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Testing mechanisms of the intermediate disturbance hypothesis using long-term

Testing mechanisms of the intermediate disturbance hypothesis using long-term data of saxicolous lichens. A. Pastore, C. Prather, E. Gornish, R. Ellis, and T. Miller Department of Biological Science, Florida State University, Tallahassee, FL 32306.

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Testing mechanisms of the intermediate disturbance hypothesis using long-term

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  1. Testing mechanisms of the intermediate disturbance hypothesis using long-term data of saxicolous lichens A. Pastore, C. Prather, E. Gornish, R. Ellis, and T. Miller Department of Biological Science, Florida State University, Tallahassee, FL 32306 For more information on this and other thrilling projects, please contact Abigail Pastore at apastore@bio.fsu.edu Results Introduction 1980 1985 1988 Figure 4. Changes in lichen cover through time on a single plot. Figure 2. A) Rates of colonization for the six most abundant species on the disturbed plots. B) Competitive abilities of the six most abundant lichen species measured on control plots. C) Radial growth rate of the six most abundant species measured on disturbed plots. The Intermediate Disturbance Hypothesis (IDH) has been frequently invoked over the last 30 years for its simple prediction that diversity can be explained as a result of a tradeoff between colonization and competition at different levels of disturbance. Despite many documented patterns of species diversity that appear consistent with the IDH, few studies actually test the presumed underlying tradeoff. Figure Legend asp = Aspicilia spp. rd = Rhizocarpon disporum xl = Xanthoparmelia lineola lm = Lecanora muralis pl = Unidentified lichen ls = Lecidella stigmataea A Kruskal-Wallis: chi-squared = 3.117, df = 5, p-value = 0.682 A preliminary analysis in 1978 of rock dwelling lichen communities revealed a unimodal relationship between rates of disturbance (shearing of the rock face) and diversity of lichen species (Fig 1). At that time, permanent plots were established that were followed until present to test the prediction of a trade off between colonization ability and competitive ability as well as other dynamics that could affect lichen species diversity. 1990 1992 1997 B Kruskal-Wallis: chi-squared = 11.010, df = 5, p-value = 0.0512 Figure 1. Each point represents a 1 m2 plot in the Gila National Forest, NM censused for lichen species in 1978. 2004 2007 2009 Methods Ten paired plots were established on horizontal rock faces near the Ben Lily Memorial in the Gila National Forest NM in 1978. All 10 cm x 10 cm plots were similar in slope, elevation (2100 m), and light exposure. One of each pair of plots was randomly selected, and the entire surface of the rock face removed with a chisel to simulate natural disturbance. Beginning in 1978, all control and disturbed plots were photographed approximately every two years, resulting in 18 photographs of each of the 20 plots over a 32-year period, allowing us to document lichen recolonization and competition. The colonization rate for each lichen species was determined by counting the number of new colonies on the disturbed plots over the 32 years. Competitive abilities were determined by placing a 100 point grid on photographs of the control plots and recording the lichen species at each point for every year photographed. We quantified competitive ability, Ci, of a lichen species i as where Wij is the number of instances a grid point transitioned from species j to species i, and Lij is the number of instances a grid point transitioned from species i to species j, for the total number of species, n. To further explore the community dynamics we also measured percent cover and average growth rate for each species. The lichen species at each grid point in the control plots was recorded, summed over all plots, and then averaged over each year as a measure for percent cover. Growth rates were determined by picking a random individual of each species on each disturbed plot and quantifying radial growth over 10 ±2 years. Kruskal Wallis tests were performed to assess significant differences among species for the response variables measured (colonization rate, competitive ability, growth rate, and abundance). Spearman’s rank correlation tests were performed across plots and across species to assess relationships between response variables. C Kruskal-Wallis: chi-squared =14.995, df = 5, p-value = 0.0104 Conclusions Figure 3. Percent cover of the six most abundant species over all control plots averaged over years. We did not find evidence for a simple trade-off between competitive ability and colonization ability. Therefore, our results do not support the mechanisms theorized to contribute to the patterns described by the IDH.  However, if we consider a broader suite of traits, we can explain the majority of the patterns of relative abundance.  For example, the most abundant species overall are Aspicilia spp. and Xanthoparmelia lineola.  Aspicilia has the highest colonization rate and competitive ability, while Xanthoparmelia also has a high competitive ability and the highest growth rate. Most of the other species have either low colonization rates or very slow growth rates, which may explain their low percent cover. This is not always the case, however (see Lecanora muralis). A final consideration is the unique natural history of lichens.  We expected, for example, that X. lineola might be the best competitor as its foliose growth form would overgrow and shade crustose species such as Aspicilia.  Instead, we observed that Aspicilia often persisted underneath the X. lineola, re-appearing when X. lineola flaked off in later years.  Results of our study suggest that we need to reconsider how species are successful, beyond simple colonization and competition traits. . Kruskal-Wallis: chi-squared = 80.498, df = 5, p-value = <0.0001 Table 1. Results of Spearman Rho tests for correlations between colonization, competition, growth, and abundance among the lichen species. Table gives Spearman Rho values – none are significant (P > 0.05). Acknowledgements This work was initiated by TEM in 1978 with the encouragement of Diane Davidson and Jim Brown. Patricia, Rick, and Bill Miller have helped with data collection.

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