2020 ESA Annual Meeting (August 3 - 6)

PS 1 Abstract - Agricultural landscape composition linked with acoustic measures of avian diversity

Adam Dixon, Department of Geography & Environmental Systems, University of Maryland, Baltmore County, Baltimore, MD, Erle Ellis, Department of Geography & Environmental Systems, University of Maryland, Baltimore County, Baltimore, MD and Matthew E. Baker, Geography & Environmental Systems, University of Maryland Baltimore County, Baltimore, MD
Background/Question/Methods

Measuring, monitoring, and managing biodiversity across agricultural regions depends on methods that can combine high-resolution mapping of landscape patterns with local biodiversity observations. Previous approaches to estimate biodiversity in relation to agricultural landscape structure have relied on labor-intensive and costly fieldwork to acquire data on both species and habitat characteristics. The advent of low-cost passive acoustic monitoring and high resolution UAS and satellite imagery offers the potential to lower barriers to measurement by greatly reducing field costs. It remains unclear whether and how these passive monitoring techniques might be used to effectively in intensively used agricultural landscapes This study explores the potential to monitor biodiversity in agricultural landscapes by linking high-resolution remote sensing with passive acoustic monitoring. Land cover maps produced using a small unmanned aerial system (UAS) and PlanetScope (PS) satellite imagery were used to investigate relationships between landscape patterns and an acoustically derived biodiversity index (vocalizing bird species richness) across 12 agricultural sample locations equipped with acoustic recorders in Iowa, USA during the 2018 growing season.

Results/Conclusions

Statistical assessment revealed a significant direct association between vocalizing bird richness and percent noncrop vegetation cover. High spatial resolution (1 m) UAS mapping produced stronger statistical associations than PS-based maps (3 m) for landscape composition metrics. Landscape configuration metrics (Shannon’s diversity index, contagion, perimeter-area-ratio, and circumscribing circle index) were either cross-correlated with composition metrics or unusable owing to complete landscape homogeneity in some agricultural landscape samples. This study shows that high resolution mapping of noncrop vegetation cover can be linked with acoustic monitoring of unique bird vocalizations to provide a useful indicator of biodiversity in agricultural landscapes. More importantly, is that our approach to ecological landscape research has the potential to be highly scalable and the importance of these relationships can continue to be evaluated with refinement of our characterization methods. The effectiveness of small habitat complexes toward biodiversity may be assessed in other human dominated landscapes which are often disregarded for conservation potential.