Next Article in Journal
A Weighted Accuracy Measure for Land Cover Mapping: Comment on Johnson et al. Local Climate Zone (LCZ) Map Accuracy Assessments Should Account for Land Cover Physical Characteristics that Affect the Local Thermal Environment. Remote Sens. 2019, 11, 2420
Previous Article in Journal
Water Balance Standardization Approach for Reconstructing Runoff Using GPS at the Basin Upstream
Previous Article in Special Issue
Insect Target Classes Discerned from Entomological Radar Data
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Editorial

Radar Aeroecology

by
Jeffrey F. Kelly
1,* and
Phillip M. Stepanian
1,2
1
Plains Institute, University of Oklahoma, Norman, OK 73701, USA
2
Department of Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, Notre Dame, IN 46556, USA
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(11), 1768; https://doi.org/10.3390/rs12111768
Submission received: 25 May 2020 / Accepted: 26 May 2020 / Published: 30 May 2020
(This article belongs to the Special Issue Radar Aeroecology)
Aeroecology is an emerging discipline founded by Tom Kunz and colleagues in the early 2000s to address the challenges of studying animal flight in the lower atmosphere [1]. By this time, radar biology had a long history of both site-based studies that employ small specialized radar units [2] and regional studies using weather surveillance radars [3]. This research was largely the purview of a few specialists with access to radar equipment or data from national radar networks. Since that time advances in computing and tracking technologies have revolutionized the possibilities for studying life in the air [4]. Rapid expansion of the utility of radar for understanding flying animals is evinced in the breadth of studies contained in this Special Issue. The diversity of taxa studied has grown beyond what was imagined a decade ago. As impressive as this growth has been, globalization of this research endeavor has been even more profound. Finally, the disciplinary diversity of scientists contributing to radar aeroecology is a harbinger of future growth of this approach to understanding life in the air.
Studies in this issue build upon a rich history of applications in radar biology and demonstrate the breadth of advances in this area. Drake et al. [5] describe how a radar used to collect decades of insect flight data has been refurbished to improve data quality and quantity, as well as extend the elevational range of the sampling area. Further expanding capacity in radar entomology, Hao et al. [6] and Hu et al. [7] both propose innovative new approaches to advance our ability to classify insect detections in terms of taxonomy, morphology, and size. Continuing on the theme of zenith-pointing observations, Stepanian and Wainwright [8] use a vertically-oriented cloud radar to investigate animal flight behavior and atmospheric conditions during a solar eclipse.
Weather surveillance radar has been a primary tool for understanding the aeroecology of birds, bats, and insects, and as this science matures it progresses along several paths that are evident within the papers of this issue. Gauthreaux and Diehl [9] explore the efficacy of polarimetric weather radar observations for bioscatter classification and delineation. Nussbaumer et al. [10] and Kranstuaber et al. [11] both examine bird migration across Europe and are examples of burgeoning use of the OPERA weather radar network to estimate both density and distribution of migration, respectively. Finally, all of these advances in data processing allow a greatly expanded capacity to ask fundamental questions about the ecology of animal movement. The work by Caberera-Cruz et al. [12] demonstrates this potential by relating spatial patterns in bird migration to those of intensity of artificial lights at night. Similarly, Clipp et al. [13] explore the links between synoptic weather patterns and radar-based measurements of bird stopover distributions. Finally, Boero et al. [14] use weather radar data from Argentina to characterize the phenology of a free-tailed bat colony and compare radar observations with those from observers on the ground.
Taken together these studies span the spectrum of radar aeroecology, from hardware improvements and retrieval techniques, to conservation implications and the behavior of flying animals. This body of work represents global efforts, including studies from Australia, South America, Europe, Asia, and North America. Moreover, these research teams demonstrate interdisciplinary collaboration among biologists, engineers, meteorologists, and computer scientists. Looking forward, this breadth of topics, locations, and people bodes well for the future of radar aeroecology.

Author Contributions

Writing of the original draft, J.F.K.; review and editing, J.F.K and P.M.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the US National Science Foundation, grant number EF-1840230.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Kunz, T.H.; Gauthreaux, S.A.; Hristov, N.I.; Horn, J.W.; Jones, G.; Kalko, E.K.V.; Larkin, R.P.; McCracken, G.F.; Swartz, S.M.; Srygley, R.B.; et al. Aeroecology: Probing and modeling the aerosphere. Integr. Comp. Biol. 2008, 48, 1–11. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  2. Chapman, J.W.; Drake, V.A.; Reynolds, D.R. Recent insights from radar studies of insect flight. Annu. Rev. Entomol. 2011, 56, 337–356. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  3. Gauthreaux, S.A. Weather radar quantification of bird migration. BioScience 1970, 20, 17–19. [Google Scholar] [CrossRef]
  4. Chilson, P.B.; Frick, W.F.; Kelly, J.F.; Liechti, F. Aeroecology; Springer International Publishing AG: Cham, Switzerland, 2018. [Google Scholar]
  5. Drake, V.A.; Hatty, S.; Symons, C.; Wang, H. Insect Monitoring Radar: Maximizing Performance and Utility. Remote Sens. 2020, 12, 596. [Google Scholar] [CrossRef] [Green Version]
  6. Hao, Z.; Drake, V.A.; Taylor, J.R.; Warrant, E. Insect Target Classes Discerned from Entomological Radar Data. Remote Sens. 2020, 12, 673. [Google Scholar] [CrossRef] [Green Version]
  7. Hu, C.; Kong, S.; Wang, R.; Zhang, F. Radar Measurements of Morphological Parameters and Species Identification Analysis of Migratory Insects. Remote Sens. 2019, 11, 1977. [Google Scholar] [CrossRef] [Green Version]
  8. Stepanian, P.M.; Wainwright, C.E. Coupling Atmospheric and Biological Remote Sensing to Investigate Boundary-Layer Evolution and Animal Flight Behavior as Affected by the 2017 North American Solar Eclipse. Remote Sens. 2020, 12, 591. [Google Scholar] [CrossRef] [Green Version]
  9. Gauthreaux, S.; Diehl, R. Discrimination of Biological Scatterers in Polarimetric Weather Radar Data: Opportunities and Challenges. Remote Sens. 2020, 12, 545. [Google Scholar] [CrossRef] [Green Version]
  10. Nussbaumer, R.; Benoit, L.; Mariethoz, G.; Liechti, F.; Bauer, S.; Schmid, B. A Geostatistical Approach to Estimate High Resolution Nocturnal Bird Migration Densities from a Weather Radar Network. Remote Sens. 2019, 11, 2233. [Google Scholar] [CrossRef] [Green Version]
  11. Kranstauber, B.; Bouten, W.; Leijnse, H.; Wijers, B.-C.; Verlinden, L.; Shamoun-Baranes, J.; Dokter, A.M. High-Resolution Spatial Distribution of Bird Movements Estimated from a Weather Radar Network. Remote Sens. 2020, 12, 635. [Google Scholar] [CrossRef] [Green Version]
  12. Cabrera-Cruz, S.A.; Cohen, E.B.; Smolinsky, J.A.; Buler, J.J. Artificial Light at Night is Related to Broad-Scale Stopover Distributions of Nocturnally Migrating Landbirds along the Yucatan Peninsula, Mexico. Remote Sens. 2020, 12, 395. [Google Scholar] [CrossRef] [Green Version]
  13. Clipp, H.L.; Cohen, E.B.; Smolinsky, J.A.; Horton, K.G.; Farnsworth, A.; Buler, J.J. Broad-Scale Weather Patterns Encountered during Flight Influence Landbird Stopover Distributions. Remote Sens. 2020, 12, 565. [Google Scholar] [CrossRef] [Green Version]
  14. Boero, L.; Poffo, D.; Damino, V.; Villalba, S.; Barquez, R.M.; Rodríguez, A.; Suárez, M.; Beccacece, H.M. Monitoring and Characterizing Temporal Patterns of a Large Colony of Tadarida brasiliensis (Chiroptera: Molossidae) in Argentina Using Field Observations and the Weather Radar RMA1. Remote Sens. 2020, 12, 210. [Google Scholar] [CrossRef] [Green Version]

Share and Cite

MDPI and ACS Style

Kelly, J.F.; Stepanian, P.M. Radar Aeroecology. Remote Sens. 2020, 12, 1768. https://doi.org/10.3390/rs12111768

AMA Style

Kelly JF, Stepanian PM. Radar Aeroecology. Remote Sensing. 2020; 12(11):1768. https://doi.org/10.3390/rs12111768

Chicago/Turabian Style

Kelly, Jeffrey F., and Phillip M. Stepanian. 2020. "Radar Aeroecology" Remote Sensing 12, no. 11: 1768. https://doi.org/10.3390/rs12111768

APA Style

Kelly, J. F., & Stepanian, P. M. (2020). Radar Aeroecology. Remote Sensing, 12(11), 1768. https://doi.org/10.3390/rs12111768

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop