Selecting costly reserves in a dynamic, uncertain world Christopher Costello Bren School, UCSB TNC Pacific Rim Conference February 21, 2003.

Selecting costly reserves in a dynamic, uncertain world

Christopher Costello

Bren School, UCSB

TNC Pacific Rim Conference

February 21, 2003

The problem

• Significant threats to biodiversity (local, global, terrestrial, marine, direct/indirect anthropogenic)

• Reserves can (in part) offset threats, therefore maintain biodiversity (other ecosystem functions)

• But creating reserves is costly; budgets are limited

• Question: How should reserves be designed to maximize biodiversity (or other objectives) given a limited budget?

A global view (TNC)…

TNC Mission

“To preserve the plants, animals and natural communities that represent the diversity of life on Earth by protecting the lands and waters they need to survive.”

The growing human footprint

(Sanderson et al., 2002)

Risks and conservation goals

• By some estimates: reserves needed to protect global biodiversity• 10-50% of terrestrial

(7.9% currently protected)• 20-35% of marine (0.5%

currently protected)

• An extremely complex problem!

They keep coming…

An economist’s simpler view…

3 sites

8 species

threats

(to get our heads around the idea)

[Costello & Polasky, 2003]

Site A

Site B Site C

1

8

2 34 5 6

7

12

56

40%50% 20%

A: Most endemic speciesB: Highest threatC: Greatest # species

Which site do you choose first?

A “warm-up exercise”

Key innovation from threat

• Traditional reserve selection literature treats all sites as 100% threatened.

• Influence of threats depends entirely on objective:

• To maximize protection of habitats & species (what we protect is what’s important) vs.

• To maximize composition, condition, and/or diversity of habitats & species (what is left is what’s important).

A tractable problem

• Landscape partitioned into sites

• At each time, each site is either:• (1) Reserved, (2) Unreserved (but still in good

condition and available for conservation action), or (3) Developed

• Characteristics of each site are tracked (e.g. species presence/absence, habitat quality, etc)

• Annual conservation budget, can carry over

The solution procedure

• Cumbersome to solve• Requires sophisticated stochastic dynamic

programming techniques• Computationally-intensive, non-intuitive,

difficult to implement in practice.

• So why am I telling you about this?– Modeling might help us learn general lessons

What can we learn in general?

• Does incorporating threat and dynamics change our thinking about the approach to conservation?

• Can this be implemented in practice for real-world problems?

• Monte Carlo simulation analysis to derive general conclusions, and

• Model applied to data for 333 native vertebrate species, 280 sites in S. California– Threat from spatially-explicit development forecasts for

year 2050

Some results

• Budget Timing: Can improve conservation outcomes by > 20% by up-front vs. sequential investment.

– Premium for making selections prior to development of prime conservation sites.

• Threat Timing: Looking at threat one period ahead yields nearly same conservation as with infinite foresight.

– Suggests an implementable heuristic.

2 brief advertisements

1. Ecological Linkage spanning the Santa Clara River (TNC/Bren)

• Collaborators: Casterline, Fegraus, Fujioka, Hagan, Mangiardi, Riley, Tiwari, McGinness

2. California Legacy Project (Bren Biogeography Lab)

• Collaborators: Davis, Stoms, Machado, Metz, NCEAS working group

Threat & cost in practice: Ecological Linkages

• Bren School interdisciplinary group project• Students work with TNC to design ecological

linkages to connect core habitat areas • Integrate into analysis:

• Ecological cost/Economic cost of alternative corridor designs

• Development forecasts and changes in corridor needs/quality

• Implementation strategy & feasibility

Ecological vs. economic costs

Ecological Cost

Eco

nom

ic C

ost

Each point representsa different path between2 core habitat areas.

Threat & cost in practice: California Legacy Project

• Statewide strategy to inform allocation of limited conservation budget

• Modeling, analysis, synthesis at Bren• Integrate into analysis:

• Land value

• Spatially-explicit development forecasts (2010, 2050, 2100)

• Context-dependent conservation values

• Approach allows us to: Prioritize conservation investments, compare/evaluate proposed projects.

Legacy: Sierra example

Value scaleZeroLowMediumHighVery High

Conclusions & remaining questions

• Incorporating dynamics & threat forces us to be explicit about our objectives• May get better outcomes at the same cost.

• If conservation budget available up-front, can get >20% improvement in conservation outcomes

• Simple methods exist for including threat, cost, dynamics in real-world conservation problems.

• Threat/cost tradeoff: can we say anything in general?• Market responses to conservation (restricted supply,

development feedbacks, and endogenous prices)?