1. Macroecology & uneven distributions of wealth Ken Locey

2. http://tchester.org/srp/plants/communities/figures/global_biodiversity_by_area.gif

3. 183,913,348 records of birds in the Global Biodiversity Information Facility database

4. Abundance: n i /N Distribution: f(k;λ) = λ k e -λ /k! Diversity: H’ = -Σp i *ln(p i ) …study of ecological relationships that involves characterizing and explaining statistical patterns of… Macroecology

5. Land birds Land mammals Geographic range patterns North-South (km) East-West (km) 100 1,000 10,000

6. Metabolic Theory of Ecology (MTE) Ecological phenomenon ∝ M 3/4 e -E/kt Temp. corrected max. rate of whole organism biomass production Slope = 0.76 R 2 = 0.99

7. Species Abundance Distribution Abundance Class frequency (frequency distribution)

8. http://encyclopediaurantia.org/images/ROM11.JPG

10. DATA

11. Computing GIS Math & Stats Metabolic rate ∝ M 3/4 e -E/kt Information: Tools

12. COLLABORATION & SHARING Code development Sharing Source networks

13. GIS Programming Published Research Data management Math & Stats Collaboration Undergraduate & Graduate research Skills Jobs Grad School

15. Center for Macroecology, Evolution, & Climate www.macroecology.ca macroecology.ku.dk whitelab.weecology.org

18. Species Abundance Distribution Abundance Class frequency (frequency distribution)

19. Species Abundance Distribution Rank in Abundance Abundance (Rank-abundance distribution)

20. Wheat Production (tons) tons 62.9 104588178.7

21. Poverty in Rural America, 2008 Percent in Poverty 54.5 - 2525 - 2020 – 14.314.2 – 12.212.1 - 1010 – 3.1

23. Distributions of Wealth (DOW) Supreme importance attaches to one economic problem, that of the distribution of wealth. Is there a natural law according to which the wealth of society is divided? – John Bates Clark Wealth: sources of human welfare which are material, transferable, and limited in quantity.

24. Total quantity ( Q) Community abundance Global Oil Consumption GDP, GNP Number of entities ( N) Species Nations Economic classes Distributions of Wealth (DOW)

25. If Q = 10 and N = 3, then: 8 unordered ways to sum N positive integers to obtain Q 8+1+1 7+2+1 6+3+1 6+2+2 5+4+1 5+3+2 4+4+2 4+3+3 Distributions of Wealth (DOW)

26. Do we observe the average of possible DOWs?

27. The feasible set (all possible shapes of the DOW) 16,958 shapes for Q = 50 & N = 10 Rank Wealth

28. Combinatorial Explosion QNSize of feasible set 501016,928 500102.013 × 10 12 5000101.531 × 10 21

29. Heat mapping the feasible set (or a random sample) ln(wealth) Rank Q=1,000 N=80

30. Heat mapping the feasible set (or a random sample) ln(abundance) Rank in abundance ca. 4.02x10 29 possible shapes for N=1000 & S=80

31. Ecological DOWs (species-abundance distributions) North American Breeding Bird Survey (1,583 sites) Forest Inventory and Analysis (7,403 sites) Mammal Community Database (42 sites) North American Butterfly Association (306 sites) Aquatic prokaryotes (92 metagenomes) – Arctic surface waters, Deep-sea Hydrothermal vents Terrestrial prokaryotes (48 metagenomes) – Arctic soils, agricultural soils Indoor fungi (124 metagenomes) – All continents except Antarctica Total: 9,598 different sites of diverse communities

32. Q = Total community abundance ( i.e. number of individuals) N = Species richness (i.e. number of species) Ecological DOWs (species-abundance distributions)

33. Observed wealth 10 0 10 1 10 2 Predicted wealth 10 2 10 1 10 0 R 2 per site OBSERVED: [1, 2, 10, 12, 20, 30, 40, 60, 110] PREDICTED: [1, 2, 11, 11, 22, 28, 43, 50, 117] R 2 = 0.99

34. Observed abundance 10 0 10 1 10 2 Predicted abundance 10 2 10 1 10 0 R 2 per site R 2 = 0.99 R 2 = 0.89 R 2 = 0.80 R 2 = 0.75

35. Observed abundance 10 0 10 1 10 2 Predicted abundance 10 2 10 1 10 0 R 2 per site R 2 = 0.99 R 2 = 0.89 R 2 = 0.80 R 2 = 0.75 R 2 per site 0.0 1.0

36. Observed abundance 10 0 10 1 10 2 Predicted abundance 10 2 10 1 10 0 R 2 per site 0.0 1.0 R 2 = 0.93

37. Observed abundance R 2 = 0.93 1,583 sites in the Breeding Bird Survey 10 0 10 1 10 2 10 2 10 1 10 0 R 2 per site Predicted abundance 0.0 1.0

38. R 2 = 0.84 7,403 tree communities R 2 = 0.80 306 butterfly communities R 2 = 0.78 42 mammal communities Observed abundance vs. Abundance at the center of the feasible set Count data

39. R 2 = 0.58 48 terrestrial prokaryote Observed abundance vs. Abundance at the center of the feasible set R 2 = 0.83 92 aquatic prokaryote R 2 = 0.76 124 indoor fungi Metagenomes

40. Food & Agriculture Organization of the UN US Dept of Energy, Energy Information Admin.

41. 0.830.910.93 Predicted supply Observed supply Food supply among nations (1960-2010) grams/capita/day * 0.1tons * 0.0001grams/capita/day

42. 0.690.770.91 Predicted pop. size Observed pop. size Population sizes among nations (1960-2009, millions of people)

43. 0.880.92 Predicted Observed Oil use among nations (1980-2009, barrels per day * 0.01)

44. Predicted home runs Observed home runs 0.930.880.90 0.91 0.89 0.940.93 (2002-2010) http://mlb.mlb.com

45. Are DOWs similar to the average of possible shapes? …very often Do Q and N constrain the DOW more than ever realized? …Yup Is the feasible set good for more than predictions? …Absolutely Is combinatorial explosion a pain in the *expletive*? …Not for long…?

46. Funding USU College of Science – Willard L. Eccles Fellowship NSF CAREER award to Ethan White Research grant from Amazon Web Services

47. Acknowledgments Individuals, agencies, organizations responsible for the collection and management of the: – Breeding Bird Survey, Christmas Bird Count, Forest Inventory and Analysis, Mammal Community Database, North American Butterfly Association, Argonne National Laboratory’s MG-RAST metagenomic server Colleagues & Collaborators – USU: Ethan White, Xiao Xiao, Dan McGlinn – Berkeley Harte Lab: Justin Kitzes – SESYNC: Bill Burnside UCO college of Math and Science

48. The feasible set as a framework Understanding Comparing Inequality

49. Percentile of the feasible set Gini’s coefficient of inequality

50. The feasible set (all possible values of species evenness) Species evenness Species richness, S Total abundance, N = 60

51. pdf 10,173 sites R 2 (obs vs. random sample)

52. Combinatorial Explosion QNSize of feasible set 100010886,745,696,653,253 1000100 302,194,941,264,401,427,042,462,944,147 1000900190,569,292

53. pdf 1,583 sites in the Breeding Bird Survey 0.2 0.4 0.6 0.8 0.8 0.6 0.4 0.2 R 2 (obs vs. random sample)

55. Feasible sets are dominated by hollow-curves Q=50, N=20 Q=50, N=10 Evenness (Smith & Wilson, 1996)

56. MTE prediction: species richness decreases with temperature (S ∝ Ae -E a /kT ) Computer Science Student: Biology student: Chemistry Student models based on chemical kinetics/activation energy microbe data, reasons why MTE should (not) work for microbes model development data scraping & management Temperature-richness predictions of MTE do not hold for diverse microbe communities as tested using several models of chemical kinetics. This may be explained by microbial dormancy and dispersal. + Conclusion(?)

57. Body mass (g) Land birdsLand mammals Body-size distributions Number of species continental regional patch