Heliodoxa jacula

NOTES

To elaborate our model 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 289 m and above 2,502 m.

The habitat suitability model generated in Maxent showed very good fit, showing very few suitable areas out of the main Andean Ranges and serrania de San Lucas. These were in in the eastern slope of the northern Eastern Andes, the Sierra Nevada de Santa Marta and serrania del Baudo. Those areas are not known to be occupied by this species and were deleted from the final potential distribution map.

Distribution of specimens according to BioMap suggest that the whole range of subspecies jamersoni in Colombia may be a zone of intergradation (11,914 km2) between that subspecies and the nominate subspecies, which extends from southwestern Valle del Cauca towards the south to Nariño.

Assuming that the distribution of the species may have filled the complete climatic model generated, its distribution today in remnants of forest is about 54,122 km2, which corresponds to a loss of 53 % of its potential original distribution due to deforestation.

MODEL METADATA

Regularized training gain is 2.332, training AUC is 0.976, unregularized training gain is 2.844.

Algorithm terminated after 2000 iterations (84 seconds).

The follow settings were used during the run:

106 presence records used for training.

10106 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: 0.050, categorical: 0.250, threshold: 1.000, hinge: 0.500

Feature types used: hinge product linear threshold quadratic

responsecurves: true

jackknife: true

maximumiterations: 2000

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

17.470-13.903-Cumulative threshold

0.216-0.179-Logistic threshold

0.083-0.097-Fractional predicted area

0.085-0.047-Training omission rate