Autonomous Monitoring of Vulnerable Habitats And other tales.. Robin Freeman, CEES, Microsoft...

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

0

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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