Heslop-Harrison Stochastic Modelling in Ecosystems - Introductory Talk

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Modelling of processes lets one understand the functions of interacting components, helps to identify parts of processes, and can predict outcomes of changes in the system. Unfortunately, what was a major area of financial modelling is now largely discredited, much to the cost of the rest of us; other areas such as insurance are becoming so constrained by rules and regulation as to be useless. Biological modelling, in contrast is advancing rapidly, whether with respect to subcellular events, whole organism development, or disease epidemiology. Professor Xueron Mao has organized a meeting at the University of Strathclyde in Glasgow, Scotland, on “Stochastic Modelling in Ecosystems.”
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  • Oddly, UN seems to focus on ‘financial modelling – now largely discredited except by those who got very rich by getting it wrong. Nature in Jan 2011 recognized ecological theory …
  • Heslop-Harrison Stochastic Modelling in Ecosystems - Introductory Talk

    1. 1. Workshop on Stochastic Modelling in EcosystemsGlasgow, June 2012 Between biodiversity andcrops: needs from stochasticmodels at the ecosystem scale Pat Heslop-Harrison www.AoBBlog.com phh4@le.ac.uk www.molcyt.com ID/PW „visitor‟13/06/2012 1
    2. 2. 2
    3. 3. 3
    4. 4. Rainfall Distribution mm/yr 4
    5. 5. 5Artist: R . Sphestre?, Le Tadorne, Piney, France. 2012
    6. 6. NASA The Blue MarbleApollo 17 7 Dec 1972
    7. 7. Stochastic Modelling in EcosystemsLiving components – Plants and cyanobacteria (primary producers) – Bacteria, fungi, animalsInteracting with abiotic components – Light – Water – Wind, soil, nutrients, toxins, gasses ...Recognizable homogeneity in one ecosystem 7
    8. 8. Ecosystems anchor slide Largely – Self-organizing – Self-maintained – Cycling – Defined scope – cf Household – Aircraft – 8
    9. 9. Stochastic Modelling in EcosystemsRecognizing – Inputs – Outputs – Networks / webs of organisms – Cycles – Scales – Functions 9
    10. 10. Inputs – Light – Heat – Water – Gasses – Nutrients 10
    11. 11. 50% of the worlds protein needs are derived from atmospheric nitrogen fixed by the Haber-Bosch process and its successors.Global consumption of fertilizer (chemically fixed nitrogen) 80 million tonnes<<200 million tonnes fixed naturally
    12. 12. Outputs – Light – Heat – Water – Gasses– Nutrients 12
    13. 13. Outputs – Light – Heat – Water – Gasses – NutrientsDiscussion at the meeting: Prof MathewWilliams pointed out that the „heat‟ inputis also an important modified output of anecosystem. Consider the differenttemperatures and temperature cycles ofthe desert and jungle ecosystems in thesecond slide. 13
    14. 14. OutputsEcosystemServicesWater, gasses,nutrients”nature‟s services, like flood control, waterfiltration, waste assimilation” 14
    15. 15. Outputs – Light – Heat – Ecosystem services• Water, gasses, nutrients – Chemical energy
    16. 16. Ecosystems: What do we take out? The seven Fs – Food – Feed – Fuel – Fibre – Flowers – Pharmaceuticals – Fun 16
    17. 17. Outputs – Light – Heat– Ecosystem services • Water, gasses, nutrients – Chemical energy – Long term storage 18
    18. 18. Stores of biologically produced carbon inLimestonePeatOil and gas 19
    19. 19. Dynamic processes: turn-over Outputs – Limestone 20– Made by marine organisms, formation and stability affected by pH and temperature
    20. 20. Inputs - Biotic – Diseases – New organisms • Aliens/invasives – New genes and genotypes of existing organisms 21
    21. 21. Outputs – Light – Heat– Ecosystem services – Chemical energy – Long term storage Required and valued 22
    22. 22. Rio de Janeiro Conference in June 1992Biological diversity as “the variability among living organisms and the ecological complexes of which they are part”Conservation of ecosystemsSustainability of human activityAnalysis of human effects and interactions with the environment 23
    23. 23. … all suggest modelling … but 24
    24. 24. 25
    25. 25. Biotic Inputs – New genes – New species • Diseases • Alien speciesAbiotic inputs – Irrigation – „Salt‟ (NaCl) – Nitrogen – Phosphorous 26
    26. 26. Water hyacinth – Eichornia: an invasive alienplant from South America, fills water courses (asurface habitat not used by any native species)in Asia and Africa 27
    27. 27. Argenome mexicana: a goat-proof plant from Mexcio introduced and successful in Africa 28
    28. 28. 29
    29. 29. Inputs are random variables – with known or unknown distributionsDoes the mean or the extreme matter?How does oscillation lead to robustness?Can routes from input to output be simplified? 30
    30. 30. Rainfall Distribution mm/yr 31
    31. 31. Occasional ‘extreme inputs’:Limiting composition of ecosystemsmore than ‘mean input’ - Robustness 32
    32. 32. 33
    33. 33. 34
    34. 34. Anhalt, Barth, HHEuphytica 2009 Theor App Gen
    35. 35. Regulation of oscillations Synchronization without external regulators
    36. 36. Oscillations: noise and stability  Stochastic fluctuations – preserve stable oscillations – ensure robustness of the oscillations to cell-to-cell variations  Robustness analysis requires stochastic simulationJongRae Kim et al. Stochastic noise and synchronisation during Dictyostelium aggregation make cAMPoscillations robust. PLoS Computational Biology 2007
    37. 37. Coupling of oscillators seen at all scales from subcellular to ecosystemJeong-Rae Kim, PHH, Kwang-Hyun Cho. J Cell Sci 2010
    38. 38.  Stable cAMP oscillations in the cells with other molecules/ionsValeyev et al. Mol Biosyst 2009
    39. 39.  Entrainment of a cell by surrounding cells: Individual cells synchronized/oscillate in phase Regardless of frequency, some effect of [cAMP]Valeyev et al. Mol Biosyst 2009
    40. 40. No Stronger Coupling
    41. 41. 43
    42. 42. 44
    43. 43. Eyespot (fungus Pseudocercosporella) resistance from Aegilops ventricosa introduced to wheat by chromosome engineeringMany diseases where all varieties are highly susceptibleAlien variation can be found and used7Host and non-host
    44. 44. Crop standingLodging in cerealsCrop fallen
    45. 45. Ecosystems anchor slide Largely – Self-organizing – Self-maintained – Cycling – Defined scope Networks are – Stable – Oscillating – Complex and maybe modular – Simplification – Models for modelling 47
    46. 46.  Dynamic interactions between calcium, IP3 and G protein-dependent modules Valeyev et al. Mol Biosyst 2009 5: 612
    47. 47. Identification of design principles: points of structural fragility in networks Dynamic interactions between the different modules generate more stable and robust cAMP oscillations Robustness comparison includin module interactionsAnalysis and extension of a biochemical network model using robust controltheory J.-S. Kim, Valeyev, Postlethwaite, PHH, Cho, BatesInt. J. Robust Nonlinear Control 2010; 20:1017–1026. DOI: 10.1002/rnc.1528 49
    48. 48. Light in ecosystems Heat Information Energy Quantity Quality Direction PeriodicityPhotosynthesis Control of development
    49. 49. Simplification of genetic networks while maintaining dynamic propertiesReduction of Complex SignalingNetworks to a Representative KernelJeong-Rae Kim, Junil Kim,Yung-KeunKwon, Hwang-Yeol Lee, PHH. Kwang-Hyun Cho. Science Signaling 4 (175), 51ra35. [DOI:10.1126/scisignal.2001390
    50. 50. Network reduction Circadian Clock regulation after Leloup & Goldbeter; Andrew Millar in Arabidopsis X X Y Y Z ZKim, HH, Cho et al. 2011 Science Signaling
    51. 51. Integrin gene network 53
    52. 52. Function and multifunctionHow many genes are there?1990s: perhaps 100,0002000: 25,000How does this give the range of functions and control? Najl Valeyev
    53. 53. Lolium Biomass productionSusanne Barth, Ulrike Anhalt, Celine Tomaszewski
    54. 54. Anhalt, Barth, HH et al.Segregation distortion inLolium: evidence for geneticeffects. Theoretical & AppliedGenetics 2008
    55. 55. Anhalt, Barth, HH Euphytica 2Theor App Gen 2008
    56. 56. Anhalt UCM, Heslop-Harrison JS, Piepho HP, Byrne S, Barth S. 2009. Quantitative trait locimapping for biomass yield traits in a Lolium inbred line derived F2 population. Euphytica 170: 99-107.
    57. 57. Network structures differ between systems: what about ecosystems?Kim TH, Kim J, PHH, Cho KH. 2011. Evolutionary design principles and functionalcharacteristics based on kingdom-specific network motifs. Bioinformatics 27: 245-251. http://dx.doi.org/10.1093/bioinformatics/btq633 59
    58. 58. 60
    59. 59. Threats to sustainability: no different for 10,000 yearsHabitat destructionClimate change (abiotic stresses)Diseases (biotic stresses)Changes in what people wantMORE outputs neededMORE stability in outputs from less stable inputs / poorer environments
    60. 60. 62
    61. 61. How to exploit models Increased sustainability Increased value Genetic improvement Robustness („food security‟) Benefits to all stakeholders: Breeders, Farmers, Processors, Retailers, Consumers, Citizens 64
    62. 62. 50 years of plant breeding progress 4 GM maize Maize Genetics3.5 3 Rice2.5 Agronomy Wheat 2 Human1.5 Area 10.5 0 1961 1970 1980 1990 2000 2007
    63. 63. United Nations Millennium Development Goals-MDGs • Goal 1 – Eradicate extreme poverty and hunger • Goal 2 – Achieve universal primary education • Goal 3 – Promote gender equity and empower women • Goal 4 – Reduce child mortality • Goal 5 – Improve maternal health • Goal 6- Combat HIV/AIDS, malaria and other diseases • Goal 7 - Ensure environmental sustainability • Goal 8 - Develop a global partnership for development
    64. 64. Conventional BreedingCross the best with the best and hope for something better SuperdomesticationDecide what is wanted and then plan how to get it – Variety crosses – Mutations – Hybrids (sexual or cell-fusion) – Genepool – Transformation
    65. 65. Economic growthSeparate into increases in inputs (resources, labour and capital) and technical progress90% of the growth in US output per worker is attributable to technical progress Robert Solow – Economist
    66. 66. Market Demand “MORE”Food production volume – No possibility of market collapse – Only slow market increase – Reduced post-harvest loss – Some crops gain/hit by global trends
    67. 67. InputsBetter genetically – Harvest more – Stress resistant (Disease = biotic and environment – abiotic)Higher – Weed control improving for 8000 yearsLower – Production loss less than cost decrease – Better agronomy (cropping cycles etc.)
    68. 68. Needs from Stochastic Models of Ecosystems Outputs Inputs Ecosystem – Light services – Heat – Chemical – Water energy – Gasses– Long term – Nutrients storage 72
    69. 69. Workshop on Stochastic Modelling in EcosystemsGlasgow, June 2012 Between biodiversity andcrops: needs from stochasticmodels at the ecosystem scale Pat Heslop-Harrison www.AoBBlog.com phh4@le.ac.uk www.molcyt.com ID/PW „visitor‟13/06/2012 73

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