ColForPAM

Unsupervised Graph-Based Tools for Biodiversity Planning in Human-Impacted Landscapes 

DESCRIPTION

Global biodiversity and ecosystems face increasing threats from land use changes and global warming, leading to a pressing need for effective conservation efforts. A profound understanding of landscape heterogeneity, which refers to the variability of natural features, is essential for designing targeted conservation strategies. 

Soundscape analysis, which involves studying the diverse sound sources within ecosystems, has emerged as a promising tool for monitoring and understanding these complex environments. However, traditional methods in soundscape analysis often rely on supervised learning models that are limited by their dependency on labeled data, potentially overlooking unknown ecological patterns. 

An innovative approach introduced by recent research uses "sonotypes" to characterize the biophony of landscapes, providing a detailed acoustic profile. In response to the limitations of current methodologies, this research proposes an unsupervised graph-based network architecture. The project aims to incorporate the acoustic profile of the sites and temporal data and thereby yield highly interpretable results that capture the dynamic relationships and complexities of ecosystems. Thus, it will provide a comprehensive understanding of acoustic heterogeneity across geographical locations, ultimately helping in the design of more informed and effective conservation strategies.

Collaborators

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

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

Maria GUERRERO-MURIEL (Junior Researcher) Anastasia ZAKHAROVA (Senior Researcher)

      (Junior Researcher)