Mitu salvini


To elaborate the habitat suitability model we added during the modelling exercise two records of specimens collected in the Amazon region, both deposited in the ornithology collection of the IAvH. One taken '50 km de la desembocadura al rio Cuemani' (Caqueta) and another taken in 'P.N.N. Cahuinari, cerca de la confluencia del ri­o Cahuinari con el Caqueta' (Amazonas).

The habitat suitability model generated in Maxent showed extensively areas that are suitable in climatic terms for this species in most of tropical Colombia. Areas west of the Andes are not known to be occupied by this curassow and were excluded from its potential distribution map. Likewise, areas along the northern portion of the eastern slope of the Eastern Andes and the Amazon Trapezium were not included in our final potential distribution map. Nonetheless, we suspect the species might exist in the Trapezium or part of it, since there are records to the east as far as ≈ -75.52° in the 'Zona Reservada Yaguas' in Peru (EBIRD, 2015), which is located at similar latitudes to the Cahuinari National Park in Colombia.

Assuming that the distribution of the species may have filled the areas predicted as suitable (i.e. marginally suitable, suitable and highly suitable) in its most likely area of distribution in the southwestern Orinoco region and Amazon region (excluding the southeastern portion), its potential distribution today in remnants of forest is about 426,653 km2, which corresponds to a loss of 11 % of its potential original distribution due to deforestation.


Regularized training gain is 0.285, training AUC is 0.889, unregularized training gain is 0.772.

Algorithm converged after 240 iterations (1 seconds).

The follow settings were used during the run:

10 presence records used for training.

10010 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: 0.800, categorical: 0.500, threshold: 1.900, hinge: 0.500

Feature types used: linear quadratic

responsecurves: true

jackknife: true

askoverwrite: false

maximumiterations: 2000

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


57.737-4.915-Cumulative threshold

0.527-0.238-Logistic threshold

0.2-0.752-Fractional predicted area

0.2-0-Training omission rate