The Reliability and Application of Methods Used to Predict Suitable Nesting Habitat for Marbled Murrelets

Identifying and mapping suitable nesting habitat within coastal forests is a key element in the recovery and management of the Marbled Murrelet (Brachyramphus marmoratus), which is listed as Threatened in Canada. This article reviews the reliability and application of three primary methods used to assess habitat suitability: the BC Model, a GIS-based algorithm using Vegetation Resources Inventory (VRI); air photo interpretation (API), direct assessments from air photos based on forest structure; and low-level aerial surveys (LLAS), helicopter surveys assessing forest canopy structure and the presence of potential nest platforms. In general, LLAS provides the most reliable identification and is the only method of the three that estimates the occurrence of potential nest platforms in the forest canopy. The other two methods, API and the BC Model, are substantially less reliable in identifying habitat actually used by nesting murrelets. Spatial scale and survey intensity affect habitat classification using all three methods. Generally, fine-scale (~3 ha), high-intensity classifications with LLAS and API are more likely to detect suitable habitat at known nest sites than those using medium-scale (10s or 100s ha) and/or low-intensity classifications. Even with fine-scale high-intensity application, 15% and 25% of known nest sites were still classified as “unsuitable” habitat with LLAS and API, respectively. All three methods applied at the medium scale for mapping appeared to miss fine-scale nesting habitat (i.e., small numbers of suitable trees occurring in otherwise unsuitable habitat). Areas of mapped suitable habitat can therefore be adjusted to take this discrepancy into account, and methods to do this are discussed.