ABSTRACT of presentation:

Whitney, P., B. G. Marcot, McConnaha, D. H. Johnson, and D. Hart. 2001. A fish and wildlife rosetta stone: developing a common basis for the ecosystem diagnosis and treatment (EDT) method.  Presented at: Annual Meeting, Northwest Chapter of Society for Ecological Restoration, 4-6 April 2001. Bellevue, WA.
 

An impediment to developing an integrated ecological approach to watershed management is that wildlife and fish biologists lack a common intellectual tradition and lexicon. Management objectives and terminology differ between the two disciples, which often inhibits communication and progress. In the Multi-species planning process, Ecosystem Diagnosis and Treatment (EDT) provided a common intellectual framework that has fostered a multi-species approach. In this paper we will discuss a fish and wildlife "Rosetta Stone" that argues for the multi-species application of EDT. The theoretical underpinnings of the EDT method are defined in terms of productivity and capacity equations that are taken from the disaggregated Beverton-Holt model of Moussalli and Hilborn.

The Beverton-Holt model, usually in its aggregated form, has been widely used in fisheries modeling and management. It describes the density-dependent relationship between numbers of recruits and adult spawners that produce them. In its aggregated form, the Beverton-Holt stock-recruit relationship is identical to the difference form of the logistic equation for lag-free density-dependent population growth. The logistic equation as described in ecology text books are more familiar to wildlife biologists than Beverton -Holt equations. The disaggregated form of the Beverton-Holt is identical to the disaggregated form of the logistic model for density-dependent population growth as described by Leslie. Both the Mousalli and Hilborn equation and the Leslie matrix can be expanded mathematically in the same manner to express the expected number of recruits in terms of adult breeders. These points provide a rationale for free translation between EDT information types (e.g. Level 2 habitat description) for fish and wildlife. It also provides a point of commonality between EDT and other models such as those based on a Leslie matrix.