PS 11-82 - Priority effects in sessile herbivore interactions

Monday, August 2, 2010
Exhibit Hall A, David L Lawrence Convention Center
Mailea Miller-Pierce and Evan Preisser, Biological Sciences, University of Rhode Island, Kingston, RI
Background/Question/Methods:

Although research into plant-herbivore interactions often focuses on the impact(s) of a single herbivore species, multiple herbivores and/or pathogens can jointly affect host plants and each other in ways that cannot necessarily be inferred from single-species evidence. Recognition of the importance of such enemy-plant interactions has driven interest in exploring both short and long-term interactions between multiple species.

We conducted a multi-year experiment in which we assessed competitive interactions between two sessile herbivores, the hemlock woolly adelgid Adelges tsugae (‘HWA’) and the elongate hemlock scale Fiorinia externa (‘EHS’). Both species are invasive on the east coast of the US and share a common host, the eastern hemlock Tsuga canadensis. HWA emerges in the spring 1-2 months before EHS, allowing it to settle and feed in the absence of competition from the later-arriving species. Over multiple years, however, either species may attempt to settle on a host plant that has been already been colonized by the other species.

We tested for priority effects by allowing the two species to colonize eastern hemlock simultaneously (i.e., both species colonize during the same growing season) or sequentially (i.e., one species is present for two years prior to the second species’ arrival).

Results/Conclusions:

When colonizing simultaneously, neither species reduced the other’s density. When colonization proceeded sequentially, however, HWA densities were 45% lower on foliage that had been previously colonized by EHS. In contrast, EHS densities were not affected by previous HWA colonization. Our results indicate that within- and between-year priority effects can differ substantially in both nature and magnitude, and argues that caution should be used when attempting to extrapolate long-term effects from short-term experiments.

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