HIERARCHICAL ANALYSIS OF FOREST BIRD SPECIES–ENVIRONMENT RELATIONSHIPS IN THE OREGON COAST RANGE

Abstract

Species in biological communities respond to environmental variation simultaneously across a range of organizational levels. Accordingly, it is important to quantify the effects of environmental factors at multiple levels on species distribution and abundance. Hierarchical methods that explicitly separate the independent and confounded influences of environmental variation across several levels of organization are powerful tools for this task. Our study used a hierarchical approach to partition explained variance in an Oregon Coast Range bird community among plot‐, patch‐, and landscape‐level factors. We used a series of partial canonical ordinations to decompose species–environment relationships across these levels of organization to test four hypotheses about the importance of environmental control over community structure. We found that plot‐level factors were better predictors of community structure than patch‐ or landscape‐level factors. In addition, although landscape‐level variables contributed substantial independent explanatory power, there was little evidence that patch‐level environmental variability provided additional explanation of community structure beyond that provided by plot‐ and landscape‐level factors. At higher levels of the hierarchical analysis, we found that, among plot‐level factors, vegetation cover type was as powerful a predictor of community structure as detailed floristics, and more powerful than vegetation structure. At the landscape level, we found that landscape composition and configuration both provided substantial independent explanatory power, with landscape composition being the better overall predictor. Our results have a number of implications for sampling, analysis, and conservation. For example, misleading results could be obtained by studies conducted at a single organizational level. Also, the high degree of confounding among several levels of our analysis suggests that there is a lack of independence between the influences of environmental structure at different organizational levels. Due to this confounding, our results suggest that patch‐based studies of forest–bird ecological relationships in the Oregon Coast Range may be equivocal. In addition, the power of mapped cover class as a plot‐level predictor variable suggests that coarse‐filter, multiscale approaches utilizing remote sensing and GIS may be nearly as effective at predicting local patterns as expensive field surveys of habitat conditions at the plot level, and more effective at predicting patterns continuously across large regions.