Autonomous Monitoring of Vulnerable Habitats
And other tales..
Robin Freeman, CEES, Microsoft Research13 July 2007
Overview
• Introduction• Previous Work
– Analysing Avian Navigation
• Habitat Monitoring• Brief Results• Future Work
Introduction
– About Me• BSc CS-AI, MSc Evolutionary and Adaptive
Systems, • D.Phil (Engineering and Zoology)
– Part of the Life Sciences Interface Doctoral Training Centre, Oxford
– Trains physical and computation sciences graduates in biology before starting PhD in life sciences.
• Now a Post-Doc at Microsoft Research– Computational Ecology and Biodiversity Science Group – European Science Initiative, External Research Office.
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~9hrs
~15min
Introduction
• Analysing Avian Navigation• GPS Tracking of Pigeons, Oxford • GPS Tracking of Manx Shearwaters, Skomer
• Habitat Monitoring • Manx Shearwater
– Skomer Island, Wales
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Introduction– Zoological Interest
• Specific questions (Sensory basis of navigation),• Conservation (home range, behavioural anomalies),• Other general questions.
– Technical Interest• Novel algorithms/methods
– Analysis of positional information– Feedback to bio-robotics, Complex Systems, Artificial
Life, etc
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Pigeons? - Why Pigeons?
• Model Navigational Species– Much easier to study than wild birds,
• Birds return to a maintained loft (Wytham).– Allows attachment of GPS device
– Large body of research to draw on.• Pigeon navigation has been studied for over
100 years.
How Do They Navigate?
• Two hypotheses for the sensory basis of navigation in the familiar area– ‘Map and Compass’
• Compass controlled navigation (as it is at unfamiliar locations).
– Series of decision points using compass.
– ‘Pilotage’• Independent of a compass, relying directly
on visual cues– Oh look, there’s that house!
Clock Shift
• Experiment– Train the birds to ‘recapitulate’ routes to
home,– Then ‘clock-shift’ the birds by 90°
• Sets up a direct competition between visual landmarks (the recapitulated route) and erroneous compass instructions
With D Biro, J Meade, T Guilford & S J Roberts
• Nearest Neighbour Analysis
• Shows offset and variance between controls and familiar clock-shift.
Tracks ranked by Mahalonobis distance from recapping
distribution
Delayed Clock shift response (landmark related)
• Demonstrates that both mechanisms must be involved.– The birds must be able to home using
visual information alone (they recapitulate)
– Consistent deviation from recapitulated path
• Offset? Zigzag?
Biro D, Freeman R, Meade J, S. Roberts, Guilford T. (2007) PNAS. 104(18)
Behavioural Segmentation
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- Hidden-Markov Models- Positional Entropy
• More likely to fly over edge ‘rich’ areas
• Flight pattern becomes less predictable over edge rich areas.
Lau KK, Roberts S, Biro D, Freeman R, Meade J, Guilford T. (2006) J. Theo. Bio. 239(1) pp71-78
Landscape Analysis
Paired Homing Pigeon Flight GPS data for 48 Pigeons from
4 diff. sites
All possible pairs considered
Any real interaction between the birds should be seen as higher coupling between real pairs
Other pairs may show High coupling due to same
landscape/other unknown variables
Bird paired with self
Actual pair
Bird & random bird from different site
Birds which flew together show significantly (p < 0.05) higher coupling than other possible pairings. Implies some form of information transfer.
Manx Shearwater (Puffinus puffinus)
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• Highly pelagic, migratory seabird.• Burrow dwelling, central
place forager. • UK summer breeding• Winters in South
America
• 250, 000 – 300, 000 breeding pairs.• 45% on three
Pembrokeshire islands, Skomer, Skokholm and Middleholm;
• 36% on Rum.
Motivation
• Ecology and Behaviour very similar to other Procellariiformes– Albatrosses, Petrels and Shearwaters.
• 19 of 21 Albatross Species now globally threatened;
• Devastating impact of long-line fishing
• Understanding their behaviour, habitat and ecology may allow us to reduce this decline.
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Motivation
Source: JNCC, UK Seabirds 2005
UK Seabird decline over recent years
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Skomer Island
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• Small Island (~2km long) off coast of Wales• Home to large
populations of Guillemots, Razorbills, Kittiwakes, Puffins, Fulmars
• Worlds largest population of Manx Shearwaters• Well established
research centre and study programmes
Skomer Island
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Previous Work
• GPS Tracking of Manx Shearwater– Distribution of foraging was largely
unknown;• South to Spain;
– Interaction• With fisheries? • Environmental variables?
– Establishment of Marine protection zones.
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– Foraging largely confined to Irish Sea;
– Birds did not fly far south..
• Even when they had the opportunity to do so.
• Climate effect?
– Clustered areas;– Rafting.Right: Distribution of individual over
trips of 1 to 7 days. Red shows incubating birds, blue chick rearing
Speed Vs VecN
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0.2
0.4
0.6
0.8
1
1.2
-5 0 5 10 15 20 25 30
Speed (m/s)
No
rma
lise
d V
ec
tor
– Each 2-hourly fix gives a small burst of 1Hz data.
– Bursts can be segmented into different behaviours.
– Speed Vs Directionality
27Sitting & Erratic Movement Directional Movement
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– Speed has no obvious effect on depth
– Time of day appears to (right)
Autonomous Habitat Monitoring• Working closely with Academic
Partners– University of Oxford
• Prof. Tim Guilford, Animal Behaviour• Prof. Chris Perrins, Edward Grey Ornithology
Institute
– University of Freie Berlin• Tomasz Naumowicz, PHD, Free University Berlin• Prof Torben Weis, U Duisburg-Essen
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Autonomous Habitat Monitoring• Create and deploy a wireless sensor
network that can:– Monitor the visitations of individual birds;– Monitor environmental conditions inside and
outside the burrow;– Provide a pilot system for eventual integration
with GPS tracking;
– Do this all night, every night…
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Methods
• Approx. 10 Burrow monitored– Ringed and RFID
tagged pair of birds in each burrow;
– Sensors & wireless sensor node to each burrow;
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Methods
• Network– ScatterWeb platform
from Freie Universitat Berlin;
• Nodes– 2 x Passive Infrared– 2 x Temp/Humidity– RFID Detector
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Initial Results
• No observable impact on birds’ behaviour– No evidence of digging, distress or
abandonment.
• Of 10 monitored burrows– 7 hatched (last week)– Remainder still on eggs
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Initial Results
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– Obvious nocturnal distribution of activity
• Bimodal?
– Resolution and density of data already significantly higher that achievable using traditional methods.
All recorded events
352007/05/14 12:00 2007/05/15 00:00 2007/05/15 12:00
Initial Results
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Temperature Variation over 4 days (20-23 June)
• Red: Temp Outside
• Green: Temp Inside
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00:00
06:00
12:00
18:00
Future Questions…
– Do individuals return at specific times?– How do pairs alternate feeding
strategies?– How does activity/environment vary
across space and time?– How do the results vary with weather?
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Future Directions
• Deploy second network– Pilot has allowed us to iron out most
problems;– Hope to set up additional network this
winter.• Create a toolkit that any ecologist can deploy
and use.
• Integrate GPS tracking with network– Continual monitoring of foraging behaviour.
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~9hrs
~15min
An Aside (1)
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An Aside (2)
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