Lophornis delattrei


To elaborate our models 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 290 m and above 2,200 m.

The habitat suitability model generated in Maxent showed areas suitable in climatic terms for this hummingbird extensively west of the Andes. Thus we retained areas in the East Andes and the east slope of the Central Andes including serrania de San Lucas, as well as a few areas in the border with Panama. Otherwise, most areas were deleted from our final potential distribution map for this species. Areas in the southern portion of the eastern slope of the Eastern Andes were left in our map since they are climatically suitable although there are no known records from them.

Assuming that the distribution of the species may have filled the complete climatic model generated, its distribution today in remnants of forest is about 71,358 km2, which corresponds to a loss of 58 % of its potential original distribution due to deforestation.


Regularized training gain is 0.774, training AUC is 0.893, unregularized training gain is 1.117.

Algorithm converged after 180 iterations (1 seconds).

The follow settings were used during the run:

13 presence records used for training.

10013 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: 0.671, categorical: 0.393, threshold: 1.870, hinge: 0.500

Feature types used: linear quadratic

responsecurves: true

jackknife: true

maximumiterations: 2000

'Equal Training Sensitivity and Specificity' and 'Equate Entropy of Thresholded and Original Distributions' thresholds and omission rates:


38.469-9.318-Cumulative threshold

0.483-0.152-Logistic threshold

0.157-0.461-Fractional predicted area

0.154-0.000-Training omission rate