Augmentation of Plant Genetic Diversity in Synecoculture: Theory and Practice in Temperate and Tropical Zones

Part of the Sustainable Development and Biodiversity book series (SDEB, volume 22)


Natural vegetation forms a complex fractal structure of ecological niche distribution, in contrast to human-managed monoculture landscape. For the sustainable management of diverse plant genetic resources, including crop and wild species, the introduction of such ecologically optimum formation is important to compensate for the biodiversity loss and achieve higher ecological state that can provide sufficient ecosystem services for increasing human population. In this chapter, we first develop a conceptual and theoretical framework for the implementation and management of self-organized niche structures and develop an adaptive strategy of sustainable food production resulting from the statistical nature of ecosystem dynamics called power law. Second, we construct the integrative measures for the management of plant genetic resources for food and agriculture in ecological optimum that incorporate both phylogenic and phase diversities as important functional indicators of plant communities. This formalization leads to the extension of conventional concepts of biodiversity and ecosystem services toward human-assisted operational ecological diversity and utility and provides the definition and property of potentially realizable and utilizable plant genetic resources in the augmented ecosystems beyond natural preservation state. Finally, case studies from the synecoculture project in temperate and tropical zones are reported in reference to the developed framework, which draws out legislative requirements for future protection and propagation of plant genetic resources. The necessity of supportive information and communication technologies is also demonstrated. This article contains theoretical foundation and the results of the proof of concept experiments that are essential to establish a novel developmental and legislative framework for the sustainable use of plant genetic resources, overarching the protection of the natural environment and agricultural production mainstreaming biodiversity.


Plant genetic resources (PGR) Ecological optimum Power-law distribution Synecoculture Anthropogenic augmentation of ecosystems Operational species diversity Adaptive diversification Ecological recapitulation principles Open complex systems Complexity measure Information and communication technologies (ICT) Traditional knowledge of indigenous peoples and local communities Aichi biodiversity targets United Nations sustainable development goals (SDGs) The Nagoya Protocol on Access and Benefit-Sharing 



Kousaku Ohta and Tatsuya Kawaoka contributed as a research assistant at Sony CSL. Experiments of synecoculture were conducted in collaboration with in Japan: Takashi Otsuka, Sakura Shizen Jyuku; in Taiwan: Kai-Yuan Lin, Asian SustaInable Agriculture Research and production Center (ASIARC); and in Burkina Faso: André Tindano, Association de Recherche et de Formation du Développement Rural Autogéré (AFIDRA) and Centre Africain de Recherche et de Formation en Synécoculture (CARFS).


  1. Akasaka M, Kadoya T, Ishihama F et al (2017) Smart protected area placement decelerates biodiversity loss: a representation-extinction feedback leads rare species to extinction. Conserv Lett 10(5):539–546CrossRefGoogle Scholar
  2. Albert CH, de Bello F, Boulangeat I et al (2012) On the importance of intraspecific variability for the quantification of functional diversity. Oikos 121:116–126CrossRefGoogle Scholar
  3. Anderson C (2008) The long tail. ISBN 9781401387259Google Scholar
  4. Arrhenius O (1921) Species and area. J Ecol 9:95–99CrossRefGoogle Scholar
  5. Barnosky AD, Hadly EA, Bascompte J et al (2012) Approaching a state shift in Earth’s biosphere. Nature 486:52–58CrossRefPubMedGoogle Scholar
  6. Bastian M, Heymann S, Jacomy M (2009) Gephi: an open source software for exploring and manipulating networks. International AAAI Conference on Weblogs and Social Media.
  7. Cadotte MW, Carscadden K, Mirotchnick N (2011) Beyond species: functional diversity and the maintenance of ecological processes and services. J Appl Ecol 48:1079–1087CrossRefGoogle Scholar
  8. Carmona CP, Guerrero I, Morales MB et al (2017) Assessing vulnerability of functional diversity to species loss: a case study in Mediterranean agricultural systems. Funct Ecol 31:427–435CrossRefGoogle Scholar
  9. Convention on Biological Diversity (CBD) (2000) The Cartagena protocol on biosafety to the convention on biological diversity.
  10. Convention on Biological Diversity (CBD) (2010a) The Nagoya protocol on access to genetic resources and the fair and equitable sharing of benefits arising from their utilization (ABS) to the convention on biological diversityGoogle Scholar
  11. Convention on Biological Diversity (CBD) (2010b) Aichi biodiversity targets.
  12. Convention on Biological Diversity (CBD) (2017) The access and benefit-sharing clearing-house.
  13. Crutzen PJ (2002) Geology of mankind. Nature 415:23. Scholar
  14. Cushing JM, Costantino RF, Dennis B et al (2005) Chaos in ecology experimental nonlinear dynamics, vol 1. Theoretical ecology series. Academic Press. ISBN 978-0-12-198876-0Google Scholar
  15. de Bello F, Lavorel S, Albert CH et al (2011) Quantifying the relevance of intraspecific trait variability for functional diversity. Methods Ecol Evol 2:163–174CrossRefGoogle Scholar
  16. DGM (Dedicated Grant Mechanism for Indigenous Peoples and Local Communities) (2017) Annual report.
  17. FAO (Food and Agriculture Organization) (2001) Food balance sheets a handbook.
  18. FAO (Food and Agriculture Organization) (2011) Global food losses and food waste.
  19. FAO (Food and Agriculture Organization) (2016) FAO guideline: voluntary guidelines for mainstreaming biodiversity into policies, programmes and national and regional plans of action on nutrition.
  20. Farrior CE, Bohlman SA, Hubbell S et al (2016) Dominance of the suppressed: power-law size structure in tropical forests. Science 351:155–157CrossRefPubMedGoogle Scholar
  21. Flynn DFB, Mirotchnick N, Jain M et al (2011) Functional and phylogenetic diversity as predictors of biodiversity-ecosystem-function relationships. Ecology 92:1573–1581CrossRefPubMedGoogle Scholar
  22. Funabashi M (2013) IT-mediated development of sustainable agriculture systems-toward a data-driven citizen science. J Inf Technol Appl Educ 2(4):179–182Google Scholar
  23. Funabashi M (2016a) Synecological farming: theoretical foundation on biodiversity responses of plant communities. Plant Biotechnol 33:213–234CrossRefGoogle Scholar
  24. Funabashi M (2016b) Synecoculture manual 2016 version (English version). Research and Education material of UniTwin UNESCO Complex Systems Digital Campus, e-laboratory: Open Systems Exploration for Ecosystems Leveraging, No. 2Google Scholar
  25. Funabashi M (2016c) Chapter 4.1. In: Tokoro M, Takahashi K (eds) Water cycle and life: creating water environment in 21st century. [Mizu daijunkan to kurashi: 21 seiki no mizu kankyo wo tsukuru (in Japanese)]. Maruzen Planet, Japan, pp 95–112Google Scholar
  26. Funabashi M (2017a) Synecological farming for mainstreaming biodiversity in smallholding farms and foods: implication for agriculture in India. Indian J Plant Genet Resour 30(2):99–114. Scholar
  27. Funabashi M (2017b) Citizen science and topology of mind. Entropy 19(4). Scholar
  28. Funabashi M (2017c) Open systems exploration: an example with ecosystems management. First Complex Systems Digital Campus World E-Conference, vol 2015, pp 223–243Google Scholar
  29. Funabashi M, Hanappe P, Isozaki T et al (2017) Foundation of CS-DC e-laboratory: open systems exploration for ecosystems leveraging. First Complex Systems Digital Campus World E-Conference, vol 2015, pp 351–374Google Scholar
  30. Guimarães PR Jr, Pires MM, Jordano P et al (2017) Indirect effects drive coevolution in mutualistic networks. Nature 550:511–514CrossRefPubMedGoogle Scholar
  31. Hashiguchi Y (2005) Islands need “food self-sufficiency ability”. J Island Stud 2005(5):33–53CrossRefGoogle Scholar
  32. Houlton BZ, Morford SL, Dahlgren RA (2018) Convergent evidence for widespread rock nitrogen sources in Earth’s surface environment. Science 360:58–62CrossRefGoogle Scholar
  33. Jaenicke H, Ganry J, Hoeschle-Zeledon I et al (eds) (2009) International symposium on underutilized plants for food security, nutrition, income and sustainable development. Arusha, Tanzania. ISBN 978-90-66057-01-2Google Scholar
  34. Larkin DL, Bruland GL, Zedler JB (2016) Heterogeneity theory and ecological restauration. In Palmer MA, Zedler JB, Falk DA (eds) Foundations of restoration ecology. Island Press. ISBN 9781610916974Google Scholar
  35. Laurance WF (2009) Beyond island biogeography theory. In: Losos JB, Ricklefs RE (eds) The theory of island biogeography revisited. Princeton University Press, United States, pp 214–236CrossRefGoogle Scholar
  36. Laurance W, Mesquita R, Luizão R et al (2004) The biological dynamics of forest fragments project: 25 years of research in the Brazilian Amazon. Tropinet 15(2/3):1–3Google Scholar
  37. Nayak C (2008) Comparing various fractal models for analyzing vegetation cover types at different resolutions with the change in altitude and season. Master Thesis, Faculty of Geo-Information Science and Earth Observation of the University of Twente (ITC), Enschede, the Netherlands, and Indian Institute of Remote Sensing (IIRS), National Remote Sensing Agency (NRSA), Department of Space, Dehradun, India.
  38. NRC (National Research Council) (1993) Managing global genetic resources: agricultural crop issues and policies. The National Academies Press, Washington, DC.
  39. Paroda RS, Tyagi RK, Mathur PN et al (eds) (2017) Proceedings of the ‘1st international agrobiodiversity congress: science, technology and partnership’, New Delhi, India, November 6–9, 2016. Indian Society of Plant Genetic Resources, New Delhi and Bioversity International, Rome, 152 ppGoogle Scholar
  40. Pecl GT, Araújo MB, Bell JD et al (2017) Biodiversity redistribution under climate change: impacts on ecosystems and human well-being. Science 355. Scholar
  41. Pereira HM et al (2010) Scenarios for global biodiversity in the 21st century. Science 330:1496. Scholar
  42. Petherick A (2012) A note of caution. Nat Clim Change 2:144–145CrossRefGoogle Scholar
  43. Prusinkiewicz P, Lindenmayer A (2012) The algorithmic beauty of plants. Springer, ISBN 9781461384762Google Scholar
  44. Putman RJ, Wratten SD (1984) Principles of ecology. University of California Press, CaliforniaGoogle Scholar
  45. R Core Team (2015) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.
  46. Reich PB, Tilman D, Isbell F et al (2012) Impacts of biodiversity loss escalate through time as redundancy fades. Science 336:589–592CrossRefPubMedGoogle Scholar
  47. Reuter MA, Hudson C, Hagelüken C et al (2013) Metal recycling: opportunities, limits, infrastructure. A Report of the Working Group on the Global Metal Flows to the International Resource Panel. UNEPGoogle Scholar
  48. Richards CM, Falk DA, Montalvo AM (2016) Population and ecological genetics in restoration ecology. In Palmer MA, Zedler JB, Falk DA (eds) Foundations of restoration ecology. Island Press, ISBN 9781610916974Google Scholar
  49. Rippke U, Ramirez-Villegas J. Jarvis A et al (2016) Timescales of transformational climate change adaptation in sub-Saharan African agriculture. Nat Clim Change 6:605–609CrossRefGoogle Scholar
  50. Rohde RA, Muller RA (2005) Cycles in fossil diversity. Nature 434:208–210CrossRefPubMedGoogle Scholar
  51. Scanlon TM, Caylor KK, Levin SA et al (2007) Positive feedbacks promote power-law clustering of Kalahari vegetation. Nature 449:209–212CrossRefPubMedGoogle Scholar
  52. Seuront L (2010) Fractals and multifractals in ecology and aquatic science. CRC Press. ISBN 9781138116399Google Scholar
  53. Steffen W, Richardson K, Rockström J et al (2016) Planetary boundaries: guiding human development on a changing planet. Science 347:1259855CrossRefGoogle Scholar
  54. Takayasu H, Sato A, Takayasu M (1997) Stable infinite variance fluctuations in randomly amplified Langevin systems. Phys Rev Lett 79:966–969CrossRefGoogle Scholar
  55. Tindano A, Funabashi M (eds) (2016) Proceedings of the 1st African forum on synecoculture (English version). Research and Education material of UniTwin UNESCO Complex Systems Digital Campus, e-laboratory: Open Systems Exploration for Ecosystems Leveraging, No. 5Google Scholar
  56. Tindano A, Funabashi M (eds) (2017) Proceedings of the 2nd African forum on synecoculture (English version). Research and Education material of UniTwin UNESCO Complex Systems Digital Campus, e-laboratory: Open Systems Exploration for Ecosystems Leveraging, No. 7Google Scholar
  57. Turner GM (2008) A comparison of the limits to growth with 30 years of reality. Glob Environ Chang 18(3):397–411CrossRefGoogle Scholar
  58. UA (African Union) (2015) Lignes directrices pratiques de l’Union Africaine pour la mise en oeuvre coordonnée du Protocole de Nagoya en Afrique.
  59. UN (United Nations) (2015) Sustainable development goals.
  60. UN (United Nations) (2017) UN member states.
  61. Whittaker RH (1960) Vegetation of the Siskiyou mountains, Oregon and California. Ecol Monogr 30:280–338CrossRefGoogle Scholar
  62. Wu H, Sun Y, Shi W et al (2013) Examining the satellite-detected urban land use spatial patterns using multidimensional fractal dimension indices. Remote Sens 5:5152–5172. Scholar
  63. Yong RN, Mulligan CN, Fukue M (2006) Geoenvironmental sustainability. CRC Press, United StatesCrossRefGoogle Scholar
  64. Zuppinger-Dingley D, Schmid B, Petermann JS et al (2014) Selection for niche differentiation in plant communities increases biodiversity effects. Nature 515:108–111CrossRefPubMedGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Sony Computer Science Laboratories, Inc.TokyoJapan

Personalised recommendations