Null models and observed patterns of native and exotic diversity: Does native richness repel invasion? Rebecca L. Brown, 1,2 Jason D. Fridley, 1 and John F. Bruno 1 1 University of North Carolina-Chapel Hill 2 Patrick Center for Environmental Research

Diversity Invasion Prieur-Richard et al Stachowitz et al Dukes 2002 Tilman 1997 Hector et al Knops et al (mostly experimental) Stohlgren and Chong 2002 Wiser et al Bruno et al Burger et al Sax 2002 Lonsdale 1999 (mostly observational) Levine 2001 Lavorel et al Brown and Fridley 2003 Duncan 1996 Stohlgren et al Brown and Peet 2003 Does diversity control invasion? Diversity Invasion + - Confounded or neutral relationship

Small scales: Saturation, plant to plant competition = negative relationship Spatial scale effects Larger scales: Variation in other factors (disturbance, propagules, fertility) = positive or no relationship

Native species richness Exotic species richness 100 m 2 1 m m m Southern Appalachian Riparian Plant Communities NS p = 0.02p <.001p = 0.001

What is the scale-dependence of the native- exotic richness relationship in a randomly assembled community? BUT – do these relationships imply biological mechanisms or could they be observed in randomly assembled communities?

Randomly assembled communities: the null model Create simulated communities with native and exotic species sampled at multiple scales Randomize native and exotic species codes in real communities

5 Species Pool: 75% Native spp 15% Exotic spp 10% Blank Richness varied randomly, spp Abundance varied randomly, 1 to 10,000 individuals Quadrats: 6 scales Species drawn from pool Simulation of randomly assembled communities

Simulation method Randomly pick # of sp in pool, assign abund. to each sp Randomly pick 1 “individual” from pool Add one individual of that sp to quadrat Repeat until quadrat is filled (5 to 800 spaces) When full, repeat process 100 times for each quadrat scale 20 – 100 spp 1-10,000 individuals Pool: 75% native 15% exotic 10% blank

Exotic Richness Native Richness N = 800 Simulation of random quadrats

Exotic Richness Native Richness N = 800N = 100 Simulation of random quadrats

Exotic Richness Native Richness N = 800N = 100N = 50 Simulation of random quadrats

Exotic Richness Native Richness Exotic Richness N = 800N = 100N = 50 N = 20 Simulation of random quadrats

Exotic Richness Native Richness Exotic Richness Native Richness N = 800N = 100N = 50 N = 20N = 10 Simulation of random quadrats

Exotic Richness Native Richness Exotic Richness N = 800N = 100N = 50 N = 20N = 5N = 10 Simulation of random quadrats

Native species richness Exotic species richness Constraints on high native-exotic richness at smallest scales 100 individuals Null relationship Species pool: 75 Natives, 15 Exotics

Native species richness Exotic species richness Constraints on high native-exotic richness at smallest scales 100 individuals 50 individuals Null relationship Species pool: 75 Natives, 15 Exotics

Native species richness Exotic species richness Constraints on high native-exotic richness at smallest scales 100 individuals 50 individuals Null relationship Species pool: 75 Natives, 15 Exotics 10 individuals

Native species richness Exotic species richness 100 individuals 50 individuals Null relationship Species pool: 75 Natives, 15 Exotics 10 individuals

Summary – Simulated Data In simulated randomly assembled communities, the relationship between native and exotic richness is positive at large scales, and negative at small scales Positive: because plots differ in total richness; slope is simply ratio of natives to exotics in the species pool Negative: due to constraints on total richness at very small scales

Next: real data To test whether observed patterns of native and exotic species richness are different from pattern generated by random assembly (the null expectation): –Randomize native and exotic species labels in the species pool

Permutation tests for observational data Species pool Sp A Sp B Sp C Sp D Nativity Label Native Exotic Native Permuted Label Exotic Native Calculate correlation coefficient (r) or slope (s) Calculate correlation coefficient (r) or slope (s) Repeat 500x, compare null distribution to real value Repeat 500x, compare null distribution to real value

Native species richness Exotic species richness 100 m 2 1 m m m Actual results: Riparian plant communities NS p = 0.02p <.001p = 0.001

Permutation results: Riparian plant communities

Coastal plant communities, 24 sites at 500 m Site native richness Site exotic richness

Coastal plant communities, 24 sites at 500 m Site native richness Site exotic richness

Conclusions The native-exotic richness relationship is scale-dependent, BUT, this is the null expectation –With our null model – “competition” for space among individuals, not species It is important to consider the null expectation when evaluating mechanistic explanations for patterns in data

Acknowledgements Advising and Discussion: Bob Peet, Peter White, Jim McNair, UNC Plant Ecology Lab Funding: National Science Foundation, UNC Graduate School, UNC Department of Biology, UNC Ecology Curriculum, Sigma Xi, The Nature Conservancy, USDA National Forest Service, Patrick Center for Environmental Research Field crews