Phaethornis syrmatophorus

NOTES

To elaborate our model we removed all records with coordinates laying down in sites with estimated elevations below 500 m and above 2,500 m. Also three records in DatAves from the area of Sierra Nevada de Santa Marta, which represent corrupted data, were deleted previous to model the distribution.

The habitat suitability model generated in Maxent showed a very few areas suitable in climatic terms for this species in Sierra Nevada de Santa Marta. These areas are not known to be occupied by the species and were excluded from the potential distribution map of this hummingbird. Also some areas in the southern serrania del Baudo that were predicted as suitable were trimmed off from our final potential distribution map since we did not have any knowledge of records from the zone. Nonetheless, in EBird (2016) there are a few records from the mid serrania del Baudo, which may indicate that possibly this species is also distributed along that mountain range in Choco.

The distribution of subspecies in most of the eastern slope of the Central Andes is not clear since there are no specimens. Distribution of specimens according to BioMap, suggests that possibly in the north is present the nominate subspecies while in the south occurs subspecies columbianus. Currently we do not know up to which point each subspecies is distributed and limits we have drawn in our maps are tentative; this needs further revision.

Assuming that the distribution of the species may have filled the complete climatic model generated, its distribution today in remnants of forest is about 71,909 km2, which corresponds to a loss of 57 % of its potential original distribution due to deforestation. Nonetheless, this species favours edges and secondary vegetation and therefore possibly deforestation has not negatively affected greatly its populations.

MODEL METADATA

Regularized training gain is 2.022, training AUC is 0.967, unregularized training gain is 2.395.

Algorithm terminated after 2000 iterations (63 seconds).

The follow settings were used during the run:

105 presence records used for training.

10103 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

17.517-6.91-Cumulative threshold

0.327-0.148-Logistic threshold

0.086-0.133-Fractional predicted area

0.086-0.029-Training omission rate