NCEAS Working Groups
Biggest Bang for the Buck: Really melding demographic theory with economics
Project Description
Because society has limited resources, the recovery of endangered species must contend with scarcity. Ecologists may be able to identify a host of beneficial management actions, but economics resources (and political will) are rarely sufficient to pursue all of those actions. An important question to address, then, is the following: Among the many possible actions that can aid the recovery of a species, which ones should be given higher priority? In practice, these decisions are informed by an ad hoc mixture of biological data, demographic theory, economic information, and politics. Although we cannot improve the political process, there is room for substantial improvements in how the economics and ecology are combined when addressing the issue of priorities.
First it is worth noting that both ecologists and economists often feel they do address priorities within the context of their own disciplines. For example, when ecologists calculate so-called elasticities in demographic matrix models the implication is that in doing so, they are identifying those opportunities for management that will yield the largest improvements in annual rate of population growth (l) per unit increase in survival. The prominence (and limitation) of this ecological theory aimed at priority-setting is highlighted by a recent collection of papers in Ecology (Heppell et al. 2000). Unfortunately, examinations that focus only on demographic parameters and do not explicitly include economics really do not get at the question of "biggest bang for the buck" (BBB). Conversely, economists make eminently reasonable-sounding recommendations about conservation priorities using cost-benefit analyses, or perhaps even formal economic optimization algorithms. Unfortunately, these purely economic analyses, which consider costs and benefits without regard to demographic responses, cannot really provide an apt description of net ecological benefits. A gap needs to be closed. We intend to bring together a small group of economists and ecologists to develop formal analytical tools that combine ecological and demographic processes into the same framework, and form the question "where do we get the biggest bang for the buck?" in the way we think it should be asked. To ground the theory in the real world we will apply our analyses to two important ecological case studies: managing for the recovery of loggerhead sea turtles in southeastern United States, and managing for the recovery of chinook salmon in Northwestern United States. Our project will provide both practical results for real-world decisions, and the development of methods and theory that combine demographic matrix theory with economic approaches.
Principal Investigator(s)
Gardner M. Brown, Peter Kareiva, Mark L. Plummer
Project Dates
Start: October 5, 2000
End: January 26, 2002
completed
Participants
- Timothy Beechie
- NOAA, Northwest Fisheries Science Center
- Barbara Best
- University of Washington
- Gardner M. Brown
- University of Washington
- Ted Case
- University of California, San Diego
- Hal Caswell
- Woods Hole Oceanographic Institution
- Donna Darm
- Unknown
- Blake Feist
- NOAA, Northwest Fisheries Science Center
- Daniel Goodman
- Montana State University
- Wade L. Griffin
- Texas A and M University
- Danelle Heatwole
- NOAA, Northwest Fisheries Science Center
- Selina S. Heppell
- Oregon State University
- Daniel D. Huppert
- University of Washington
- Peter Kareiva
- NOAA, Northwest Fisheries Science Center
- Jim Kramer
- Unknown
- Michelle McClure
- NOAA, Northwest Fisheries Science Center
- George Pess
- NOAA, Northwest Fisheries Science Center
- Mark L. Plummer
- Discovery Institute
- James Regetz
- Princeton University
- Amy Robinson
- NOAA, National Marine Fisheries Service (NMFS)
- Mary Ruckelshaus
- NOAA, Northwest Fisheries Science Center
- Michael H. Schiewe
- Unknown
- E. A. Steel
- NOAA, Northwest Fisheries Science Center
- James Wilen
- University of California, Davis