Lepidopyga goudoti

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 above 1,877 m. Two records in BioMap from the high Cauca Valley and central Nariño although suspicious were left in the dataset to model.

The habitat suitability model generated in Maxent showed areas suitable in climatic terms for this species in the Cauca Valley and in the eastern slope of the Eastern Andes in its most southern portion. These areas are not known to be occupied by the species and were excluded from the potential distribution map of this hummingbird. Some areas in the Caribbean and in extreme northeast Colombia likely suitable for this species were not predicted by our model, those areas were noted as such in our maps.

Distribution of specimens according to BioMap suggest a possible area (5,410 km²) of intergradation between subspecies luminosa and zuliae in Alta Guajira.

Assuming that the distribution of the species may have filled the complete climatic model generated, its distribution today in remnants of forest is about 43,498 km², which corresponds to a loss of 82 % of its potential original distribution due to deforestation. Nonetheless, this species favours edges, open woodland and secondary vegetation and therefore possibly deforestation has not negatively affected greatly its populations.

MODEL METADATA

Regularized training gain is 1.744, training AUC is 0.952, unregularized training gain is 2.051.

Algorithm terminated after 2000 iterations (89 seconds).

The follow settings were used during the run:

240 presence records used for training.

10239 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:

ETSS-EETOD-Description

21.075-9.716-Cumulative threshold

0.296-0.168-Logistic threshold

0.108-0.175-Fractional predicted area

0.108-0.054-Training omission rate