Juan Sebastian UlloaInstituto de Investigación de Recursos Biológicos Alexander von Humboldt · Biodiversity Assessment and Monitoring
Juan Sebastian Ulloa
PhD Ecology
Scientist and engineer developing smart tools for ecology and biodiversity conservation.
About
18
Publications
9,275
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277
Citations
Citations since 2017
Introduction
Acoustic signalling is a common behavioural trait among terrestrial animals. The rich sound textures of neotropical forest echo that wildlife is not only abundant, but also diverse and dynamic. How to best measure tropical acoustic diversity to address ecological questions? Aiming to develop more accurate and effective monitoring programs, I adapt engineering tools to capture (e.g. automated acoustic sensors) and decipher (e.g. machine learning algorithms) tropical soundscapes.
Additional affiliations
June 2019 - present
September 2014 - June 2018
Muséum National d'Histoire Naturelle - Université Paris-Sud
Position
- PhD Student
September 2013 - June 2014
Publications
Publications (18)
Noise is one of the fastest growing and most ubiquitous type of environmental pollution, with prevalence in cities. The COVID-19 confinement in 2020 in Colombia led to a reduction in human activities and their associated noise. We used this unique opportunity to measure the impacts of noise on urban soundscapes, and explore the effects of urbanizat...
Soundscape ecology, ecoacoustics and bioacoustics have witnessed an explosion of work over the last decade due to the advances in passive acoustic recorders, new conceptual frameworks that integrate the study of sound into environmental change research, abilities to store and analyze massive data, and the growing need to understand how the rapid de...
Background:
Anurans largely rely on acoustic communication for sexual selection and reproduction. While multiple studies have focused on the calling activity patterns of prolonged breeding assemblages, species that concentrate their reproduction in short-time windows, explosive breeders, are still largely unknown, probably because of their ephemer...
The confinement caused by the COVID-19 pandemic was the ideal scenario to implement an unprecedented strategy that assessed the impact that urbanization and human activities have on the soundscape of cities.
La iniciativa 'Paisajes sonoros desde tu ventana' posibilitó, por primera vez y a nivel nacional, medir los efectos de las actividades humanas en el paisaje sonoro de las ciudades. Los sonidos originados por la fauna silvestre son el 59 % de los registros y los sonidos originados por los humanos el 18 %. Con el paulatino retorno a la normalidad, se...
Passive acoustic monitoring is growingly being applied to terrestrial, marine and freshwater environments, providing cost‐efficient methods for surveying biodiversity. However, processing the avalanche of audio recordings remains challenging, and represents nowadays a major bottleneck that slows down its application in research and conservation. We...
El monitoreo acústico permite evaluar cambios espacio-temporales en poblaciones animales. Sin embargo, analizar grandes volúmenes de información es desafiante. Se evaluó el desempeño de una técnica de detección (función autodetec del paquete warbleR de R) para identificar vocalizaciones de Megascops centralis, utilizando 6877 grabaciones de un minu...
The global lockdown to mitigate COVID-19 pandemic health risks has altered human interactions with nature. Here, we report immediate impacts of changes in human activities on wildlife and environmental threats during the early lockdown months of 2020, based on 877 qualitative reports and 332 quantitative assessments from 89 different studies. Hundr...
Las rapaces nocturnas, búhos y lechuzas, son un grupo de aves con importantes roles en los ecosistemas, como bioindicadores y predadores tope. Entender aspectos de su ecología e historia natural es vital para la conservación puesto que pueden actuar como especies sombrilla. Dada su naturaleza nocturna, su estudio es complicado, sin embargo, las her...
en In tropical regions, some anuran species breed "explosively", reproducing in massive and highly diverse aggregations during a brief window of time. These aggregations can serve as acoustic beacons, attracting other anurans toward seasonal ponds. We hypothesize that conspecific and heterospecific calls play a role in navigation toward ponds and s...
Tropical forests are facing threats that may affect the dynamics of seed dispersers which participate in the forest regeneration. To implement appropriate conservation programs, it appears necessary to monitor seed dispersers and to estimate their response to local changes. Here, we used non-invasive ecoacoustic methods to monitor the activity of a...
El estudio de paisajes sonoros es una oportunidad costo efectiva de investigar los procesos que afectan la diversidad biológica de un ecosistema, ofreciendo nuevas herramientas para el manejo del territorio y abriendo perspectivas para atraer otro tipo de público interesado en la conservación.
Ecoacoustic research mainly relies on signal and data analysis. Beyond manual inspection, the current solutions to decipher the content of population, community or soundscape recordings either refer to supervised classification methods that need labelled data (e.g. SVM, CNN, RF) or to global diversity indices that totally avoid species identificati...
• Acoustic population monitoring is a noninvasive method that can be deployed continuously over long periods of time and at large spatial scales. One of the newly discovered threats acting on biological diversity is anthropogenic noise. High levels of anthropogenic noise occur in aquatic environments, yet their effects on animals living in freshwat...
Projects
Projects (2)
scikit-maad is an open source Python package dedicated to the quantitative analysis of environmental audio recordings. This package was designed to (1) load and process digital audio, (2) segment and find regions of interest, (3) compute acoustic features, and (4) estimate sound pressure level. This workflow opens the possibility to scan large audio datasets and use powerful machine learning techniques, allowing to measure acoustic properties and identify key patterns in all kinds of soundscapes.
GitHub page: https://github.com/scikit-maad/scikit-maad
Documentation: https://scikit-maad.github.io/
