extent of occurrence estimated in 34,200 km2 (BirdLife International 2016). Our analysis suggest the species has lost, at least in Colombia, a major proportion of what potentially was its original distribution due to deforestation, giving the extent of occurrence and the threats to its habitat such as deforestation and fragmentation, which still continue, likely this species may be catalogued as Near Threatened (NT). This is very clear at least in Colombia where our analysis suggest a extent of occurrence of 23, 147 km2.


Regularized training gain is 3.023, training AUC is 0.987, unregularized training gain is 3.353.

Algorithm terminated after 2000 iterations (67 seconds).

The follow settings were used during the run:

107 presence records used for training.

10106 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:

13.696-9.877-Cumulative threshold

0.197-0.146-Logistic threshold

0.039-0.049-Fractional predicted area

0.037-0.028-Training omission rate