Explaining biodiversity patterns, or

Transcription

1 Explaining biodiversity patterns, or how to characterize an elephant Hawkins et al Allen Hurlbert University of North Carolina James Stegen Pacific Northwest National Lab

2 Explaining biodiversity patterns, or how to characterize an elephant Hawkins et al Allen Hurlbert University of North Carolina James Stegen Pacific Northwest National Lab

3 Images: pageresource.com

4 Image: pageresource.com radiointeractive.blogspot.com

5 Disturbance Ecological Limits Tropical Niche Conservatism Diversification Rates Biotic Interactions Out-of-the-Tropics Image: radiointeractive.blogspot.com

6 Disturbance Ecological Limits Diversification Rates Biotic Interactions Out-of-the-Tropics Image: radiointeractive.blogspot.com

7 Richness Ecological Limits Latitude

8 Richness Richness Richness Richness Richness Richness Disturbance Ecological Limits Tropical Niche Conservatism Latitude Diversification Rates Latitude Biotic Interactions Latitude Out-of-the-Tropics Latitude Latitude Latitude

9 Take Home Messages 1 Testing the predictions (and assumptions) of multiple hypotheses will yield the strongest inferences

10 Take Home Messages 1 Testing the predictions (and assumptions) of multiple hypotheses will yield the strongest inferences --But the simplest predictions of diversity hypotheses are often not mutually exclusive

11 Take Home Messages 1 Testing the predictions (and assumptions) of multiple hypotheses will yield the strongest inferences --But the simplest predictions of diversity hypotheses are often not mutually exclusive 2 Simulation models can help identify potentially diagnostic predictions and evaluate assumptions

12 Simulating diversification COOL TEMPERATE WARM TROPICS Hurlbert & Stegen 2014 Ecology Letters

13 Simulating diversification COOL TEMPERATE WARM TROPICS

14 Simulating diversification COOL TEMPERATE WARM TROPICS speciation

15 Simulating diversification COOL TEMPERATE WARM TROPICS dispersal speciation

16 Simulating diversification COOL TEMPERATE WARM TROPICS Population sizes (N i ) assigned based on the match between traits and environment

17 Simulating diversification K max Population sizes (N i ) assigned based on the match between traits and environment And if energetic constraints are present, N i are rescaled so that Σ N i K max

18 Simulating diversification K max Population sizes (N i ) assigned based on the match between traits and environment And if energetic constraints are present, N i are rescaled so that Σ N i K max

19 Simulating diversification Stochastic extinction as a function of population size

20 Simulating diversification

21 Developing a simulation model

22 Simulating diversification Pure niche conservatism Diversification scenario Energy gradient Speciation gradient Disturbance gradient Niche conservatism Regional carrying capacity NA Per individual speciation probability Disturbance magnitude 0 0 0

23 Simulation patterns What empirical patterns are diagnostically predictive of the simulated scenario that generated them?

24 Simulation patterns classical gradient reverse gradient tropical ancestor temperate ancestor

25 Simulation patterns

26 β Simulation patterns

27 Simulation patterns Niche conservatism alone Niche conservatism plus a zero sum constraint β

28 Simulation patterns 2014 bamm-project.org

29 Simulation patterns fast RATE slow

30 Simulation patterns fast RATE slow

31 Simulation patterns fast RATE slow tropics REGION temperate

32 Speciation rate Simulation patterns fast RATE slow tropics REGION temperate

33 Evaluating an empirical system Sebastes rockfish Hyde & Vetter 2007

34 Evaluating an empirical system Hurlbert & Stegen 2014 Time

35 Evaluating an empirical system Hurlbert & Stegen 2014 Time

36 Evaluating an empirical system Hurlbert & Stegen 2014 Time

37 Evaluating an empirical system Hurlbert & Stegen 2014 Time

38 Evaluating an empirical system Hurlbert & Stegen 2014 Time

39 Evaluating an empirical system

40 Evaluating an empirical system

41 Evaluating an empirical system Speciation rate Time Latitude

42 Conclusions Simulations can address complex interactions of processes Energetic constraints Niche conservatism Episodic Disturbance Speciation rates

43 Conclusions Simulations can address complex interactions of processes Energetic constraints Niche conservatism Episodic Disturbance Speciation rates Coevolutionary interactions Resource competition Dispersal limitation Evolutionary innovations

44 Conclusions Simulations can point to potentially diagnostic patterns Temperate Tropical Time Phylogeny shape Variation in phylogenetic structure across space Variation in rates across time and space

45 Conclusions Simulations can keep us focused on addressing multiple working hypotheses Hypothesis Niche conservatism Ecological limits Speciation rates Disturbance Out-of-the-tropics Biotic interactions Predicted Patterns A B C D E F G H I

46 Conclusions Simulations can keep us focused on addressing multiple working hypotheses Hypothesis Niche conservatism Ecological limits Speciation rates Disturbance Out-of-the-tropics Biotic interactions Predicted Patterns A B C D E F G H I

47 Conclusions Simulations can keep us focused on addressing multiple working hypotheses Hypothesis Niche conservatism Ecological limits Speciation rates Disturbance Out-of-the-tropics Biotic interactions Predicted Patterns A B C D E F G H I

48 Conclusions Simulations can keep us focused on addressing multiple working hypotheses Hypothesis Predicted Patterns A B C D E F G H I Niche conservatism Ecological limits Speciation rates Disturbance Out-of-the-tropics Biotic interactions

49 Conclusions Simulations can keep us focused on addressing diagnostic predictions Hypothesis Predicted Patterns A B C D E F G H I Niche conservatism Ecological limits Speciation rates Disturbance Out-of-the-tropics Biotic interactions

50 Disturbance Ecological Limits Tropical Niche Conservatism Diversification Rates Biotic Interactions Out-of-the-Tropics