Comparing Cost, Risk, and Benefit Trade-offs Under Uncertainty:

Cheatgrass Case Study

Lisa Wainger and Dennis King,

University of MarylandRichard Mack, Washington State University

Jim Opaluch, University of Rhode Island

Establish Management Priorities

Evaluate Risks of No Treatment Option

Estimate Costs and Risk-Adjusted Benefits of

Site/Treatment Options

Identify Options with highest Cost-Effectiveness

Select Portfolio of Options to Manage Risk

Test Assumptions

DecisionFramework

Decision analysis components to examine with case study

• Benefits of Treatment– How do measures of damage avoided vary with

location and scale of analysis?

• Probability of Successful Restoration– How do site, location and characteristics of invasion

influence whether ecosystem services will be restored?

• Costs of Treatment– How do costs vary by location and scale of treatment?

Columbia Basin Study Area

Bromus tectorum (cheatgrass) distribution through time

1930s - present

Federal Land Ownership

Source data: USGS

Risks created by cheatgrass invasion

Increasing scale

Impact Mechanism Potential scale of Impact

Loss of rangeland productivity Provides lower quality forage than displaced natives or forage species

On-site

Loss of habitat in grasslands Displaces native bird species On-site to local Loss of life Increased fire frequency Local to regional Damage to property (homes, businesses, roads, dams)

Fire, post-fire erosion Local to regional

Health/amenity impacts Fire creates particulates in air and diminishes visibility

Local to regional

Lost recreation (amenity) value and lost income

Fire reduces number of visitors and quality of experience

Regional

Instream resource impacts (salmon fisheries)

Erosion diminishes water quality, substrate quality

Regional

with projectwithout project

Measuring Benefits

Benefits

Timei = service, t = time period

i

it

itt DEZ

E

D

Risk-Adjusted Benefits as a Function of Site and Landscape Conditions

Service Capacity

Service Scarcity

Service Loss Risk

Site Qualities

Service Value Index

Treatment effectivenessX

Performance Risk

E= [f(sr,lr) * p] + [f(sd,ld) * (1- p)] s = site qualities; l = location factors r = restored conditions; d = degraded conditions p = probability of restoring service

Does the Site Provide a Valued Service?

Site has features necessary to produce serviceSite has capacity to produce service because

“users” have access and complementary inputs are available

Service value is enhanced because service is scarce and substitutes are unavailable or expensive

The risk that the stream of services will end due to factors beyond the control of restoration is low.

Fire Risk

Source data: USDA FS ICBEMP

Fire Risk with Population

Treatment Scenarios

1. Preventive reseeding following fire– Apply to uninvaded sites

– Spread seeds aerially or use drill-seeding

– Sometimes follow aerial seeding with chaining

2. Herbicide treatment of existing stands– Applied to heavily invaded sites

– Multi-step process of burning, herbicide, seeding

Treatment Decision Tree

Type of Seed

B1

B3

Treat / No-treat

Cheatgrass Dominant

Natives Dominant

Forage Species Dominant

Cheatgrass Dominant

Cheatgrass Dominant

Natives Dominant

B1

B2

B1

B3

native

forage

No-treat

treat

(p = 0.90)

(p = 0.10)

Restorability Model

Probability of Success

Site Variables

Landscape Variables

Stochastic Variables

Cheatgrassregrowth

New cheatgrassinfestation

Native / Forage regrowth

Comparing Restorability

Contagion Index = 0.30 Contagion Index = 0.85

sparse dense

Evaluating Costs

• Trying to supply treatment effort to multiple sites for minimum cost– How do costs vary over infested area?– How many sites to treat?– How much area to treat in each location?

• Is it worth treating?

Site

Town

Road

Initial Costjk = Fixed Costk + Travel Costj*timej + Search Costj*area + Treatment Costjk*area j = location k=treatment method

SC = f(site factors); TC = g(site factors)

Minimum-Cost Network Flow

Equipment Sources and Treatment Destinations

Cost Per Unit Distance

low

high

Cumulative Travel Cost Map

Evaluating Marginal Costs of Treatment

Not Infested

High Cost

Avg. Cost

Low cost

Lowest costSource cell

MC = max {cell costjk | m}

Treated area m

Cell Costjk = Travel Cj*timej + Search Cj*area + Treat Cjk*area j = location k=treatment method

Marginal Cost Surface(time-dependent costs)

Sparse Infestation   Dense Infestation

8.8 Total Cost 31.2

0.5 Marginal Cost 1.4

227.4 Total Treatment (m2) 6,628.0

73.1 Marginal Treatment 366.0

Comparing Costs and Kill Efficiencysparse dense

Intensity of Invasion

Ecosystem Service Benefits Site A

Risk of Treatment Failure

Uncertainty of Returns from Treatment

Reversibility of Decline

p

Transferring Results to Risk Analysis for Recent Invasions

• How well do GIS databases perform for doing this type of modeling?

• What were the main factors contributing to cost of control and degree of impact?

• How does an evaluation of cost-effectiveness change with the scale of analysis?

• How do costs of control and level of impact change through time?

• How have transitions in land uses (e.g., recreation vs. rangeland) changed our perception of the impacts of cheatgrass?

• Given our current values, when, in the progression of the cheatgrass invasion, would treatment have been the most cost-effective?