ColForPAM

A Novel Clustering Approach For Ecosystem Health using Audio Recordings

DESCRIPTION

Ecosystems in Colombia have unique flora and fauna components with high endemism levels. Due to deforestation the degradation is increasing. Then, it is necessary to apply conservation plans based on the biodiversity changes.

Passive Acoustic Monitoring (PAM) is considered as an alternative to overcome the disadvantages of traditional methods as the site’s perturbations, the cost, and study time. Most of PAM methods determine acoustic heterogeneity apply supervised algorithms in sites where the labels are metrics or qualities of study sites as transformations, habitat prototypes landcover types, and landscape types. However, the ecosystem health depends on transitional changes reflected through the species behavior or local communities changes. Sound provides information about ecosystems without predefined information about the distributions or label s of each spot. Whereby, it is necessary to work with unsupervised algorithms that find patterns between study sites.

Collaborators

Universitad de Antoquia (UdeA, Medellin, Colombia)                                La Rochelle Université

Claudia Victoria ISAZA-NARVAEZ (Senior Researcher)         Thierry BOUWMANS (Senior Researcher)

Juan Manuel DAZA-ROJAS (Senior Researcher)         Anastasia ZAKHAROVA (Senior Researcher)

Nestor David RENDON-HURTADO (Junior Researcher)                 Jhony Heriberto GIRALDO-ZULUAGA (Junior Researcher)

   Wieke PRUMMEL (Junior Researcher)