Examining songbird migration along the Delaware Bay: a comprehensive approach
Date
2013
Authors
Horton, Kyle
Journal Title
Journal ISSN
Volume Title
Publisher
University of Delaware
Abstract
There are several remote-sensing tools readily available for the study of nocturnally flying animals (e.g., migrating birds); each possessing unique measurement
biases. I used multiple techniques to measure migratory bird passage (weather surveillance
radar, thermal-infrared camera, acoustic recorder) and bird stopover (daily transect
counts) to better understand relationships among methods during the spring and
fall migrations of 2011 and 2012 in Lewes, DE. When comparing mean-nightly traffic rates across nights, I found methods to be positively correlated. I also found the
strength of correlations generally increased throughout the night, peaking 2-3 hours
before morning twilight. For radar and thermal imaging, the greatest observed traffic
rate tended to occur at or shortly after evening twilight, while for the acoustic recorder
peak bird flight-calling activity was observed just prior to morning twilight. Radar
and thermal imaging tended to show positive within night relationships, while acoustic
detections were inversely related to other methods, although all comparisons showed
a high degree of variability. I determined that height of nocturnal migrants strongly
influenced thermal imaging and flight call detections, positively for thermal imaging
and negatively for acoustic detections. Thermal imaging detections decreased with
increased mean ground speed and cloud cover presence; acoustic detections decreased
with increased mean ground speed but showed no influence with the presence of clouds.
My comparisons of radar target flow with acoustic and thermal imaging data to assess
detection probabilities are novel and provide insight into the biases of these tools for
detecting flying animals. With my assessment of nocturnal passage estimates (radar
reflectivity and thermal-infrared detections) and daily transect counts I found relationships
between nocturnal traffic and stopover densities to be strongest during the spring,
and between stopover densities and weather surveillance radar data from the following
evening. Although we found relationships to be positive, they tended to be weak and
likely due to the complexity of these comparisons. I identified several probable sources
of bias, including study-site placement, our inability to accurately estimate migrant
turnover, and determine nocturnal migrant composition.