Boissonneaua matthewsii


To elaborate our model we produced four pseudoreplicas from two original localities in Putumayo and Nariño. The new points were located at approximate 1-2 km from the fist localities, all localities and pseudoreplicas were placed at elevations in the range 1,380-2,200 m.

The habitat suitability model generated in Maxent showed areas suitable in climatic terms for this species in the mid Central and Western Andes, the head of the Magdalena Valley and even in the far east in the region of the Rio Negro. Those 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 2,372 km2, which corresponds to a loss of 28 % of its potential original distribution due to deforestation.

This species inhabits Colombia, Ecuador and Peru and has a large extent of occurrence, estimated in 614,000 km2 and therefore it is considered of Low Concern given it does not approach to the thresholds for Vulnerable (VU) under the range size, population trend or population size criterion (BirdLife International 2016). Despite a major proportion of its habitat still is forested in Colombia its potential extent of occurrence in the country is very small, some 3,294 km2. Giving the fact that the habitat of this species still continues to be threatened by deforestation and fragmentation, possibly it may be considered of certain importance for conservation in Colombia if it is intended to conserve its populations in the country.


Regularized training gain is 3.058, training AUC is 0.994, unregularized training gain is 4.101.

Algorithm converged after 120 iterations (0 seconds).

The follow settings were used during the run:

6 presence records used for training.

10006 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: 1.000, categorical: 0.560, threshold: 1.940, hinge: 0.500

Feature types used: linear

responsecurves: true

jackknife: true

maximumiterations: 2000

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

23.465-13.207-Cumulative threshold

0.258-0.108-Logistic threshold

0.024-0.047-Fractional predicted area

0.000-0.000-Training omission rate