Integrating 3D information from ecoacoustics and lidar remote sensing to characterize landscape-level biodiversity variability

Biodiversity monitoring in support of international efforts such as GEO BON requires scalable solutions that leverage remote sensing and analysis tools. Monitoring protocols that capture a diversity of taxa and minimize the need for expert knowledge during data collection offer a promising pathway for routine assessment of essential biodiversity variables (EBVs). Here, we present a novel methodological approach that combines ecoacoustic and airborne lidar data to characterize biodiversity across a degraded forest landscape along the arc of deforestation in the southern Amazon. This integrated remote sensing and modeling methodology overcomes several of the key obstacles for biodiversity monitoring in complex tropical forest landscapes. Ecoacoustics represent a novel, cost-effective avenue for directly observing the animal community at broad scales, while circumventing the need to identify individual taxa. The 3D configuration of acoustic space (time, frequency, amplitude) is strongly associated with the composition and diversity of the animal community within range of acoustic sensors. Further, the 3D configuration of physical space, which can be captured by lidar, is strongly associated with species diversity and acoustic transmission. We integrated coincident airborne lidar and ecoacoustic data along gradients of forest degradation in a hierarchical occupancy modeling framework to characterize biodiversity variability at the landscape scale, while accounting for imperfect detection. The biodiversity legacy of forest degradation was clearly reflected within the patterns of acoustic space utilization, with the largest transformations evident after recurrent fire events. This work paves the way for more integrated research applications of remote sensing and demonstrates the utility of ecoacoustics and lidar to advance biodiversity monitoring at the scales needed to support global efforts such as GEO BON. This integrated approach may also represent a vehicle for considering ecosystem services to support other international objectives that routinely collect both field and lidar data, such as REDD+, which could further advance biodiversity monitoring integral to EBV goals.