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Global Sensitivity Analysis for
Impact Assessments
Matthew Aiello-Lammens
H. Resit Akçakaya
Stony Brook University
Ecological Society of America 2013
Integration of Sea-Level Rise model
(SLAMM) and Population Viability Analysis
(RAMAS GIS)
•Land cover
•Geology
•Local accretion and
erosion rates
•SLR / climate change
scenario

Current species
distribution

Sea-level Rise
Model (SLAMM)

Population size
through time

Land cover
change
through time

Demographic Model
(RAMAS GIS)
Current demographic data

Habitat Suitability
Model (MaxEnt)

Habitat suitability
through time
Integration of Sea-Level Rise model
(SLAMM) and Population Viability Analysis
(RAMAS GIS)
•Land cover
•Geology
•Local accretion and
erosion rates
•SLR / climate change
scenario

Current species
distribution

Sea-level Rise
Model (SLAMM)

Extinction risk
Population viability
analysis

Land cover
change
through time

Demographic Model
(RAMAS GIS)
Current demographic data

Habitat Suitability
Model (MaxEnt)

Habitat suitability
through time
Results
1.1

Relative value to 2010

1
0.9
0.8
0.7
0.6
0.5

N (No SLR; Ceiling)

0.4
0.3
2010

2020

2030

2040

2050

2060

Year

2070

2080

2090

2100
Results
1.1

Relative value to 2010

1
0.9
0.8
0.7

∆ Carrying Capacity

0.6
0.5

N (No SLR; Ceiling)

0.4
0.3
2010

2020

2030

2040

2050

2060

Year

2070

2080

2090

2100
Results
1.1

Relative value to 2010

1
0.9
0.8
0.7

∆ Carrying Capacity

0.6
0.5

N (No SLR; Ceiling)

0.4
0.3
2010

N (2m SLR; Ceiling)
2020

2030

2040

2050

2060

Year

2070

2080

2090

2100
2m SLR

1m SLR

No SLR

Expected Minimum
Abundance
Extinction

120
100
80
60
40
20
0
2m SLR

1m SLR

No SLR

2m SLR

1m SLR

No SLR

Risk
0.30
0.25
0.20
0.15
0.10
0.05
0.00

Results

Decline to 20
Patterns?
Patterns?

Adult Males

0.6
0.4
0.2

Juveniles

0.0

Adult Females

Risk of Decline

0.8

1.0

Processes?
Processes?

0

200

400
Abundance

Risk

600

800
Patterns?
Patterns?

Adult Males

0.6
0.4
0.2

Juveniles

0.0

Adult Females

Risk of Decline

0.8

1.0

Processes?
Processes?

0

200

400
Abundance

600

Uncertainty

800
Risk-Max - Risk-Min Parameter Value
-0.2

-0.4

-1
Survival, Juvenile

Rmax - Contest DD

Initial Abundance

Correlation

StdDev - Surv, Juvenile

Dispersal

Carrying Capacity

StdDev - Fecundity

StdDev - Survival, Adult

-0.8
Survival, Adult

-0.6
Fecundity

Sensitivity Analysis

1

0.8

0.6

0.4

0.2

0
Δ Risk Extiction

Δ Risk to N=20
Sensitivity Analysis
Fecundity

Sensitivity Analysis

Adult Survival
Fecundity

Sensitivity Analysis

Best Estimates

Adult Survival
Fecundity

Sensitivity Analysis

Uncertainty

Adult Survival
Fecundity

Sensitivity Analysis

Uncertainty

Adult Survival
Fecundity

Sensitivity Analysis

Adult Survival
Fecundity

Sensitivity Analysis

Adult Survival
Fecundity

Sensitivity Analysis

Adult Survival
Fecundity

Sensitivity Analysis

Adult Survival
Sensitivity Analysis
Snowy Plover Revisited
Uncertain Population and
Vital Rate Parameters
1. Adult Survival
2. Variability of Adult Survival
3. Fecundity (Juvenile Survival
and Maternity)
4. Variability of Fecundity
5. Dispersal
6. Spatial Correlation
7. Carrying Capacity
8. Initial Abundance
Sensitivity Analysis
Snowy Plover Revisited
Sample Size / Partition
Number Comparisons:

•
•
•
•
•

100
250
500
1000
10000
Relative Influence of Parameters - 10k Simulations
Sensitivity Analysis
Snowy Plover Revisited
Sample Size / Partition
Number Comparisons:

•
•
•
•
•

100
250
500
1000
10000
Sensitivity Analysis
Snowy Plover Revisited
Sample Size / Partition
Number Comparisons:

•
•
•
•
•

100 (100 sets)
250 (40 sets)
500 (20 sets)
1000 (10 sets)
10000
Sensitivity Analysis
Snowy Plover Revisited
Parameter

Fecundity
Adult Survial
Variability of Adult
Survival
Variability of
Fecundity
Carrying Capacity
Spatial Correlation
Dispersal
Initial Abundance

Relative Influence Values as
Determined by BRT Analysis
Sample Size 10k
76.859
20.960

Sample Size 100
79.028
13.861

1.499

2.945

0.441

0.698

0.184
0.025
0.019
0.013

0.628
0.700
0.827
1.312
Snowy Plover Sensitivity Analysis – Sample Size 100
53

71

83

87

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0.35

fecund

Fecundity

0.34
0.33

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0.68 0.69 0.70

0.68 0.69 0.70

0.35

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0.33

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0.68 0.69 0.70

0.68 0.69 0.70

0.68 0.69 0.70

0.68 0.69 0.70

72

0.68 0.69 0.70

91
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84

88

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96

0.1 0.2 0.3

0.1 0.2 0.3

0.1 0.2 0.3

0.1 0.2 0.3

0.1 0.2 0.3

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0.68 0.69 0.70

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Unif

38
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Unif

30
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LHS

29
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LHS

10
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ad.surv

Adult Survival
2

10

31

39

54

0.1 0.2 0.3

0.1 0.2 0.3

0.1 0.2 0.3

0.1 0.2 0.3

0.1 0.2 0.3

15
LHS

10

count

5
0
15
Unif

10
5
0

near.neighbor
Snowy Plover Sensitivity Analysis – Sample Size 100
53

71

83

87

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0.35

fecund

Fecundity

0.34
0.33

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0.68 0.69 0.70

0.68 0.69 0.70

0.35

●
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●

0.34

●
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●

0.33

●

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●

0.68 0.69 0.70

●

0.68 0.69 0.70

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95
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0.68 0.69 0.70

0.68 0.69 0.70

0.68 0.69 0.70

0.68 0.69 0.70

72

0.68 0.69 0.70

91
●
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84

88

92

96

0.1 0.2 0.3

0.1 0.2 0.3

0.1 0.2 0.3

0.1 0.2 0.3

0.1 0.2 0.3

●
● ●

●

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0.68 0.69 0.70

●●
●●

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Unif

38
● ● ●
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●
●

●

Unif

30
●
● ●
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●

LHS

29
●
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●

LHS

10
● ●
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●●

ad.surv

Adult Survival
2

10

31

39

54

0.1 0.2 0.3

0.1 0.2 0.3

0.1 0.2 0.3

0.1 0.2 0.3

0.1 0.2 0.3

15

LHS
LHS

10

count

Frequency

5
0

15

Unif
Unif

10

5
0

near.neighbor

Nearest Neighbor Distance
Snowy Plover Sensitivity Analysis – Box Plots of Variable
Importance Correlation with Sample Size 10K
100

1.00

250

snpl.100.SA2

1.0

Correlation Value

snpl.1000.SA2
●
●

●
●
●
●

No SLR
2m

●
●
●
●

1000

snpl.500.SA2
●

●

0.95

500

snpl.250.SA2

●
●
●
●
●
●

●

0.90

●
●

●

0.85

0.85

●

1.00

1.0

cor.val

●
●
●

0.90

●
●
●

●

2mnocc
SLR

0.95

●
●
●
●
●
●
●
●
●

●
●

0.85

0.85

●

1.0

LHS

Unif

LHS

Unif

LHS

Unif

LHS

Unif

unif

lhs

unif

0.5

−0.5

relEnds

0.0

●

●
●

lhs

unif

lhs

unif

lhs

samp
Snowy Plover Sensitivity Analysis – Box Plots of Variable
Importance Correlation with Sample Size 10K
100

1.00

250

snpl.100.SA2

1.0

Correlation Value

snpl.1000.SA2
●
●

●
●
●
●

No SLR
2m

●
●
●
●

1000

snpl.500.SA2
●

●

0.95

500

snpl.250.SA2

●
●
●
●
●
●

●

0.90

●
●

●

0.85

0.85

●

1.00

1.0

cor.val

●
●
●

0.90

●
●
●

●

2mnocc
SLR

0.95

●
●
●
●
●
●
●
●
●

●
●

0.85

0.85

●

1.0

LHS

Unif

LHS

Unif

LHS

Unif

LHS

Unif

unif

lhs

unif

0.5

−0.5

relEnds

0.0

●

●
●

lhs

unif

lhs

unif

lhs

samp
Sensitivity Analysis
1.1
0.9
0.7
0.5
0.3
2010

2060

Year
2m SLR: ∆ Carrying Capacity

Relative value to 2010

Relative value to 2010

Paired Simulations for Impact Assessment
1.1
0.9
0.7
0.5
0.3
2010

2060

Year
No SLR: ∆ Carrying Capacity
Sensitivity Analysis
Paired Simulations for Impact Assessment
1.1

Relative value to 2010

1
0.9
0.8
0.7
0.6
0.5

N (No SLR; Ceiling)

0.4
0.3
2010

N (2m SLR; Ceiling)
2020

2030

2040

2050

2060

Year

2070

2080

2090

2100
Sensitivity Analysis
Paired Simulations for Impact Assessment
1.1

Relative value to 2010

1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
2010

∆N Due to 2m SLR
2020

2030

2040

2050

2060

Year

2070

2080

2090

2100
Density

Density of Probability of Decline to 50 – No SLR

0.0

0.2

0.4

0.6

Probability of Decline to 50

0.8
Density

Density of Probability of Decline to 50 – No SLR

0.0

0.2

0.4

0.6

Probability of Decline to 50

0.8
Density

Density of Probability of Decline to 50 – 2m SLR

0.0

0.2

0.4

0.6

Probability of Decline to 50

0.8
Density of Probability of ∆ Decline to 50

Density

Unpaired Bootstrap

-0.5

0.0

0.5

∆ Probability of Decline to 50

1.0
Density of Probability of ∆ Decline to 50
Unpaired Bootstrap

Density

Mean Difference = 0.074

-0.5

0.0

0.5

∆ Probability of Decline to 50

1.0
Density of Probability of ∆ Decline to 50

Density

Paired Simulations

-0.5

0.0

0.5

∆ Probability of Decline to 50
Snowy Plover – Sample Size 100 – Probability of Decline to 50

Unif

Frequency

LHS

Probability of Decline to 50 – No SLR

Unif

Frequency

LHS

Probability of Decline to 50 – 2m SLR
Snowy Plover – Sample Size 100 – Probability of Decline to 50

Unif

Frequency

LHS

Probability of Decline to 50 – No SLR

Unif

Frequency

LHS

∆ Probability of Decline to 50 (Result of 2m SLR)
Snowy Plover Sensitivity Analysis – Box Plots of Variable
Importance Correlation with Sample Size 10K
100

1.00

250

snpl.100.SA2

1.0

Correlation Value

snpl.1000.SA2
●
●

●
●
●
●

No SLR
2m

●
●
●
●

1000

snpl.500.SA2
●

●

0.95

500

snpl.250.SA2

●
●
●
●
●
●

●

0.90

●
●

●

0.85

0.85

●

1.00

1.0
●
●
●

0.90

●
●
●

●

2mnocc
SLR

0.95

cor.val

●
●
●
●
●
●
●
●
●

●
●

0.85

0.85

●

1.0

1.0

0.0

0.0

-0.5

−0.5

Paired
relEnds

0.5

●

●
●

lhs

LHS

unif

Unif

lhs

LHS

unif

Unif

lhs

samp

LHS

unif

Unif

lhs

LHS

unif

Unif
Current Implementations

Glossy Buckthorn Invasive
Effects of land-use change
Density dependence
models

Passenger Pigeon –
Extinctions
Effects of land-use change
Impact of harvest /
hunting

NA Herps – Impacts of
Climate Change
Effects of climate change
scenarios
Acknowledgements:
HR Akcakaya, J Stanton, A Cahill, G Sorrentino, H Ryu, E Kneip,
K Shoemaker, M Aldred, S Sabatino, SERDP Collaborators
Funding:
SERDP and NASA

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Aiello-Lammens: Global Sensitivity Analysis for Impact Assessments.

  • 1. Global Sensitivity Analysis for Impact Assessments Matthew Aiello-Lammens H. Resit Akçakaya Stony Brook University Ecological Society of America 2013
  • 2.
  • 3. Integration of Sea-Level Rise model (SLAMM) and Population Viability Analysis (RAMAS GIS) •Land cover •Geology •Local accretion and erosion rates •SLR / climate change scenario Current species distribution Sea-level Rise Model (SLAMM) Population size through time Land cover change through time Demographic Model (RAMAS GIS) Current demographic data Habitat Suitability Model (MaxEnt) Habitat suitability through time
  • 4. Integration of Sea-Level Rise model (SLAMM) and Population Viability Analysis (RAMAS GIS) •Land cover •Geology •Local accretion and erosion rates •SLR / climate change scenario Current species distribution Sea-level Rise Model (SLAMM) Extinction risk Population viability analysis Land cover change through time Demographic Model (RAMAS GIS) Current demographic data Habitat Suitability Model (MaxEnt) Habitat suitability through time
  • 5. Results 1.1 Relative value to 2010 1 0.9 0.8 0.7 0.6 0.5 N (No SLR; Ceiling) 0.4 0.3 2010 2020 2030 2040 2050 2060 Year 2070 2080 2090 2100
  • 6. Results 1.1 Relative value to 2010 1 0.9 0.8 0.7 ∆ Carrying Capacity 0.6 0.5 N (No SLR; Ceiling) 0.4 0.3 2010 2020 2030 2040 2050 2060 Year 2070 2080 2090 2100
  • 7. Results 1.1 Relative value to 2010 1 0.9 0.8 0.7 ∆ Carrying Capacity 0.6 0.5 N (No SLR; Ceiling) 0.4 0.3 2010 N (2m SLR; Ceiling) 2020 2030 2040 2050 2060 Year 2070 2080 2090 2100
  • 8. 2m SLR 1m SLR No SLR Expected Minimum Abundance Extinction 120 100 80 60 40 20 0 2m SLR 1m SLR No SLR 2m SLR 1m SLR No SLR Risk 0.30 0.25 0.20 0.15 0.10 0.05 0.00 Results Decline to 20
  • 9. Patterns? Patterns? Adult Males 0.6 0.4 0.2 Juveniles 0.0 Adult Females Risk of Decline 0.8 1.0 Processes? Processes? 0 200 400 Abundance Risk 600 800
  • 10. Patterns? Patterns? Adult Males 0.6 0.4 0.2 Juveniles 0.0 Adult Females Risk of Decline 0.8 1.0 Processes? Processes? 0 200 400 Abundance 600 Uncertainty 800
  • 11. Risk-Max - Risk-Min Parameter Value -0.2 -0.4 -1 Survival, Juvenile Rmax - Contest DD Initial Abundance Correlation StdDev - Surv, Juvenile Dispersal Carrying Capacity StdDev - Fecundity StdDev - Survival, Adult -0.8 Survival, Adult -0.6 Fecundity Sensitivity Analysis 1 0.8 0.6 0.4 0.2 0 Δ Risk Extiction Δ Risk to N=20
  • 13.
  • 22. Sensitivity Analysis Snowy Plover Revisited Uncertain Population and Vital Rate Parameters 1. Adult Survival 2. Variability of Adult Survival 3. Fecundity (Juvenile Survival and Maternity) 4. Variability of Fecundity 5. Dispersal 6. Spatial Correlation 7. Carrying Capacity 8. Initial Abundance
  • 23. Sensitivity Analysis Snowy Plover Revisited Sample Size / Partition Number Comparisons: • • • • • 100 250 500 1000 10000
  • 24. Relative Influence of Parameters - 10k Simulations
  • 25. Sensitivity Analysis Snowy Plover Revisited Sample Size / Partition Number Comparisons: • • • • • 100 250 500 1000 10000
  • 26. Sensitivity Analysis Snowy Plover Revisited Sample Size / Partition Number Comparisons: • • • • • 100 (100 sets) 250 (40 sets) 500 (20 sets) 1000 (10 sets) 10000
  • 27. Sensitivity Analysis Snowy Plover Revisited Parameter Fecundity Adult Survial Variability of Adult Survival Variability of Fecundity Carrying Capacity Spatial Correlation Dispersal Initial Abundance Relative Influence Values as Determined by BRT Analysis Sample Size 10k 76.859 20.960 Sample Size 100 79.028 13.861 1.499 2.945 0.441 0.698 0.184 0.025 0.019 0.013 0.628 0.700 0.827 1.312
  • 28. Snowy Plover Sensitivity Analysis – Sample Size 100 53 71 83 87 ● ●● ● ● ● ●● ●● ● ● ● ●● ● ●● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ●● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ●●● ● ● ● ● ● ● ●● ● ● ● ●● ● ●●● ● ● ● ● ● ● ● ● ●● ●● ●● ● ● ● ● ●● ● ● ● ●● ● ●● ● ● ●●● ● ● ● ● ● ● ● ● ●● ●● ● ● ●● ●● ● ● ● ● ●● ● ●● ● ●● ● ● ●● ● ● ●●● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ●● ●● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ●●● ● ●● ● ● ● ● ●● ● ● ●● ● ● ● ●● ● ●● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ●● ● ● ● ● ●● ● ● ● ● ●● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ●● ● ●● ● ●● ● ●● ● ● ● ● ●● ● ● ● ● ● ● ● ● ●● ● ●● ● ● ●● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ●●● ● ● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●●● ● ● ● ●● ● ●● ● ● ●● 0.35 fecund Fecundity 0.34 0.33 ● ● ● ●●● ● ● ● ● ● ● ●● ● ● ●● ●●● ●● ● ●● ●● ●● ● ●●● ●● ● ● ● ● ● ●● ● ● ● ●●● ●● ● ● ● ● ● ●● ●● ● ● ●● ● ● ● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ●● ●● ● ●● ● ● ● ● ● ● ● ● ● ●● ●● ● ● ●● ● ● ● ● ●● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ●● ●●● ● ●● ● ●● ● ● ● ● ●● ● ● ● ● ● ● ●●● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ●● ● ●●●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ●● ● ● ● ●● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ●● ● ● ● ● ●● ● ● ●● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ●● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ●● ● ● ● ● ● ●● ●● ● ●● ● ●● ● ● ●● ● ● ●● ● ● ●● ● ● ●● ● ● ● ● ● ●● ●● ● ● ●● ● ● ● ● ● ● ● ●● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ●● ● ● ●● ● ●● ● ●● ● ● ● ● ● ● ●● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●●● ●● ● ● ● ● ●●●● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ●● ● ●● ● ● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ●● ● ● 0.68 0.69 0.70 0.68 0.69 0.70 0.35 ● ● ● 0.34 ● ● ● ● ●● ● 0.33 ● ● ● ● ● ● ● ●● ● ● ● ● ● 0.68 0.69 0.70 ● 0.68 0.69 0.70 ● ● ● ●● 95 ● ●● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●●● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ● ● ●● ● ● ●● ●● ● ●● ● ●● ● ● ●● ● ● ●●● ● ●● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ●● ● ● ● ● ●● ● ● ● ●● ● ● ● ● ●● ● ● ●● ●● ● ● ●● ● ● ●● ● ● ●● ● ● ● ●● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ●● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ●● ● ●●● ● ● ● ● ● ●● ● ● ● ●● ● ● ●● ● ● ●● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●● ●● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ●● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ●● ●● ● ● ●●● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ●● ● ●● ●●● ● ● ● ● ● ● ● ● 0.68 0.69 0.70 0.68 0.69 0.70 0.68 0.69 0.70 0.68 0.69 0.70 72 0.68 0.69 0.70 91 ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ●● ● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●●● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ●● ● ● ●● ● ● 84 88 92 96 0.1 0.2 0.3 0.1 0.2 0.3 0.1 0.2 0.3 0.1 0.2 0.3 0.1 0.2 0.3 ● ● ● ● ● ● ● ●● ● ● ● ● 0.68 0.69 0.70 ●● ●● ● ● ● ●●● ● ●● ● ●● ● ● ● ● ● ● ● ● ● Unif 38 ● ● ● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ●● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ●● ●● ● ● ● ●● ● ● ● ● ● ● ● ● ● Unif 30 ● ● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ●● ● ● ● ● ● ●● ● ● ●● ● ● ●● ● ● ● ● ●● ● ● ● ●● ● ● ●● ● ●● ●● ●● ● ● ● ● ● ● ●●● ● ● ● ● ● ●● ● ● ● ●● ● ● ● LHS 29 ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ●● ● ●●● ● ● ● ● ● ● ● ●●● ●● ● ●● ● ● ● ●● ● ● ● ●● ●● ● ● ● ●● ● ●● ● ● ●● ● ● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ● ●● ● LHS 10 ● ● ● ● ● ● ● ●●● ●● ● ● ● ●● ● ● ● ● ● ● ● ● ●● ● ●● ● ● ● ● ●● ● ● ● ● ●● ● ●● ● ●● ● ● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ●● ● ●● ● ●● ad.surv Adult Survival 2 10 31 39 54 0.1 0.2 0.3 0.1 0.2 0.3 0.1 0.2 0.3 0.1 0.2 0.3 0.1 0.2 0.3 15 LHS 10 count 5 0 15 Unif 10 5 0 near.neighbor
  • 29. Snowy Plover Sensitivity Analysis – Sample Size 100 53 71 83 87 ● ●● ● ● ● ●● ●● ● ● ● ●● ● ●● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ●● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ●●● ● ● ● ● ● ● ●● ● ● ● ●● ● ●●● ● ● ● ● ● ● ● ● ●● ●● ●● ● ● ● ● ●● ● ● ● ●● ● ●● ● ● ●●● ● ● ● ● ● ● ● ● ●● ●● ● ● ●● ●● ● ● ● ● ●● ● ●● ● ●● ● ● ●● ● ● ●●● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ●● ●● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ●●● ● ●● ● ● ● ● ●● ● ● ●● ● ● ● ●● ● ●● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ●● ● ● ● ● ●● ● ● ● ● ●● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ●● ● ●● ● ●● ● ●● ● ● ● ● ●● ● ● ● ● ● ● ● ● ●● ● ●● ● ● ●● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ●●● ● ● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●●● ● ● ● ●● ● ●● ● ● ●● 0.35 fecund Fecundity 0.34 0.33 ● ● ● ●●● ● ● ● ● ● ● ●● ● ● ●● ●●● ●● ● ●● ●● ●● ● ●●● ●● ● ● ● ● ● ●● ● ● ● ●●● ●● ● ● ● ● ● ●● ●● ● ● ●● ● ● ● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ●● ●● ● ●● ● ● ● ● ● ● ● ● ● ●● ●● ● ● ●● ● ● ● ● ●● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ●● ●●● ● ●● ● ●● ● ● ● ● ●● ● ● ● ● ● ● ●●● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ●● ● ●●●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ●● ● ● ● ●● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ●● ● ● ● ● ●● ● ● ●● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ●● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ●● ● ● ● ● ● ●● ●● ● ●● ● ●● ● ● ●● ● ● ●● ● ● ●● ● ● ●● ● ● ● ● ● ●● ●● ● ● ●● ● ● ● ● ● ● ● ●● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ●● ● ● ●● ● ●● ● ●● ● ● ● ● ● ● ●● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●●● ●● ● ● ● ● ●●●● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ●● ● ●● ● ● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ●● ● ● 0.68 0.69 0.70 0.68 0.69 0.70 0.35 ● ● ● 0.34 ● ● ● ● ●● ● 0.33 ● ● ● ● ● ● ● ●● ● ● ● ● ● 0.68 0.69 0.70 ● 0.68 0.69 0.70 ● ● ● ●● 95 ● ●● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●●● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ● ● ●● ● ● ●● ●● ● ●● ● ●● ● ● ●● ● ● ●●● ● ●● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ●● ● ● ● ● ●● ● ● ● ●● ● ● ● ● ●● ● ● ●● ●● ● ● ●● ● ● ●● ● ● ●● ● ● ● ●● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ●● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ●● ● ●●● ● ● ● ● ● ●● ● ● ● ●● ● ● ●● ● ● ●● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●● ●● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ●● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ●● ●● ● ● ●●● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ●● ● ●● ●●● ● ● ● ● ● ● ● ● 0.68 0.69 0.70 0.68 0.69 0.70 0.68 0.69 0.70 0.68 0.69 0.70 72 0.68 0.69 0.70 91 ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ●● ● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●●● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ●● ● ● ●● ● ● 84 88 92 96 0.1 0.2 0.3 0.1 0.2 0.3 0.1 0.2 0.3 0.1 0.2 0.3 0.1 0.2 0.3 ● ● ● ● ● ● ● ●● ● ● ● ● 0.68 0.69 0.70 ●● ●● ● ● ● ●●● ● ●● ● ●● ● ● ● ● ● ● ● ● ● Unif 38 ● ● ● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ●● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ●● ●● ● ● ● ●● ● ● ● ● ● ● ● ● ● Unif 30 ● ● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ●● ● ● ● ● ● ●● ● ● ●● ● ● ●● ● ● ● ● ●● ● ● ● ●● ● ● ●● ● ●● ●● ●● ● ● ● ● ● ● ●●● ● ● ● ● ● ●● ● ● ● ●● ● ● ● LHS 29 ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ●● ● ●●● ● ● ● ● ● ● ● ●●● ●● ● ●● ● ● ● ●● ● ● ● ●● ●● ● ● ● ●● ● ●● ● ● ●● ● ● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ● ●● ● LHS 10 ● ● ● ● ● ● ● ●●● ●● ● ● ● ●● ● ● ● ● ● ● ● ● ●● ● ●● ● ● ● ● ●● ● ● ● ● ●● ● ●● ● ●● ● ● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ●● ● ●● ● ●● ad.surv Adult Survival 2 10 31 39 54 0.1 0.2 0.3 0.1 0.2 0.3 0.1 0.2 0.3 0.1 0.2 0.3 0.1 0.2 0.3 15 LHS LHS 10 count Frequency 5 0 15 Unif Unif 10 5 0 near.neighbor Nearest Neighbor Distance
  • 30. Snowy Plover Sensitivity Analysis – Box Plots of Variable Importance Correlation with Sample Size 10K 100 1.00 250 snpl.100.SA2 1.0 Correlation Value snpl.1000.SA2 ● ● ● ● ● ● No SLR 2m ● ● ● ● 1000 snpl.500.SA2 ● ● 0.95 500 snpl.250.SA2 ● ● ● ● ● ● ● 0.90 ● ● ● 0.85 0.85 ● 1.00 1.0 cor.val ● ● ● 0.90 ● ● ● ● 2mnocc SLR 0.95 ● ● ● ● ● ● ● ● ● ● ● 0.85 0.85 ● 1.0 LHS Unif LHS Unif LHS Unif LHS Unif unif lhs unif 0.5 −0.5 relEnds 0.0 ● ● ● lhs unif lhs unif lhs samp
  • 31. Snowy Plover Sensitivity Analysis – Box Plots of Variable Importance Correlation with Sample Size 10K 100 1.00 250 snpl.100.SA2 1.0 Correlation Value snpl.1000.SA2 ● ● ● ● ● ● No SLR 2m ● ● ● ● 1000 snpl.500.SA2 ● ● 0.95 500 snpl.250.SA2 ● ● ● ● ● ● ● 0.90 ● ● ● 0.85 0.85 ● 1.00 1.0 cor.val ● ● ● 0.90 ● ● ● ● 2mnocc SLR 0.95 ● ● ● ● ● ● ● ● ● ● ● 0.85 0.85 ● 1.0 LHS Unif LHS Unif LHS Unif LHS Unif unif lhs unif 0.5 −0.5 relEnds 0.0 ● ● ● lhs unif lhs unif lhs samp
  • 32. Sensitivity Analysis 1.1 0.9 0.7 0.5 0.3 2010 2060 Year 2m SLR: ∆ Carrying Capacity Relative value to 2010 Relative value to 2010 Paired Simulations for Impact Assessment 1.1 0.9 0.7 0.5 0.3 2010 2060 Year No SLR: ∆ Carrying Capacity
  • 33. Sensitivity Analysis Paired Simulations for Impact Assessment 1.1 Relative value to 2010 1 0.9 0.8 0.7 0.6 0.5 N (No SLR; Ceiling) 0.4 0.3 2010 N (2m SLR; Ceiling) 2020 2030 2040 2050 2060 Year 2070 2080 2090 2100
  • 34. Sensitivity Analysis Paired Simulations for Impact Assessment 1.1 Relative value to 2010 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 2010 ∆N Due to 2m SLR 2020 2030 2040 2050 2060 Year 2070 2080 2090 2100
  • 35. Density Density of Probability of Decline to 50 – No SLR 0.0 0.2 0.4 0.6 Probability of Decline to 50 0.8
  • 36. Density Density of Probability of Decline to 50 – No SLR 0.0 0.2 0.4 0.6 Probability of Decline to 50 0.8
  • 37. Density Density of Probability of Decline to 50 – 2m SLR 0.0 0.2 0.4 0.6 Probability of Decline to 50 0.8
  • 38. Density of Probability of ∆ Decline to 50 Density Unpaired Bootstrap -0.5 0.0 0.5 ∆ Probability of Decline to 50 1.0
  • 39. Density of Probability of ∆ Decline to 50 Unpaired Bootstrap Density Mean Difference = 0.074 -0.5 0.0 0.5 ∆ Probability of Decline to 50 1.0
  • 40. Density of Probability of ∆ Decline to 50 Density Paired Simulations -0.5 0.0 0.5 ∆ Probability of Decline to 50
  • 41. Snowy Plover – Sample Size 100 – Probability of Decline to 50 Unif Frequency LHS Probability of Decline to 50 – No SLR Unif Frequency LHS Probability of Decline to 50 – 2m SLR
  • 42. Snowy Plover – Sample Size 100 – Probability of Decline to 50 Unif Frequency LHS Probability of Decline to 50 – No SLR Unif Frequency LHS ∆ Probability of Decline to 50 (Result of 2m SLR)
  • 43. Snowy Plover Sensitivity Analysis – Box Plots of Variable Importance Correlation with Sample Size 10K 100 1.00 250 snpl.100.SA2 1.0 Correlation Value snpl.1000.SA2 ● ● ● ● ● ● No SLR 2m ● ● ● ● 1000 snpl.500.SA2 ● ● 0.95 500 snpl.250.SA2 ● ● ● ● ● ● ● 0.90 ● ● ● 0.85 0.85 ● 1.00 1.0 ● ● ● 0.90 ● ● ● ● 2mnocc SLR 0.95 cor.val ● ● ● ● ● ● ● ● ● ● ● 0.85 0.85 ● 1.0 1.0 0.0 0.0 -0.5 −0.5 Paired relEnds 0.5 ● ● ● lhs LHS unif Unif lhs LHS unif Unif lhs samp LHS unif Unif lhs LHS unif Unif
  • 44. Current Implementations Glossy Buckthorn Invasive Effects of land-use change Density dependence models Passenger Pigeon – Extinctions Effects of land-use change Impact of harvest / hunting NA Herps – Impacts of Climate Change Effects of climate change scenarios
  • 45. Acknowledgements: HR Akcakaya, J Stanton, A Cahill, G Sorrentino, H Ryu, E Kneip, K Shoemaker, M Aldred, S Sabatino, SERDP Collaborators Funding: SERDP and NASA

Hinweis der Redaktion

  1. ** ACKNOWLEDGE THE WORK OF MY COLLABORATORS** The Snowy Plover is a Threatened shore-bird that is listed asState Threatened (Florida), USFWS Threatened (West Coast), THREATENED BY Development of nesting areas, Sea Level Rise, and Military training missions (Hence the SERDP funding)
  2. We integrated three stand alone ecological models, using the SLR model as environmental information in our suitability model and the results of the habitat suitability model in the demographic model, accounting for the changing habitat through time
  3. ** Looking at my model results, the prospects for snowy plover seem bleak** Here I’m showing you the mean population size over 1000 replicate simulations through time
  4. Here is what the change in carrying capacity looks like
  5. And here is the mean population size through time given that sea-level rise affect
  6. sea-level rise increases risk of decline and decreases the expected minimum abundance
  7. BUT there’s a lot of uncertainty in our model input parameters, or our knowledge of the processes that are producing these patterns
  8. And this uncertainty should be accounted for when we are analyzing our model outputsSo as any good modeler does, I did a sensitivity analysis
  9. One-at-a-time sensitivity analysis
  10. ** can we make this more efficient and do a thorough sensitivity analysis on a single computer?** Also, for many of our applications, we want to assess the sensitivity of our models to our uncertainty __GIVEN__ some assumed impact – here climate change impacts on habitat suitability, specifically due to SLR --- so we want to separate our uncertainty in model parameters from the impact –
  11. To compare our different sample sizes, I’m assuming the parameter importance values generated by the sample size 10k simulations represents the TRUE importance values
  12. I then generated replicate sets for each sample size, so that for each sample size 10k simulations were carried out
  13. ** __Relative influence__ “is a function of the number of times a variable is selected for splitting, weighted by the square improvement to the model as a result of each split, and averaged over all trees”** I then calculate a simple linear correlation between these two sets of values, and again assuming 10k is __True__, we can think of this correlation value as a measure of “Information Recovery”
  14. ** On to the resultsDo we sample the parameter space more efficiently using Latin Hypercube Sampling over uniform random sampling? Here I am showing you 10 of the 100 replicates from sample size = 100 for adult survival and fecundity
  15. No evidence for major differences
  16. ** But, for many of our applications, we want to assess the sensitivity of our models to our uncertainty __GIVEN__ some assumed impact – here I’m looking at the impact of SLR on carrying capacity --- so we want to separate our uncertainty in model parameters from the impact –
  17. Run simulations with exactly the same parameter set, and only change parameters related to SLR impact
  18. And we do this for our risk measures as well, ie risk of extinction, risk of decline, and expected minimum abundance
  19. Notice how wide the range is for sea-level rise case versus how narrow the range is for the change
  20. In this example, many more replications are required to determine the relative influence (variable importance) of variables on the relative change measures than when looking at the absolute risk measures.