Skip to main content

Modelling the Flowering of Four Eucalypt Species Using New Mixture Transition Distribution Models

  • Chapter
  • First Online:
Phenological Research

Abstract

The multivariate relationship between the probability of flowering, in relation to two discrete states of rainfall and of temperature (high/low), is investigated via a mixture transition distribution (MTD) analysis, which allows for a different transition matrix for each lag (up to 12 months backwards in time) to present flowering via a so-called MTDg analysis. The conventional mixture transition distribution (MTD) model considers the effect of each lag to the present independently, and uses equal transition matrices among different lags. Flowering data consisted of monthly flowering records of E. leucoxylon, E. microcarpa, E. polyanthemos and E. tricarpa (1940 and 1970). We extend the MTDg model to allow for interactions (between rain and temperature) to account for changes in the transition matrices amongst the differing lags. The MTDg model with interactions shows that the flowering of E. leucoxylon and E. tricarpa behave similarly with temperature (both flower at low temperature) and have a positive relationship with flowering intensity 11 months ago. Eucalyptus microcarpa behaves differently, in that it flowers at high temperature. MTDg analysis also found a highly significant interaction between mean temperature and rainfall for E. polyanthemos, in that E. polyanthemos does not tend to flower during the winter time (when it is cold and wet). Rainfall has a direct positive impact only on E. tricarpa. These four species are influenced by temperature (and to a lesser extent rainfall) and as a consequence their flowering phenology will possibly change in response to climate change.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 259.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 329.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 329.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Abu-Asab MS, Peterson PM, Shelter SG et al. (2001) Earlier plant flowering in spring as a response to global warming in the Washington DC, area. Biodivers Conserv 10:597–612

    Article  Google Scholar 

  • Ashton DH (1956) Studies on the autecology of Eucalyptus regnans. Dissertation, University of Melbourne

    Google Scholar 

  • Bassett OD (1995) Development of seed crop in Eucalyptus sieberi L. Johnson and E. globoidea Blakely in a lowland sclerophyll forest of East Gippsland. Department of Conservation and Natural Resources, Victoria

    Google Scholar 

  • Bassett OD, White MD (1993) Development and testing of seed crop assessment models for three Lowland Sclerophyll forest eucalypts from East Gippsland. Department of Conservation and Natural Resources, Victoria.

    Google Scholar 

  • Berchtold A (2004) Optimization of mixture models: comparison of different strategies. Computation Stat 19:385–406

    Google Scholar 

  • Berchtold A (2006) March v.3.00 Markovian models computation and analysis users guide. URL http://www.andreberchtold.com/march.html

  • Berchtold A, Raftery AE (2002) The mixture transition distribution model for high-order Markov chains and non-Gaussian time series. Stat Sci 17:328–356

    Article  Google Scholar 

  • Brémaud P (1999) Markov chains: Gibbs fields, Monte Carlo simulation, and queues. Springer, New York

    Google Scholar 

  • Fielding JM (1956) Notes on the flowering and seeding of Eucalyptus delegatensis and E. fastigata in the Australian Capital Territory. Aust For 20:40–43

    Google Scholar 

  • Fitter AH, Fitter RSR (2002) Rapid changes in flowering time in British plants. Science 296:1689–1691

    Article  CAS  PubMed  Google Scholar 

  • Fournier DA (1996) AUTODIFF. A C++ array language extension with automatic differentiation for use in nonlinear modeling and statistics. Otter Research Ltd, British Columbia, Canada

    Google Scholar 

  • Fournier DA (2000) AD model builder, version 5.0.1. Otter Research Ltd, Canada

    Google Scholar 

  • Gill AM (1966) The ecology of mixed species forests of Eucalyptus in Central Victoria, Australia. Dissertation, University of Melbourne

    Google Scholar 

  • Harris AC (1956) Regeneration of Jarrah (Eucalyptus marginata). Aust For 20:54–62

    Google Scholar 

  • Harrison M, Campbell R, McCormick M (1990) Seed crop monitoring in Mountain Ash forests. Department of Conservation and Environment, Victoria

    Google Scholar 

  • Hodgkinson K, Freudenberger D (1997) Production pulses and flow-ons in rangeland landscapes. In: Ludwig J, Tongway D, Freudenberger D et al. (eds) Landscape ecology: function and management. CSIRO, Australia, pp 23–34

    Google Scholar 

  • Hudson IL, Barnett A, Keatley MR et al. (2003) Investigation into drivers for flowering: effects of climate on flowering. In: Verbeke G, Moelenberghs G, Aaerts M et al. (eds) Proceedings of the 18th International Workshop on Statistical Modeling. Katholieke Universiteit Leuven, Belgium

    Google Scholar 

  • Hudson IL, Keatley MR, Roberts AMI (2005) Statistical methods in phenological research. In: Francis AR, Matawie KM, Oshlack A et al. (eds) Statistical solutions to modern problems. Proceedings of the 20th International Workshop on Statistical Modelling. Sydney, Australia

    Google Scholar 

  • Hudson IL, Kim SW, Keatley MR (2009) Climatic influences on the flowering phenology of four eucalypts: a GAMLSS approach. In: Anderssen RS, Braddock RD, Newham LTH (eds) 18th IMACS World Congress – MODSIM09 International Congress on Modelling and Simulation. Cairns, Australia

    Google Scholar 

  • Keatley MR (1999) The flowering phenology of box-ironbark eucalypts in the Maryborough region, Victoria. Dissertation, University of Melbourne

    Google Scholar 

  • Keatley MR, Fletcher TD, Hudson IL et al. (2002) Phenological studies in Australia: potential application in historical and future climate analysis. Int J Climatol 22:1769–1780

    Article  Google Scholar 

  • Keatley MR, Hudson IL (1998) The influence of fruit and bud volumes on eucalypt flowering: an exploratory analysis. Aust J Bot 42:281–304

    Article  Google Scholar 

  • Keatley MR, Hudson IL (2000) Influences on the flowering phenology of three eucalypts. In: de Dear RJ, Kalma JD, Oke TR et al. (eds) Biometeorology and urban climatology at the turn of the century. Selected papers from the Conference ICB-ICUC 99. World Meteorological Organisation, Geneva, Switzerland

    Google Scholar 

  • Keatley MR, Hudson IL (2007) A comparison of the long-term flowering patterns of box-ironbark species in Havelock and Rushworth forests. Environ Model Assess 12:279–292

    Article  Google Scholar 

  • Keatley MR, Hudson IL, Fletcher TD (2004) Long-term flowering synchrony of box-ironbark eucalypts. Aust J Bot 52:47–54

    Article  Google Scholar 

  • Kim SK, Hudson IL, Agrawal M et al. (2008) Modelling and synchronization of four Eucalyptus species via mixed transition distribution MTD and extended kalman filter EKF. In: Eilers PHC (ed) Proceedings of the 23rd International Workshop on Statistical Modelling. Ipskamp Partners, Enschede, The Netherlands

    Google Scholar 

  • Kim SW, Hudson IL, Keatley MR (2005) Mixture transition distribution analysis of flowering and climatic states. In: Francis AR, Matawie KM, Oshlack A et al. (eds) Statistical solutions to modern problems. Proceedings of the 20th International Workshop on Statistical Modelling. Sydney, Australia

    Google Scholar 

  • Kim SW, Hudson IL, Keatley MR (2009) Modelling the flowering of four eucalypts species via MTDg with interactions. In: Anderssen RS, Braddock RD, Newham LTH (eds) World Congress – MODSIM09 International Congress on Modelling and Simulation, Cairns, Australia

    Google Scholar 

  • Mac Nally R, Bennett AF, Thomson JR et al. (2009) Collapse of an avifauna: climate change appears to exacerbate habitat loss and degradation. Diversity Distrib:1–11

    Google Scholar 

  • Parmesan C (2007) Influences of species, latitudes and methodologies on estimates of phenological response to global warming. Glob Change Biol 13:1860–1872

    Article  Google Scholar 

  • Parmesan C, Yohe G (2003) A globally coherent fingerprint of climate change impacts across natural systems. Nature 421:37–42

    Article  CAS  PubMed  Google Scholar 

  • Parry M, Canziani O, Palutikof J et al. (eds) (2007) Climate change 2007 – impacts, adaptation and vulnerability. Contribution of Working Group II to the fourth assessment report of the IPCC. Cambridge University Press, Cambridge

    Google Scholar 

  • Peñuelas J, Filella I, Comas P (2002) Changed plant and animal cycles from 1952 to 2000 in the Mediterranean region. Glob Change Biol 8:531–544

    Article  Google Scholar 

  • Porter JW (1978) Relationships between flowering and honey production of red ironbark, Eucalyptus sideroxylon (A. Cunn.) Benth, and climate in the Bendigo district of Victoria. Aust J Agric Res 29:815–829

    Article  Google Scholar 

  • Raftery AE (1985) A model for high-order Markov chains. J R Stat Soc Ser B 47:528–539

    Google Scholar 

  • Rehfeldt GE, Tchebakova NM, Parfenova EI (2004) Genetic responses to climate and climate-change in conifers of the Temperate and Boreal forests. Recent Res Devel Genet Breeding 1:113–130

    Google Scholar 

  • Root TL, Price JT, Hall KR et al. (2003) Fingerprints of global warming on wild animals and plants. Nature 421:57–60

    Article  CAS  PubMed  Google Scholar 

  • Rosenzweig C, Karoly D, Vicarelli M et al. (2008) Attributing physical and biological impacts to anthropogenic climate change. Nature 453:353–358

    Article  CAS  PubMed  Google Scholar 

  • Seneta E (1996) Markov and the birth of chain dependence theory. Int Stat Rev 64:255–263

    Article  Google Scholar 

  • Traill B (1991) Box-ironbark forests: tree hollows, wildlife and management. In: Lunney D (ed) Conservation of Australia’s forest fauna. Royal Zoological Society of NSW, Mosman

    Google Scholar 

  • Victorian Environment Assessment Council (2001) Box-ironbark forests and woodlands investigation. Final report. Victorian Environment Assessment Council, East Melbourne

    Google Scholar 

  • Wells K (2000) Long term cyclic and environmentally induced effects on flowering of four box-ironbark eucalypts. Dissertation, University of Melbourne

    Google Scholar 

  • Wilson J, Bennett AF (1999) Patchiness of a floral resource: flowering of red ironbark Eucalyptus tricarpa in a Box and Ironbark forest. Victorian Nat 116:48–53

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Irene L. Hudson .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer Science+Business Media B.V.

About this chapter

Cite this chapter

Hudson, I.L., Kim, S.W., Keatley, M.R. (2010). Modelling the Flowering of Four Eucalypt Species Using New Mixture Transition Distribution Models. In: Hudson, I., Keatley, M. (eds) Phenological Research. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-3335-2_14

Download citation

Publish with us

Policies and ethics