Shelterbelts are human-made habitats consisting of rows of shrubs and trees planted either in fields or on the windward side of farmstead dwellings. Shelterbelts provide wooded habitat for a large variety of birds and other wildlife. A model to predict wildlife species richness in shelterbelts (Schroeder 1986) was published as part of the U.S. Fish and Wildlife Service Habitat Suitability Index (HSI) model series (Schamberger et al. 1982). HSI models have been used extensively by wildlife managers and land use planners to assess habitat quality. Several HSI models have become the focus of a test program that includes analysis of field data for corroboration, refutation, or modification of model hypotheses. Previous tests of HSI models focused either on single species (e.g., Cook and Irwin 1985, Morton et al. 1989, Schroeder 1990) or examined portions of HSI models, such as the relationship between cavity abundance and tree diameter (Allen and Corn 1990). The shelterbelt model, however, assesses habitat value at the community level. The effects of habitat characteristics, area, and perimeter on diversity and abundance of bird and mammal species in shelterbelts were first studied by Yahner (1983a, b). Johnson and Beck (1988) confirmed the importance of shelterbelts to wildlife and identified area, perimeter, and diversity and complexity of vegetation as key measurements of habitat quality. The shelterbelt model incorporates both specific habitat variables and larger scale parameters, such as area and configuration, to predict wildlife species richness. This shift in perspective comes at a time of increasing interest in conservation and planning beyond the species levels (e.g., Graul and Miller 1984, Hutto et al. 1987, Schroeder 1987: 26).

We report results of a 3-year study of spatial and vegetative parameters and their relationship to breeding bird species richness (BSR) in 34 Kansas shelterbelts. Our objectives were to test the hypothesis presented in the original shelterbelt model (Schroeder 1986) that species richness can be predicted by shelterbelt characteristics and to investigate alternative models for predicting BSR in shelterbelts.