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May 07, 2023 •270 likes •618 views

Searching for needles in haystacks Michael McCarthy Quantitative and Applied Ecology Group qaeco.com ARC ceed Centre of Excellence for Environmental Decisions Optimal surveillance Gilbert et al . (2008) Proc. Natl. Acad. Sci. USA 105,

  1. Searching for needles in haystacks Michael McCarthy Quantitative and Applied Ecology Group qaeco.com ARC ceed Centre of Excellence for Environmental Decisions

  2. Optimal surveillance Gilbert et al . (2008) Proc. Natl. Acad. Sci. USA 105, 4769-4774

  3. Optimal surveillance Orchi, Wikimedia Maelgwn, Wikimedia

  4. Orange hawkweed 4219 x 4-ha grid cells Orchi, Wikimedia Pr(hawkweed) vegetation 0.000 – 0.003 0.003 – 0.007 low grassy 0.007 – 0.014 shrubby 0.014 – 0.026 0.026 – 0.050 Williams, Hahs & Morgan (2008) Ecological Applications

  6. This talk • a simplification of decision problems – straight-forward solutions – ability to deal with uncertainty • examples • an empirical evaluation

  7. Prob non-detection 1.0 0.8 0.6 0.4 0.2 0.0 0 5 10 15 Effort (hr/ha)

  8. p ( x ) a exp( b x ) Pr(Not detected) 0.6 i i i i i Pr(Extinction) 0.5 0.4 0.3 0.2 0.1 0.0 0 10 20 30 40 50 Money spent on surveys Money spent on species ($'000)

  9. Pr(Not detected) 0.6 Pr(Extinction) 0.5 0.4 0.3 0.2 0.1 0.0 0 10 20 30 40 50 Money spent on surveys Money spent on species ($'000)

  10. Pr(Not detected) 0.6 Pr(Extinction) 0.5 0.4 0.3 0.2 0.1 0.0 0 10 20 30 40 50 Money spent on surveys Money spent on species ($'000)

  11. Pr(Not detected) 0.6 Pr(Extinction) 0.5 0.4 0.3 0.2 0.1 0.0 0 10 20 30 40 50 Money spent on surveys Money spent on species ($'000)

  12. Management outcome n L p i x ( ) i i 1 reward function summed over n options

  13. Management outcome n L p i x ( ) i i 1 n subject to x B i i 1 * * p ( x ) for x 0 the solution i i i

  14. Pr(presence)

  15. Rate of detection

  16. Orange hawkweed 4219 x 4-ha grid cells Orchi, Wikimedia Pr(hawkweed) Visit length (min) vegetation 0.000 – 0.003 0 – 7 0.003 – 0.007 low grassy 7 – 24 0.007 – 0.014 24 – 54 shrubby 0.014 – 0.026 54 – 92 0.026 – 0.050 92 – 175 Williams, Hahs & Morgan (2008) Hauser & McCarthy (2009) Ecological Applications Ecology Letters

  17. Gilbert et al . (2008) Proc. Natl. Acad. Sci. USA 105, 4769-4774

  18. McCarthy et al. (2010) Ecology Letters 13: 1280-1289

  19. Optimal number of flocks Min. expected no. undetected outbreaks Risk of H5N1 outbreak McCarthy et al. (2010) Ecology Letters 13: 1280-1289

  20. Uncertain outcome Prob non-detection 1.0 0.8 0.6 0.4 0.2 0.0 0 5 10 15 Effort (hr/ha)

  21. Uncertain outcome n n L p ( x ) b x i i i i i 1 i 1 n subject to x B i i 1 Harry Markowitz

  22. Financial investment Max Pr(gain) Min Pr(loss) Markowitz (1952) J Finance 7, 77-91

  23. Optimal number of flocks Min. expected no. undetected outbreaks Max. prob. detecting >5% of outbreaks Risk of H5N1 outbreak McCarthy et al. (2010) Ecology Letters 13: 1280-1289

  25. Lomandra Dianella Themeda Einadia Atriplex

  27. Factors driving detection rate • abundance (+ve) • experience (+ve) • species • height of vegetation ( – ve) • extra variation among – searchers – quadrats

  29. Expected benefit 0.8 Proportion detected 0.7 0.6 Observed benefit 0.5 0.4 Expected - optimal 0.3 Observed - optimal 0.2 Expected - uniform 0.1 Observed - uniform 0.0 0 20 40 60 Budget (minutes)

  30. 9 8 Benefit (detections) 7 Observed benefit 6 5 Expected benefit 4 3 2 1 0 0 10 20 30 40 50 60 Budget (minutes)

  31. Finding at least 2 occurrences 1.0 Probability of success 0.8 Incorporates: assumptions of the stats binomial nature of data 0.6 variation among quadrats uncertain detection rates correlations in this uncertainty 0.4 Predicted - optimal 0.2 Predicted - uniform 0.0 0 10 20 30 Budget (minutes)

  32. Relative predictions 0.30 Increased probability Predicted 0.25 Observed 0.20 0.15 0.10 0.05 0.00 0 10 20 30 Budget (minutes)

  33. A useful model n L p i x ( ) Surveillance i i 1 Hotspot investment Biodiversity surveys n subject to x B Reserve design i Conservation triage i 1 Species management Vegetation management Greenhouse gas mitigation …. and it works experimentally

  34. Thank you mamcca@unimelb.edu.au mickresearch.wordpress.com qaeco.com

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