2000 Progress Report: Land and Management with Biological and Economic ObjectivesEPA Grant Number: R826619
Title: Land and Management with Biological and Economic Objectives
Investigators: Montgomery, Claire , Arthur, Jeffrey L. , Polasky, Stephen
Institution: Oregon State University
EPA Project Officer: Lee, Sonja
Project Period: October 1, 1998 through December 31, 2000 (Extended to December 31, 2001)
Project Period Covered by this Report: October 1, 1999 through December 31, 2000
Project Amount: $131,089
RFA: Decision-Making and Valuation for Environmental Policy (1998) RFA Text | Recipients Lists
Research Category: Economics and Decision Sciences
The proposed research will combine biological models of wildlife population dynamics and of timber stand growth with a financial evaluation of timber harvest in a unified framework that can be used by land managers to assist in developing effective management decisions. This research will build upon a small but growing body of research that attempts to demonstrate tradeoffs between conservation and financial land use objectives.
A preliminary model identifies the production relationship between total timber harvest over a 100-year time horizon and likelihood of persistence for species parameterized to represent the Northern flying squirrel (Glaucomys sabrinus) as predicted by the PATCH population simulation model. The squirrel prefers old conifer forests; its maximum dispersal distance is relatively small making the quality of neighboring habitat important for persistence. We developed results for two 62,500-hectare study areas drawn from a 1.2-million-hectare landscape in the western Cascade region of Oregon: one with abundant high quality habitat, one with limited amount of medium quality habitat. A simulated annealing heuristic algorithm was employed to maximize the net present value of timber harvest subject to a range of targets for the likelihood of persistence. We developed and used a proxy for full PATCH simulations in the optimization algorithm. Each potential squirrel territory was assigned a score based on the quality of habitat in it and in neighboring territories within three surrounding rings. Logistic regression was used to estimate weights for each ring. The proxy was a function of a set of the top-scoring territories in each 10-year period in the 100-year time horizon. Solutions to the optimization algorithm consisted of a time series of timber management prescriptions (no action, wildlife thin, or clearcut harvest) for each territory in each 10-year period and a time series of the habitat maps that resulted from timber management. PATCH simulations were run for each solution to identify points close to the bounds on the production possibility set. Results were compared to a simple habitat reserve system in which a set of top-scoring territories were reserved from timber management activities and the remaining landscape was managed for maximum net present value of timber harvest. Results give the opportunity cost of achieving specific levels of certainty of population persistence on each study area in terms of the value of timber harvest forgone. They also provide a means for estimating efficiency loss associated with alternative conservation and timber management regimes.
Future model development will include:
- Simulation of an additional species that differs from the current species in body size, life span, fecundity, habitat preference, and dispersal characteristics. This will allow us to investigate tradeoffs between species with different habitat needs.
- Solving for a larger landscape. This will make the methods we use more widely useful, as land managers and forest policy makers come to rely on landscape level assessments of the impacts of forest management activities. It also will allow a more sophisticated representation of economic impacts of constraining timber harvest levels.
- Simulation of likely forest management scenarios for the landscape using predictions from the Oregon Department of Forestry "Oregon Forest Assessment" study that recognize differing landowner objectives and regulatory constraints. The model that we are developing traces out the production possibilities for species persistence and timber harvest for the study area in the absence of institutional or regulatory constraints. This simulation will demonstrate the usefulness of the model for assessing efficiency loss associated with such constraints (that is, the difference between the potential and the realized outcomes).