Ensifera ensifera


To elaborate our model we removed uncertain localities such as those localities with no coordinates and all records with coordinates laying down in sites with estimated elevations below 1,700 m and above 3,774 m. Also two records in BioMap from Magdalena, which represent corrupted information in the database were deleted.

The habitat suitability model generated in Maxent showed very good fit not showing suitable areas out of the main Andean Ranges.

Assuming that the distribution of the species may have filled the complete climatic model generated, its distribution today in remnants of forest is about 31,000 km2, which corresponds to a loss of 65 % of its potential original distribution due to deforestation.


Regularized training gain is 2.423, training AUC is 0.974, unregularized training gain is 2.609.

Algorithm converged after 1460 iterations (51 seconds).

The follow settings were used during the run:

209 presence records used for training.

10208 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:

13.328-6.191-Cumulative threshold

0.289-0.198-Logistic threshold

0.069-0.089-Fractional predicted area

0.067-0.033-Training omission rate