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Abstract: Disturbance interactions are of great interest in ecology due to their potential to cause non-linear, unexpected results. Increases in disturbance frequency and intensity as a result of climate change increase the need for better conceptual and mechanistic understanding of ecosystem response to compounded perturbations. Impacts on structural elements of ecosystems, such as tree species, are particularly important, as changes in these species’ populations, frequencies, and distributions may influence landscape functioning for extended periods of time. This study investigated the impact of three overlapping disturbances common to western US forests (wind, logging, and fire) on three dominant tree species: Lodgepole pine, Engelmann spruce, and quaking aspen. Ninety-nine study plots were examined across a gradient of interaction severities from a 1997 blowdown, subsequent salvage logging, and a 2002 fire in a Rocky Mountain subalpine forest. Regeneration of dominant species was analyzed in the context of disturbance history and species-specific disturbance response strategies. Results indicated that species are differentially affected by disturbance interactions. Lodgepole pine is highly sensitive to both previous disturbances and their severities, whereas spruce and aspen are insensitive to disturbance history, although both showed higher recruitment levels in three-disturbance environments. Disturbance types, combinations, and specific resilience mechanisms appear to be more important than number of disturbances. Disturbance interactions were not necessarily additive, and in some cases, three disturbances were less severe than two. As a result of long-distance dispersal, aspen seems likely to greatly increase in dominance across the landscape. Species-specific responses are generalized through their individual response strategies, with specialized responses being less resilient to multiple disturbances than generic seed dispersal strategies. Differential responses by structural tree species will likely drive an increase in future landscape heterogeneity and potential decreases in future landscape resilience to fire. [Copyright &y& Elsevier]

Illustrates the use of linear spectral mixture analysis (LSMA) in detecting fire and grazing patterns in tallgrass prairie in Kansas. Procedure used in LSMA; Description of the study site in Konza Prairie; Need to identify several indicator variables to assess the state and structure of managed grassland systems.