Error and the Gap Analysis Model
Jennifer N. Morgan and Basil G. Savitsky
ERROR is a concept of growing concern to the geographic community as GIS usage and products rapidly are becoming more widespread. An understanding of the limitations of ecological modeling should serve to further the appropriate application of the gap analysis model.
Three functions have been identified that biological models perform to varying degrees of quality (Levins 1966). Any given model can maximize realism, precision, or generality, but no model can maximize all three qualities. Realism indicates the ability of the model to define reality. Precision is the accuracy associated with the measurements used in the model. Generality is the ability to apply the model in a variety of settings. A model that is highly realistic to the wildlife and habitat characteristics of the western United States probably would have low generality to the study of wildlife in Central America. A model that also requires high precision is difficult to apply in other settings which cannot meet the high precision standards. Gap analysis is a model that has great generality—it can be applied in a variety of geographic settings and at a variety of geographic scales. However, there are precision and realism limitations associated with the gap analysis model as a result of its generality. The constraints associated with precision will be discussed in the context of geographic error. The constraints associated with realism will be discussed in the context of biological error.
Cartographic and thematic error are two major categories of geographic error (Veregin 1989). The cartographic errors introduced in the Costa Rica project were