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EconFirst Associates LLC with HSUS Support
WILD HORSE MANAGEMENT SYSTEM:
POPULATION PROJECTION & COSTING MODEL
Horse Population Management
Over Populated
Range
Desired Range Population
Gather?
Remove?
Short & Long Term Holding
NoYes
NoYes
Adoption
Foaling
Contraception
3
Achieve target range populations
Treat wild horses humanely
Respect Budget Constraints
Goals of Wild Horse Management
4
Range populations grow as much as 25% /Yr.
Therefore frequency & size of removals grow
CURRENT APPROACH NOT SUSTAINABLE
High pop. growth means more young horses
Therefore longer time in holding facilities
5
Federal budget constraints will limit
BLM’s Management Options
Therefore costs must be considered if this
committee’s recommendations are to endure
The BUDGET must be considered
Population ModelStarting range
population
Ending Range Population
Short & Long Term
Holding
Add Foals
Subtract Deaths
Environmental Impacts
(weather, drought, etc.)
Foaling Probability
Contraception Effectiveness
Subtract Removals
Survival Probability
Gather Efficiency
7
Simulates Probable Population Outcomes
1 2 3 4 5 6 7 8 9 10 Year
8
Optimize Population Intervention
Optimize Use of Scarce Resources
Optimize Population Target Levels
Optimize within Budget Constraints
This System Adds Optimization to Simulation
9
Successful Management will Optimize Initial Plan
and Adjustas Data is Augmented
10
Planning is a Moving TargetGiven Variability of Range
Environments
Active Interaction with Simulations
11
Successful Management will Includeall HMAs
12
Successful Management will Require
Better Data Collection
13
I. Dynamic Population Simulation model
II. Economic Costing Model
III. Management Optimization Model
IV. Population & Range Database System
MODEL COMPONENTS
14
Simulates single or multiple HMAs
Adjusts as new data becomes available
Integrates population simulation and costs
Combines simulation and optimization to reach population and cost targets
The Projection Model
15
Find optimum mix and timing of
Gathers, Removals and Fertility Treatment
A Tool to Manage Wild Horse Areas
16
Timing & Frequency of Gathers
Extent of Fertility Treatment
Reach or adjust AML targets
Subject to Cost constraints
Optimization under Uncertainity
17
Given budget, determine reachable AMLs
Subject to carrying capacity constraints
Subject to min-max levels
Reverse Optimization
18
Simulation Examplefor Single HMA
19
Single HMA: Baseline Simulation if no Mgt.
0
2,000
4,000
6,000
8,000
10,000
12,000
0 1 2 3 4 5 6 7 8 9 10 11 12
Years
12 Year Count of Horses in HMA
No Mgt.
Base Year = 3,750
Year 12 = 10,418
20
If Planned Removals every 3 yrs
Base Year 3,750
0
2,000
4,000
6,000
8,000
10,000
12,000
0 1 2 3 4 5 6 7 8 9 10 11 12
Years
12 Year Count of Horses in HMA
No Mgt.
Target Mgt. level
with Mgt.
AML target = 333
21
Planned Removals every 3 yrs – relaxed AML
0
2,000
4,000
6,000
8,000
10,000
12,000
0 1 2 3 4 5 6 7 8 9 10 11 12
Years
12 Year Count of Horses in HMA
No Mgt.
Target Mgt. level
with Mgt.
AML target = 1,500
22
If Only 1 Removal & Treatments Every 3 Yrs
0
2,000
4,000
6,000
8,000
10,000
12,000
0 1 2 3 4 5 6 7 8 9 10 11 12
Years
12 Year Count of Horses in HMA
No Mgt.
Target Mgt. level
with Mgt.
Single HMA Simulation
12 Year PV Cost* ($millions)
12 Year dollar outlay ($millions)
A. Removals every 3 yrs.
22.2 26.5
B. Removals with relaxed AML
20.0 24.7
C. 1 removal + multiple fertility treatments
15.7 18.5
Savings (B over A) 2.2 1.8
Savings (C over A)6.5
(29.3% savings)8.0
(30.2% savings)
23
Cost Comparisons
*Present value at 4.3% (CBO)
24
Simulation Approximation for All HMAs
25
Age Distribution on Range
0 2 4 6 8 10 12 14 16 18 20-5%
0%
5%
10%
15%
20%
25%
30%1. Based upon Garfield flat 1993
Age of Horses
Share
of
Tota
l
0 2 4 6 8 10 12 14 16 18 20-5%
0%
5%
10%
15%
20%
25%
30%4. Based upon Grange 1995
Age of Horses
Share
of
Tota
l
26
Young Horses Expand Rapidly
0 2 4 6 8 10 12 14 16 18 20
-5%
0%
5%
10%
15%
20%
25%
30%
Age of Horses
Sh
are
of
Tota
l
All approach Log Normal distribution over time
27
Does approach work with different initial population distributions?
Does it work for multiple HMAs?
Does it incorporate new data as it becomes available?
Tests of Robustness
28
All HMAs : 3 Year Phase-in Removals Only
-
50,000
100,000
150,000
200,000
250,000
0 1 2 3 4 5 6 7 8 9 10 11 12
Years
12 Year Count of Horses in HMAs
No Mgt.
Target Mgt. level
with Mgt.
AML target = 24,750
Base Year = 40,044
29
All HMAs : 3 Year Phase-in With Treatment
-
50,000
100,000
150,000
200,000
250,000
0 1 2 3 4 5 6 7 8 9 10 11 12
Years
12 Year Count of Horses in HMAs
No Mgt.
Target Mgt. level
with Mgt.
AML target = 24,750
Simulation of HMAs 12 Year PV Cost* ($millions)
12 Year dollar outlay ($millions)
A. Removals every 3 yrs. (limited treatment at best)
346.8 468.6
B. 1 removal + multiple fertility treatments
208.5 264.6
Savings (B over A)138.3
(39% savings)204.0
(43% savings)
30
Cost Comparison All HMAs
*Present value at 4.3% (CBO)
31
I. Dynamic Population Simulation model
II. Economic Costing Model
III. Management Optimization Model
IV. Population & Range Database System
MODEL COMPONENTS
EconFirst Associates LLC with HSUS Support
WILD HORSE MANAGEMENT SYSTEM:
POPULATION PROJECTION & COSTING MODEL
