Juliamyia julie


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 above 1,868 m. Three records in BioMap from Meta and Norte de Santander, which correspond to corrupted data in the database were deleted previous to modelling.

The habitat suitability model generated in Maxent showed areas suitable in climatic terms for this species in the eastern slope of the Eastern Andes in extreme northeast Colombia and in the most southern portion of the cordillera. These areas are not known to be occupied by the species and were excluded from the potential distribution map of this hummingbird. Some areas in the Caribbean and in extreme southwest Colombia likely suitable for this species were not predicted by our model, those areas were noted as such in our maps. It is of particular interest those areas from the extreme southwest that correspond partially to the potential areal of distribution of subspecies feliciana that is just known in Colombia from 'Bogota skins'.

Distribution of specimens according to BioMap suggest a possible area (38,828 km2) of intergradation between subspecies panamensis and julie in the region of Uraba, southern Cordoba and northern Antioquia.

Assuming that the distribution of the species may have filled the complete climatic model generated, its distribution today in remnants of forest is about 75,296 km2, which corresponds to a loss of 74 % of its potential original distribution due to deforestation. Nonetheless, this species favours edges, open woodland, secondary vegetation, plantations and clearings and therefore possibly deforestation has not negatively affected greatly its populations.


Regularized training gain is 1.614, training AUC is 0.957, unregularized training gain is 2.138.

Algorithm terminated after 2000 iterations (175 seconds).

The follow settings were used during the run:

104 presence records used for training.

10103 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:


23.944-8.899-Cumulative threshold

0.339-0.162-Logistic threshold

0.108-0.199-Fractional predicted area

0.106-0.019-Training omission rate