Quantifying animal phenology in the aerosphere at a continental scale using NEXRAD weather radars

One of the primary ecological manifestations of climate change is a shift in the timing of events in a species' annual cycle. Such phenological shifts have been documented in numerous taxa, but data for animals have been derived primarily from human observers rather than networks of instruments used for remote sensing. The potential to use the network of weather radars in the United States (NEXRAD) to remotely sense animal phenologies could advance our understanding of the spatiotemporal scaling of phenologies in relation to shifts in local and regional climate. We tested the utility of NEXRAD radar products for quantifying the phenology of the purple martin (Progne subis) at summer roost sites in the United States. We found that the maximum radar reflectivity value in the hour before local sunrise above purple martin roost sites contained a strong phenological signal of significantly increased radar reflectivity during June, July, and August 2010. The seasonal pattern in this radar signal matched our expectation of the timing of formation and dissipation of these seasonal roosts. Radar reflectivity was greater and less variable when considering roosts close to NEXRAD stations (<25 km) than when including all 358 documented roosts; there was a negative relationship between maximum reflectivity and the distance between a roost and the nearest NEXRAD. Our results suggest that: (1) mosaicked NEXRAD radar products are a valuable source of information on the phenology of bioscatter in the aerosphere; (2) citizen scientists who document the locations of roosts on the ground are providing critical information for advancing our understanding of animal phenology and aeroecology; and (3) ongoing research that examines spatiotemporal relationships among radar-derived phenologies in airborne organisms, climate, and land cover change are likely to provide further insights.

[1]  J. Abatzoglou,et al.  Tracking the rhythm of the seasons in the face of global change: phenological research in the 21st century. , 2009 .

[2]  S. Gauthreaux,et al.  SPATIAL AND TEMPORAL DYNAMICS OF A PURPLE MARTIN PRE-MIGRATORY ROOST , 1999 .

[3]  Jason W. Horn,et al.  Analyzing NEXRAD doppler radar images to assess nightly dispersal patterns and population trends in Brazilian free-tailed bats (Tadarida brasiliensis). , 2007, Integrative and comparative biology.

[4]  John K. Westbrook,et al.  Partly Cloudy with a Chance of Migration: Weather, Radars, and Aeroecology , 2012 .

[5]  T. Wilbanks,et al.  Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change , 2007 .

[6]  Sidney A. Gauthreaux,et al.  RADAR ORNITHOLOGY AND BIOLOGICAL CONSERVATION , 2003 .

[7]  Josh Van Buskirk,et al.  Variable shifts in spring and autumn migration phenology in North American songbirds associated with climate change , 2009 .

[8]  Jian Zhang,et al.  Four-Dimensional Dynamic Radar Mosaic , 2004 .

[9]  Jian Zhang,et al.  Constructing Three-Dimensional Multiple-Radar Reflectivity Mosaics: Examples of Convective Storms and Stratiform Rain Echoes , 2005 .

[10]  Elizabeth R. Ellwood,et al.  Forecasting phenology under global warming , 2010, Philosophical Transactions of the Royal Society B: Biological Sciences.

[11]  S. Gauthreaux,et al.  USE OF WEATHER RADAR TO CHARACTERIZE MOVEMENTS OF ROOSTING PURPLE MARTINS , 1998 .

[12]  J. McGinley,et al.  Improving QPE and Very Short Term QPF: An Initiative for a Community-Wide Integrated Approach , 2007 .

[13]  C. Both,et al.  Climate change and population declines in a long-distance migratory bird , 2006, Nature.

[14]  Hans Peter Schmid,et al.  Evidence of increased net ecosystem productivity associated with a longer vegetated season in a deciduous forest in south‐central Indiana, USA , 2010 .

[15]  David B. Roy,et al.  Phenology of British butterflies and climate change , 2000 .

[16]  R. Ohlemüller,et al.  Rapid Range Shifts of Species Associated with High Levels of Climate Warming , 2011, Science.

[17]  A. Strahler,et al.  Monitoring vegetation phenology using MODIS , 2003 .

[18]  C. Rahbek,et al.  Local temperature fine-tunes the timing of spring migration in birds. , 2010, Integrative and Comparative Biology.

[19]  S. Gauthreaux,et al.  LARGE-SCAI.E MAPPING OF PURPLE MARTIN PRE-MIGRATORY ROOSTS USING WSR-88D WEATHER SURVEILLANCE RADAR , 2004 .

[20]  Ronald P. Larkin,et al.  RADAR OBSERVATIONS OF BIRD MIGRATION OVER THE GREAT LAKES , 2003 .

[21]  D. Lack,et al.  Detection of Birds by Radar , 1945, Nature.

[22]  Jian Zhang,et al.  National mosaic and multi-sensor QPE (NMQ) system description, results, and future plans , 2011 .

[23]  Lee A. Vierling,et al.  A simple filtered photodiode instrument for continuous measurement of narrowband NDVI and PRI over vegetated canopies , 2010 .

[24]  Robert J. Serafin,et al.  Operational Weather radar in the United States : Progress and opportunity , 2000 .

[25]  O. Hoegh‐Guldberg,et al.  Ecological responses to recent climate change , 2002, Nature.

[26]  Jr. Sidney A. Gauthreaux,et al.  Bird Migration: Methodologies and Major Research Trajectories (1945-1995) , 1996 .

[27]  W. G. Harper ROOSTING MOVEMENTS OF BIRDS AND MIGRATION DEPARTURES FROM ROOSTS AS SEEN BY RADAR , 2008 .

[28]  H. Mooney,et al.  Shifting plant phenology in response to global change. , 2007, Trends in ecology & evolution.

[29]  A. Miller‐Rushing,et al.  Toward a synthetic understanding of the role of phenology in ecology and evolution , 2010, Philosophical Transactions of the Royal Society B: Biological Sciences.

[30]  Timothy D. Crum,et al.  The WSR-88D and the WSR-88D Operational Support Facility , 1993 .

[31]  C. Parmesan Ecological and Evolutionary Responses to Recent Climate Change , 2006 .

[32]  C. McCulloch,et al.  Predicting the effects of climate change on avian life-history traits , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[33]  N. Pettorelli,et al.  The Normalized Difference Vegetation Index (NDVI): unforeseen successes in animal ecology , 2011 .

[34]  Jenny A. Hodgson,et al.  Predicting insect phenology across space and time , 2011 .

[35]  Ramakrishna R. Nemani,et al.  A global framework for monitoring phenological responses to climate change , 2005 .

[36]  Jian Zhang,et al.  Three- and four-dimensional high-resolution national radar mosaic , 2004 .

[37]  Jason W. Horn,et al.  Aeroecology: probing and modeling the aerosphere. , 2007, Integrative and comparative biology.