Amazilia rosenbergi


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 above 1,907 m. Also four records in BioMap from Santander and Norte de Santander, which represent corrupted information 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 mid-low Cauca and mid Magdalena valleys an few pixels in the far eastern Amazonia. 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 biogeographic Choco suitable for this species were not predicted by our model, those areas were noted as such in our maps.

Our maps point to an area in the Magdalena Valley that corresponds to a couple of records from EBIRD and DatAves from Rio Claro and Barbosa in Antioquia, these may represent potentially an extension of the known range. However, they have been treated as suspicious and this have been noted in such way in our maps.

Assuming that the distribution of the species may have filled the complete climatic model generated, its distribution today in remnants of forest is about 61,301 km2, which corresponds to a loss of 44 % of its potential original distribution due to deforestation.


Regularized training gain is 2.571, training AUC is 0.975, unregularized training gain is 2.933.

Algorithm converged after 1080 iterations (102 seconds).

The follow settings were used during the run:

56 presence records used for training.

10055 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: 0.176, categorical: 0.250, threshold: 1.440, hinge: 0.500

Feature types used: hinge linear quadratic

responsecurves: true

jackknife: true

maximumiterations: 2000

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


10.000-14.625-13.426-Cumulative threshold

0.103-0.162-0.148-Logistic threshold

0.095-0.071-0.076-Fractional predicted area

0.054-0.071-0.054-Training omission rate