Early detection of human impacts using acoustic monitoring: an example with forest elephants

The impacts of human activities and climate change on animal populations often take considerable time before they are reflected in typical measures of population health such as population size, demography, and landscape use. Earlier detection of such impacts could enhance the effectiveness of conservation strategies, particularly for species with slow population growth. Passive acoustic monitoring is increasingly used to estimate occupancy and population size, but this tool can also monitor subtle shifts in behavior that might be early indicators of changing impacts. Here we use data from an acoustic grid, monitoring 1250 km2 of forest in the northern Republic of Congo, to study how forest elephants (Loxodonta cyclotis) assess the risk of poaching across a landscape that includes a national park as well as active and inactive logging concessions. By quantifying emerging patterns of behavior at the population level, arising from individual-based decisions, we gain an understanding of how..., Core data are 24-hour continuous sound files acquired on 50 digital sound recorders deployed in the northern Republic of Congo. Sound files are processed with a detection algorithm running in MatLab, which tags putative elephant rumble vocalizations. Output files from the detection process are reviewed to remove false positive detections. Data tables were compiled from the edited detector output files, which include the location, date, and time of each verified vocalization. Ecological metadata (season, habitat, study stratum, etc.) were then added to these files to construct analysis dataset tables., , # Data from: Early detection of human impacts using acoustic monitoring: an example with forest elephants

This README file was generated on 2024-07-09 by Peter H. Wrege

## GENERAL INFORMATION

**Author Information**

* Principal Investigator Contact Information
* name: Peter H. Wrege
* Institution: Cornell University
* Email: [[e-mail]](mailto:[e-mail])

**Date of data collection:** 15Jan2017-27April2021

**Geographic location of data collection:** Nouabale-Ndoki National Park, Republic of Congo

## SHARING/ACCESS INFORMATION

1. **Licenses/restrictions placed on the data:** CC0 1.0 Universal (CC0 1.0) Public Domain
2. **Publications that cite or use the data:**
Peter H. Wrege, Frelcia Bien-Dorvillon Bambi, Phial Jackel Ferdy Malonga, Onesi Jared Samba, Terry Brncic (2024). Early detection of human impacts using acoustic monitoring: an example with forest elephants. PLOS ONE
3. **Data is also available at:**
The Registry of Open Data on Amazon Web Services ...