Eutoxeres condamini

NOTES

The habitat suitability model generated in Maxent showed areas that might be possibly occupied by this species west of the Andes, particularly in the Pacific lowlands. However, we do know this species is distributed only east of the Andes and excluded those areas from the potential distribution map of the species. Equally, we excluded areas predicted as suitable in the far southeastern Amazonia.

There is one record from BioMap that represents a Bogota skin, and it was excluded to conduct the modelling.

Assuming that the distribution of the species may have filled the complete climatic model generated, its distribution today in remnants of forest is about 104,724 km2, which corresponds to a loss of 20 % of its potential original distribution due to deforestation. Nevertheless, if we restrict the potential distribution to the most likely areas according to the known records, its distribution today in remnants of forest is lowered to about 23,132 km2, which corresponds to a loss of 37 % of its potential original distribution due to deforestation.

MODEL METADATA

Regularized training gain is 0.992, training AUC is 0.925, unregularized training gain is 1.446.

Algorithm converged after 120 iterations (0 seconds).

The follow settings were used during the run:

6 presence records used for training.

10005 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: 1.000, categorical: 0.560, threshold: 1.940, hinge: 0.500

Feature types used: linear

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

30.389-9.453-Cumulative threshold

0.432-0.151-Logistic threshold

0.167-0.371-Fractional predicted area

0.167-0.00-Training omission rate