Modeling Bird Migration in Changing Habitats

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Modeling Bird Migration in Changing Habitats

• James A. Smith NASA GSFC
• Jill L. Deppe UMBC GEST

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Outline

• Where weve been -- Where we are now
  Where were going
• Some technical aspects of our work
• How were going about it
• Modeling
• Calibration
• Validation Approach
• Phenotypic plasticity scenario
• Wrap-up

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Where Weve Been
Spherical Birds
Myiarchus nasaii
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Where We Are Now
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Where Were Going
Use primarily a mechanistic approach to
understand how migrating organism respond to
changes in their environment
What are the impacts of resulting changes in the
quality, location, and quantity of
stopover habitat?
What is the coupling between timing of migration
and key environmental processes?
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Technical challenge

• Our animals are completely mobile and free to
  move anywhere
• At 10 min resolution, there are over 100,000
  candidate stopover locations in NA
• (Previous research limited to few, fixed
• stopovers, e.g. 50)

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Scientific Aspect

• Were attacking the en-route migration problem
• Our organisms move through a changing
  spatio-temporal environment
• (Most research deals with spring migration, few
  address winter we are model both)

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Characteristics

• Individual based biophysical model
• Movement behavior and decision rules
• Daily time step
• Arbitrary geographic grid
• Simulate the migration routes, timing and energy
  budgets of individual birds under dynamic weather
  and land surface conditions
• (Driving variables from satellite and numerical
  weather prediction models)

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Changing habitat

• Exploring two avenues
• One is data driven using dynamic landscape layers
  derived from remote sensing and bird location
  records
• Second is a functional Jarvis type approach
  similar to how people model stomatal resistance
  again using satellite/climate models

(Hybrid)
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Effective Fuel Deposition Rate (FDR)

• Ecological niche modeling

Max Ent
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Functional approach

• FDR Fopt ƒ(NDVI) f(soil moist)
• Scale between 0 and maximum observed in field

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Evolutionary learning
Initialize a population with random candidate
solutions and then repeatedly expose the
population to the environment, calculating
fitness of survivors, reproducing and
selecting individuals for the next population
Reproduction
Currently Pseudo Maybe Natural Later
Group
Stopover behavior
Endogenous direction
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Evolutionary learning
Fitness (50th percentile)
Generations
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Consistent and Plausible
Bird banding data Survey data at stopovers Stable
isototpe analysis Telemetry data
Bird Hydrographs
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Phenotypic Plasticity

• Migrate birds through a non-limiting landscape
• Then
• Fly them over more natural landscapes
• i) Without relearning
• ii) With ability to adapt their behavior

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Dynamic Habitat

• Monthly Landscape Features
• i) Maximum Number of Days with Ground Frost (10)
• ii) Effective FDR / Stop overs scaled to NDVI
• North American Topographic Barrier
• (2000 meters --- mainly impact in Rocky
  Mountains)

Average over dry years 1982-1988
Palmer Index
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Non Limiting Landscape
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No Learning Adaptation
Shifts in Pattern
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No Learning Adaptation
Change in Stop over Strategy
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No Learning Adaptation
Increase in Fitness Distribution
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Wrap-Up

• Modeling and simulation test bed coming along
  fine
• Developing evidence of plausibility and
  consistency
• Have linkages with an AIST GMU project (Liping
  Di) pragmatics for linking models to satellite
  and data systems
• ( 540 met files (3 dry years 3 wet years ) x
  90 days for wetland study

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Publications
M. Wikelski, R.W. Kays, N.J. Kasdin, K. Thorup,
J.A. Smith and G.W. Swenson, Jr.. 2007. Going
wild what a global small-animal tracking system
could do for experimental biologists. Journal
of Experimental Biology 210 181-186. J.A. Smith
and J.L. Deppe. 2007. Simulating bird migration
using satellites and Biophysics. Proc. Of the
IASTED Symposium on Environmental Modeling and
Simulation, 5096-11. J.L. Deppe, K. Wessels,
and J.A. Smith. 2007. Alaska at the crossroads of
migration Space-based ornithology. Alaska Park
Science, 653-58. J.A. Smith and J.L. Deppe.
2008. Simulating the effects of wetland loss and
inter-annual Variability of the fitness of
migratory bird species. IEEE IGARSS J.A. Smith
and J.L. Deppe. 2008. Space-based
ornithologystudying bird migration and
environmental change in North America. SPIE
ERS08, Remote sensing for agriculture, ecosystems,
and hydrology.