Autonomous Monitoring of Vulnerable Habitats

1. Autonomous Monitoring of Vulnerable Habitats And other tales.. Robin Freeman, CEES, Microsoft Research 13 July 2007

2. Overview • Introduction • Previous Work • Analysing Avian Navigation • Habitat Monitoring • Brief Results • Future Work

3. 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.

5. ~9hrs ~15min

6. Introduction • Analysing Avian Navigation • GPS Tracking of Pigeons, Oxford • GPS Tracking of Manx Shearwaters, Skomer • Habitat Monitoring • Manx Shearwater • Skomer Island, Wales

7. 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

8. 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.

9. 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!

10. 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

11. Nearest Neighbour Analysis • Shows offset and variance between controls and familiar clock-shift.

12. Delayed Clock shift response (landmark related) Tracks ranked by Mahalonobis distance from recapping distribution

13. 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)

14. Behavioural Segmentation - Hidden-Markov Models - Positional Entropy

15. Landscape Analysis • 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

16. Paired Homing Pigeon Flight Actual pair • 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 Bird & random bird from different site

17. Birds which flew together show significantly (p < 0.05) higher coupling than other possible pairings. Implies some form of information transfer.

18. Manx Shearwater (Puffinus puffinus) • 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.

19. 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.

20. Motivation UK Seabird decline over recent years Source: JNCC, UK Seabirds 2005

22. Skomer Island • 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

23. Skomer Island

24. 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.

25. 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

26. Each 2-hourly fix gives a small burst of 1Hz data. • Bursts can be segmented into different behaviours. • Speed Vs Directionality

27. Sitting & Erratic Movement Directional Movement

28. Speed has no obvious effect on depth • Time of day appears to (right)

29. 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

30. 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…

31. Methods • Approx. 10 Burrow monitored • Ringed and RFID tagged pair of birds in each burrow; • Sensors & wireless sensor node to each burrow;

32. Methods • Network • ScatterWeb platform from Freie Universitat Berlin; • Nodes • 2 x Passive Infrared • 2 x Temp/Humidity • RFID Detector

33. 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

34. Initial Results • Obvious nocturnal distribution of activity • Bimodal? • Resolution and density of data already significantly higher that achievable using traditional methods. All recorded events

35. 2007/05/15 12:00 2007/05/15 00:00 2007/05/14 12:00

36. Initial Results

37. 00:00 Temperature Variation over 4 days (20-23 June) • Red: Temp Outside • Green: Temp Inside 06:00 18:00 12:00

38. 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?

39. 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.

40. ~9hrs ~15min

41. An Aside (1)

42. An Aside (2)