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 below 322 m and above 1,600 m.
The habitat suitability model generated in Maxent showed areas suitable in climatic terms for this species in the Pacific, the head of the Magdalena Valley, and in the Amazon region in the far east (Rio Negro) and mid-low rio Putumayo . Those areas are not known to be occupied by this species and were deleted from our final potential distribution map. It is important to highlight that our maps point as suitable areas in Caqueta from where there are no known records yet.
Assuming that the distribution of the species may have filled the complete climatic model generated plus the areas not predicted but likely suitable, its distribution today in remnants of forest is about 7,557 km2, which corresponds to a loss of 23 % of its potential original distribution due to deforestation.
This species has been catalogued by BirdLife International (2017) as Near Threatened (NT) because it is believed it has a moderately small range which is decreasing because of habitat loss. It is considered to be rare and local (McMullan & Donegan 2014) and its extent of occurrence has been estimated in 163,000 km2 (BirdLife International 2017). Our maps suggest its extent of occurrence just in Colombia is about 9,839 km2. Forested areas have not been much degraded in is potential original geographical distribution as our analyses suggest. Nonetheless, given its small extent of occurrence in Colombia and the fact that forest areas in the eastern slope of the Andes continue being threatened we believe it can be up-listed as Vulnerable (VU) at national level in Colombia.
Regularized training gain is 2.874, training AUC is 0.986, unregularized training gain is 3.976.
Algorithm converged after 300 iterations (1 seconds).
The follow settings were used during the run:
9 presence records used for training.
10009 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: 0.515, threshold: 1.910, hinge: 0.500
Feature types used: linear
'Equal Training Sensitivity and Specificity' and 'Equate Entropy of Thresholded and Original Distributions' thresholds and omission rates:
0.111-0.056-Fractional predicted area
0.111-0.111-Training omission rate