Island eradications: Approaches and assessment of success

Biodiversity Bonanza

Dean AndersonLandcare Research

Central question:

How can we determine whether an eradication effort has been successful?

Answer is important:

1) Influence management practice

2) Funders want to know outcome

3) If fail, want to know sooner rather than later.

Assessing success• Establish relationship between search

effort and probability of detection.

• Actively search for survivors

• Collect spatial and temporal data on search effort

Key relationship

1

0Search effort

Probability of detection

Probability of detection and success

1

0Search effort

Probability of detection

Probability of eradication success

Probability of detection and success

1

0Search effort

Probability of detection

Probability of eradication success

Threshold

Probability of detection and success

1

0Search effort

Probability of detection

Probability of eradication success

How do we get this “key” relationship?

1

0Search effort

Probability of detection Depends on

eradication method

Carcasses collected

Pigs on Santa Cruz Island, USA- (Ramsey et al. 2009)

Stoats on Resolution Island, NZDOC

Goats on Guadalupe Island, Mexico- Luciana Luna, Conservacion de

Islas

Catch – effort model:(knock-down phase)

0 200 400 600 800 1000 1200

200

400

600

800

1000

1200

Cumulative Observer Hours

Goa

ts D

ispa

tche

d

Helicopter

Helicopter

Helicopter

Ground

Goa

ts d

ispa

tche

d

Hunting hours

Probability of detection and success

1

0Search effort

Probability of detection

Probability of eradication success

No carcasses: Rat Eradication with single toxin drop

2 Approaches when missing carcasses

1) Wait and see– Easy– Takes time– If fail, the problem is big

2) Actively search– Requires data and statistics– If fail, survivors may be very localised

Isabel82 ha

Mexico

Pacific Ocean

Gulf of Mexico

Araceli Samaniego Conservacion de Islas

Isabel Island, Mexico• 1 toxin drop

• 3 annual wax-tag surveys

• No rats detected

Eradication success???

Spatial-detection Model• Home range size• Detection probability

of tags

Isabel Island, 1 pregnant female

*

Wax-tag survey year 2

Isabel Island, N rats = 10

*

Spatial-detection Model• Home range size• Detection probability

of tags• Population growth

rate• Dispersal kernel

Wax-tag survey year 3Isabel Island, N rats = 106

*

Repeat 1000 times

Isabel Island, 1 pregnant female

*

Isabel Island, 1 pregnant female

*Isabel Island, 1 pregnant female

*

Each female takes on slightly different parameter values

Results

Median Low 2.5% CI High 97.5 CIProb. Success 2009 0.74 0.62 0.83Prob. Success 2010 0.96 0.76 0.99Prob. Success 2011 0.99 0.99 1.00

* Confidence intervals reflect the uncertainty in input parameters

Results

Median Low 2.5% CI High 97.5 CIProb. Success 2009 0.74 0.62 0.83Prob. Success 2010 0.96 0.76 0.99Prob. Success 2011 0.99 0.99 1.00

* Confidence intervals reflect the uncertainty in input parameters

One – survey approach

50 100 150 200

0.6

0.7

0.8

0.9

1.0

Device Spacing (m)

Pro

babi

lity

of S

ucce

ss

One – survey approachIsabel Island

*50-m spacing

Summary

• Why quantify probability of success?– Management– Funders– Identify failure early

Isabel Island, N rats = 106

*

Summary

Carcasses counted1) Catch – effort model

• Collect data during “knock-down” phase• Establish relationship between detection & effort

SummaryCarcasses not available

2) Spatial – detection model• Estimate parameters with experiments or literature

– Homerange size– Detection probability of device– Reproductive rates– Dispersal kernels

• Incorporate uncertainty

Isabel Island, 1 pregnant female

*

Summary

• Requires biological understanding and statistics

• Arguably better than “wait-and-see”

Acknowledgements

• John Parkes• Araceli Samaniego• Luciana Luna• Conservacion de Islas, Mexico• Department of Conservation, NZ