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Defense (edited)

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Defense (edited)

  1. 1. Have some donuts
  2. 2. background study sites measurement statistical conclusions Self patterning of piñon-juniper woodlands in the American southwest. Hugh Stimson Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  3. 3. Somalia 0 2 4 km Mcfayden Nature 1950
  4. 4. Somalia 0 2 4 km Mcfayden Nature 1950
  5. 5. Somalia 0 200 400 m Mcfayden Nature 1950
  6. 6. Australia 0 500 1000 m Dunkerley & Brown Arid Environments 1995
  7. 7. Mali 0 2 4 km Couteron & Kokou Plant Ecology 1997
  8. 8. Mexico Cornet & Delhoume 0 500 1000 m Diversity and Pattern In Plant Communities 1988
  9. 9. Mexico Cornet & Delhoume 0 500 1000 m Diversity and Pattern In Plant Communities 1988
  10. 10. background study sites measurement statistical conclusions Self patterning vegetation world wide world-wide Description and conceptual models: • Somalia 1950 • Niger 1970 • Mexico 1988 • Australia 1995 • West African savanna 1997 • others Dynamic modeling: 1995 on. Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  11. 11. background study sites measurement statistical conclusions Conceptual model Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  12. 12. background study sites measurement statistical conclusions Conceptual model established plant Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  13. 13. background study sites measurement statistical conclusions Conceptual model established plant Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  14. 14. background study sites measurement statistical conclusions Conceptual model established plant vegetated patch Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  15. 15. background study sites measurement statistical conclusions Conceptual model established plant area of facilitation Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  16. 16. background study sites measurement statistical conclusions Conceptual model established plant area of facilitation • water retention • soil organic content il i • temperate microclimate • soil structure Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  17. 17. background study sites measurement statistical conclusions Conceptual model Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  18. 18. background study sites measurement statistical conclusions Conceptual model Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  19. 19. background study sites measurement statistical conclusions Conceptual model Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  20. 20. background study sites measurement statistical conclusions Conceptual model Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  21. 21. background study sites measurement statistical conclusions Conceptual model What determines consistency? What determines shape & Wh t d t i h orientation? Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  22. 22. Mexico Cornet & Delhoume 0 500 1000 m Diversity and Pattern In Plant Communities 1988
  23. 23. Mexico Cornet & Delhoume 0 500 1000 m Diversity and Pattern In Plant Communities 1988
  24. 24. background study sites measurement statistical conclusions Conceptual model What determines consistency? Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  25. 25. background study sites measurement statistical conclusions Consistency Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  26. 26. background study sites measurement statistical conclusions Consistency Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  27. 27. background study sites measurement statistical conclusions Consistency Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  28. 28. background study sites measurement statistical conclusions Consistency Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  29. 29. background study sites measurement statistical conclusions Consistency Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  30. 30. background study sites measurement statistical conclusions Conceptual model What determines consistency? What determines shape & Wh t d t i h orientation? Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  31. 31. background study sites measurement statistical conclusions Shape/Orientation Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  32. 32. background study sites measurement statistical conclusions Shape/Orientation Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  33. 33. background study sites measurement statistical conclusions Shape/Orientation Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  34. 34. background study sites measurement statistical conclusions Shape/Orientation Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  35. 35. background study sites measurement statistical conclusions Shape/Orientation Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  36. 36. background study sites measurement statistical conclusions Formal models motivation • testing plausibility of conceptual model • exploring dynamic outcomes Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  37. 37. background study sites measurement statistical conclusions Formal models formulation • cellular automata • equation-based Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  38. 38. background study sites measurement statistical conclusions Formal models outcomes from Reitkerk et al Science 2004 p. 1928 modified from Thiery Ecology 1994 Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  39. 39. background study sites measurement statistical conclusions Formal models outcomes from Reitkerk et al Science 2004 p. 1929 Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  40. 40. background study sites measurement statistical conclusions Formal models self-patterned semi-arid systems are theorized to • be more efficient at retaining p p g precipitation • undergo “catastrophic shifts” under a threshold • not re-establish unless returned to above that threshold Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  41. 41. background study sites measurement statistical conclusions In America "The patterns proved very difficult to recognize in the field so that air photographs are field, essential for their study.“ Mcfayden Nature 1950 p 121 p. Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  42. 42. 0 100 200 m Central New Mexico 34°11’34”N 106°32’08”W
  43. 43. 0 150 300 m North Western New Mexico 34°47’44”N 106°15’56”W
  44. 44. 0 250 500 m Central Arizona 35°23’26”N 111°36’20”W
  45. 45. 0 100 200 m Central Arizona 35°24’32”N 111°35’29”W
  46. 46. background study sites measurement statistical conclusions Question: Is the subtle patterning observable at p g some semi-arid locations attributable to resource-limited self patterning? p g Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  47. 47. background study sites measurement statistical conclusions Question: Is the subtle patterning observable at p g some semi-arid locations attributable to g water-limited self organization? Approach: Test the spatial correlation of pattern with surface water conditions. conditions Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  48. 48. background study sites measurement statistical conclusions Study sites • piñon juniper woodland piñon-juniper • 5 sites Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  49. 49. Piñon-juniper Piñon juniper woodland
  50. 50. background study sites measurement statistical conclusions Sites 3 in northern Arizona 2 in northern New Mexico Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  51. 51. background study sites measurement statistical conclusions Sites Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  52. 52. background study sites measurement statistical conclusions Sites site size (ha) canopy cover elevation (m) 1 1150 25% 1960 to 2230 Arizona: 2 2030 16% 1680 to 1880 3 2500 27% 1940 to 2260 4 250 52% 1900 to 2000 New Mexico: N M i 5 450 27% 1890 to 1990 Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  53. 53. background study sites measurement statistical conclusions Measurement • Mapping vegetation • Quantifying vegetation shape Estimation • Modeling surface water hydrology Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  54. 54. background study sites measurement statistical conclusions Mapping vegetation Input: 1m color aerial orthoimagery Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  55. 55. background study sites measurement statistical conclusions Mapping vegetation Input: 1m color aerial orthoimagery Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  56. 56. background study sites measurement statistical conclusions Quantifying vegetation shape landscape metrics Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  57. 57. background study sites measurement statistical conclusions Quantifying vegetation shape landscape metrics • Shape Index p = perimeter of a patch a = area of a patch Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  58. 58. background study sites measurement statistical conclusions Quantifying vegetation shape Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  59. 59. background study sites measurement statistical conclusions Quantifying vegetation shape Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  60. 60. background study sites measurement statistical conclusions Quantifying vegetation shape Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  61. 61. background study sites measurement statistical conclusions Quantifying vegetation shape landscape metrics • Shape Index p = perimeter of a patch a = area of a patch Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  62. 62. background study sites measurement statistical conclusions Quantifying vegetation shape landscape metrics • Mean Shape Index (MSI) pij = perimeter of patch ij aij = area of a patch ij Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  63. 63. background study sites measurement statistical conclusions Quantifying vegetation shape landscape metrics also tried: • Area Weighted Mean Shape Index • Mean Patch Fractal Dimesion • Area Weighted Mean Patch Fractal Dimension Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  64. 64. background study sites measurement statistical conclusions Quantifying vegetation shape landscape metrics • Class Area (CA) aij = area of a patch ij Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  65. 65. background study sites measurement statistical conclusions Quantifying vegetation shape landscape metrics • Mean Shape Index (MSI) pattern • Class Area (CA) density Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  66. 66. background study sites measurement statistical conclusions Modeling surface water hydrology Input: • digital elevation model • 1/3rd arc-second National Elevation Dataset Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  67. 67. background study sites measurement statistical conclusions Modeling surface water hydrology • Relative Stream Power (RSP) • Wetness Index (WI) Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  68. 68. background study sites measurement statistical conclusions Modeling surface water hydrology • Relative Stream Power (RSP) As = accumulation surface S = slope Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  69. 69. background study sites measurement statistical conclusions Modeling surface water hydrology • Relative Stream Power (RSP) RSP accumulation l slope surface Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  70. 70. background study sites measurement statistical conclusions Modeling surface water hydrology • Relative Stream Power (RSP)  highest when accumulation is high and slope is high  estimates the erosive force of flowing water Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  71. 71. background study sites measurement statistical conclusions Modeling surface water hydrology • Wetness Index (WI) As = accumulation surface S = slope Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  72. 72. background study sites measurement statistical conclusions Modeling surface water hydrology • Wetness Index (WI) accumulation surface WI slope Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  73. 73. background study sites measurement statistical conclusions Modeling surface water hydrology • Wetness Index (WI)  highest when accumulation is high and slope is low  estimates amount of ground water Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  74. 74. background study sites measurement statistical conclusions Statistical correlation water WI, RSP shape MSI ? density CA Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  75. 75. background study sites measurement statistical conclusions Spatial lag model regression • accounts for spatial autocorrelation • accounts for interactivity Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  76. 76. background study sites measurement statistical conclusions Expected under self patterning self-patterning water WI, RSP shape density MSI CA Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  77. 77. background study sites measurement statistical conclusions Expected under self patterning self-patterning water WI, RSP shape density MSI CA Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  78. 78. background study sites measurement statistical conclusions Expected under self patterning self-patterning water WI, RSP shape density MSI CA Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  79. 79. background study sites measurement statistical conclusions Expected under self patterning self-patterning water WI, RSP shape density MSI CA Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  80. 80. background study sites measurement statistical conclusions Expected under self patterning self-patterning water WI, RSP shape density MSI CA Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  81. 81. background study sites measurement statistical conclusions Expected in any case water WI, RSP shape density MSI CA Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  82. 82. background study sites measurement statistical conclusions Expected in any case water WI, RSP shape density MSI CA Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  83. 83. background study sites measurement statistical conclusions Expected in any case water WI, RSP shape density MSI CA Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  84. 84. background study sites measurement statistical conclusions Expected relationships water WI, RSP shape density MSI CA Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  85. 85. background study sites measurement statistical conclusions Measured relationships – Arizona sites water WI, RSP WI: 0.67 (-) WI 0 67 ( ) WI: WI none RSP: 0.67 RSP: 0.67 shape 0.89 density MSI CA 0.80 Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  86. 86. background study sites measurement statistical conclusions Measured relationships – Arizona sites water WI, WI RSP  WI: 0.67 (-) WI: none ?  RSP: 0.67 RSP: 0.67 ? shape 0.89 density MSI CA 0.80 Interpretation • some relationships consistent with hypothesis p yp • some relationships ecologically unlikely (although not inconsistent with hypothesis) • surface water not the only (or strongest) driver of vegetation shape Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  87. 87. background study sites measurement statistical conclusions Measured relationships – New Mexico sites water WI, RSP WI: 0.60 WI 0 60 (+) WI: WI 0.78 ( ) 8 (+) RSP: 0.60 RSP: 0.78 shape 0.84 density MSI CA 0.71 Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  88. 88. background study sites measurement statistical conclusions Measured relationships – New Mexico sites water WI, WI RSP  WI: 0.60 (+) WI: 0.78 (+)  RSP: 0.60 RSP: 0.78 ? shape 0.84 density MSI CA 0.71 Interpretation • one relationship consistent with hypothesis p yp • one relationship inconsistent with hypothesis • expected ecological relationship present Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  89. 89. background study sites measurement statistical conclusions Questions • If self patterning happens in Arizona, why not in New Mexico? • How could there be no relationship between ground water and vegetation density in Arizona? • Wh is there a relationship b t Why i th l ti hi between stream power and t d density? • How much vegetation structure is really due to self- patterning, and how much due to density? Hugh Stimson – SNRE University of Michigan – 15 Dec 2008
  90. 90. background study sites measurement statistical conclusions Conclusions Even if all the relationships had been consistent with the hypothesis, it wouldn’t have proven that self-patterning is happening. • BUT given the underlying ecological mechanisms, the results relationships suggest it may well occur in Arizona sites. • If self-patterning is occurring, water may be a driver both as a limited resource and as a physical force. • This is a start. Hugh Stimson – SNRE University of Michigan – 15 Dec 2008

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