Coeligena prunellei
NOTES
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 985 m and above 3,077 m. Also one record in BioMap from Popayan of the hybrid Coeligena purpurea (C. coeligena x C. prunellei).
The habitat suitability model generated in Maxent showed areas suitable in climatic terms for this species in the three Andean ranges. Except areas in the western slope of the Eastern Andes (slightly extended further than what records show), those areas are not known to be occupied by this species and were deleted from our final potential distribution map.
The most northern and southern portion of the potential distribution in the western slope of the Eastern Andes needs further collections to confirm if the species is present in those sections of the cordillera.
Assuming that the distribution of the species may have filled the complete climatic model generated, its distribution today in remnants of forest is about 8,089 km2, which corresponds to a loss of 73 % of its potential original distribution due to deforestation.
This Colombian endemic has been catalogued by BirdLife International (2016) as Vulnerable (VU). The species has a extent of occurrence estimated in 6,400 km2 (BirdLife International 2016), which possibly is much smaller than what it really is. Our analysis suggest an extent of occurrence of 30,367 km2, which is well above the 20,000 km2 threshold for Vulnerable. Nonetheless, our analysis also suggest the species has lost a major proportion of what potentially was its original distribution due to deforestation, giving the extent of occurrence of forested areas and the threats to its habitat such as deforestation and fragmentation, which still continue, likely this species is correctly classified as Vulnerable (VU).
MODEL METADATA
Regularized training gain is 2.898, training AUC is 0.990, unregularized training gain is 3.408.
Algorithm converged after 920 iterations (51 seconds).
The follow settings were used during the run:
54 presence records used for training.
10054 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: 0.181, categorical: 0.250, threshold: 1.460, hinge: 0.500
Feature types used: hinge 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:
18.597-10.291-Cumulative threshold
0.252-0.141-Logistic threshold
0.036-0.055-Fractional predicted area
0.037-0.000-Training omission rate