Master Thesis
Introduction to Phenology
Phenology is a term derived from the Greek word phaino meaning to show or to appear. It
studies repeatable phenomena and their reasons. The phenomenon could be the life stages of
plants and animals, spectral reflectance of vegetation on satellite imageries, or the range of
glaciers. Plant phenology studies the botanical cycle events, and addresses the developmental
phases of plant organisms, recurring biological phases of species, biotic and abiotic causes, and
the interrelation of phases within or among species (Badeck et al., 2004; Leith, 1970; Rathcke
and Lacey, 1985). The timing of biological phases and its reaction to the variations of
environment is the major focus of this subject matter because of their significant responses to
fluctuation of climate (Menzel et al., 2006; Parmesan, 2006; Walther et al., 2002). Once the
response has genetically fixed, it became a phenological traits among populations. For the spring
phenology, these traits refer to flowering, budburst, or leave unfolding. These phenological traits
are usually used to monitor adaptive traits of the plants and evaluate their relationships to the
ecosystem where they grow (Arora and Boer, 2005; Howe et al., 2003). It has been applied in
agriculture to determine timing of planting and harvesting in order to achieve the maximum crop
yield (Sakamoto et al., 2005), and also used to decide the timings of applying pesticide and
herbicide (Moola and Mallik, 1998). In forest management, tree phenology has been used to
estimate forest productivity (Goetz and Prince, 1996) and variation of biochemical mass in
leaves (Kause et al., 1999), and to improve seed zoon selections (Hamann and Wang, 2006). In
addition, plant phenology is considered the key element that affects the carbon balance of
terrestrial ecosystems (Gill et al., 1998) and characterizes plant competition capabilities (Rathcke
and Lacey, 1985).
The basic knowledge of phenology has a long history of application in agriculture and forest.
Europe has the longest scientific phenological observation and research history that could be
tracked back as far as the 18th century (Leinonen and Hanninen, 2002; Luterbacher et al., 2007).
In North America, however, Thomas Mikesell started the earliest systematic phenology
observation between 1883 and 1921, about a century later, and recorded about 25 species during
that period of time (Lechowicz, 1995). The modern phenological recording was started by a
Swedish biologist Carolus Linnaeus and a British landowner Robert Marsham in the 18th
century (Lechowicz, 2001). The historical recorder still contributes for today’s research(Sparks
and Carey, 1995). Since then, records of explicit phenological observations were started, and
extensive plant phenological observation networks were established across the world, such as
Encyclopedia of Life (EOL) and Project BudBurst. Nowadays, one of the most influential
phenology watch networks, the Plantwatch, is based in Western Canada and is still very active1.
This network has documented phenological observations for decades and covered hundreds of
species' flowering and leave flushing. Beside the field observation, digital camera, aerial photo
(Carreiras et al., 2006), and satellite imagery(Fisher and Mustard, 2007; Reed et al., 1994) have
been introduced into the studying of phenology.
1
http://plantwatch.sunsite.ualberta.ca/misc/tracking.php
Environmental control of budburst
Temperature, thermal time,
Walther
Chilling requirement, photoperiod , CO2 ,
Temperature supply kinetic energy for biochemical reactions and enzyme’s catalyst. It controls
plant’s respiration, growth, and carbon uptake (Saxe et al., 2001). Spring phenology is also
driven by temperature (Menzel, 2003; Morin et al., 2009; Penuelas and Filella, 2001). However,
instead of using temperature itself, heatsum is convenient to describe the rate of development of
plants and their organs. Heatsum is the accumulation of degree-days for a phenological event in
its active period. Degree-days also known as heat units, thermal units, or day degrees and defined
as the accumulation of effective temperature. Generally, it sums the algebraic average of daily
temperature within a range of thematic threshold (Ghelardini et al., 2006; Hunter and Lechowicz,
1992). For example, budburst, the active period from the cessation of dormant to the beginning
of leaf flush, will not happen until temperature surpasses its thermal threshold and certain
amount of heatsum is achieved. Using heatsum as predictor, Reaumur successfully predicted the
occurrence of a phenological stage more than 200 years ago, suggesting heatsum is a constant
and could be used to project future or past phenological event of the same kind. Following this
idea, investigating the relationships between heatsum and phenological events of various species
has become a major topic in phenological researches. Some studies show the rate of botanic
development is linearly related to heatsum (Johnson and Thornley, 1985; Sharpe and Demichele,
1977). Considering the variation of heatsum requirement for different genotypes (Lappalainen,
1994), the distribution of heatsum may therefore reflect the spring phenology and genotypic
ranges of a specific species (Howe et al., 2003).
The accuracy of thematic threshold and starting date for a phenological event impacts on the
precision of heatsum computations, and different approaches have been adopted to estimate these
values. Yang et al. (1995) summarized four most common used approaches including the
smallest stantard deivation method, linear regression model, iteration method, and the triangle
method. The main idea of these approaches was to approximate a thematic threshold with
regression or iteration method based on the field-measured phenological data. Snyder et al.
(1999) found that the results from iteration method usually provid the smallest root mean square
error (RMSE) in most cases, indicating this is a better approach in effective temperature
estimates. Although these thresholds are theoretical rather than realistic value which are based on
biological tests or field observations, these thresholds are considered close enough in practice
(Snyder et al., 1999). Normally, temperature between 0°C and 10°C, optimum at about 5°C, is
considered sufficient for dormancy release for most species based on experiments (Perry, 1971),
and many studies suggested to set 0°C or 5°C for budburst effective temperature in predict
models (Snyder et al., 1999). For aspen, Heide (1993)set the threshold as 1°C and Beaubien
(2000) set as 0°C. Generally, the threshold simply using 0 is nearly as good for most modal
(Ring et al., 1983; Snyder et al., 1999). After setting the threshold, the heatsum could be
calculated by adding up all the effective temperatures from the starting to the end of a
phenological event, this computation is also called thermal time model (Delahaut, 2003; Reader,
1983) 2.
Threshold), 0 (Elisabeth), -3 to 15 effective as chilling (Santini 2004)
Temperature below threshold cannot attribute to the organism’s development anymore, but it still
influences phenological timing, especially budburst (e.g. Campbell and Sugano 1975, Murray et
al. 1989). Tree has a period to dormancy during the winter for avoid the cold damage. This
mechanism is prevalent under maritime climates, requiring a certain amount of chilling degreedays (accumulated temperatures below a certain threshold), before accumulating degree-days
toward the heatsum requirement starts. A chilling requirement prevents premature heatsum
accumulation and budbreak if fall and winter temperatures are unusually mild.
After growth cessation and before budburst, bud is in two states: the state of rest and the state of
quiescence.
Chilling hour
Photoperiod and others.
This mechanic protects plants to expose such risk
Spring phenology as an adaptive trait
Geographic patterns of budburst
(latitudinal, altitudinal, and coastal Davis 2001 )
Roughly, the phenotypic variations can be considers as the genotypic variation.
Title: Running to stand still: adaptation and the response of plants to rapid climate change
Author(s): Jump, AS; Penuelas, J
(Brissetter Barnes 1984)
Earlier researches noticed the geographic variation of spring phenology and attributed this
difference to their adaptations to local climates (Lechowicz, 1984). For example, the latitudinal
phenology variations were observed for budburst of Scots pine (Pinus sylvestris) and Norway
spruce (Picea abies) that plants from the south usually have earlier budburst while they are
planted in the same environment (Beuker, 1994; Leinonen and Hanninen, 2002), and similar
trends were found in some boreal tree species such as silver birch (Betula pendula) (Leinonen,
1996) and European elms (Ulmus minor, Ulmus glabra, and Ulmus laevis) (Santini et al., 2003).
The interpretation to all these phenomena is that these phenological variations are the results of
2
For a particular species, their geographical variation of heatsum requirements could be summarized as
the Linsser’s law (Ref. Reader 1983): the fractions of the heatsum required for a particular phenological
stage divided by the total annual heatsum for a plant at its site of origin are the same for plants from all
locations.
species’ adaptation to their local climates by minimizing their exposition to frost damage
(survival adaptation), while maximizing the duration of growing season (capacity adaptation)
(Leinonen and Hanninen, 2002). Mismatches between the spring weather and plant phenological
responses could potentially cause the plants from failing to produce seeds or fruits to increasing
the chance of mortality (Billington and Pelham, 1991). And plants that cannot respond to interannual climate variability to sufficiently use the growing season will be at a competition
disadvantage.
Recent researchers also found that adaptive traits of a species appear to be different through their
life stages, and plants of different ages usually choose different adaptive strategies to the same
environment (???). For example, because the frost damage is negatively correlated with the
timing of budburst, a seedling or sapling usually choose a 'threshold' strategy that it scarifies
taking the advantage of the full growing season, and takes a late budburst before its stem grows
longer and bigger; however, an adult tree may have more endurance to frost damage and may
take more risk to have an earlier budburst (Leinonen and Hanninen, 2002). [The same species
adapting to different environments or same plant at different age adapting the same environment
are overall the embodiment of phenotypic plasticity. Phenotypic plasticity is defined as the
adaptive traits of a plant to the altered environment.] With this concept, the species adaptation
could be better explained…………….
Usually, phenological events, such as budburst or flowering, could be statistically described by
timings of their occurrence, duration, and synchrony (Rathcke and Lacey, 1985) . Studies of
these phenological events usually based on onsite observations and recordings (Beaubien and
Freeland, 2000); however, some events, such as budburst, could be observed with the help of
remote sensing technologies (Sellers et al., 1995). Plant phenological phases are usually
categorized as budburst, bud set, flowering, and fruiting (???), although some studies classified
these events somewhat differently (Schwartz, 2003). Biologische Bundesanstalt and Chemical
industry (BBCH) unified the description and coding system by separating growth stages into 10
general phenological phases based on the development stages of bud, leave, stem, flower, and
fruit (Schwartz 2003) (detailed definitions see Appendix table 1), which has been widely adapted
by phenological studies. Following these criteria and standard procedures, plant phenology of
many species, especially those from the temperate zone, have been recorded and studied (e.g. ???
review), these information have provided great help to forest management (??) and agricultural
development (??).
Interpretation
Plant phenology is considered the result of plants adapting to their environment, especially for
those that grow in extreme environments such as the ecosystems u cold temperature or less
moisture (Perry, 1970). Abiotic factors usually have direct impacts on plant phenology. These
factors could be seasonal temperature variations (Beaubien and Freeland, 2000), frost damage in
spring and fall (Leinonen and Hanninen, 2002; Vitasse et al., 2009), or chilling effect in early
spring (Jonsson et al., 2004). However, differences in precipitation and soil moisture (Beaulieu et
al., 2002; Kramer et al., 2000; Reich, 1995) or variations in photoperiod (Partanen et al., 1998)
also have major influences on plant phenology. Biotic factors, on the other hand, are more
influential to plant regenerations. For example, the population dynamics of pollinators could
determine the timing of flowering, and the population variation of seed predators would also
affect whether the fruiting is successful (Elzinga et al., 2007; Kolb et al., 2007). Among all the
abiotic and biotic factors, temperature is the most important driver to plant phenology, especially
for the deciduous plants in the temperate zone (Badeck et al., 2004; Kramer et al., 2000). For
instance, in the moist temperate zone, most dormant trees require winter chilling to end the
dormancy in the beginning of spring and certain amount of heat to start bud bursting (Hunter and
Lechowicz, 1992). In addition, research found that the higher temperature speeds up the
phenology development (Saxe et al., 2001).
Genetic differentiation with respect to quantitative aspects of the phenotypes are not reflected in
patterning of enzyme variation, indicating that populations diverged in relation to local climate
despite gene flow (Davis and Shaw, 2001).
Selection and rapidly differentiate populations along an environmental gradient as a species is
expanding its rang
Phenology and forest management
Forest management is to guide forests toward a society's goals: preserving the environment,
meeting the current and future forest products needs of human society, or the combinations of
these former goals. Besides growing trees, forest management deals with other benefits provided
by forested land, the non-wood forest products, such as habitats for wildlife, food resources,
biodiversity, agroforestry, or recreation (Zeide, 2008) . Forest management is a long-range
viewpoint of a planner (Davis et al., 2005), it considers the predictable changes (such as human
population and climates) in the future and finds the resolutions, for example, to answer the
question about how we can share benefits from forests (e.g. forest service) with our descendants.
A sustainable human-forest ecosystem is desirable under this context and the core of modern
forest management (Davis et al., 2005).
Among all the factors affecting forest management, climate change is one of the biggest threats
for the forest industry. Climate change impacts forest reproductions by failing tree flowering and
fruiting. Kudo (2004), for example, found that bee-pollinated species had less seed-set in 2000 in
Japan because of a shortage of pollinators for the earlier flowering in the warm spring.
Considerable climate change has been observed around the world (Parmesan and Yohe, 2003),
and the trend is predicted to be continuous for the next century (Mbogga et al., 2009)(IPCC,
2007). Studies showed that the temperature has been increased dramatically since the 1980's
(Karl et al 2005); however, climate change also increased the frequencies of storms, fire,
precipitation, flood, snow, and other extreme events (Groisman et al., 2005; Saxe et al., 2001).
These changes have major impacts on species abundance, biological process, organic matter
decomposition, species range shift, as well as species adaptations (e.g. plant phenology) (Badeck
et al., 2004; Parmesan and Yohe, 2003; Saxe et al., 2001; Walther et al., 2002). Species change
their phenology to cope with the changing environments have been widely observed, such as the
changes of budburst and flowering timings (Beaubien and Freeland, 2000), leaf coloring (Estrella
and Menzel, 2006), and length of growing season (???). However, the climate change is too fast
for some species to keep up with, the physical migrations and gene flow from warm-adapted
population will be more important than species' evolution for maintaining the level of forest
ecosystem services (Billington 2008). Therefore, assistant plant migrations are necessary and the
major tasks for the future forest management.
Species with large ranges growing under a variety of environmental conditions will likely show
phenotypes differences in their adaptive traits (Howe et al., 2003), which are usually important
factors to be considered in the movement of planting stock for reforestation and in genetic tree
improvement programs. For example, if genotypes are selected for growth traits in short-term
experiments, adaptive traits may be sub-optimal. Consequently, the better growth may be the
result of risking late spring and early fall frost damage for an extended growing season (Brissette
and Barnes, 1984). Therefore, phenotypes with high mortality risk due to susceptibility to frost
damage or drought may not be a suitable choice for reforestation. Ideally, we would like to
choose phenotypes that show lower adaptive risks while maintaining superior growth.
Provenance
Genetic variation is an evolutionary result of plant adaption to the environmental heterogeneity
(Jelinski, 1997), and can be maintained through reproduction if the diversity was acquired
through recombination, introgression, or somatic mutation (Rasmussen and Kollmann, 2007).
The genetic variations are regulated by forces such as mutation, genetic drift, gene flow, and
natural selection (Ohsawa and Ide, 2008). Studying of genetic variation can help us to identify
species, assess their spatial distribution, examine the genetic structure, or probe their phenotypes.
Moreover, it has been used to select the high-quality timber resources or seed zones for forest
industry.
Genetic variations can be detected by many methods such as field observation, molecular genetic
marker, or quantitative traits locus (QTL) mapping (Gonzalez-Martinez et al., 2006). Molecular
genetic markers can be used to directly detect the genetic variations of a species because they
could be found at a known location on a chromosome and associated with a particular gene or
phenological trait. However, researches also found that genetic variations do not alway march to
the phenological or growth variations (Hall et al., 2007), and genetic variations detected by these
markers do not always associate with the suitable growth or phenological traits that are desirable
for the forest industry. For example, research found that the genetic variations in the conifer
species are much less than their adaptive traits (Gonzalez-Martinez et al., 2004). QTL mapping is
relatively straightforward than the other methods (Damerval et al., 1994). With this method,
many adaptive traits of tree species have been successfully identified, such as poplar (Ferris et
al., 2002) and Douglas fir (Wheeler et al., 2005). However, this method requires a large sample
size, and it is very time-consuming and expensive to construct.
All phenological traits show significant genetic differentiation among population and the results
were similar at the common garden sites (Hall et al., 2007).
(Ohsawa and Ide)
Field observation of phenological traits is the most traditional way to reveal the genetic
variations of a species; however, these observed differences might be confounded by
environmental variations. To eliminate the environmental factors and protrude the genetic
variations, the provenance trial, which is also called common garden, progeny test, or clonal test,
has been routinely performed (e.g. Hamann et al., 2000; Kleinschmit et al., 2004; Savva et al.,
2007). The essence of the provenance trials is to compare phenological and growth traits of
different genotypes within or among species from different sites in a same experimental site,
where they can be exposed to the same environmental conditions—soils, climate, water, and
photoperiod—with a systematic experimental design that accounts for random site variation
(Bower and Aitken, 2008). Because different genotypes may respond to the same environment
conditions differently in phenological traits, the observed differences can reflect within-species
genetic variations. This information can be used to create guidelines of seed transfers and to
delineate seed zones. The objective of limiting seed movement in reforestation is to ensure that
planting stock is not mal-adapted to environmental conditions of the planting site. For example,
northern provenances of Norway spruce (Picea abies), have earlier budburst and should
therefore not be used in southern planting environments to avoid late spring frost damage
(Leinonen and Hanninen, 2002).
- The advantage and disadvantage of provenance trials
Studying genetic variation through provenance trials has advantages and disadvantages. Major
advantage of provenance trials is with environmental variables controlled, a variety of growth
and adaptive traits can be evaluated for genetic variation, e.g.: growth traits (Lesser et al., 2004),
wood properties (Beaulieu et al., 2002), and adaptive traits (i.e. phenological characters)
(Backman, 1991; Li et al., 1997; Lobo et al., 2003). It should be kept in mind, however, that the
failure to detect genetic differences among populations in a common garden trial does not mean
that genotypes are identical. Genetic differences may be revealed under one set of environmental
conditions, but not under another. Therefore, provenance trials are typically replicated over
several environments. Testing multiple genotypes over multiple environments makes provenance
trial series expensive research efforts. To evaluate growth traits in trees at rotation age, they are
also very time-consuming. Studying budburst, however, is simpler. The trait can be observed
early on in seedlings or saplings (assuming that there is no change in phenology between
juvenile and adult trees), and environmental factors such as soil conditions and soil moisture are
thought to play a minor role (Backman, 1991). Therefore, results from a single provenance trial
observed in a single year should provide sufficient information. This offers the opportunity to
abandon the provenance trial approach entirely and attempt to study genetic variation in situ: this
study proposed a new approach of using remote sensed data to differentiate genotypes. This
would allow for the first time to generate seamless maps of genetic variation in populations
rather than obtaining information for a very limited set of samples.
Remote sensing
What it’s been used for
Remotely sensed observation phenology is land surface phenology
Cloud and other noise, tempera resolution, imagery calibration, and mixture pixels.
The sharp increases in NDVI that can be related to the onset of significant photosynthetic
activity (Reed et al., 1994)
Onset and offset of ‘green period’
New application
Objectives
Spatial patterns of genetic variations;
Remote sensing approach;
Reason for spatial patterns: understand the mechanic of adaptation to climate, application for
forest management; and predict the shift in the future responded to the climate change.
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