EcoMaths - The Numbers of Life (and Death)

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Presentation to Year 10 students at Scotch College, Adelaide on 16/06/2010

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  • Russia has the most extensive forest cover, followed by Brazil, Canada and USAEstimated area of gross forest cover loss at the global scale is 1,011,000 km2, or 3.1 % of year 2000 forest area (0.6% per year from 2000 to 2005)Gross forest cover loss was highest in the boreal biome, with fire accounting for 60 % of that lossThe humid tropics had the second-highest gross forest cover loss, due mainly to broad-scale clearing for agriculture in Brazil, Indonesia and MalaysiaWhen expressed as proportion lost from the 2000 extent estimates, the humid tropics is the least disturbedThe Amazon interior is the largest remaining ‘intact’ forest, followed by the Congo basinThe dry tropics has the 3rd-highest gross forest cover loss, with Australia, Brazil, Argentina and Paraguay accounting for most of thisAlthough the temperate biome had the lowest forest cover (due mainly to forest clearances long, long ago), it had the 2nd-highest proportional gross forest cover lossNorth America has the greatest area of gross forest cover loss, followed by Asia and South AmericaNorth America alone accounts for ~ 30 % of global gross forest cover loss, and has the highest proportional gross forest cover loss at 5.1 %Brazil has the highest gross national forest cover loss of any nationIndonesia and the Democratic Republic of Congo are next in line for tropical countriesUSA has the highest proportional global forest cover loss since 2000Despite previous estimates suggesting that Canada has had little forest loss, the new estimates place it second in terms of gross forest cover loss only to Brazil
  • > 19,000 species (7 % of all Eudicots)Papilionoideae (73 %), Caesalpinioideae (10 %), Mimosoideae (17 %)36 tribes; 650 generaall continents; all terrestrial biomesdwarf herbs to large treeshigh economic importance (food, fodder, medicine)
  • > 19,000 species (7 % of all Eudicots)Papilionoideae (73 %), Caesalpinioideae (10 %), Mimosoideae (17 %)36 tribes; 650 generaall continents; all terrestrial biomesdwarf herbs to large treeshigh economic importance (food, fodder, medicine)
  • EcoMaths - The Numbers of Life (and Death)

    1. 1. EcoMathsThe Numbers of Life (and Death)<br />Professor Corey J. A. Bradshaw<br />THE ENVIRONMENT INSTITUTE, University of Adelaide<br />South Australian Research & Development Institute<br />
    2. 2. <ul><li>> 4 million protists
    3. 3. 16600 protozoa
    4. 4. 75000-300000helminth parasites
    5. 5. 1.5million fungi
    6. 6. 320000 plants
    7. 7. 4-6 million arthropods
    8. 8. > 6500 amphibians
    9. 9. > 30000 fishes
    10. 10. 10000 birds
    11. 11. > 5000 mammals</li></li></ul><li>99 % of ALL species that have ever existed...<br />EXTINCT<br />species lifespan = 1-10 M years<br />Ordovician (490-443 MYA)<br />Devonian (417-354 MYA)<br />Permian (299-250 MYA)<br />Triassic (251-200 MYA)<br />Cretaceous (146-64 MYA)<br />Anthropocene<br />extinction rate 100-10000× background<br />© Tiantian Zhang, Good50x70.org<br />Crutzen 2002 Nature 415:23; Bradshaw & Brook 2009 J Cosmol2:221-229<br />
    12. 12. Bradshaw et al. 2009 Trends Ecol Evol24:541-548<br />Bradshaw et al. 2009 Front Ecol Environ 7:79-87<br /><ul><li>1,011,000 km2 lost 2000-2005 (3.1 %; 0.6 %/year)
    13. 13. highest in boreal biome (60 %)
    14. 14. humid tropics next (Brazil, Indonesia, Malaysia)
    15. 15. dry tropics next highest (Australia, Brazil, Argentina)
    16. 16. N.A. greatest proportional lost by continent
    17. 17. Nationally, Brazil, Canada, Indonesia, DR Congo</li></ul>Hansen et al. 2010 PNAS<br />doi:10.1073/pnas.0912668107<br />Barson et al. 2000 Land Cover<br />Change in Australia, Bur RurSci<br />
    18. 18. IUCN RED LIST OF THREATENED SPECIES www.iucnredlist.org<br /><ul><li>21 % of all known mammals
    19. 19. 30 % of all known amphibians
    20. 20. 12 % of all known birds
    21. 21. 35 % of conifers & cycads
    22. 22. 17 % of sharks
    23. 23. 27 % of reef-building corals</li></ul>threatened with extinction<br />
    24. 24. Correlates of extinction<br /><ul><li>3366 spp
    25. 25. life history (reproduction, fecundity, body size, habit)
    26. 26. ecological (range size)
    27. 27. environment (temperature, precipitation, human density)
    28. 28. threat ~ X1 + X2 + X3… (Order/Family)
    29. 29. decline ~ …</li></ul>Sodhi et al. 2008 PLoS One 3:e1636<br />Sodhi et al. (2008) PLoS One 3:e1636<br />
    30. 30. Sodhi et al. 2008 PLoS One 3:e1636<br />
    31. 31. Sodhi et al. 2008 PLoS One 3:e1636<br />
    32. 32.
    33. 33. range(number of FAO Fishing Areas),<br /><ul><li> risk for sharks with small range size
    34. 34. similar for teleosts with slightly larger ranges</li></ul> habitat <br /><ul><li> threat risk for reef sharks
    35. 35. and for pelagic teleosts</li></ul>environmental temperature regime<br /><ul><li> risk for deepwater sharks
    36. 36.  risk deepwater teleosts</li></ul>Field et al. 2009 Advances in Marine Biology 56:275-363<br />
    37. 37. Bradshaw et al. 2008 J Ecol 96:869-883<br />
    38. 38. Bradshaw et al. 2008<br />J Ecol 96:869-883<br />
    39. 39. invasive species and starfish outbreaks<br />bleaching<br />deforestation, soil erosion, sediment & nutrient loading<br />destructive fishing practices<br />overfishing<br />
    40. 40. Mellin et al. 2010 Glob EcolBiogeog19:212<br />
    41. 41. 3.0 ± 0.4<br />3.1 ± 0.4<br />2.2 ± 0.4<br />2.0 ± 0.3<br />1.7 ± 0.3<br />1.5 ± 0.3<br />Reef isolation<br />Reef area<br />Mellin et al. In press Ecology<br />
    42. 42. Mellin et al. In press Ecology<br />
    43. 43. Evil quartet<br />habitat destruction<br />over-exploitation<br />introduced species<br />extinction cascades<br />Diamond 1984 Extinctions Chicago University Press<br />
    44. 44. Brook et al. 2008 Trends Ecol Evol25:453-460<br />
    45. 45. Evil quintet<br />Evil sextet<br />habitat destruction<br />over-exploitation<br />introduced species<br />extinction cascades<br />climate change<br />synergies<br />Brook et al. 2008 Trends Ecol Evol25:453-460<br />
    46. 46. justification to maintain healthy ecosystems is intangible because it seems unrelated to personal well-being<br />© Millennium Ecosystem Assessment<br />
    47. 47. reduce desertification<br />maintain soils<br />crop pollination<br />seed dispersal<br />food provision<br />water purification<br />fuel provision<br />fibre provision<br />climate regulation<br />flood regulation<br />disease regulation<br />waste decomposition/detoxification<br />nutrient cycling<br />soil formation<br />primary production<br />pharmaceutical sources<br />cultural appreciation (aesthetic, spiritual, educational, recreational…)<br />€153 billion/year<br />fisheries: €50 billion/year<br /><ul><li>€50 billion lost/year
    48. 48. land-based ecosystem loss €545 billion by 2010
    49. 49. > €14 trillion/year lost by 2050</li></ul>Cost of Policy Inaction (COPI):<br />The case of not meeting the 2010 biodiversity target.<br />European Commission<br />
    50. 50. 1990-2000<br /><ul><li>~100,000 people killed
    51. 51. 320 million people displaced
    52. 52. total reported damages > US$1151 billion </li></ul>Bradshaw et al. 2007 Glob Change Biol13:2379-2395<br />
    53. 53. <ul><li>decades of warning
    54. 54. human population 6.8 B; 9-10 B by 2050
    55. 55. competition for resources – famine, wars
    56. 56. loss of basic ecosystem services
    57. 57. fundamental worldwide shifts in policy required
    58. 58. identifying relative country degradation
    59. 59. highlight nations needing assistance
    60. 60. better-performing nations as model governance structures</li></li></ul><li>City Development Index www.unchs.org<br />Ecological Footprint www.footprintnetwork.org<br />Environmental Performance Index epi.yale.edu<br />Environmental Sustainability Index sedac.ciesin.columbia.edu<br />Genuine Savings Index worldbank.org<br />Human Development Index hdr.undp.org<br />Living Planet Index www.panda.org<br />Well-Being Index www.well-beingindex.com<br />Environmental Impact Rank<br />Böhringer & Joachim 2007 Ecol Econ 63:1-8<br />
    61. 61. <ul><li>inability to describe complexity of ‘sustainability’
    62. 62. not comprehensive
    63. 63. mix environmental, economic and health data
    64. 64. often subjective combinations, weightings, normalisation
    65. 65. not available for large sample of nations
    66. 66. not consistent</li></li></ul><li><ul><li>natural forest loss</li></ul>2005-1990 D/ha<br /><ul><li>natural habitat conversion</li></ul>human-modified landcover/total landcover<br /><ul><li>marine captures</li></ul>1990-2005 fish, whales, seals/EEZ km<br /><ul><li>fertiliser use</li></ul>NPK/ha arable land<br /><ul><li>water pollution</li></ul>biochemical oxygen demand/total renewable water resources<br /><ul><li>carbon emissions</li></ul>forestry, land-use change, fossil fuels/km2<br /><ul><li>biodiversity threat</li></ul>Red List threatened birds, mammals, amphibians/listed species<br />Bradshaw et al. 2010 PLoS One 5:e10440<br />
    67. 67.
    68. 68. Bradshaw et al. 2010 PLoS One 5:e10440<br />
    69. 69. “I anticipate that the anti-science crowd will be screeching and howling with indignation when they read this one.”<br />“This is such BS, China is WAY worse then the U.S.”<br />“This researcher is a waste ...”<br />“This article is crap.”<br />“Can we really depend on some study when the Chinese could have funded this or maybe some group who was angry at the US and Brazil for whatever? I highly doubt the accuracy of the findings. Looks like the Treehuggers are at it again.”<br />“Shame on you Australia !!! I guess your dying great Barrior[sic] reef is America's fault too!!!!”<br />“here we go again. I'm so frickin' sick of these watermelons (green on the outside, red (communist) on the inside) treehuggers. The only f*^king green I care about is made of paper and folds.”<br />
    70. 70.
    71. 71. Bradshaw et al. 2010 PLoS One 5:e10440<br />
    72. 72. Bradshaw et al. 2010 PLoS One 5:e10440<br />
    73. 73. ENVIRONMENTAL<br />KUZNETS CURVE<br />environmental damage<br />per capita prosperity<br />Bradshaw et al. 2010 PLoS One 5:e10440<br />
    74. 74. Bradshaw et al. 2010 PLoS One 5:e10440<br />
    75. 75. Does a sick environment make sick people?<br />© http://tropicaltoxic.blogspot.com<br />
    76. 76. <ul><li>physician-assessed morbidity declines with more green spaces near Dutch patients</li></ul>Maas et al. 2009 J EpidemiolComm Health 63:967-973<br /><ul><li>dioxin-poisoning accident in Milan – increased circulatory disease, lymphoma, pulmonary disease & diabetes 25 years later</li></ul>Consonni et al. 2008 Am J Epidemiol167:847-858<br /><ul><li>low water quality, poor sanitation & indoor air pollution from household solid fuels increased child mortality and reduced life expectancy in Mexico</li></ul>Stevens et al. 2009 Proc NatlAcadSci USA 105:16860-16865<br /><ul><li>malaria-vector mosquito bite rates 278× higher in deforested sites in Amazon</li></ul>Vittor et al. 2006 Am J Trop Med Hyg74:3-11<br /><ul><li>Anopheline mosquito density  after deforestation in 60% of 60 studies over past century; 70 % of cases  incidence of malaria</li></ul>Yasuoka & Levins 2007 Am J Trop Med Hyg76:450-460<br />
    77. 77. DATA<br />Human health: World Health Organization Global Burden of Disease database<br />Environment: - Environmental Combination Index (adapted from Yale Env Performance Index)<br />- Proportional Environmental Impact rank (Bradshaw et al. 2010 PLoS One 5:e10440)<br />- natural habitat conversion proportion (Global Land Cover 2000 dataset)<br /> - air/water quality (Yale Environmental Performance Index)<br /> - NPK fertiliser use/area arable land (FAOSTAT database)<br /> - CO2 emissions (Climate Analysis Indicators tool)<br />Control: - human population size (United Nations Common Database)<br /> - purchasing-power parity-adjusted GNI (World Resources Institute)<br /> - health expenditure (WHO Statistical Information System)<br />
    78. 78. DATA<br />Human health: WHO Global Burden of Disease database<br /><ul><li>Disability-Adjusted Life Years (DALY) - years of life lost due to premature mortality and healthy years of life lost due to disability
    79. 79. Infant Mortality (male) – 2004 mortality per 1000 live births
    80. 80. Life Expectancy at birth (male) – 2004
    81. 81. Diarrhoea deaths among children < 5 years (2000)
    82. 82. Malaria deaths among children < 5 years (2000)
    83. 83. Deaths due to Cardiovascular Disease (2002 age-standardised per 10,000)
    84. 84. Deaths due to Cancers (2002 age-standardised per 10,000)</li></li></ul><li>10 %  ECI   mINFM 7.0/1000 live births <br /> mLE 1.9 years<br />http://epi.yale.edu<br />
    85. 85. <ul><li>extinction must be inferred from record of sightings/collections
    86. 86. when a species becomes increasingly rare before extinction, might persist unseen for many years
    87. 87. so the time of last sighting often poor estimate of extinction date</li></ul>x<br />x<br />x<br />x<br />x<br />x<br />x<br />x<br />x<br />x<br />x<br />?<br />?<br />present<br />past<br />Roberts & Solow 2003 Nature 426:245<br />
    88. 88. <ul><li>optimal linear estimation
    89. 89. joint distribution of k same Weibull form regardless of parent distribution
    90. 90. estimated extinction time q
    91. 91. L: symmetric k×k matrix
    92. 92. n: Estimated shape parameter of joint Weibull distribution of k</li></ul>CI<br />q<br />x<br />x<br />x<br />x<br />x<br />x<br />x<br />x<br />x<br />x<br />x<br />present<br />past<br />Roberts & Solow 2003 Nature 426:245<br />
    93. 93. <ul><li>maximum likelihood to account for radio carbon dating error
    94. 94. assume true ages U independent/uniformly distributed over (b1,g1) where b1 = extinction date
    95. 95. PDF of Xj:</li></ul>b1<br />x<br />x<br />x<br />x<br />x<br />x<br />x<br />x<br />x<br />x<br />x<br />present<br />past<br />Solow et al. 2006 PNAS 103:7351<br />
    96. 96. <ul><li>but... previous sighting rate important
    97. 97. length of period since last sighting informative
    98. 98. given previous sighting rate(n/tn), probability of next sighting
    99. 99. where p drops below threshold with increasing T-tn, TE inferred</li></ul>TE<br />x<br />x<br />x<br />x<br />x<br />x<br />x<br />x<br />x<br />x<br />x<br />present<br />past<br />McInerny et al. 2006 ConservBiol20:562<br />
    100. 100. <ul><li>but... TE depends on number of samples in ‘final’ period
    101. 101. declining influence of dates within time since last sighting
    102. 102. sequentially recalculated TE, weighting by cumulative distance from T1</li></ul>T1<br />TE<br />x<br />x<br />x<br />x<br />x<br />x<br />x<br />x<br />x<br />x<br />x<br />present<br />past<br />
    103. 103. extinctions - constrained<br />P(rand overlap) = 0.09<br />
    104. 104.
    105. 105.
    106. 106. © Moronail.net<br />
    107. 107. © WWF<br />
    108. 108. <ul><li>Barry Brook University of Adelaide
    109. 109. Alan Cooper University of Adelaide
    110. 110. Camille MellinUniversity of Adelaide/AIMS
    111. 111. Mark MeekanAIMS
    112. 112. Iain Field Macquarie University
    113. 113. XingliGiamPrinceton University
    114. 114. Navjot S. SodhiNational University of Singapore
    115. 115. Tony McMichael Australian National University</li></ul>corey.bradshaw@adelaide.edu.au<br />www.adelaide.edu.au/directory/corey.bradshaw<br />ConservationBytes.com<br />© Tiantian Zhang, Good50x70.org<br />

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