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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.

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Presentation on theme: "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."— Presentation transcript:

1 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

2 Diversity Invasion Prieur-Richard et al. 2000 Stachowitz et al. 2002 Dukes 2002 Tilman 1997 Hector et al. 2001 Knops et al. 1999 (mostly experimental) Stohlgren and Chong 2002 Wiser et al. 1998 Bruno et al. 2002 Burger et al. 2001 Sax 2002 Lonsdale 1999 (mostly observational) Levine 2001 Lavorel et al. 1999. Brown and Fridley 2003 Duncan 1996 Stohlgren et al. 1998 Brown and Peet 2003 Does diversity control invasion? Diversity Invasion + - Confounded or neutral relationship

3 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

4 0246810 0 1 2 3 05 1520 0 1 2 3 4 012345 0 1 2 3 Native species richness Exotic species richness 100 m 2 1 m 2 0.1 m 2 0.01 m 2 020406080100 0 10 20 30 40 Southern Appalachian Riparian Plant Communities NS p = 0.02p <.001p = 0.001

5 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?

6 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

7 5 Species Pool: 75% Native spp 15% Exotic spp 10% Blank Richness varied randomly, 20-100 spp Abundance varied randomly, 1 to 10,000 individuals Quadrats: 6 scales Species drawn from pool Simulation of randomly assembled communities 800 100 50 20 10

8 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

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

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

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

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

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

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

15 050100 Native species richness 0 50 100 Exotic species richness Constraints on high native-exotic richness at smallest scales 100 individuals Null relationship Species pool: 75 Natives, 15 Exotics

16 050100 Native species richness 0 50 100 Exotic species richness Constraints on high native-exotic richness at smallest scales 100 individuals 50 individuals Null relationship Species pool: 75 Natives, 15 Exotics

17 050100 Native species richness 0 50 100 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

18 050100 Native species richness 0 50 100 Exotic species richness 100 individuals 50 individuals Null relationship Species pool: 75 Natives, 15 Exotics 10 individuals

19 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

20 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

21 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

22 0246810 0 1 2 3 05 1520 0 1 2 3 4 012345 0 1 2 3 Native species richness Exotic species richness 100 m 2 1 m 2 0.1 m 2 0.01 m 2 020406080100 0 10 20 30 40 Actual results: Riparian plant communities NS p = 0.02p <.001p = 0.001

23 Permutation results: Riparian plant communities

24 Coastal plant communities, 24 sites at 500 m 2 46810121416 Site native richness 4 6 8 10 12 14 Site exotic richness

25 Coastal plant communities, 24 sites at 500 m 2 46810121416 Site native richness 4 6 8 10 12 14 Site exotic richness

26 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

27 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


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