Amazilia castaneiventris


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 300 m and above 2,382 m. Also one record in BioMap from Buenaventura (Valle del Cauca), which represents corrupted information in the database was deleted previous to modelling.

The habitat suitability model generated in Maxent showed areas suitable in climatic terms for this species in several spots along the main Andean ranges off the main distribution area between serrania de San Lucas south to Boyaca, also serrania del Perija and Sierra Nevada de Santa Marta. These areas are not known to be occupied by the species and were excluded from the potential distribution map of this hummingbird.

Assuming that the distribution of the species may have filled the complete climatic model generated, its distribution today in remnants of forest is about 2,590 km2, which corresponds to a loss of 68 % of its potential original distribution due to deforestation.

BirdLife International has categorised this species as Endangered (EN) because it has a very restricted range where the habitat is very fragmented and there is continuing degradation of forested habitats. Its range has been estimated in 3,200 km2 (BirdLife International 2017). Our maps suggests an extent of occurrence of 8,011 km2, possibly underestimated in the zone of serrania de San Lucas. BirdLife International (2017) has estimated its population in the band of 1,000-2,499 individuals that equates to 667-1,666 mature individuals based on known records, descriptions of its abundance and known range. Although it is uncommon and local along its distribution, this species uses secondary vegetation and it is not clear if deforestation has impacted negatively its populations. This species is in great need of further research of its ecology to define better its distribution and the threats to its populations.


Regularized training gain is 3.556, training AUC is 0.996, unregularized training gain is 4.450.

Algorithm converged after 980 iterations (29 seconds).

The follow settings were used during the run:

29 presence records used for training.

10029 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: 0.269, categorical: 0.250, threshold: 1.710, hinge: 0.500

Feature types used: hinge linear quadratic

responsecurves: true

jackknife: true

maximumiterations: 2000

'Fixed Cumulative Value of 10%', 'Equal Training Sensitivity and Specificity' and 'Equate Entropy of Thresholded and Original Distributions' thresholds and omission rates:


10.000-17.369-14.745-Cumulative threshold

0.087-0.168-0.136-Logistic threshold

0.039-0.024-0.028-Fractional predicted area

0.000-0.034-0.000-Training omission rate