Measuring biodiversity change due to Amazon forest degradation

Amazon soundscapes reveal key markers of forest degradation from fire and logging

Safeguarding tropical forest biodiversity requires tractable solutions for monitoring ecosystems over time. In the Amazon, logging and fire are altering forest carbon and composition, but the long-term consequences for wildlife remain unclear, especially for lesser-known animal taxa. Sound surveys may reduce the effort and cost associated with long-term monitoring by simultaneously capturing multiple species and sites, but improved analytic methods are needed to measure differences in animal communities based on sound.

Published in: Animal soundscapes reveal key markers of Amazon forest degradation from fire and logging Proceedings of the National Academy of Sciences, 119 (18), e2102878119. 

Rappaport, D. I., Swain, A., Fagan, W.F., Dubayah, R., Morton, D.C. (2022)

We show that diurnal measurements of animal diversity from ecoacoustics provide a very different picture of changing animal community following degradation than what can be surmised from field studies of finite taxa during finite snapshots in time. By applying network theory to soundscape data for the first time, we provide a new and promising analytic avenue for characterizing animal communities.

Here, we combined data from diurnal acoustic surveys, airborne lidar, and satellite time series covering logged and burned forests (n=39) in the southern Brazilian Amazon to identify acoustic markers of degradation using statistical and novel network-based analyses. Our findings contradicted theoretical expectations that animal communities in more intact habitats occupy more ‘acoustic niche’ space, even during bird choruses. Instead, we found biomass was not a consistent proxy for biodiversity following forest degradation, with divergent soundscape responses in logged and burned forests over time.  Animal communication networks highlighted a stark and sustained shift in structure after multiple fires: animal communities in forests burned at least twice were quieter, less connected, and more homogenous than logged or once-burned forests. In contrast to fire, the patterns following logging appear to reflect community recovery rather than reassembly. Broadband cicadas and insect choruses accounted for the dominant signals of degradation (e.g. mid-morning, noon and nighttime), warranting additional investment into distributed monitoring infrastructure for collecting continuous diurnal measurements. Based on the consistency in soundscape structure among replicate sites, animal communication networks may represent dynamic typologies for monitoring successional state following disturbance. Soundscape data covering multiple taxa highlight the biodiversity co-benefits from protecting Amazon forests from recurrent fire activity. Soundscapes represent a promising pathway for standardizing community-level assessments of tropical biodiversity change.