Lank, David B.

The coastal old-growth forests of North America’s Pacific Coast are renowned both for their commercial and ecological value. This study adds to growing evidence that selective harvesting of the largest trees may have a disproportionate ecological impact. Marbled Murrelets (Brachyramphus marmoratus), a threatened species, nest almost exclusively in these old-growth forests. Detailed knowledge of nesting habitat selection provides guidance for habitat management and conservation. Habitat selection for this species has been studied at a variety of scales using ground and remote methods. However, because Marbled Murrelet nesting activity is limited to a single mossy platform on a single tree, we investigated nest tree selection within old-growth forest patches, using a set of 59 forest patches containing active nests. Nest trees were usually distinctive compared with neighboring trees in the surrounding 25 m radius patch. They averaged 15 to 20% taller than neighboring trees depending on region, had significantly larger stem diameters, more potential nesting platforms, and more moss. They had the most extreme values of height and width about three times as often as expected by chance. An analysis of moss platform use as a function of number of platforms per platform tree suggests that murrelets select individual platforms, rather than platform trees per se. Nonetheless, highly selective logging practices that remove high-value trees from stands may also remove trees most likely to be selected by nesting murrelets.

The Marbled Murrelet (Brachyramphus marmoratus) is a threatened alcid that nests almost exclusively in old-growth forests along the Pacific coast of North America. Nesting habitat has significant economic importance. Murrelet nests are extremely difficult and costly to find, which adds uncertainty to management and conservation planning. Models based on air photo interpretation of forest cover maps or assessments by low-level helicopter flights are currently used to rank presumed Marbled Murrelet nesting habitat quality in British Columbia. These rankings are assumed to correlate with nest usage and murrelet breeding productivity. Our goal was to find the models that best predict Marbled Murrelet nesting habitat in the ground-accessible portion of the two regions studied. We generated Resource Selection Functions (RSF) using logistic regression models of ground-based forest stand variables gathered at plots around 64 nests, located using radio-telemetry, versus 82 random habitat plots. The RSF scores are proportional to the probability of nests occurring in a forest patch. The best models differed somewhat between the two regions, but include both ground variables at the patch scale (0.2-2.0 ha), such as platform tree density, height and trunk diameter of canopy trees and canopy complexity, and landscape scale variables such as elevation, aspect, and slope. Collecting ground-based habitat selection data would not be cost-effective for widespread use in forestry management; air photo interpretation and low-level aerial surveys are much more efficient methods for ranking habitat suitability on a landscape scale. This study provides one method for ground-truthing the remote methods, an essential step made possible using the numerical RSF scores generated herein.