Title

Habitat Suitability Mapping for Marbled Murrelets in Clayoquot Sound

Document Type

Book Chapter

Publication Date

3-2003

Abstract

Digitally mapped information on the habitats of threatened wildlife species, in particular the Marbled Murrelet (Brachyramphus marmoratus), is important to the management of forest resources in this region. We created habitat suitability maps for Marbled Murrelets based on a Habitat Suitability Index model, which evaluates forest polygons from Vegetation Resource Inventory (VRI) maps. The VRI maps, which contain detailed land cover information with a focus on forest cover, were determined to be better suited as a basis for the model than the Terrestrial Ecosystem (TEM) maps, which contain biogeoclimatic information on vegetation associations. We reached this conclusion by comparing mapped vegetation data with field data and by considering the relevance of the mapped information to murrelet nesting. Information on habitat requirements of murrelets, which was the basis for the model, came from past murrelet inventories and from the literature. This information guided our selection of vegetation characteristics used to represent habitat suitability. We sampled these characteristics in vegetation plots in stratified, randomly-selected polygons from VRI maps. The sampled variables describing habitat suitability were summarized in two factors by a Principal Component Analysis (PCA) and related to mapped variables available for these polygons. The significant relationships between mapped and PCA factor variables were modelled with 90th quantile least absolute deviation regressions. Based on these regressions and information from literature we selected seven mapped variables to be included in a habitat suitability model. We constructed non-linear, individual suitability indices (SI), which assigned evaluation scores to the values of the seven selected mapped variables. The seven individual SIs were combined in a single equation whose output is a habitat suitability index (HSI) between 0 and 1 for each mapped polygon. We divided the HSI scores into four categories: “Excellent” (HSI >0.875); “Good” (HSI between 0.78 and 0.875); “Sub-optimal” (HSI between 0.65 and 0.78); and “Unsuitable” (HSI