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Escucha Aves is a two-year Audubon-led initiative that combines autonomous sound recorders, AI-assisted bird detection and community review to give protected-area managers repeatable evidence about birds in the Tropical Andes. Communities and local organizations deploy recorders, upload the resulting audio, check the software’s suggested identifications and use dashboards to examine trends. The approach is intended to complement field knowledge, not replace it.
Audubon reported 193 recorders deployed across nine Colombian locations by the first weekend of May 2026, including 19 installed in the Zonquer páramo near Puerres, Nariño. Those numbers describe deployment, while the broader project’s planned scale and conservation benefits remain targets rather than measured outcomes.
What Escucha Aves is designed to do
Protected areas often have baseline bird inventories but lack a monitoring program that can be repeated in the same way over many months or years. Escucha Aves addresses that gap by turning regular recordings into a potential time series: the same kinds of sensors can sample the same territory at programmed intervals, and the resulting observations can be reviewed and compared over time.
Audubon describes the initiative as community-led acoustic monitoring in new or expanding protected areas associated with Conserva Aves. Its stated aims are to identify species, measure changes in bird communities, build local technical capacity and provide evidence for management decisions. They are aims, not independently measured results. No source currently establishes that the project has changed a legal boundary, prevented resource exploitation or produced a quantified ecological improvement.
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Jorge Velásquez, Audubon’s Director of Science for Latin America and the Caribbean, explains the method this way: “The Escucha Aves project consists of training communities and local organizations in the use of acoustic monitoring to identify the species present in their territories and measure changes over time. For this research, we use small recorders programmed to capture sounds at regular intervals throughout the 24-hour cycle, and later we use AI tools to identify the songs found in the recordings.”
Where the initiative operates and how large it may become
Reported Colombian deployments
Audubon’s July 9, 2026 implementation report listed deployments at Puerres and Ricaurte in Nariño; San Carlos in Antioquia; Tauramena in Casanare; Charalá in Santander; San Juan Nepomuceno in Bolívar; and Calima and Dagua in Valle del Cauca. Taken together with another Colombian location in the report, these amounted to 193 recorders across nine locations during the first weekend of May 2026.
At the Zonquer páramo in the Atuczara territory near Puerres, the Gran Tescual Indigenous Reserve helped install and georeference 19 units on May 1 and 2, 2026. Audubon presents this as documentation of a relatively little-monitored landscape. The report does not claim that the installation discovered previously unknown species.
Planned regional scale
Audubon’s project overview describes three pilot Colombian reserves and an expansion to 15 sites in Colombia, Peru and Bolivia, with the potential to serve as a model for more than 70 Conserva Aves sites. A separate July 2026 account describes the two-year effort as spanning 17 projects and aiming for 600 recorders and more than 1.3 million minutes of bird recordings. The 600-unit and 1.3-million-minute figures are targets, not completed totals.
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| Figure | What it means | Status and date |
|---|---|---|
| 193 recorders | Units deployed across nine Colombian locations | Reported deployment, May 2026 |
| 19 recorders | Units installed and georeferenced at Zonquer near Puerres | Reported installation, May 1–2, 2026 |
| 600 recorders | Planned equipment for the wider initiative | Target reported in July 2026 |
| More than 1.3 million minutes | Planned volume of bird recordings | Target reported in July 2026 |
| 15 sites and 70+ potential sites | Expansion described in Audubon’s project overview | Planned scope, not an achieved count |
How AI-assisted acoustic monitoring works
1. Recorders sample the soundscape
Small autonomous recorders are programmed to capture audio at regular intervals through the 24-hour cycle. They can collect dawn choruses and other periods without requiring a person to remain at the site. Installation teams record the position of each unit, making the audio traceable to a place and allowing later comparisons among sites.
2. Audio is uploaded and segmented
After collection, recordings are uploaded to the project’s digital workflow. Long files are handled as segments so that models can process manageable clips and users can inspect the portion of audio associated with a proposed detection.
3. Models propose candidate species
The platform being developed for Escucha Aves, called Chorus, is described by WildMon as processing recordings with models including BirdNET, Perch and BirdSET. It also uses audio embeddings and location-specific species lists informed in part by GBIF and eBird. These tools narrow a large archive to candidate bird sounds; they do not make every identification correct automatically.
4. People validate the suggestions
Practitioners can inspect a spectrogram, listen to the clip, compare it with reference calls and confirm or reject an identification. This human-in-the-loop step is essential when calls overlap, recordings contain noise, a species is unusual for the location or the model is uncertain. The available descriptions explain the workflow and its planned capabilities, but they do not provide an independently validated accuracy rate.
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5. Results feed dashboards and indicators
Validated observations can be exported and displayed in dashboards for tracking trends and biodiversity indicators. A manager might use repeated detections to ask whether a species remains present, whether activity changes seasonally or whether a habitat intervention deserves closer attention. The data become more useful when sampling schedules, recorder locations and validation rules are documented consistently.
Why community participation is central
Escucha Aves is not presented as a remote sensor network operated solely by outside analysts. Community partners participate in deployment, training and interpretation, while local users review detections and use the resulting information. That arrangement helps connect automated analysis with knowledge of terrain, seasons, culturally important species and practical access constraints.
Natalia Chamorro, an agroforestry engineer, reserve member and Escucha Aves coordinator for Gran Tescual, describes the approach as compatible with local learning: “From the reserve perspective,” says Chamorro, “following the Escuela Viva process and the training sessions, we are not closed off to technology. On the contrary, we are ready to collaborate, to share what we have, and to learn how to take advantage of these technological tools.”
Giovanni Cárdenas of Asociación Calidris emphasizes stewardship of the information: “this knowledge remains within the territory under the stewardship of the Indigenous reserve. The primary files and results, together with feedback on the goals achieved, will strengthen knowledge of the territory and foster ownership of this specific technology.” His statement describes the intended data relationship; it is not evidence that every participating community already has the same long-term data-governance arrangement.
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Gran Tescual Indigenous Governor Vicente Obando connects monitoring with the reserve’s broader ecological and cultural responsibilities: “As a community, we recognize the importance of ecological restoration because, in our life plan, restoring the land begins with restoring our way of thinking—a legacy passed down by our elders. Within that vision, we understand the importance of conserving birds. They are guardians of seeds and biodiversity, messengers of the spirits, and a bridge between the spirituality of the cosmos and the sacred places within our environmental reserves.”
How recordings can inform protected-area management
Acoustic data are most useful as evidence in a management cycle rather than as a standalone answer. A practical cycle has five parts:
- Define the question. Decide whether the priority is a species list, seasonal activity, a comparison among habitats or a baseline before restoration.
- Design repeatable sampling. Select recorder locations, schedules, deployment duration and file-handling rules that can be repeated. Record georeferenced metadata with every unit.
- Review and validate. Use AI to prioritize clips, then have trained reviewers check spectrograms and sounds. Flag uncertain detections instead of forcing a species label.
- Interpret with local knowledge. Discuss whether apparent changes could reflect weather, microphone placement, access, migration, habitat work or a change in recording effort.
- Connect evidence to an action. Use the findings to focus field surveys, adjust restoration priorities, identify areas needing protection or decide what the next monitoring round should test.
Velásquez says the project arose from “the need to understand exactly what we are conserving within the Conserva Aves initiative,” because baseline inventories can support designation of protected areas while a complete, repeatable monitoring strategy is still missing. Acoustic monitoring is intended to help fill that gap; it is not a substitute for field inventories, habitat measurements or consultation with people who know the territory.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What Chorus contributes—and what remains unproven
WildMon describes Chorus as a modular platform intended to reduce technical barriers while allowing additional AI models and analytical capabilities to be added. Dr. Nelson Buainain, WildMon’s Head of Product & Innovation, says: “Every design decision behind Chorus has been guided by a simple question: how do we help conservation practitioners use advanced AI without having to make complex technical decisions?” He also says, “We’re building a modular platform that removes technical barriers while allowing new AI models and analytical capabilities to be incorporated over time.”
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Those statements describe the platform’s development direction. The available sources do not establish a public commercial release, a current subscription price, a named recorder model, or a benchmark showing how Chorus performs against alternative systems. They also do not show that an automated label is reliable without review. Anyone adopting a similar workflow should budget for data management, reviewer time, equipment maintenance and field verification.
How to judge an acoustic-monitoring program
Escucha Aves presents an integrated method rather than a controlled comparison of competing products. When evaluating any bird-acoustic program, use these questions:
- Coverage: How many sites and habitats can be sampled, and are recorder locations documented well enough to revisit?
- Repeatability: Can the same schedule and analysis be run again so that a trend is distinguishable from a one-time observation?
- Validation: Who reviews detections, how are uncertain clips handled and is model performance checked for the local species community?
- Community role: Do local partners receive training, participate in decisions and retain practical access to primary files and results?
- Management connection: Is there a defined decision that the evidence will inform, rather than an archive created without a use?
A large number of recordings alone does not guarantee a useful result. Changes in microphone placement, weather, vegetation, recorder uptime or reviewer effort can look like ecological change. A credible interpretation therefore reports sampling effort and uncertainty alongside species detections.
Partners and support
Audubon names WildMon and the Kitzes Lab at the University of Pittsburgh as technology partners. Asociación Calidris contributes to local capacity work, and the Gran Tescual Indigenous Reserve was the local partner for the reported Zonquer deployment. The initiative has support from the Bezos Earth Fund after selection as a global winner of the AI Grand Challenge for Climate and Nature Fund.
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Conserva Aves is described by Audubon as a regional initiative led by American Bird Conservancy, National Audubon Society, BirdLife International, Birds Canada and RedLAC to promote subnational protected areas from Mexico to Chile. Escucha Aves is positioned as a monitoring component for protected areas connected with that wider effort.
What readers should—and should not—conclude
Escucha Aves demonstrates a way to combine autonomous recording with AI triage and community validation in places where repeated monitoring has been difficult. The reported Colombian deployments show that equipment and training are already being put into the field, while the larger recorder and recording-minute figures remain future targets. The project’s value will ultimately depend on sustained sampling, careful validation, local stewardship of data and decisions that use the evidence.
At present, the public descriptions establish a method, a set of partners and deployment milestones. They do not establish a conservation-impact statistic, a universal AI accuracy rate or proof that monitoring has already changed protection outcomes. Those distinctions matter: acoustic monitoring can make a conservation program more systematic, but only people working with the territory can determine what the evidence means and what action follows.
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