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The Annual Phenological Cycle

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Boreal and Temperate Trees in a Changing Climate

Part of the book series: Biometeorology ((BIOMET))

Abstract

The hypothetico-deductive modelling framework introduced in Chap. 2 is applied to the modelling of the annual phenological cycle of boreal and temperate trees. The ecophysiological models of the annual phenological cycle predict the timing of discontinuous developmental events, such as bud burst and height growth cessation. With such events only one, or maximally a few, empirical observations per year are available for testing these models; but as in all other models of the annual cycle, the values of the state variables are nevertheless calculated for each day of the simulation period. The methodological problems caused by this discrepancy are discussed, and an ecophysiological explication of the models is introduced. Most effort is devoted to modelling the springtime developmental events, such as bud burst. The direct environmental regulation by air temperature is first discussed by examining the classical temperature sum (or day degree) models. The ecophysiological interpretation of these models, which use the arbitrary unit of day degree, is explicated, and the experimental research aimed at determining the real ecophysiological air temperature responses of the trees and thus supplementing the day degree approach is discussed. Subsequently, effects of dormancy are introduced into the modelling. Most models for growth cessation are conceptually more straightforward, so that they are not discussed at the same length as the models of springtime development. The chapter is concluded with a discussion of models for the entire annual phenological cycle.

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Notes

  1. 1.

    Only the activation visible to the naked eye is discussed here. At the anatomical level, the activation starts earlier (Fig. 2.2).

  2. 2.

    In addition to height growth onset, the concept “high temperature requirement” and the corresponding acronym Hcrit are used in the present volume for a wide range of spring phenological events, such as the bud burst, leaf unfolding, and flowering of the trees. In addition to these phenological events, the concept is also used for microscopic phases of meiosis prior to flowering.

  3. 3.

    This procedure is followed when the model is fitted to the data, which is the case discussed here. When the data are used for independent testing of the model, the value of Hcrit is also fixed on the basis of a priori information.

  4. 4.

    Except in the case where the value of the Hcrit is known a priori. In that case, the prediction of the model can be calculated by starting directly from step (3).

  5. 5.

    This model is discussed in Sect. 3.6.3.

  6. 6.

    Sarvas (1972) actually indicated that the multiplier 5 Δt10 was introduced in order to obtain this similarity.

  7. 7.

    Compare the corresponding case with day degree models in Figs. 3.3 and 3.5.

  8. 8.

    However, Myking (1997) found no such difference when studying the bud burst in seedlings of Betula pubescens.

  9. 9.

    Two of the potential explanations are related to the dormancy of the buds and will therefore be discussed in Sects. 3.4.1.2 and 3.4.4.2.

  10. 10.

    As the dormant condition is a physiological attribute of the bud in this case, plant physiologists often prefer to restrict the use of the concept ‘dormancy’ to this case only.

  11. 11.

    In order to keep the terminology consistent with that used elsewhere in this volume, Vegis’s (1964) original concepts predormancy, true dormancy, and postdormancy are replaced with the concepts pre-rest, true rest, and post-rest, respectively.

  12. 12.

    This definition, equating rest with the existence of an obligatory chilling requirement, is not used in the present volume.

  13. 13.

    For copyright reasons, the responses published by Gilreath and Buchanan (1981) and Erez and Couvillon (1987) are not redrawn here.

  14. 14.

    Cannell and Smith’s (1983) model is discussed further in Sect. 3.4.6.5.

  15. 15.

    The models address various springtime developmental events, such as bud burst, leaf unfolding, the growth onset of vegetative buds, and the flowering of generative buds, but for the sake of brevity, only growth onset will be referred to in the description of the generalised model.

  16. 16.

    The experimental results of Hänninen (1995a) are discussed in Sects. 3.4.6.1 and 8.3.2.2.

  17. 17.

    The concept originally used by Hänninen (1990b) was “growth competence”, which was then replaced with the more informative concept “ontogenetic competence” in Hänninen and Kramer’s (2007) review.

  18. 18.

    The alternating model is discussed in Sect. 3.4.6.5.

  19. 19.

    According to Junttila (2007) there is actually very little, if any, direct experimental evidence for this notion. However, as height growth cessation is needed for rest induction, this notion is plausible for species in which long nights cause height growth session (Sect. 3.5.2).

  20. 20.

    Following the nomenclature adopted for the present volume, the concept of dormancy refers here to both rest and quiescence, so that the deepness of the dormancy can be manifested in the values of both Ccrit and Hcrit. In some of the studies referred to in this section, the concept of dormancy refers to rest only.

  21. 21.

    In the modelling of the effects of night length on rest completion, it is the value of the critical night length (or the corresponding calendar day) that is estimated instead of the value of the chilling requirement of rest completion (Häkkinen et al. 1998).

  22. 22.

    The results are discussed in detail in Sect. 8.3.2.2.

  23. 23.

    The results are discussed in detail in Sect. 8.3.2.2.

  24. 24.

    Recently, Clark et al. (2014) addressed this problem and introduced a novel approach, the continuous development model (CDM), for phenological studies. While opening new avenues for phenological modelling, Clark et al.’s (2014) approach is substantially different from the one adopted in the present volume. Therefore the reader is referred to Clark et al.’s (2014) original study rather than discussing the CDM model here.

  25. 25.

    However, as shown by Linkosalo et al. (2008), Chuine’s (2000) unified model, like any other complex model with a high number of parameters, is susceptible to over-parameterisation in these studies.

  26. 26.

    In the present volume a similar change in the air temperature response was introduced as an extension of Vegis’s (1964) theory (Fig. 3.11b in Sect. 3.3.1.2). As no reference to Vegis (1964) is made in Caffarra et al.’s (2011b) study, their model is evidently not explicitly based on Vegis’s (1964) theory.

  27. 27.

    Cannell and Smith (1983) used the concept “thermal time” for the day degree model used in their study.

  28. 28.

    These studies are discussed in Sect. 8.3.1.3.

  29. 29.

    This illustrative point was made by Tapio Linkosalo.

  30. 30.

    Though autumn dormancy belongs to the autonomous theory, it has an effect somewhat similar to the regulation by short-term signals such as night length. After the active period is completed, the development does not proceed further until the ‘signal’ of air temperatures dropping below +10 °C is received from the environment. This synchronises the development of different tree genotypes that attain autumn dormancy at different times in late summer (Sarvas 1974).

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Authors and Affiliations

  1. Department of Biosciences, University of Helsinki, Helsinki, Finland

    Heikki Hänninen

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List of Symbols

List of Symbols

t:

time

3.1.1 Time-Dependent Environmental Variables

T(t):

air temperature (°C)

Tmean(t):

daily mean air temperature (°C)

NL(t):

daily night length (h)

3.1.2 Time-Dependent Rate and State Variables

3.1.2.1 Ontogenetic Development

Ro,pot(t):

potential rate of ontogenetic development (% day−1)

Ro(t):

rate of ontogenetic development (% day−1)

So(t):

state of ontogenetic development (%)

Rdh :

accumulation rate of degree hour units (dh h−1)

Rdd(t):

accumulation rate of day degree units (dd day−1)

RHU(t):

accumulation rate of high temperature units (HU day−1)

RPU(t):

accumulation rate of period units (PU h−1)

RFU(t):

accumulation rate of forcing units (FU day−1)

RFU′(t):

accumulation rate of modified forcing units (FU′ day−1)

Sdd(t):

accumulated temperature sum (dd)

SPU(t):

accumulated period units (PU)

SDU(t):

accumulated dormancy units (DU)

SFU(t):

accumulated forcing units (FU)

SFU′(t):

accumulated modified forcing units (FU′)

3.1.2.2 Rest Break

Rr(t):

rate of rest break (% day−1)

Sr(t):

state of rest break (%)

RCU(t):

accumulation rate of chilling units (CU day−1, CU h−1)

SCU(t):

accumulated chilling units

3.1.2.3 Development During Growing Season

Sa :

state of active growth (%)

Sl :

state of lignification (%)

3.1.3 Variable Mediating the Effect of Rest Break on the Ontogenetic Development

Co(t):

ontogenetic competence

3.1.4 Model Parameters

3.1.4.1 Ontogenetic Development

t0 :

starting date of the simulations

Tthr :

air temperature threshold of ontogenetic development (and of accumulation of forcing units)

FUcrit :

Critical forcing unit sum (FU)

Hcrit :

high temperature requirement of growth onset (HU)

a:

steepness of air temperature response of rate of ontogenetic development (and of accumulation rate of forcing units) (°C−1)

b:

inflexion point of air temperature response of rate of ontogenetic development (and of accumulation rate of forcing units) (°C)

c:

Upper asymptote of air temperature response of accumulation rate of forcing units (FU)

NLcrit :

critical night length of growth cessation (h)

3.1.4.2 Rest Break

Ccrit :

chilling requirement of rest break (CU)

T1 :

minimum air temperature for rest break (°C)

T2 :

temperature for maximum rate of rest break (°C)

T3 :

maximum air temperature for rest break (°C)

3.1.5 Other Symbols

3.1.5.1 Ontogenetic Development

dd:

day degree unit

dh:

degree hour unit

PU:

period unit

FU:

forcing unit

FU’:

modified forcing unit

HU:

high temperature unit (general term covering all specific units)

Δt(T):

developmental time (time required for a given point event to occur in experimental conditions) in temperature T

Δt10 :

developmental time in the reference temperature 10 °C

3.1.5.2 Rest Break

CU:

chilling unit

3.1.5.3 Variables for a Regrowth Test

BB%:

bud burst percentage (%)

DBB:

days required for bud burst (day)

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Hänninen, H. (2016). The Annual Phenological Cycle. In: Boreal and Temperate Trees in a Changing Climate. Biometeorology. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-7549-6_3

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