Embed Size (px)
Citation preview
Organismal and Evolutionary Biology Research Programme
Faculty of Biological and Environmental Sciences
Doctoral Programme in Plant Sciences (DPPS)
University of Helsinki
Helsinki
LIGHT QUALITY AFFECTS LEAF PIGMENTS AND LEAF PHENOLOGY
Craig C. Brelsford
To be presented, with the permission of the Faculty of Biological and Environmental
Sciences of the University of Helsinki, for public examination in Porthania P673,
(Yliopistonkatu 3) on Thursday June 4th at 12 o’clock noon.
Helsinki 2020
ACADEMIC DISSERTATION
Supervisor:
Dr T Matthew Robson, University of Helsinki, Finland
Advisory committee:
Prof. Paula Elomaa, University of Helsinki, Finland
Assoc. Prof. Markku Larjavaara, Peking University, China
Prof. Anders Lindfors, Finnish Meteorological Institute, Finland
Pre-examiners:
Prof. Eva Rosenqvist
Assoc. Prof. Carla Valeria Giordano
Opponent:
Prof. Gareth Phoenix
Custos:
Prof. Kurt Fagerstedt, University of Helsinki, Finland
The Faculty of Biological and Environmental Sciences uses the Urkund system
(plagiarism recognition) to examine all doctoral dissertations.
ISBN 978-951-51-6135-2 (paperback)
ISBN 978-951-51-6136-9 (PDF)
ISSN 2342-5423 (print)
ISSN 2342-5431 (online)
Unigrafia Oy
Helsinki 2020
“Live in each season as it passes; breathe the air, drink the drink, taste the fruit, and
resign yourself to the influence of the earth.”
- Henry David Thoreau, Walden
I II III IV
Original Ideas TMR CCB CCB CCB, TMR
Experimental Design CCB, TMR CCB, TMR CCB CCB, TMR
Data Collection CCB, TK, JN, TMR, SMH
CCB CCB CCB, TP, MT
Analyses CCB, TMR CCB CCB CCB
Manuscript Preparation
CCB, TK, JN, TMR, SMH, LOM, PJA
CCB, TMR CCB, LN, TK, TMR CCB, TMR, TP, MT, SMH
CCB: Craig C Brelsford
JN: Jakub Nezval
LOM: Luis O Morales
MT: Marieke Trasser
PJA: Pedro J Aphalo
SMH: Saara M Hartikainen
TK: Titta Kotilainen
TP: Tom Paris
TMR: T Matthew Robson
6
ABSTRACT
Light quality varies in space and time, and plants are able to detect and respond to
these environmental cues. Plants must time when their leaves come out in spring and
fall off in autumn, to maximise opportunities for photosynthesis whilst conditions are
favourable. Similarly, they must optimise the amount of sun-screening pigments in
their leaves, to minimise the harmful effects of ultraviolet radiation at high irradiance.
Solar radiation reaching the Earth, as well as its composition, vary diurnally
and seasonally with solar angle. During twilight, plants are able to detect changes in
red:far-red light, and use this to help time their spring and autumn phenology. When
forest canopies leaf out in spring, and cause canopy closure, the understorey becomes
mostly covered in shade. This shade also causes a low red: far-red ratio, that plants
are able to detect and increase their stem elongation. However, the amount of blue
and UV radiation also varies in space and time, and we know considerably less about
how plants respond to these changes in the blue-and-UV region.
Using a combination of controlled indoor experiments, literature review, and
manipulative field experiments, we set out four aims. 1) How do blue and UV-A
radiation affect leaf pigments under controlled conditions? 2) How does blue light
affect spring bud burst under controlled conditions? 3) How do blue and UV radiation
affect leaf pigments and leaf phenology for understorey plant species? 4) How
important is light quality as a phenological cue?
We found that both under controlled conditions and in the field, blue light had
a large positive effect on the accumulation of flavonoids, most likely governed by
cryptochrome photoreceptors. Interestingly, the flavonols in more light-demanding
species of plants were more responsive to changes in light quality, particularly blue
light. Similarly, blue light advanced spring bud burst in tree species both in the lab
and in the field. We also report that both blue light and UV radiation can advance
autumn leaf senescence in understorey plants. Lastly, when critically comparing the
effect sizes of light quality treatments on phenological responses in trees, we found
that light quality effects on spring phenology are generally small. However, the effects
reported on autumn phenology are much larger. This adds to the complexity of
drivers affecting autumn phenology, and may be one reason why autumn phenology
is typically much harder to forecast compared to spring.
Future work should seek to understand how other environmental drivers such
as temperature will interact with light quality to affect leaf pigments and leaf
phenology. It will be important to understand how climate change could produce
potential phenological mismatches in cues between the canopy and understorey, and
even between different organisms such as plants, herbivores, and pollinators.
7
ACKNOWLEDGEMENTS
I would like to thank my supervisor Matthew Robson. Firstly, for giving me theopportunity to study this topic for a PhD. It would not have been possible to developand complete this project without your supervision. I feel lucky to have had thefreedom to pursue ideas, explore avenues of thought, and to be encouraged to do sofor 4 years.
Thank you Titta for being a great office mate, helping me develop an unhealthyvice for coffee, and introducing the phenomenon of “nakkisuoja”. May it serve me wellin future endeavours. I would also like to thank all of the staff at Lammi BiologicalStation, and in particular John ‘The Phil Jackson” of Lammi, who has been a greathelp over the years, and introduced me to mushroom picking.
To the other PhD students in the Canopy Spectral Ecology and Ecophysiology(CanSEE) Research Group; Saara, Marta, Twinkle and David, thanks for helping withvarious studies, failed or otherwise, throughout the PhD. Thank you to interns Makiand Tom from Lammi Biological Station for your help with fieldwork. Hopefully youhaven’t been scarred by mosquitos. I hope all of you enjoy future success!
Many co-authors have helped revise, sharpen and develop my studies; manythanks to Pedro Aphalo, Line Nybakken, Jakub Nezval, and Luis Morales, as well asmy brother Adam for his help. An important thank you goes to my pre-examiners EvaRosenqvist and Carla Valeria Giordano. My gratitude also goes to Karen Sims-Huopaniemi, for your hard work towards a huge number of PhD students. I wouldalso like to thank my follow-up committee; Paula Elomaa, Markku Larjavaara, andAnders Lindfors for providing motivation and guidance during our annual meetings.My thanks also to the DPPS for funding the PhD position, and to Lammi BiologicalResearch Grant Foundation for providing funding that enabled fieldwork possible.
Lastly, my thanks to all the friends I’ve met whilst doing my PhD in Finland,and to Ulla for putting up with me!
8
9
Contents 1. Introduction .................................................................................. 14
1.1 Phenology................................................................................ 14
1.2 The Light Environment........................................................... 16
1.3 Photoreceptors........................................................................ 19
1.4 Secondary Leaf Pigments ........................................................ 19
1.5 Climate change ....................................................................... 23
1.6 Aims ....................................................................................... 23
2. Materials and Methods ................................................................. 24
2.1 Experimental design ................................................................... 24
2.1.1 Experiment I – Pigments in the Lab ..................................... 24
2.1.2 Experiment II – Phenology in the lab .................................. 26
2.1.3 Experiment IV – Pigments and Phenology in the field......... 27
2.2 Plant Responses.......................................................................... 29
2.2.1 Optical Assessment of Pigments .......................................... 29
2.2.2 Chlorophyll Fluorescence of PSII ........................................ 29
2.2.3 Phenological Observations of Bud Burst and Leaf Senescence ................................................................................... 30
2.3 Environmental variables............................................................. 30
2.3.1 Spectral Irradiance .............................................................. 30
2.3.2 Temperature ........................................................................ 31
2.3.3 Soil Moisture ....................................................................... 31
2.3.4 Radiative transfer modelling ............................................... 31
3. Results and Discussion ................................................................. 33
3.1 CRYs and UVR8 both affect the accumulation of flavonoids in response to UV-A radiation .......................................................... 33
3.2 Blue light advances bud burst in the lab ................................. 35
10
3.3 Light quality influences the seasonal dynamics of flavonoids . 36
3.4 How important is light quality compared to other environmental factors affecting phenology? ................................. 38
3.5 How will climate change affect understorey light interactions? ................................................................................ 41
3.6 Methodological considerations ............................................... 42
3.7 Conclusions and future research............................................. 44
4. References .................................................................................... 45
11
LIST OF ORIGINAL PUBLICATIONS
This thesis is based on the following publications:
I Brelsford, C. C., Morales, L. O., Nezval, J., Kotilainen, T. K., Hartikainen, S.
M., Aphalo, P. J., & Robson, T. M. (2019). Do UV‐A radiation and blue light during
growth prime leaves to cope with acute high light in photoreceptor mutants of
Arabidopsis thaliana? Physiologia Plantarum, 165(3), 537-554.
II Brelsford, C. C., & Robson, T. M. (2018). Blue light advances bud burst in
branches of three deciduous tree species under short-day conditions. Trees, 32(4),
1157-1164.
III Brelsford, C. C., Nybaken, L., Kotilainen, T. K., & Robson, T. M. (2019). The
influence of spectral composition on spring and autumn phenology in trees. Tree
Physiology, 39(6), 925–950.
IV Brelsford, C. C., Trasser, M., Paris, T., Hartikainen, S.M., & Robson, T. M.
(2019). Understorey light quality influences leaf pigments and leaf phenology in
different functional plant types. Manuscript.
The publications are referred to in the text by their Roman numerals.
12
ABBREVIATIONS
CRY1 – cryptochrome 1
CRY2 - cryptochrome 2
CRYs – cryptochrome
Fv/Fm – maximal quantum efficiency of PSII photochemistry
Fq`/Fm` – operating efficiency of PSII photochemistry
LAI – leaf area index
PHOT1 – phototropin 1
PHOT2 – phototropin 2
PHOTs – phototropins
PSII – photosytem II
PHYs – phytochromes
PHYA – phytochrome A
PHYB – phytochrome B
R:FR – red:far-red
SAS – shade avoidance syndrome
UV-A – ultraviolet radiation A
UV-B – ultraviolet radiation B
UVR8 – ultraviolet resistance locus 8
WT – wild type
13
14
1. INTRODUCTION
1.1 PHENOLOGY
Organisms time their life cycle events to exploit natural resources, and ultimately to
successfully reproduce. However, unlike organisms that are able to migrate or travel,
plants are sessile. Because of this, they must sense seasonal changes in environmental
cues, and use them to time life-cycle events to the time of year. For instance, come
springtime, increasing solar radiation, and thus temperature, mean that conditions
for photosynthesis become suitable. As such, annual, perennial and woody plant
species in temperate and boreal regions, time their leaf out in spring to exploit these
conditions which are suitable for photosynthesis (Hänninen 1991; Augspurger
2009; Bennie et al. 2010). Come autumn time, there is a decrease in solar radiation,
and lower temperatures which could cause frost damage. Consequently, deciduous
plants will go through leaf senescence, and remobilize nutrients from leaves, before
shedding their leaves and entering dormancy over winter (Lang 1987, Hänninen
1995; Cesaraccio et al. 2004), before spring returns the next year.
The timing of biological events is known as ‘phenology’. Monitoring
phenology is widely accessible to both the public and scientists alike, and thus plays
an important role in scientific communication (Cooper et al. 2014; Bestelmeyer et al.
2015). Accordingly, it is a commonly used metric for reporting the effects of climate
change (Menzel 2002; Cleland et al. 2007). It has cultural and commercial
importance ranging from records made by Henry David Thoreau in New England, to
the timing of grape ripening in vineyards (Chuine et al. 2004; Primack et al. 2012).
Beyond this, plant phenology determines the length of the growing season, and thus
the period that plants are able to photosynthesise and store carbon. In this respect,
understanding phenology can help inform our predictions of how carb0n
sequestration will be affected by climate change (Peñuelas and Filella, 2009).
What are the major cues governing leaf phenology of plants in temperate and boreal
regions?
For temperate and boreal tree species, the major cues governing bud burst and leaf
out in spring are accumulated chilling temperatures over winter, forcing
temperatures in spring, and to some extent increasing photoperiod (Körner 2007;
Körner and Basler 2010; Caffarra and Donnelly 2011). However, these cues can
interact. If a small amount of chilling has accumulated, then the effect of photoperiod
and forcing temperatures can be greater to compensate for low chilling, so that the
plant may still reach bud burst (Flynn and Wolkovich, 2018). Likewise, if forcing
temperature is low and photoperiod short, then a high amount of chilling during
winter can compensate for this (Flynn and Wolkovich, 2018). For autumn, our
understanding of leaf senescence and bud set is more limited, and it has been aptly
15
named the ‘forgotten season’ with respect to climate change research (Gallinat et al.
2015). A meta-analysis showed that the major cues governing autumn leaf senescence
were October temperatures, cooling degree-days, latitude, photoperiod, and lastly
precipitation (Gill et al. 2015). High latitude sites were also more sensitive to
photoperiod (Gill et al. 2015). Furthermore, there was a different effect of
environmental drivers on leaf fall compared to their effect on the point at which 50%
of leaves had turned yellow (Gill et al. 2015); with latitude having the greatest effect
on the prediction of 50% of leaves turning yellow. This suggests that there may be
different environmental factors governing leaf colouration in autumn, and final leaf
fall. For some tree species, accumulated chilling temperatures have been found to
largely predict the date of leaf senescence, whilst for other tree species photoperiod
can be a better predictor (Delpierre et al. 2009; Vitasse et al. 2011). There is also
experimental evidence that decreasing photoperiod advances leaf senescence in
several tree species (Li et al. 2003; Welling and Palva 2006; Lagercrantz 2009).
How do phenological strategies differ?
Phenological strategies can also differ according to functional strategy. For instance,
it has been proposed that more light-demanding tree species often leaf out earlier,
and that this response is dominated mostly by forcing temperatures rather than
photoperiod (Basler and Körner, 2012). In contrast, species which leaf out later would
be more responsive to photoperiod cues. However, as more recent studies have shown
that different phenological cues can compensate for each other (Flynn and Wokovich,
2018), a more updated synthesis of how different functional types of plants integrate
these cues is needed. Likewise, many herbaceous species and woody species in forest
understoreys exhibit phenological avoidance, whereby they time leaf out earlier than
the canopy trees above, or leaf senescence later in autumn, to exploit periods of light
in the understorey for photosynthesis (Uemura 1994; Augspurger et al. 2005;
Richardson and O’Keefe, 2009). Earlier leaf out in understorey tree species has been
shown to be due to ontogenic factors (Vitasse, 2013), whereas the environmental
drivers that cause leaf out in herbaceous species has been less well studied compared
to tree species, but include snowmelt, and forcing temperatures (Price and Waser
1998; Rice et al. 2018). Elevated temperatures have been shown to advance leaf
senescence in the understorey herb Panax quinquefolius (Jochum et al. 2007). For
some spring ephemeral species, shading has been shown to induce earlier leaf
senescence (Augspurger and Salk, 2017). However, beyond these studies, there is
limited information on the environmental cues which specifically affect leaf
senescence in understorey plant species.
Whilst phenological differences exist between the overstorey and the
understorey, they also vary according to latitude. For autumn phenology, it has been
shown that bud set in ecotypes from higher latitudes is more responsive to
photoperiod (Ekberg et al. 1979, Li et al. 2003). However, for spring phenology this
issue remains contentious, as there is evidence to suggest that bud burst in more
northern ecotypes is more responsive to photoperiod (Vaartaja 1959; Myking and
16
Heide 1995; Robson et al. 2013; reviewed by Way and Montgomery 2015; Cooper et
al. 2018), as well as evidence to suggest that more southern species are more
responsive to photoperiod (Kriebel 1957; Olson et al. 2013; Zohner et al. 2016; Osada
et al. 2018). As such, it is not known whether bud burst of northern ecotypes of trees
is more sensitive to changes in photoperiod, or whether southern ecotypes are more
sensitive.
1.2 THE LIGHT ENVIRONMENT
Not only do the amount of light and day length vary over the course of a year, but also
the light quality. That is to say, the different colours or wavelengths of solar radiation
that a plant receives. There is growing evidence that plants can detect these changes
in light quality throughout the year and adjust their phenology accordingly.
How does the light environment vary over the year?
Light quality changes diurnally over the course of a day, and thus with day length,
latitude, and season. For instance, as solar elevation decreases, and the sun dips
below the horizon, the light quality during this twilight period before night-time
changes substantially. There is a drop in the ratio of red light relative to far-red light,
known as the R:FR ratio (Figure 1) (Robertson 1966; Smith 1982; Chambers and
Spence 1984; Hughes et al. 1984). This is because the lower elevation of the sun means
that longer wavelengths of FR light are refracted over the horizon and are thus
enriched during twilight hours (Smith 1982). Whereas the ratio of blue to red light
(B:R) increases during twilight (Johnson et al. 1967, Hughes et al. 1984). This is due
to the Chappuis bands in the ozone, which preferentially absorb red light, and also
because blue light is scattered across the sky to a greater extent than red light
(Hulburt 1953; Johnsen 2012). Of course, overall irradiance also changes drastically
over the course of a day, being higher at noon, along with the proportion of ultraviolet-
B (UV-B) radiation. Atmospheric conditions such as cloud cover and water vapour
can affect the composition of solar radiation reaching the ground as well. For
example, cloud cover can increase the amount of diffuse radiation, thus
proportionally enriching blue and UV radiation in comparison to total PAR (Urban et
al. 2007; Dengel et al. 2015). Furthermore, water vapour in the atmosphere has also
been suggested to be responsible for a peak in R:FR which is sometimes observed
during sunrise and sunset (Lee and Downum, 1991). Changes in ozone also lead to
changes in the amount of UV radiation reaching the ground, and areas where the
ozone is thinnest are around the equatorial belt, and also lead to the highest
irradiances of UV-B radiation there (Caldwell et al. 1980; Blumthaler et al. 1997;
McKenzie et al. 2001a; 2001b).
17
Figure 1. A schematic showing changes in light quality that occur diurnally, and thus vary with day length across the year.
Light quality affects phenology
Evidence is also amounting that shows plants respond to these temporal changes in light quality. For example, low R:FR during twilight has been shown to advance bud burst in Betula pendula (Linkosalo and Lechowiz, 2006), as well as delay bud set in P. abies (Mølmann et al. 2006). In this sense, changes in the duration of low R:FR during twilight hours, aid the perception of changes in photoperiod. Similarly, day length extensions with blue light have also been shown to delay bud set in P. abies, albeit not as effectively as low R:FR (Mølmann et al. 2006). Furthermore, UV-B radiation has been shown to advance bud-set in P. tremula (Strømme et al. 2015). Whilst these studies show that light quality can affect phenology, there is a lack of information on the response of bud burst to blue light, as well as leaf senescence in response to blue light and UV radiation.
How does light environment vary in the understorey?
Light quality not only varies temporally, but also spatially. Underneath canopies, there is a reduction in overall irradiance and photosynthetically active radiation (PAR), as well as a low R:FR ratio (Figure 2) (Ballaré and Pierik 2017). The low R:FR
18
ratio is produced because FR light is scattered by vegetation to a greater extent than red light, and so is enriched in the understorey (Ballaré et al. 1987). Similarly, blue light is absorbed by the canopy and so also becomes greatly depleted in the forest understorey (Casal 2013). UV radiation is also absorbed by the canopy, but because UV radiation is more diffuse, it scatters through the understorey, and so is proportionally enriched compared to the amount of PAR (Flint and Caldwell 1998, Grant et al. 2005). In response to low R:FR light, plants exhibit a shade avoidance syndrome (SAS, Ballaré et al. 1987), whereby they induce hypocotyl extension to outcompete neighbouring vegetation by growing towards light. Similarly, it has also been shown that blue light and UV radiation negatively regulate this response, i.e. high blue or UV radiation downregulates SAS (Casal 2013, Fraser et al. 2016).
Whilst the role of light quality in SAS response has been well studied, the effects of understorey light quality on plants where shade-avoidance is absent and would be detrimental are largely unknown. Lee et al. (2003) observed that understorey shade delayed leaf senescence in understorey woody species but found that R:FR had no effect. This suggests that other regions of the solar spectrum, or overall irradiance, are responsible for this phenological response in understorey woody species.
Figure 2. A schematic demonstrating changes in understorey light quality that occur from canopy opening and canopy closure.
19
1.3 PHOTORECEPTORS
Photoreceptors enable plants to detect changes in the composition of solar radiation.
This is important to plants, because it allows them to adjust their development and
growth to suit their particular environment. For instance, seed-germination,
flowering, stem elongation, and organelle movement are all affected by light quality
(Kong and Okajima, 2016). Plants are able to detect and integrate different light cues
because they are equipped with an array of photoreceptors to detect different regions
of light. Phytochromes (PHYs) are R:FR-detecting photoreceptors, and are
synthesized in the dark in their red light absorbing form (Pr, λ = 660 nm). When
exposed to light, they are converted to their far-red light absorbing form (Pfr,
λ = 730 nm; Smith 1982; Smith and Morgan 1983). The two main groups of
photoreceptors that underpin blue and UV-A responses are cryptochromes (CRYs)
and phototropins (PHOTs) (Casal 2000; Briggs and Christie 2002). Lastly, the UVR8
photoreceptor underpins responses to UV-B, and possibly some responses to UV-A
(Rizzini et al. 2011; Morales et al. 2013).
1.4 SECONDARY LEAF PIGMENTS
Function and response
Plants also modulate the concentration and content of secondary leaf pigments in
response to changes in light intensity and light quality. Flavonoids are a group of
photoprotective pigments which screen UV radiation, and reduce ROS stress,
although to varying degrees based upon the particular composition of these
compounds (Agati and Tattini 2010). Carotenoids and xanthophylls also play
important roles in photoprotection, by dissipating excess light energy produced from
photoinhibition of PSII (Young, 1991; Middleton and Teramura 1993). CRYS govern
the accumulation of flavonoids in response to blue and UV-A radiation, and UVR8
governs the accumulation of flavonoids in response to UV-A and UV-B radiation
(Christie and Jenkins 1996; Fuglevand et al. 1996; Morales et al. 2013; Rai et al. 2019).
Biochemistry
Flavonoids are present throughout the plant kingdom. They are synthesized from p-
coumaroyl-CoA with three malonyl-CoA molecules by a chalcone synthase (Roy et al.
2016). This in turn produces a flavonone with a 2-phenylchroman backbone. This 2-
phenylchromen backbone gives rise to flavonols, isoflavonoids, flavones and
anthocyanidins in the phenylpropanoid pathway (Stafford, 1991). The different
carbons of the flavonoid skeleton can be substituted and catalysed by isomerases,
reductases, hydroxylases, methylases and glycosyltransferases (Harborne and
Williams, 2001; Ferrer et al., 2008). In turn, these changes lead to a high structural
20
diversity of flavonoids, which modifies the solubility, stability, antioxidant activity,
UV-screening and compartmentalisation (Roy et al. 2016) (see Figure 3).
Flavonoids can be sub-divided into two major groups: anthocyanins and
flavonols (Agati et al. 2012). Flavonols tend to have higher UV screening ability,
whereas both flavonols and anthocyanins possess antioxidant activity (Liakoura et al.
2003). Sun-exposed leaves of plants normally have higher amounts of flavonols
compared to shaded leaves (Liakoura et al. 2003; Wang et al. 2012). In many plant
species the accumulation of anthocyanins in leaves occurs during senescence in
autumn (Feild et al. 2001; Lee 2003; Hoch et al. 2003). Shading has been found to
delay the autumnal increase in anthocyanins (Lee et al. 2003), however similarly to
its effect on leaf senescence, it is unsure whether there is a particular region of the
spectrum underpinning this response, or whether it is a response to reduced
irradiance (Lee et al. 2003).
Figure 3. The phenylpropanoid pathway leading to the production of different
flavonols and anthocyanins.
Location in the leaf
Flavonoid location can vary within the leaf, and between different plant structures.
For instance, there is large accumulation of flavonoids in external appendages, such
as trichomes (Rozema et al. 1997). This is consistent with the role of surface
flavonoids primarily as effective UV-B absorbers and anti-herbivory agents (Rozema
et al. 1997; Close and McArthur 2002). The composition of flavonoids can also vary
21
between locations. More than 90% of the total flavonoids pool which is distributed in
the nucleus, chloroplast, and vacuole of mesophyll cells, comprises compounds which
have higher anti-oxidant properties (Brunetti et al. 2018). Whereas monohydroxy-
substituted flavonoids, which are poor antioxidants, are mostly located in the adaxial
epidermal cells of shade-adapted plants (Brunetti et al. 2018).
The location within the cell of UV-screening compounds such as flavonoids
can differ between different plant species. For example, it has been shown that two
species of Antarctic moss have different strategies relating to the location of their UV-
screening compounds (Clarke and Robinson, 2008). Byrum pseudotriquestrum has
equal proportions of cell-wall-bound and –unbound UV-screening compounds. In
comparison the moss Ceratodon purpureus has a smaller proportion of cell-wall-
bound UV-screening compounds. Similarly, the deciduous Vaccinium vitis-idaea has
much more substantial cell-wall flavonoids in comparison to flavonoids throughout
the rest of the leaf (Day 1993; Semerdjieva et al. 2003). A member of the same genus,
the evergreen Vaccinium mytrillus, has no cell-wall-bound flavonoids at all
(Semerdjieva et al. 2003). Furthermore, different growth forms within the same
species can even differ in the location of their flavonoids. The red growth form of C.
purpureus has a higher concentration of cell-wall-bound UV-screening compounds
in comparison to the green growth form (Waterman et al. 2018). Considered together,
we can expect that not only do different plant species have different flavonoid
locations, but also different plant growth forms may also differ in the location of their
flavonoids.
Seasonal variation of flavonoids
Plants must optimise the accumulation of flavonoids throughout the seasons. Leaves
of Vaccinium vitis-idaea have higher flavonols and anthocyanins after snowmelt in
early spring (Solanki et al. 2019). Leaves beneath the snowpack, which are insulated
from colder temperatures and higher irradiance, have lower flavonoid content. In
comparison, after snowmelt in spring, leaves are exposed to high irradiance and low
temperatures, and so higher flavonoids can provide both better UV-screening
capabilities and higher antioxidant activity. Further into summer, with increasing
temperature, flavonoids of V. vitis-idaea begin to decrease (Solanki et al. 2019). The
composition of flavonoids can also change throughout the year. For example, in
walnut (Juglans regia), the flavonoids catechin and myricetin increase from spring
up until August (Solar et al. 2006). In contrast, phenolic acids were highest in spring
and lowest in summer. It has also been shown that for B. pendula and A. glutinosa,
flavonoids are highest in early summer, and decrease towards the end of the season
(Kotilainen et al. 2010). Not only do abiotic variables such as temperature and solar
radiation affect the seasonal dynamics in phenolic profiles in walnut, but pathogens
such as blight (Xanthomonas campestris pv. juglandis) also affect the seasonal
dynamics of flavonoids (Solar et al. 2006).
22
For many plant species, leaf anthocyanins have been shown to increase in
autumn, giving characteristically red colours. In contrast, yellow colouration comes
from yellow carotenoid pigments which become visible after the degradation of
chlorophyll (Goodwin, 1958). There are many hypotheses as to why anthocyanins
increase in autumn. These include: reducing photoinhibition and ROS generated at
low temperatures under which light-saturation more easily occurs; as a red
colouration signal to prevent herbivory; and to provide protection against pathogens
(review by Wilkinson et al. 2002). Perhaps, most aptly, Gould (2004) described
anthocyanins as “Nature’s Swiss army knife”, in relation to the cross-tolerance they
provide against a number of different environmental stressors. Interestingly, only
recently was it shown that flavonols in the leaves of Sorbus aucuparia and Betula
pendula increase in autumn, just before and during leaf senescence (Mattila et al.
2018).
Leaf pigments in forest understories
Flavonoids can vary in space as well as time. When forest canopies leaf out in spring,
the understorey becomes covered in shade. Shade has been shown to reduce flavonoid
content in several plant species (Liakoura et al. 2003; Wang et al. 2012).
Furthermore, the flavonoids in plant leaves in the forest understorey have important
interactions within the forest understorey ecosystem. For instance, leaves of
understorey shrub species growing in high light conditions have higher
concentrations of defence metabolites such as flavonoids, and are less damaged by
folivorous insects (Karolewski et al. 2013). Flavonoids in leaves that senesce in
autumn can inhibit litter decomposition via collembola (Das and Joy, 2009).
Although flavonoids are important physiologically, and affect ecosystem processes,
there are no studies we are aware of demonstrating how light quality in the forest
understorey affects their seasonal dynamics.
Functional strategies
Relatively little is known about how functional types of plants differ in their flavonoid
response to different light treatments, and which environmental cues are the most
important in determining variation in their seasonal flavonols. Most evidence
suggests that epidermal UV-screening is highest in evergreen plants, intermediate in
woody plants and lowest in herbaceous plants (Day et al. 1992; Day 1993; Semerdjieva
et al. 2003; Li et al. 2010). In contrast, a study comparing different plant growth
forms in a subtropical alpine area found no difference between the UV-screening
ability of woody plants and herbaceous plants (Barnes et al. 2017). Thus, there is a
need to investigate whether there are any differences in UV-screening among plant
functional types.
23
1.5 CLIMATE CHANGE
Different understorey plants adopt different light strategies in the forest understorey.
For instance, some may emerge in early spring, or remain in late autumn to exploit
periods of light availability whilst the canopy is open (Kudo et al. 2008; Richardson
and O’Keefe 2009). Conversely, shade-tolerant plants may adopt a strategy to not
invest resources during periods of light availability in spring and autumn, but to
photosynthesise at a steady rate during canopy closure whilst they are covered in
shade (Augspurger et al. 2005; Heberling et al. 2019). These strategies may also
dictate not only when plants time their leaf emergence and leaf senescence in the
forest understorey, but also when they invest in the accumulation of flavonoids in
their leaves, and how much they invest.
Climate change is increasing the period of canopy duration (Vitasse et al.
2009), and so these interactions between the overstorey and understorey may be
becoming unhinged. Already it has been shown that the canopy is leafing out at a
faster rate than the forest understory, and so understorey plants will be at risk of lower
carbon capture throughout the year (Heberling et al. 2019). However, it is not certain
how the change in light quality that this will bring throughout the year will affect
different functional types of plants. Regions in the blue and UV part of the solar
spectrum have received little attention thus far. How these changes will affect leaf out
and leaf senescence in different understorey species, and how it will affect their leaf
pigmentation throughout the year is not comprehensively understood.
1.6 AIMS
Our aim was to combine three approaches of literature review, controlled laboratory
studies, and field experiments to answer the following questions:
Which photoreceptors regulate flavonoids in response to low irradiance blue and UV-
A radiation? (I)
How does blue light affect spring bud burst under controlled conditions? (II)
Does light quality influence leaf phenology and leaf pigments throughout spring and
autumn? (IV)
How important is light quality as a phenological cue, compared to other
environmental drivers? (III)
24
2. MATERIALS AND METHODS
To allow easy comparison between the results, I took a consistent approach where
possible to address the aims of my dissertation across multiple experiments and
papers. To show the overlap between them, I list the main methods and devices used
across the paper in Table 1 below.
Table 1. Table summarising which studies used which methods.
Plant response variables
(main device used)
Publications
Optical assessment of pigments
(Dualex)
I, II, IV
Chlorophyll fluorescence of PSII
(mini-PAM)
I, IV
Phenological observations of
bud burst and leaf senescence
I, II, IV
Environmental variables
Spectral irradiance
(Spectroradiometer)
I, II, IV
Temperature
(ibutton sensors)
I, II, IV
Soil moisture
(time domain reflectometer [TDR] probe)
IV
Radiative transfer modelling
(libadtran)
III
2.1 EXPERIMENTAL DESIGN
2.1.1 EXPERIMENT I – PIGMENTS IN THE LAB
Plant material
Arabidopsis thaliana in the background accession of Landsberg erecta were used,
and all genotypes were sourced from seeds of plants grown under standard growth
conditions in Viikki greenhouses, Helsinki. We used the following photoreceptor
mutants: phot1 (Inada et al. 2004), cry1 and cry2 (Mazzella et al. 2001), and uvr8‐2
(Brown et al. 2005).
25
Five seeds per pot (6 x 6 cm) were sown into well-soaked 1:1 pre-fertilised peat
to vermiculite (Agra‐vermiculite; Pull Rhenen, TX Rhenen, the Netherlands). A thin
layer of peat, sieved through a 2 mm gauge, was added to provide a smooth even
surface for germinating seeds. Following this, pots were placed for 1 day in the dark
at 15˚C to allow seeds to become imbibed. Then they were placed under light
treatment conditions for 3 days at 5°C day/2°C night for cold stratification.
Temperature was then increased to approximate spring temperatures for northern
temperate latitudes (15°C day/10°C night). Water vapour pressure deficit was
0.17 kPa day/0.18 kPa night for germination and growth.
When the first pair of true leaves became visible, seedlings were thinned so
that there was one seedling per pot. In total, this left 288 plants in the experiment.
Plants were given 50ml of tap water per pot every 5-7 days. Pots were also rotated
within compartments to reduce any unknown gradients in temperature, relative
humidity and irradiance.
Light treatments – Growing conditions and high-light conditions
This experiment consisted of two phases: growth conditions and high-light
conditions. For growth conditions, six compartments of equal size were used inside a
temperature-controlled growth room. Each compartment was of equal size (97 cm
wide x 57 cm deep x 57 cm high). The six compartments were arranged into three
blocks, with each block consisting of two compartments. Each was randomly allocated
a light treatment, either a broad-spectrum LED containing blue light, or a broad
spectrum LED with blue light filtered out (attenuated). These lamps were Valoya
AP67, 400–750 nm, PAR 168 μmol m−2 s−1 plus 32 μmol m−2 s−1 FR, (Helsinki,
Finland) and in the other three compartments blue light was attenuated by wrapping
film Rosco #313 Canary Yellow (Westlighting, Helsinki, Finland) around the LED
lamps. The difference in PAR this created between the treatments was adjusted for by
controlling the height of the lamps, so that PAR was homogenous between
compartments. Each compartment was protected from outside light entering the
compartment by using white-black plastic film that blocked both visible and UV
radiation. The number of plastic sheets used was also adjusted to ensure equal
temperature between compartments. Each compartment was also given a split-plot,
with one half of the compartment having a UV-A treatment (LED arrays with peak
emission at 365 nm (mean and SE of 15.0 ± 0.6 μmol m−2 s−1: Z1‐Z1‐10UV00, LED
Engin, San Jose, CA)). UV-A was filtered out of the other half of the compartment
using Rosco #226 (Westlighting) which attenuated all wavelengths below 400 nm.
The irradiance and ratio of blue light:UV-A in the experiment was the same as that
measured under canopy shade of a B. pendula stand at Lammi Biological station
(Table S3 supplementary material, I). To reflect more realistic spring conditions, a
10-hour photoperiod was used, and UV-A treatment was applied for 4 hours centred
around noon, when UV radiation is its highest during the day (Flint and Caldwell
1998).
26
For high-light treatments, half of the plants in each treatment combination
were randomly allocated to receive high light. High light treatments were made at
midday in winter in a temperature-controlled greenhouse (25°C air temperature).
Almost no natural light entered the greenhouse and ambient light was through high-
pressure sodium (HPS) growth lights. The high light treatments were provided by
Osram Powerstar HQI‐E 400 W/D stadium lamps (Osram GmbH, Munich,
Germany). They were warmed up for at least 1 hour prior to treatment, to ensure
emission was stable. 75 mm-deep baths of flowing cold water were placed between
the lamps and plants to serve as a heat sink to reduce the warming effect of the lamps.
Plants were kept under high light treatment for exactly 30 minutes, directly following
transfer from the growth room, and were returned to the growth room immediately
after the measurements. Photon irradiance incident on the leaves of plants receiving
the high‐light treatment was 1800–2100 μmol−1 m−2 s−1 PAR and the incident
temperature measured on the leaves was about 35°C.
2.1.2 EXPERIMENT II – PHENOLOGY IN THE LAB
Plant material
We collected dormant branches of Alnus glutinosa, B. pendula, and Quercus robur
from local populations which were co-occurring in a natural forest stand in southern
Finland (60°13′04.2″N, 25°00′31.0″E). The branches were cut from lower canopy
branches on trees (2-3 m above ground) with sterile garden secateurs on 6th February
2017. We sampled from eight trees per species, and collected 10-15 branches from
each tree, making sure that each branch was dormant, free of pests and free of disease
symptoms. Several studies have exemplified the reliability of this method (Basler and
Körner 2012; Laube et al. 2014; Polgar et al 2014; Vitasse and Basler 2014; Primack
et al. 2015). We followed a similar protocol, whereby we placed the cut end of the
dormant branches into test tubes of water immediately after being re-cut, and
continuously monitored stages of their bud development.
Prior to sampling, trees received 111 chilling days, calculated as the number of
days from the 1st of November the previous year, with a mean temperature ≤5°C
(Murray et al. 1989). All trees were facing the east side of a mixed forest stand, and
branches that were receiving sunshine for the majority of the day were selected. All
branches presented at least five buds including the terminal bud. Subsequently, the
branches were immediately taken to the greenhouse into an ambient temperature
room (0˚C). Here, they were re-cut so that all branches were of a similar length
(28.35 ± 0.34 cm (mean ± SE)). Immediately after this they were placed into sterile
clear plastic tubes (10.26 cm long, 15 ml volume) which were then filled with tap
water.
27
Light treatments
Branches were moved into a temperature-controlled growth room with six
compartments (97 cm wide x 57 cm deep x 57 cm high). The branches were randomly
assigned into each compartment, with each compartment having 16 branches of Q.
robur, 20 of B. pendula, and 16 of A. glutinosa. Test tubes were rotated in the
compartments every 2 days, avoiding any bias coming from unknown microclimatic
variation. Lights were kept the same distance from branches in every compartment.
Three compartments were randomly allocated to receive a blue light LED
spectrum (Valoya AP67, 400–750 nm, Table S1: mean PAR among compartments of
161 ± ≤ 10 µmol m−2 s−1, plus 28 µmol m−2 s−1 far red). Another three compartments
were allocated to receive a no blue treatment, in which blue light was filtered out from
the broad-spectrum lamps using Rosco #313 Canary Yellow (Westlighting, Helsinki,
Finland, PAR 156 ± ≤ 10 µmol m−2 s−1, plus 31 µmol m−2 s−1 far red). A 12h photoperiod
was used to simulate similar photoperiod conditions at the beginning of spring in
southern Finland (60°13′04.2″N 25°00′31.0″E).
2.1.3 EXPERIMENT IV – PIGMENTS AND PHENOLOGY IN THE FIELD
Site information and climate
The experiment was conducted in the grounds of Lammi Biological station (61.05°N,
25.05°E). Average mean monthly temperature is 5.1°C and average mean monthly
precipitation was 47.7 mm between 2017 and 2018.
Plot design
Experimental plots were set up underneath two stand types: the first type being
deciduous stands dominated by B. pendula or Q. robur, and the second type being an
evergreen stand of P. abies. We set up nine split-plots in the deciduous stands, and
six plots in the evergreen stand. The plots were established according to space that
was available in the forest understorey. Plots were adjacent to areas chosen by
Hartikainen et al. (2018), and with similar spacing, architecture, light and LAI (IV,
supplementary material).
Each plot was split into four filter treatments which attenuated different
regions of the solar spectrum. These were made from polycarbonate (Foiltek Oy,
Vantaa, Finland). This consisted of a control filter which was transparent to all
wavelengths of solar radiation (PLEXIGLAS 2458 GT SOLARIUMLAATU), a filter
attenuating UV radiation below 350 nm (PLEXIGLAS 0Z023), a filter attenuating all
UV radiation (ARLA MAKROLIFE), and a filter attenuating blue light and all UV
radiation (PLEXIGLAS 1C33 (303)). Thus, any differences between the blue and the
UV treatments can be attributed to the effect of blue light. Every filter had the same
dimensions (88 cm length x 60 cm width x 40 cm height). Each filter was placed so
28
that the longest side faced south. Protocol was followed according to Aphalo et al.
(2012), whereby a 10-cm border inside each filter was excluded, leaving a central area
inside where plants were measured, thus avoiding any edge effects. Air flow was
facilitated by raising the filters 10 cm by placing them on wooden blocks, and via a
gap at the top of the north-facing panel. Every filter was randomly assigned a position
within each plot.
Selection of understorey species
We used both volunteer plant species already growing beneath the installed filters,
and transplanted plant species from within the same stand type, canopy architecture,
and stand spacing, underneath the filters. This enabled us to capture responses from
different functional plant types represented in the forest understoreys at our field site
in southern Finland. Germinating seedlings of Acer platanoides were transplanted in
2016 a year prior to the experiment. At the end of 2017, the 1st year of the experiment,
germinating acorns of Q. robur were transplanted under the filters. Volunteer plants
of the following species were also used: Oxalis acetosella, Fragaria vesca,
Aegopodium podagraria, Anemone nemorosa, Maianthemum bifolium, and
Ranunculus cassubicus. A. podagararia, R. cassubicus, and Q. robur were only
present in deciduous stands, and M. bifolium was only present in the evergreen stand.
Care of plots
Size, reproductive status, and time of year, were similar for all plants that were
transplanted (April 2016 following snowmelt for A. platanoides, and September 2017
for Q. robur). During transplanting, original vegetation in the plot was left intact as
much as possible. Four transplants of A. platanoides were placed under each filter,
and four transplants of Q. robur under each filter in deciduous stands, because this
was the only stand type where Q. robur seedlings were naturally occurring.
Filters reduced precipitation reaching the ground beneath, so additional
watering was given to plants every 3 days. Soil moisture of plots was monitored with
a TDR probe (SM200 Moisture Sensor with HH2 Moisture Meter, Delta-T Devices,
Cambridge, UK), ensuring that watering was consistent between treatments.
Temperature was an average of 0.3°C higher under filters compared to understorey
ambient conditions, but was consistent between treatments.
29
2.2 PLANT RESPONSES
2.2.1 OPTICAL ASSESSMENT OF PIGMENTS
A Dualex Scientific+ (Force-A TM, Paris, France) was used for non-destructive in vivo
measurements of leaf pigments, derived from their optical properties. Chlorophyll
content in the leaf is calculated by the Dualex, based on the difference in leaf
transmission at 710nm and 850nm, compared with transmission at 650nm (Cerovic
et al. 2012). Relative leaf adaxial-epidermal UV-A absorbance (flavonol content) at
375nm is calculated by the Dualex, derived from chlorophyll fluorescence at 375nm
and 650nm, whilst also accounting for chlorophyll content. Relative leaf adaxial-
epidermal absorbance at 515nm, measuring anthocyanin content, was calculated by
the Dualex, derived from chlorophyll fluorescence at 375nm and 650nm, whilst also
accounting for chlorophyll content.
2.2.2 CHLOROPHYLL FLUORESCENCE OF PSII
Chlorophyll fluorescence was used a diagnostic tool to assess the efficiency of PSII,
and whether any damage to PSII may have occurred. This was measured with a PAM
fluorometer (mini-PAM, Heinz-Walz GmbH, Effeltrich, Germany). We used ϕPSII
(calculated as Fq`/Fm`; Murchie and Lawson 2013) as an indicator of the operating
efficiency of PSII. Electron transport rate (ETR) was also calculated assuming a leaf
absorption of 0.84 and an even energy partitioning between PSII and PSI using the
equation from (Maxwell and Johnson 2000; Murchie and Lawson 2013):
ETR = ΦPSII × absorbed PAR× (0.5)
To assess damage to PSII, Fv/Fm of all plants was measured from the same
leaves as ϕPSII measurements, after they had been dark-adapted for at least 30 min
immediately follow each measurement of ϕPSII, in the growth room (I) or field (IV).
Non-photochemical quenching (NPQ) was also calculated from pairs of
measurements of Fv/Fm and ϕPSII from the same leaves (Maxwell and Johnson
2000).
NPQ = (Fm−Fm`)/Fm`
In the growth room (I), chlorophyll fluorescence measurements were
performed: (1) before the high light treatments to assess baseline response to the
spectral irradiance treatments during growth; (2) during and immediately after the
high-light treatments to assess photoinhibition and photodamage resulting from
excess irradiance; and (3) following a period of recovery from the high-light
treatments. Fully expanded horizontal Arabidopsis leaves that were fully exposed to
30
the light treatments and were large enough to hold a leaf clip went through these same
measurements. The same leaves were used for the Dualex measurements.
In the forest stands (IV), only Fv/Fm was measured on fully expanded leaves
of A. platanoides on two consecutive sunny days in late June, to assess baseline
effects on growth under spectral-irradiance treatments which attenuated different
regions of solar radiation. Leaves of the same age and size, and similar exposure to
sunlight, were chosen for measurement.
2.2.3 PHENOLOGICAL OBSERVATIONS OF BUD BURST AND LEAF SENESCENCE
Bud burst and leaf out of tree species was measured every 2-3 days along a scale of 1-
7 adapted from Teissier du Cros et al. (1981), whereby 1 = dormant, 2 = bud swelling,
3 = bud split, 4 = leaf tip protruding, 5 = leaf mostly out, 6 = leaf out but not fully
expanded, and 7 = fully expanded leaves. For the herbaceous species, emergence of
new leaves was measured once a week as 1 = shoot visible, 2 = expanded leaf. Leaf
senescence for all tree and herbaceous species was measured on a scale of 1-5,
whereby 1 = fully green, 2 = starting to yellow, 3 = mostly yellow, 4 = turning brown,
5 = all leaves fallen. Leaf senescence was measured for all the leaves on each plant
every 2 weeks.
2.3 ENVIRONMENTAL VARIABLES
2.3.1 SPECTRAL IRRADIANCE
Spectral irradiance was measured with a portable CCD array spectroradiometer Maya
2000 pro (Ocean Optics, Dunedin, FL, USA) with a D7-H-SMA cosine diffuser
(Bentham Instruments Ltd., Reading, UK) with spectral range of 200-1100 nm.
Calibration was done by the Finnish Radiation and Nuclear Safety Authority (Aphalo,
2017; Ylianttila et al. 2005). The integration time was set manually to provide
maximum resolution without saturating the array. Each measurement was
immediately followed by one measurement with a polycarbonate filter (attenuating
UV radiation) to correct for stray radiation on the array in the UV range, and one dark
signal measurement blocking all UV and visible radiation, to account for
temperature-dependent noise (details in Aphalo 2017). The diffusor was aligned
horizontally, and the spectrometer was wrapped with a white cotton cloth to decrease
the exchange of radiation between the spectrometer and its environment, (e.g.
reducing any increase in the temperature of the spectroradiometer caused by direct
heating by sunlight).
31
2.3.2 TEMPERATURE
Temperature was continuously monitored with iButton sensors (Maxim Integrated,
San Jose, CA), which were set to 0.065 °C resolution, and recorded temperature
integrated over 10-minute intervals. Heat shields made from duct tape were used to
block any direct solar radiation hitting the iButton causing it to directly heat up, as
opposed to measuring ambient temperature. Data from iButtons were downloaded
once every two months, and then wiped, to prevent the iButtons memory running out.
2.3.3 SOIL MOISTURE
The soil moisture in the plot was also monitored with a TDR probe (SM200 Moisture
Sensor with HH2 Moisture Meter, Delta-T Devices, Cambridge, UK). Soil moisture at
0-15-cm depth was recorded three times inside each filter for experiment IV, and
three times for soil conditions with no filter in each plot.
2.3.4 RADIATIVE TRANSFER MODELLING
To calculate solar angles and solar noon for different locations, we used the
photobiology packages in R (Aphalo, 2016). Twilight length was defined as civil
twilight, including solar angles from -6° and 0°. From this information, libRadtran
was used to simulate spectral composition at solar angles of -6° and at solar noon for
the spring equinox, summer solstice, autumn equinox, and winter solstice, across the
locations of Oulu, Helsinki and Madrid, spanning the range of latitudes covered in
publication III.
libRadtran is a library of radiative transfer equations that allows solar
radiation to be simulated at different locations and solar angles. There are different
models of radiative transfer available, each presenting their own advantages. For
example, the TUV model provides a simpler but more rapid calculator for spectral
composition over a shorter wavelength range (150 nm-750 nm) (Madronich et al.
1997). libRadtran, in contrast, has the advantage that it can calculate any wavelength
between 120 nm-100,000 nm (Brelsford, 2017). To incorporate changes in FR light,
as well as other spectral regions, we chose to use libRadtran.
In particular, we used the uvspec model from libRadtran, version 2.0.1,
radiative transfer package (Emde et al., 2016). The uvspec model allows for the
calculation of the radiation field in the Earth’s atmosphere, accounting for
atmospheric composition, including parameters such as water vapour and ozone
column. The absorption and scattering of solar radiation based on these constituents
of the atmosphere are taken from algorithms and databases provided in the
libRadtran package.
32
The parameters that we adjusted in our model were total ozone column and
column-integrated water vapour. We used the DISORT radiative transfer solver
(Stamnes et al. 1988) for daytime irradiance, and the SDISORT solver for twilight
solar angles, which includes pseudospherical geometry to account for the curvature
of the Earth (Dahlback and Stamnes, 1991). Water column data was taken from
Kållberg et al. (2005), and ozone column thickness data from Experimental Studies
Unit, Environment Canada (http://exp-studies.tor.ec.gc.ca/e/index.htm)
For constructing figures, ratios of spectral integrals were defined as follows:
B:R (410-500 nm/610-700 nm, Johnson et al. 1967); R:FR (650–670/720 nm–740
nm, Sellaro et al. 2010); and R:FR (655–665 nm/725–735 nm, Smith, 1982). Spectral
regions were defined as follows: blue light (420–490 nm); UV-A radiation (315-
400 nm); and UV-B (280–315 nm). Figures were then produced from irradiance data
using photobiology packages in R (Aphalo, 2015).
33
3. RESULTS AND DISCUSSION
3.1 CRYS AND UVR8 BOTH AFFECT THE ACCUMULATION OF FLAVONOIDS IN RESPONSE TO UV-A RADIATION
By combining laboratory and field manipulations, here we are able to show that light
quality affects pigment accumulation throughout spring and autumn (I, IV).
Although, as demonstrated by our field manipulations (IV), the extent of this
response is dependent on the specific plant functional type, or species, being
considered. Controlled laboratory experiments using the model species A. thaliana
point to a significant role of CRYs and UVR8 regulating the response of seasonal
variation in flavonols to changes in blue and UV radiation (I).
Using controlled laboratory conditions simulating understorey UV-A: BL, we
found that CRYs affect the accumulation of flavonol content. The cry1cry2 mutant
had the lowest flavonol content of all mutants when grown under blue light (24.5%
lower in comparison to WT). Similarly, blue light increased flavonol content in all
genotypes apart from cry1cry2. The effects of blue light on phenolic content
quantified from leaf extracts were generally consistent with the optically assessed
flavonol content, however this trend was not as consistent across genotypes.
Typically, studies reporting large increases in the accumulation of phenolic
compounds and flavonoids in response to blue light have either used solar blue light
(Siipola et al. 2015), or controlled conditions using high irradiances (Hoffmann et al.
2015; Taulavuori et al. 2015). Surprisingly, we found that in the absence of blue light,
phot1 mutants had lower flavonol content. However, it is not certain to what extent
this effect would be pleiotropic or not, and to what extent PHOT1 affects the
constitutive levels of flavonols in the absence of blue light.
Interestingly, growth under UV-A caused a decrease in epidermal flavonol
content in cry1cry2 and uvr8-2 mutants, although did not alter flavonol content in
WT. Nevertheless, this suggests that CRYs and UVR8 are involved in the regulation
of flavonols in response to UV-A (Figure 4). In contrast to our results, previous solar
UV-A attenuation studies conducted outdoors have reported an increase in flavonols
in response to UV-A (Ibdah eh et al. 2002; Kotilainen et al. 2008; Kotilainen et al.
2009; Morales et al. 2013). There are several possible explanations for this apparent
discrepancy between our findings and those of previous studies. 1) We used a UV-A
LED source with a narrow band centred around 365nm, whereas the majority of UV-
A studies using lamps/solar UV-A have a broader spectrum (Joshi et al. 2007;
Victorio et al. 2011; Štroch et al. 2015). 2) There may be overlap at different
regions/different photoreceptor interactions e.g. Rai et al. (2019). 3) Not increasing
flavonol content in response to UV-A, and allowing transmittance to the chloroplasts
of non-damaging amounts of UV-A may in fact be useful to the plant. UV-A can be
absorbed by chlorophyll and induce chlorophyll fluorescence (McCree 1981; Lang et
al. 1991), and thus may be utilised for photosynthesis (Bilger et al. 2007; Turnbull et
34
al. 2013). This could be especially relevant for understorey shade environments, where there is a limited amount of light and UV-A irradiance is unlikely to be high enough to induce stress or photodamage (Štroch et al. 2015; Casal 2013), and is proportionally enriched in comparison to PAR (Flint and Caldwell 1998; Leuchner et al. 2011; Urban et al. 2012; Dengel et al. 2015).
Figure 4. A schematic representation of the pathways which affect the accumulation of epidermal flavonol content in response to UV-A and blue light, as well as the effect of blue light and high light on the Fv/Fm of PSII.
We assessed the recovery of Fv/Fm as a measure of resistance to high light stress. In contrast to other studies (Goins et al. 1997; Matsuda et al. 2004; Terfa et al. 2013; Hoffmann et al. 2015; Štroch et al. 2015), we did not find a role for UV-A or blue light in improving resistance to high light stress under controlled conditions for mutants of A. thaliana. Similarly, although other studies have described a role for flavonoids in providing photoprotection and antioxidant properties which can improve Fv/Fm in response to stress (Wargent et al. 2011; Klem et al. 2015; Robson et al. 2015), we found no correlation between flavonoids and Fv/Fm. However, our results do suggest a role for CRYs in ameliorating the effects of high light stress. CRYs improved Fv/Fm in response to blue light under growing conditions, and also in response to high light stress.
There are several mechanisms through which it may be possible that CRYs could lead to an increase in Fv/Fm both under blue light and in response to high light
35
stress. 1) CRYs could affect leaf morphology so that the absorption of light through
the leaf, or the ratio of absorption between PSI and PSII reaction centres, changes
(Murchie and Lawson, 2013; Miao et al. 2016). 2) CRYs increase activation of D1 and
D2 proteins of PSII in response to blue light, leading to an increase in the amount of
proteins available for PSII repair (Thum et al. 2001; Tsunoyama et al. 2004; Onda et
al. 2008). In this way, CRYs may be vital for the normal functioning of PSII. 3) CRY1
activates 77 of 996 genes that respond to high light, including the gene for Vitamin
B6, which provides antioxidant activity against ROS stress (Kleine et al. 2007).
Accordingly, Boccalandro et al. (2012) suggested that non-stomatal limitations, such
as reduced electron transport rate in PSII, were the most likely cause of reduced
photosynthetic capacity in cry1cry2.
3.2 BLUE LIGHT ADVANCES BUD BURST IN THE LAB
For the three tree species we measured, we found that blue light advanced the date of
50% bud burst in branches kept under controlled conditions. This effect was greatest
in Q. robur (6.3 days), followed by A. glutinosa (6 days), and B. pendula (3 days).
These results are consistent with studies showing that early-successional species
achieve bud burst sooner than late-successional species (Wesołowski and Rowiński
2006; Basler and Körner, 2012), as B. pendula and A. glutinosa reached bud burst
before the later-successional Q. robur. We also showed the same effect when
expressed as degree-days, meaning that the effect was not due to any undetected
microclimatic differences in temperature between different chambers.
We present two hypotheses as to why blue light might advance bud burst. The
first is that enriched blue light could be a signal for increased twilight hours during
spring, as twilight hours are enriched in blue light (Robertson et al. 1966, Johnson et
al. 1967, Hughes et al. 1984). However, extending day length with narrow band blue
LEDs did not advance bud burst in P. abies (Mølmann et al. 2006), suggesting that
diurnal changes in blue light may not affect bud burst. Alternatively, blue light has
been shown to enhance photosynthesis in several plant species (Goins et al. 1997;
Matsuda et al. 2004; Hogewoning et al. 2010). Thus, it might be the case that blue
light is a cue for conditions which promote photosynthesis.
Previous research has shown that members of the Rosacea family have a
higher percentage of bud burst for axillary shoots under enriched blue light (Muleo et
al. 2001; Girault et al. 2008). Whilst this is a different process to spring bud burst, it
suggests possible mechanisms by which blue light advances springtime bud burst in
trees, for example by increasing the allocation of sugars to the growing bud (Girault
et al. 2010). Interestingly, several tree species, such as Q. robur, Fagus sylvatica,
Betula pubescens, Fraxinus excelsior and Acer pseudoplatanus (Catesson 1964;
Barnola et al. 1986; Cottignies 1986; Kelner et al. 1993; Rinne et al. 1994a, b), increase
mobilisation of stem carbohydrates towards buds when they are close to bud burst.
Thus, it appears that sugar metabolism plays a part in this process, and could be an
36
interesting line of inquiry with regards to blue light-mediated mechanisms which
promote bud burst.
3.3 LIGHT QUALITY INFLUENCES THE SEASONAL DYNAMICS OF FLAVONOIDS
Flavonol response in more light-demanding species is more sensitive than shade-
tolerant species to changes in light quality
We installed filters attenuating different wavelengths in the blue-and-UV region over
plants in a forest understorey in southern Finland. This enabled us to test how leaf
pigments and leaf phenology in different plant species responded to blue and UV
radiation, scaling from our laboratory studies, and testing these ideas in a more
ecologically relevant context.
Consistent with our laboratory study (I), we found that for most species in the
understorey, blue light had the largest effect on flavonol content, when compared to
longwave and shortwave UV radiation. This is also consistent with Siipola et al. (2015)
who found that solar blue radiation had the largest effect on flavonol content when
compared with solar UV radiation. Whilst experiments such as ours, and that used by
Siipola et al. (2015), resulted in a reduction of PAR in treatments attenuating blue
light, our results from (I) demonstrate the effects of blue light under equal PAR
conditions.
For most species, the effect of shortwave UV and longwave UV radiation was
smaller than the effect of blue light on flavonol content (see Table 2 in IV). However,
for Q. robur, shortwave UV radiation had the largest effect on flavonol content. One
reason this species-specific effect may occur is because Q. robur is at the edge of its
northern range limit at our Finnish field site, meaning that it is typically exposed to
higher UV radiation at more southern latitudes in its distribution range core. In this
way, Q. robur may be more sensitive to UV radiation as a cue for flavonol content, in
comparison to blue light.
Anthocyanin content was largely unaffected by filter treatments throughout
most of the season. Thus, we may expect that seasonal dynamics in anthocyanin
content are affected more by cues other than light quality, such as temperature
(Pescheck and Bilger 2019; Renner and Zohner, 2019).
The more light-demanding species in our study were most responsive to our
filter treatments. In addition, more light-demanding species tended to have higher
flavonol content throughout the season, when compared to most of the species which
had overwintering leaves (e.g. O. acetosella and M. bifolium). Previous research
suggested that evergreen and woody species would have higher constitutive contents
of UV-B absorbing compounds in comparison to herbaceous species, because they
have a longer leaf life-span (Semerdjieva et al. 2003; Li et al. 2010). However, one
study comparing the UV-screening ability of different growth forms in a sub-tropical
37
alpine environment found no differences (Barnes et al. 2017). Here, we suggest that despite having shorter leaf life-spans, more light-demanding species tend to have higher induced flavonol content, and are more sensitive to changes in light quality, so that higher photoprotection can allow them to more readily exploit periods of light availability (Takahashi and Badger, 2011).
Light quality affects flavonol and anthocyanin content in autumn
Until recently, it was generally considered that flavonol content did not increase during autumn (Wilkinson et al. 2002). However, Mattila et al. (2018) showed that flavonols increase during autumn senescence in the tree species B. pendula and Sorbus aucuparia. Similarly, we report an autumn increase in adaxial epidermal flavonol content for A. platanoides, A. podagraria, F. vesca, and Q. robur (weeks 35-40). This increase coincided with a period of canopy opening during autumn in the deciduous stands, and was absent, or much smaller, under filters attenuating blue and UV radiation. A similar trend was observed with anthocyanins, although anthocyanins were generally less responsive than flavonols to light quality for most species, apart from A. platanoides and A. podagraria.
Figure 5. Schematic of the factors affecting seasonal dynamics in understorey flavonoids. The figure shows the phenological progress of a typical deciduous tree from our experiment, and the phenology of species present in the understorey: forbs, Anemone nemorosa, Aegopodium podagraria and seedling Acer platanoides. “+”
38
means that particular cue or environmental stressor is increasing during that period
in the understorey, whereas “-” means the opposite. Colour coding is purely aesthetic.
It is possible that the increased solar radiation in the blue and UV region
reaching the understorey during autumn could lead to this increase in flavonoids.
However, this pattern was also present in the evergreen stands, suggesting that colder
temperatures are also a contributing factor. The accumulation of autumn flavonoids
in response to colder temperatures would be consistent with their role as antioxidants
(Pescheck and Bilger 2019; Renner and Zohner, 2019). In addition, it could be that
the increase in anthocyanins is part of the leaf senescence timetable, also supporting
their role as antioxidants to remove ROS produced during chlorophyll breakdown
(Figure 5) (Archetti et al. 2009).
3.4 HOW IMPORTANT IS LIGHT QUALITY COMPARED TO OTHER ENVIRONMENTAL FACTORS AFFECTING PHENOLOGY?
Spring Phenology
Under field conditions, we found that blue light advanced bud burst by an average 1.4
days, and final leaf out by 2.8 days in A. platanoides seedlings in a forest understorey.
This is equivalent of 0.8% and 1.5% of the average growing season length for A.
platanoides seedlings growing under the ambient control filter in our experiment
(182 days). The blue light effect we report is consistent with the effects that we found
in (II). Although experiments such as ours attenuating blue light also reduce the
amount of PAR (Siipola et al. 2015), we demonstrated this effect of blue light was
consistent under controlled PAR conditions, which provided equal PAR to both
treatments in (II). We did not find evidence showing that UV radiation affects bud
burst. Similarly, long-term UV-B supplementation had no effect on the bud burst of
four dwarf shrub species (Phoenix et al. 2001).
The evidence from our review and meta-analyses conducted in (III) support
the larger effect of blue light, in comparison to UV radiation, on bud burst that we
report in (IV). In general, both the mean and median effect sizes for different light
quality treatments on spring bud burst were of a similar magnitude to the size of
effects which have been reported for photoperiod (2.1 days advanced bud burst per
hour photoperiod increase, and 4–6 days earlier bud burst in treatments of enriched
blue light and twilight R:FR). We also found that previously reported significant
effects of UV radiation (reviewed in III) are negligible when considered in terms of
biological effect size (e.g. an average of 0.67 days earlier under UV-B radiation). In
comparison, the mean effect sizes of chilling and forcing temperatures were 1.0 days
advanced bud burst per one chilling day increase (III: Table 3), and 2.0 days advanced
bud burst per 1°C increase in forcing temperature (III: Table 3), respectively.
Considering the relatively large responses to an increase in chilling days or forcing
39
temperatures compared with photoperiod and spectral composition, we might expect
chilling days and forcing temperature to have a greater potential to affect the bud
burst of trees than other cues (Figure 6).
We did not find evidence that the spring leaf out of herbaceous species is
affected by light quality. This is because they are covered by snow during winter, and
so ground temperature and snowmelt are probably more important environmental
factors affecting their leaf out (Price and Waser 1998; Rice et al. 2018). One caveat
here is that herbaceous species were not sampled as often as A. platanoides in our
field study due to time constraints, so this could mean that small differences in leaf
out between filter treatments of herbaceous species were not detected.
Autumn Phenology
Attenuating blue light delayed leaf senescence in A. platanoides (14.3 days for stage
2; 7.6 days for stage 5), A. podagraria (5.6 days for stage 2; 0 days for stage 5), and
R. cassubicus (7.4 days for stage 2; 7.0 days for stage 5). These differences can also be
expressed as a percentage of the growing season length (A. platanoides – 7.8% for
stage 2; 4.2% for stage 5; A. podagraria – 3.8% for stage 2; R. cassubicus – 5.5% for
stage 2; 5.3% for stage 5). Blue light enhances photosynthesis in several plant species
(Sæbø et al. 1995; Goins et al. 1997; Matsuda et al. 2008; Košvancová-Zitová et al.
2009; Hogewoning et al. 2010). This is because blue light allows rapid stomatal
opening to exploit sunflecks, and also enables rubisco activation (Košvancová-Zitová
et al. 2009). It is possible that by attenuating blue light, we reduced photosynthesis
in these plants, and so they compensated for reduced carbon gain by extending their
leaf phenology further into autumn (Chabot and Hicks, 1982; Zhang et al. 2013). As
previously discussed, in agreement with other filter experiments attenuating solar
blue light (Siipola et al. 2015), there was a reduction in PAR (34.4%). This means that
delayed leaf senescence in response to attenuated blue light could be due to the
reduction in PAR (Lee et al. 2003). Accordingly, attenuating blue light delayed leaf
senescence the most for A. platanoides seedlings growing in the evergreen stand,
where PAR was also the lowest. However, we found no difference in Fv/Fm or stomatal
conductance between our filter treatments to support the idea that the reduction in
PAR or blue light might have affected gas exchange or photosynthetic capacity.
Furthermore, CRYs are involved in the regulation of leaf senescence in Glycine max
(Meng et al. 2013), which may indicate a role for blue light in advancing leaf
senescence.
Attenuating UV radiation below 350 nm delayed leaf senescence in A.
platanoides (4.1 days for stage 2; 0 days for stage 5). Supplementary UV-B radiation
from lamps can advance leaf senescence in saplings of F. sylvatica, and it has been
suggested that this effect is due to photodamage to the leaves (Zeuthen et al. 1997).
As such, it is possible that attenuating UV radiation below 350 nm delayed leaf
senescence, because of reduced photodamage throughout the year. Conversely, long
term UV-B supplementation had no effect on the leaf senescence of Vaccinium
40
myrtillus and Vaccinium uliginosum (Phoenix et al. 2001). This suggests that more research is required to understand why autumn leaf senescence of different plant species is affected by UV radiation.
Figure 6. Conceptual schematic of environmental factors affecting leaf out in the forest understorey. Changes in solar radiation also result in changes in light quality entering the forest understorey, as displayed in Figure 2. “+” means that particular
cue or environmental stressor is increasing in the understorey, whereas “-” means the
opposite. Colour coding is purely aesthetic.
We found that the effects of light quality were larger for autumn leaf senescence in comparison to spring bud burst and leaf out. This is one of the few studies to conduct experiments on the effects of light quality on leaf senescence. However, when conducting our literature review (III), we found a similar general trend to that observed in our experiments that the effects of light quality were greater for autumn phenology (e.g. bud set), than for spring phenology (bud burst). For instance, twilight R:FR light can advance bud burst by 4 days in B. pendula, but daylength extension with R:FR can nearly prevent bud set occurring altogether (III). The mean and median percentage of trees reaching bud set after daylength extension with FR light was 2.4% and 0% (III). Beyond these findings, there is currently a paucity of studies that have been conducted on both bud set and leaf senescence, meaning that the effects of light quality in comparison to other environmental drivers cannot presently be ranked (Gallinat et al. 2015, III).
41
3.5 HOW WILL CLIMATE CHANGE AFFECT UNDERSTOREY LIGHT INTERACTIONS?
Climate change is advancing spring leaf-out in trees in the north-east USA, faster than
the emergence and leaf out of understorey plants (Heberling et al. 2019). This
mismatch in phenology means that the carbon assimilation of many herbaceous
species is being restricted by earlier canopy shading. The inability of understorey
plants to respond as much as canopy trees to rising temperatures in spring may be
the result of soil temperatures being cooler than air temperatures in the canopy
(Coulson et al. 1995; Ling & Zhang 2003). The lag in understorey springtime warming
relative to the canopy would be further exacerbated by earlier canopy closure,
reducing the transmission of IR radiation to the ground.
We found that changes in light quality did not affect the spring emergence of
herbaceous species, because these species principally rely on timing their phenology
according to ground temperatures and snowmelt (Augspurger and Salk 2017).
Changes in blue light in particular can accelerate the spring bud burst of trees (II) and
tree seedlings (IV). The treatments we used excluded blue light completely, whereas
we found that in nature, the amount of blue light is reduced by 50.5% under canopy
shade compared to sun gaps in the forest understorey (IV, supplementary material).
Furthermore, tree seedlings have ontogenic safeguards against being overshaded by
adult trees (Vitasse et al. 2013). Altogether, this makes it less likely that seedlings of
the same species will experience overshading and reduced blue light resulting from
advanced canopy spring leaf-out.
It has been suggested that plants covered by snow in early spring may also be
exposed to different spectral cues (Robson and Aphalo, 2019). There is a much larger
(98.9%) reduction of blue light 30cm under the snowpack, compared to the surface
(Robson and Aphalo, 2019). Earlier snow melt in spring under climate change could
expose plants to a higher irradiance of blue light, which could accelerate their
phenology even further, although many tree seedlings have buds above the snowpack
which are exposed to ambient light conditions. Furthermore, it is probable that for
tree seedlings, factors such as chilling and forcing temperatures have a larger role to
play under these conditions (III).
Whilst we did not assess leaf senescence of spring ephemeral species in this
study, there is some evidence suggesting that earlier shade can induce earlier leaf
senescence in spring ephemerals (Augspurger and Salk, 2017). This is very interesting
to note, as other studies have suggested that for woody species which senesce in
autumn, shading delays leaf senescence even further (Lee et al. 2003). As such, it
would be interesting to investigate whether changes in blue and UV radiation
underpin this response as well. Furthermore, this could demonstrate that different
functional plant types may respond differently to changes in canopy duration under
climate change, with spring ephemerals reaching leaf senescence earlier, and
autumnal species reaching leaf senescence later.
42
There have been range expansions under climate change for some temperate
tree species, with them shifting either further north in the Northern Hemisphere, or
to higher elevations (Beckage et al. 2008, Harsch et al. 2009; Vitasse et al. 2012). It
has been proposed that phenology in more northern ecotypes of trees is more
sensitive to changes in photoperiod than more southern trees (Vaartaja 1959, Myking
and Heide 1995, Robson et al. 2013, review by Way and Montgomery 2015, Cooper et
al. 2018). If this is the case, greater variation in photoperiod at higher latitudes may
constrain northwards range-shifts of southern trees under climate change (Way and
Montgomery, 2015).There have, however, also been studies suggesting the opposite,
that more southern trees have a greater sensitivity to photoperiod changes (Kriebel
1957, Olson et al. 2013, Zohner et al. 2016, Osada et al. 2018).
In addition to possibly being more sensitive to changes in photoperiod, studies
have also suggested that more northern trees are more sensitive to changes in light
quality (III). As such, we may expect that the greater variation in seasonal and diurnal
changes in light quality at higher latitudes could also be a factor limiting northwards
range shifts. Failure to adapt to these changes in light quality at higher latitudes could
result in frost damage (if for instance spring bud burst is too early, or autumn leaf
senescence/bud-set occurs too late). Conversely, if spring bud burst occurs too late
or autumn leaf senescence occurs too early, then this constitutes a missed opportunity
for photosynthesis. Either way, this failure to correctly time phenology could result in
reduced fitness. Whilst the latitudinal effects of light quality may correlate with the
effects of photoperiod, light quality, unlike photoperiod, can also vary longitudinally.
Changes in atmospheric conditions, water vapour, cloud cover, and ozone all vary
with location, and can affect light quality reaching the ground (Emde et al. 2016).
Considering this, it is important to understand plant phenological responses to light
quality in different biomes and regions beyond temperate and boreal regions in North
America and Europe.
3.6 METHODOLOGICAL CONSIDERATIONS
In the field experiment conducted for this Thesis (IV), we used an optical leaf sensor
to assess the differences in seasonal leaf epidermal flavonol and anthocyanin content
among species. This comparison was based on the assumption that the relationship
between the absorbance indices are approximately linear with their respective leaf
pigment contents (unpublished data; Hartikainen et al. 2020). The Dualex
absorbance indices have a positive correlation with leaf flavonoid content for some
plant species (Agati et al. 2008, Morales et al. 2010), but some alpine plant species
do not exhibit this positive correlation (Lefebvre et al. 2016). Accordingly, it is
possible that species-specific differences in the relationship between Dualex
absorbance indices and total flavonoid content, could contribute to the species-
specific patterns in optically assessed flavonoids we observed throughout the growing
season.
43
Using filters attenuating solar radiation, as we did (IV), can also increase the
temperature of the plants beneath. This is why it was essential that we incorporated
a transparent control filter. While the average increase in temperature due to heating
was very small in our experiment (an average of 0.3°C higher under all filters
compared to ambient understorey conditions), it is possible that filter presence in the
understorey could alter the responses of underlying plants , for example by changing
air flow or herbivore access. The leaf epidermal flavonol and anthocyanin contents in
our study fell within the normal range of values reported by Hartikainen et al. (2020)
in the same forest stands. Similarly, the timing of leaf senescence for plants beneath
the filters was similar to that of plants in ambient forest understorey conditions (Fig.
S10, IV). Considering the controls in place and comparisons with ambient conditions
given here, any effect of the filters altering plant responses is probably of insufficient
magnitude to interfere with our conclusions derived from the comparison of spectral
attenuation treatments.
44
3.7 CONCLUSIONS AND FUTURE RESEARCH
Conclusions
CRYS and UVR8 both regulate flavonols in response to UV-A. The effects of blue light
on the accumulation of flavonols were larger than those of UV radiation, both under
controlled conditions and under field conditions using understorey plants.
Interestingly, flavonols in the more-light-demanding species we studied were more
sensitive to changes in light quality, despite having shorter leaf life-spans than shade-
tolerant species. We found that blue light can advance both bud-burst and autumn
leaf senescence. While the effects of UV radiation on spring phenology were
negligible, UV radiation may affect autumn leaf senescence. In general, most
published studies have found that light quality has a small effect on spring phenology,
however the limited number of studies on light quality related to autumn phenology
suggests its effect could be greater at the end of the growing season.
Future research
Future work should endeavour to understand the processes by which blue light and
UV radiation affect leaf senescence. This will reveal the reasons for, and mechanisms
by which, different species’ autumn phenology follows different patterns. In addition,
this will reveal whether prolonged canopy shade can produce phenological
mismatches between understorey and overstorey species, or segregate different plant
functional types within the understorey community. The template provided by this
research could also be expanded to studying different plant communities in different
plant biomes around the globe. For instance, studying responses between
understorey plant communities in American and European temperate and boreal
regions, which have different seasonality, and so may receive differing amounts of
solar radiation throughout the year.
Whilst it may be ambitious to attempt to introduce the effects of spectral
composition into phenological models, doing this may help us understand the
mechanisms by which commonly used phenological model parameters such as
photoperiod, solar irradiance, solar insolation, and daily light integral (DLI) can
affect plants (Foggo and Warrington, 1989, Borchert et al. 2015, Calle et al. 2010, Liu
et al. 2015, Fu et al. 2015, Liu et al. 2016). Understanding the mechanisms by which
solar insolation and DLI could affect phenology, would provide further insight into
their application into phenological models. Similar approaches could also be applied
to integrating processes and models that underpin new leaf production in tropical
trees, and flowering in trees in general.
45
4. REFERENCES
Agati, G., and Tattini, M. (2010). Multiple functional roles of flavonoids in
photoprotection. New Phytologist, 186(4), 786-793.
Aphalo, P. J. (2015). The r4photobiology suite: spectral irradiance. UV4Plants
Bulletin, 2015(1), 21-29.
Aphalo, P. J. (2017). Quantification of UV radiation. UV-B Radiation and Plant Life:
Molecular Biology to Ecology. B. R. Jordan (Ed,) CAB International, Wallingford,
UK. 10-22.
Aphalo, P. J., Albert, A., Björn, L. O., McLeod, A., Robson, T. M., and Rosenqvist, E.
(Eds.). (2012). Beyond the visible: a handbook of best practice in plant UV
photobiology. COST FA0906 UV4growth. Helsinki, University of Helsinki, pp 176. .
Aphalo, P. J. (2016). The r4photobiology suite: sun angles and day length. UV4Plants
Bulletin, 2016(1), 29-39.
Archetti, M., Döring, T. F., Hagen, S. B., Hughes, N. M., Leather, S. R., Lee, D. W., ...
and Thomas, H. (2009). Unravelling the evolution of autumn colours: an
interdisciplinary approach. Trends in Ecology and Evolution, 24(3), 166-173.
Augspurger, C.K. (2009) Spring 2007 warmth and frost: phenology, damage and
refoliation in a temperate deciduous forest. Functional Ecology, 23(6), 031–1039.
Augspurger, C. K., Cheeseman, J. M., and Salk, C. F. (2005). Light gains and
physiological capacity of understorey woody plants during phenological avoidance
of canopy shade. Functional Ecology, 19(4), 537-546.
Augspurger, C. K., and Salk, C. F. (2017). Constraints of cold and shade on the
phenology of spring ephemeral herb species. Journal of Ecology, 105(1), 246-254.
Ballaré, C. L., and Pierik, R. (2017). The shade‐avoidance syndrome: multiple signals
and ecological consequences. Plant, Cell and Environment, 40(11), 2530-2543.
Ballaré, C. L., Sánchez, R. A., Scopel, A. L., Casal, J. J., and Ghersa, C. M. (1987). Early
detection of neighbour plants by phytochrome perception of spectral changes in
reflected sunlight. Plant, Cell and Environment, 10(7), 551-557.
Barnes, P. W., Ryel, R. J., and Flint, S. D. (2017). UV screening in native and non-
native plant species in the tropical alpine: Implications for climate change-driven
migration of species to higher elevations. Frontiers in Plant Science, 8, 1451.
Barnola, P., Crochet, A., Payan, E, Gendraud, M., and Lavarenne, S. (1986)
Modifications of energy-metabolism and permeability in the apical bud and in stem
during the temporary rest of the growth of young oak trees. Physiologie Vegetale,
24(3), 307–314
Basler, D., and Körner, C. (2012). Photoperiod sensitivity of bud burst in 14 temperate
forest tree species. Agricultural and Forest Meteorology, 165, 73-81.
46
Beckage, B., Osborne, B., Gavin, D. G., Pucko, C., Siccama, T., and Perkins, T. (2008).
A rapid upward shift of a forest ecotone during 40 years of warming in the Green
Mountains of Vermont. Proceedings of the National Academy of Sciences, 105(11),
4197-4202.
Bennie J., Kubin E., Wiltshire A., Huntley B., and Baxter, R. (2010) Predicting spatial
and temporal patterns of bud-burst and spring frost risk in north-west Europe: the
implications of local adaptation to climate. Global Change Biology, 16(5), 1503–
1514.
Bestelmeyer, S. V., Elser, M. M., Spellman, K. V., Sparrow, E. B., Haan-Amato, S. S.,
and Keener, A. (2015). Collaboration, interdisciplinary thinking, and
communication: new approaches to K–12 ecology education. Frontiers in Ecology
and the Environment, 13(1), 37-43.
Bilger W, Rolland M, Nybakken L (2007) UV screening in higher plants induced by
low temperature in the absence of UV‐B radiation. Photochemical and
Photobioloical Sciences 6(2), 190–195
Blumthaler, M., Ambach, W., and Ellinger, R. (1997). Increase in solar UV radiation
with altitude. Journal of photochemistry and Photobiology B: Biology, 39(2), 130-
134.
Boccalandro, H. E., Giordano, C. V., Ploschuk, E. L., Piccoli, P. N., Bottini, R., and
Casal, J. J. (2012). Phototropins but not cryptochromes mediate the blue light-
specific promotion of stomatal conductance, while both enhance photosynthesis
and transpiration under full sunlight. Plant Physiology, 158(3), 1475-1484.
Borchert, R., Calle, Z., Strahler, A. H., Baertschi, A., Magill, R. E., Broadhead, J. S., ...
and Muthuri, C. (2015). Insolation and photoperiodic control of tree development
near the equator. New Phytologist, 205(1), 7-13.
Brelsford, C. C. (2017). Radiative transfer theory and modelling with libRadtran.
UV4Plants Bulletin, 2016(2), 45-50.
Briggs, W. R., and Christie, J. M. (2002). Phototropins 1 and 2: versatile plant blue-
light receptors. Trends in Plant Science, 7(5), 204-210.
Brown, B. A., C. Cloix, G. H. Jiang, E. Kaiserli, P. Herzyk, D. J. Kliebenstein and G. I.
Jenkins (2005) A UV‐B‐specific signaling component orchestrates plant UV
protection. Proceedings of the National Academy of Sciences, 102(50), 18225–
18230
Brunetti, C., Fini, A., Sebastiani, F., Gori, A., and Tattini, M. (2018). Modulation of
phytohormone signaling: a primary function of flavonoids in plant–environment
interactions. Frontiers in Plant Science, 9, 1042.
Caffarra and A., and Donnelly, A. (2011) The ecological significance of phenology in
four different tree species: effects of light and temperature on bud burst.
International Journal of Biometeorology, 55(5), 711–721.
47
Caldwell, M. M., Robberecht, R., and Billings, W. D. (1980). A steep latitudinal
gradient of solar ultraviolet‐B radiation in the arctic‐alpine life zone. Ecology, 61(3),
600-611.
Calle, Z., Schlumpberger, B. O., Piedrahita, L., Leftin, A., Hammer, S. A., Tye, A., and
Borchert, R. (2010). Seasonal variation in daily insolation induces synchronous bud
break and flowering in the tropics. Trees, 24(5), 865-877.
Casal, J. J. (2000). Phytochromes, cryptochromes, phototropin: photoreceptor
interactions in plants. Photochemistry and Photobiology, 71(1), 1-11.
Casal, J. J. (2013). Photoreceptor signaling networks in plant responses to shade.
Annual review of plant biology, 64, 403-427.
Catesson, A. M. (1964) Modifications cytochimiques saisonnieres des points
vegetatifs dans les bourgeons de lacer pseudoplatanus. Comptes rendus de
l'Académie des Sciences. 258, 5709.
Cerovic, Z. G., Masdoumier, G., Ghozlen, N. B., and Latouche, G. (2012). A new optical
leaf‐clip meter for simultaneous non‐destructive assessment of leaf chlorophyll and
epidermal flavonoids. Physiologia plantarum, 146(3), 251-260.
Cesaraccio C., Spano D., Snyder R. L., Duce, P. (2004). Chilling and forcing model to
predict bud-burst of crop and forest species. Agricultural and Forest Meteorology,
126 (1-2), 1–13.
Chabot, B. F., and Hicks, D. J. (1982). The ecology of leaf life spans. Annual Review
of Ecology and Systematics, 13(1), 229-259.
Chambers, P. A., and Spence, D. H. (1984). Diurnal changes in the ratio of underwater
red to far red light in relation to aquatic plant photoperiodism. The Journal of
Ecology, 72(2), 495-503.
Christie, J. M., and Jenkins, G. I. (1996). Distinct UV-B and UV-A/blue light signal
transduction pathways induce chalcone synthase gene expression in Arabidopsis
cells. The Plant Cell, 8(9), 1555-1567.
Chuine, I., Yiou, P., Viovy, N., Seguin, B., Daux, V., and Ladurie, E. L. R. (2004).
Historical phenology: grape ripening as a past climate indicator. Nature, 432(7015),
289.
Clarke, L. J., and Robinson, S. A. (2008). Cell wall‐bound ultraviolet‐screening
compounds explain the high ultraviolet tolerance of the Antarctic moss, Ceratodon
purpureus. New Phytologist, 179(3), 776-783.
Cleland, E. E., Chuine, I., Menzel, A., Mooney, H. A., and Schwartz, M. D. (2007).
Shifting plant phenology in response to global change. Trends in Ecology and
Evolution, 22(7), 357-365.
Close, D. C., and McArthur, C. (2002). Rethinking the role of many plant phenolics–
protection from photodamage not herbivores? Oikos, 99(1), 166-172.
48
Cooper, C. B., Shirk, J., and Zuckerberg, B. (2014). The invisible prevalence of citizen
science in global research: migratory birds and climate change. PloS One, 9(9),
e106508.
Cooper, H. F., Grady, K. C., Cowan, J. A, Best, R. J., Allan, G. J, Whitham, T. G. (2018).
Genotypic variation in phenological plasticity: reciprocal common gardens reveal
adaptive responses to warmer springs but not to fall frost. Global Change Biology,
25(1), 187–200.
Cottignies, A. (1986) The hydrolysis of starch as related to the interruption of
dormancy in the ash bud. Journal of Plant Physiology, 123(4), 381–388.
Coulson, S. J., Hodkinson, I. D., Strathdee, A. T., Block, W., Webb, N. R., Bale, J. S.,
and Worland, M. R. (1995). Thermal environments of Arctic soil organisms during
winter. Arctic and Alpine Research, 27(4), 364-370.
Dahlback, A., and Stamnes, K. (1991). A new spherical model for computing the
radiation field available for photolysis and heating at twilight. Planetary and Space
Science, 39(5), 671-683.
Das, S., and Joy, V. C. (2009). Chemical quality impacts of tropical forest tree leaf
litters on the growth and fecundity of soil Collembola. European Journal of Soil
Biology, 45(5-6), 448-454.
Day, T. A. (1993). Relating UV-B radiation screening effectiveness of foliage to
absorbing-compound concentration and anatomical characteristics in a diverse
group of plants. Oecologia, 95(4), 542-550.
Day, T. A., Vogelmann, T. C., and DeLucia, E. H. (1992). Are some plant life forms
more effective than others in screening out ultraviolet-B radiation? Oecologia,
92(4), 513-519.
Delpierre, N., Dufrêne, E., Soudani, K., Ulrich, E., Cecchini, S., Boé, J., and François,
C. (2009). Modelling interannual and spatial variability of leaf senescence for three
deciduous tree species in France. Agricultural and Forest Meteorology, 149(6-7),
938-948.
Dengel, S., Grace, J., and MacArthur, A. (2015). Transmissivity of solar radiation
within a Picea sitchensis stand under various sky conditions. Biogeosciences, 12(14),
4195-4207.
Ekberg, I., Eriksson, G., and Dormling, I. (1979). Photoperiodic reactions in conifer
species. Ecography, 2(4), 255–263.
Emde, C., Buras-Schnell, R., Kylling, A., Mayer, B., Gasteiger, J., Hamann, U., ... and
Bugliaro, L. (2016). The libRadtran software package for radiative transfer
calculations (version 2.0. 1). Geoscientific Model Development, 9(5), 1647-1672.
Feild, T. S., Lee, D. W., and Holbrook, N. M. (2001). Why leaves turn red in autumn.
The role of anthocyanins in senescing leaves of red-osier dogwood. Plant Physiology,
127(2), 566-574.
49
Ferrer, J. L., Austin, M. B., Stewart Jr, C., and Noel, J. P. (2008). Structure and
function of enzymes involved in the biosynthesis of phenylpropanoids. Plant
Physiology and Biochemistry, 46(3), 356-370.
Flint, S. D., and Caldwell, M. M. (1998). Solar UV‐B and visible radiation in tropical
forest gaps: measurements partitioning direct and diffuse radiation. Global Change
Biology, 4(8), 863-870.
Flynn, D. F. B., and Wolkovich, E. M. (2018). Temperature and photoperiod drive
spring phenology across all species in a temperate forest community. New
Phytologist, 219(4), 1353-1362.
Foggo, M. N., and Warrington, I. J. (1989). The influence of photosynthetically active
radiation and vernalization on flowering of Deschampsia flexuosa (L.)
Trin.(Poaceae). Functional Ecology, 3(5), 561-567
Fraser, D. P., Hayes, S., and Franklin, K. A. (2016). Photoreceptor crosstalk in shade
avoidance. Current Opinion in Plant Biology, 33(10), 1-7.
Fu, Y. H., Piao, S., Vitasse, Y., Zhao, H., De Boeck, H. J., Liu, Q., ... and Janssens, I.
A. (2015). Increased heat requirement for leaf flushing in temperate woody species
over 1980–2012: effects of chilling, precipitation and insolation. Global Change
Biology, 21(7), 2687-2697.
Fuglevand, G., Jackson, J. A., and Jenkins, G. I. (1996). UV-B, UV-A, and blue light
signal transduction pathways interact synergistically to regulate chalcone synthase
gene expression in Arabidopsis. The Plant Cell, 8(12), 2347-2357.
Gallinat, A. S., Primack, R. B., Wagner, D. L. (2015). Autumn, the neglected season in
climate change research. Trends in Ecology and Evolution 30(3), 169–176.
Gill, A. L., Gallinat, A. S., Sanders-DeMott, R., Rigden, A. J., Short Gianotti, D. J.,
Mantooth, J. A., and Templer, P. H. (2015). Changes in autumn senescence in
northern hemisphere deciduous trees: a meta-analysis of autumn phenology
studies. Annals of Botany, 116(6), 875-888.
Girault, T., Bergougnoux, V., Combes, D., Viemont, J. D., and Leduc, N. (2008). Light
controls shoot meristem organogenic activity and leaf primordia growth during bud
burst in Rosa sp. Plant, Cell and Environment, 31(11), 1534-1544.
Girault, T., Abidi, F., Sigogne, M., Pelleschi‐Travier, Sandrine, Boumaza, R., Sakr, S.,
and Leduc, N. (2010). Sugars are under light control during bud burst in Rosa sp.
Plant, Cell and Environment, 33(8), 1339-1350.
Goins, G. D., Yorio, N. C., Sanwo, M. M., and Brown, C. S. (1997).
Photomorphogenesis, photosynthesis, and seed yield of wheat plants grown under
red light-emitting diodes (LEDs) with and without supplemental blue lighting.
Journal of Experimental Botany, 48(7), 1407-1413.
50
Goodwin, T. W. (1958). Studies in carotenogenesis. 24. The changes in carotenoid and
chlorophyll pigments in the leaves of deciduous trees during autumn necrosis.
Biochemical Journal, 68(3), 503.
Gould, K. S. (2004). Nature's Swiss army knife: the diverse protective roles of
anthocyanins in leaves. BioMed Research International, 2004(5), 314-320.
Grant, R. H., Apostol, K., and Gao, W. (2005). Biologically effective UV-B exposures
of an oak-hickory forest understory during leaf-out. Agricultural and Forest
Meteorology, 132(1-2), 28-43.
Hänninen, H. (1991). Does climatic warming increase the risk of frost damage in
northern trees? Plant, Cell and Environment, 14(5), 449–454.
Hänninen, H. (1995). Effects of climatic change on trees from cool and temperate
regions: an ecophysiological approach to modelling of bud burst phenology.
Canadian Journal of Botany, 73(2), 183–199.
Harborne, J. B., and Williams, C. A. (2001). Anthocyanins and other flavonoids.
Natural product reports, 18(3), 310-333.
Harsch, M. A., Hulme, P. E., McGlone, M. S., and Duncan, R. P. (2009). Are treelines
advancing? A global meta‐analysis of treeline response to climate warming. Ecology
Letters, 12(10), 1040-1049.
Hartikainen, S. M., Jach, A., Grané, A., and Robson, T. M. (2018). Assessing scale‐
wise similarity of curves with a thick pen: As illustrated through comparisons of
spectral irradiance. Ecology and Evolution, 8(20), 10206-10218.
Hartikainen, S. M., Pieristè, M., Lassila, J., and Robson, T. M. (2020). Seasonal
patterns in spectral irradiance and leaf UV-A absorbance under forest canopies.
Frontiers in plant science, 10, 1762.
Heberling, J. M., McDonough MacKenzie, C., Fridley, J. D., Kalisz, S., and Primack,
R. B. (2019). Phenological mismatch with trees reduces wildflower carbon budgets.
Ecology Letters, 22(4), 616-623.
Hoch, W. A., Singsaas, E. L., and McCown, B. H. (2003). Resorption protection.
Anthocyanins facilitate nutrient recovery in autumn by shielding leaves from
potentially damaging light levels. Plant Physiology, 133(3), 1296-1305.
Hoffmann, A. M., Noga, G., and Hunsche, M. (2015). High blue light improves
acclimation and photosynthetic recovery of pepper plants exposed to UV stress.
Environmental and Experimental Botany, 109, 254-263.
Hogewoning, S. W., Trouwborst, G., Maljaars, H., Poorter, H., van Ieperen, W., and
Harbinson, J. (2010). Blue light dose–responses of leaf photosynthesis,
morphology, and chemical composition of Cucumis sativus grown under different
combinations of red and blue light. Journal of Experimental Botany, 61(11), 3107-
3117.
51
Hughes, J. E., Morgan, D. C., Lambton, P. A., Black, C. R., and Smith, H. (1984).
Photoperiodic time signals during twilight. Plant, Cell and Environment, 7(4), 269-
277.
Hulburt, E. O. (1953). Explanation of the brightness and color of the sky, particularly
the twilight sky. JOSA, 43(2), 113-118.
Hyyryläinen, A., Turunen, M., Rautio, P., and Huttunen, S. (2018). Sphagnum mosses
in a changing UV-B environment: A review. Perspectives in Plant Ecology, Evolution
and Systematics, 33, 1-8.
Ibdah, M., Krins, A., Seidlitz, H. K., Heller, W., Strack, D., and Vogt, T. (2002).
Spectral dependence of flavonol and betacyanin accumulation in
Mesembryanthemum crystallinum under enhanced ultraviolet radiation. Plant, Cell
and Environment, 25(9), 1145-1154.
Inada, S., Ohgishi, M., Mayama, T., Okada, K., and Sakai, T. (2004). RPT2 is a signal
transducer involved in phototropic response and stomatal opening by association
with phototropin 1 in Arabidopsis thaliana. The Plant Cell, 16(4), 887-896.
Jochum, G. M., Mudge, K. W., and Thomas, R. B. (2007). Elevated temperatures
increase leaf senescence and root secondary metabolite concentrations in the
understory herb Panax quinquefolius (Araliaceae). American Journal of Botany,
94(5), 819-826.
Johnsen, S. (2012). The optics of life: a biologist's guide to light in nature. Princeton
University Press, Princeton, pp48.
Johnson, T. B., Salisbury, F. B., and Connor, G. I. (1967). Ratio of blue to red light: a
brief increase following sunset. Science, 155(3770), 1663-1665.
Joshi, P. N., Ramaswamy, N. K., Iyer, R. K., Nair, J. S., Pradhan, M. K., Gartia, S., ...
and Biswal, U. C. (2007). Partial protection of photosynthetic apparatus from UV-
B-induced damage by UV-A radiation. Environmental and Experimental Botany,
59(2), 166-172.
Kållberg, P., Berrisford, P., Hoskins, B., Simmons, A., Lamy-thépaut, S., and Hine, R.
(2005). ERA-40 atlas.
Karolewski, P., Giertych, M. J., Żmuda, M., Jagodziński, A. M., and Oleksyn, J. (2013).
Season and light affect constitutive defenses of understory shrub species against
folivorous insects. Acta Oecologica, 53, 19-32.
Kelner, J. J., Lachaud S., Bonnemain J. L. (1993). Seasonal variations in ABA
exchange between the apical bud and the underlying stem of beech. Comparison
with nutrients. Plant Physiology and Biochemistry 31(4), 523–530
Kleine, T., Kindgren, P., Benedict, C., Hendrickson, L., and Strand, Å. (2007).
Genome-wide gene expression analysis reveals a critical role for
CRYPTOCHROME1 in the response of Arabidopsis to high irradiance. Plant
Physiology, 144(3), 1391-1406.
52
Klem, K., Holub, P., Štroch, M., Nezval, J., Špunda, V., Tříska, J., ... and Urban, O.
(2015). Ultraviolet and photosynthetically active radiation can both induce
photoprotective capacity allowing barley to overcome high radiation stress. Plant
Physiology and Biochemistry, 93, 74-83.
Körner, C. (2007). The use of ‘altitude’ in ecological research. Trends in Ecology and
Evolution. 22(11), 569–574.
Körner, C., Basler, D. (2010). Phenology under global warming. Science, 327(5972),
1461–1462.
Kong, S. G., and Okajima, K. (2016). Diverse photoreceptors and light responses in
plants. Journal of Plant Research, 129(2), 111-114.
Kotilainen, T., Tegelberg, R., Julkenen-Tiitto, Riita., Lindfors, A., and Aphalo, P. J.
(2008). Metabolite specific effects of solar UV‐A and UV‐B on alder and birch leaf
phenolics. Global Change Biology, 14(6), 1294-1304.
Kotilainen, T., Tegelberg, R., Julkunen‐Tiitto, R., Lindfors, A., O'Hara, R. B., and
Aphalo, P. J. (2010). Seasonal fluctuations in leaf phenolic composition under UV
manipulations reflect contrasting strategies of alder and birch trees. Physiologia
Plantarum, 140(3), 297-309.
Kotilainen, T., Venäläinen, T., Tegelberg, R., Lindfors, A., Julkunen‐Tiitto, R.,
Sutinen, S., ... and Aphalo, P. J. (2009). Assessment of UV biological spectral
weighting functions for phenolic metabolites and growth responses in silver birch
seedlings. Photochemistry and Photobiology, 85(6), 1346-1355.
Körner, C. (2007). The use of ‘altitude’ in ecological research. Trends in Ecology and
Evolution. 22(11), 569–574.
Körner, C., Basler, D. (2010). Phenology under global warming. Science, 327(5972),
1461–1462.
Košvancová-Zitová, M., Urban, O., Navrátil, M., Špunda, V., Robson, T. M., and
Marek, M. V. (2009). Blue radiation stimulates photosynthetic induction in Fagus
sylvatica L. Photosynthetica, 47(3), 388.
Kriebel, H. B. (1957) Patterns of genetic variation in sugar maple. Bulletin of Ohio
Agricultural Experiment Station. 791. 3–56.
Kudo, G., Ida, T. Y., and Tani, T. (2008). Linkages between phenology, pollination,
photosynthesis, and reproduction in deciduous forest understory plants. Ecology,
89(2), 321-331.
Lagercrantz, U. L. F. (2009). At the end of the day: a common molecular mechanism
for photoperiod responses in plants? Journal of Experimental Botany, 60(9), 2501-
2515.
Lang, G. A. (1987). Endo-, para-, and ecodormancy: physiological terminology and
classification for dormancy research. Horticultural Science, 22(3), 371–377.
53
Lang, M., Stober, F., and Lichtenthaler, H. K. (1991). Fluorescence emission spectra
of plant leaves and plant constituents. Radiation and Environmental Biophysics,
30(4), 333-347.
Laube, J., Sparks, T. H., Estrella, N., Höfler, J., Ankerst, D. P., and Menzel, A. (2014).
Chilling outweighs photoperiod in preventing precocious spring development.
Global Change Biology, 20(1), 170-182.
Le Roy, J., Huss, B., Creach, A., Hawkins, S., and Neutelings, G. (2016). Glycosylation
is a major regulator of phenylpropanoid availability and biological activity in plants.
Frontiers in Plant Science, 7, 735.
Lefebvre, T., Millery-Vigues, A., and Gallet, C. (2016). Does leaf optical absorbance
reflect the polyphenol content of alpine plants along an elevational gradient? Alpine
Botany, 126(2), 177-185.
Leuchner, M., Hertel, C., and Menzel, A. (2011). Spatial variability of
photosynthetically active radiation in European beech and Norway spruce.
Agricultural and Forest Meteorology, 151(9), 1226-1232.
Li, C., Junttila, O., Ernstsen, A., Heino, P., and Palva, E. T. (2003). Photoperiodic
control of growth, cold acclimation and dormancy development in silver birch
(Betula pendula) ecotypes. Physiologia Plantarum, 117(2), 206-212.
Li, F. R., Peng, S. L., Chen, B. M., and Hou, Y. P. (2010). A meta-analysis of the
responses of woody and herbaceous plants to elevated ultraviolet-B radiation. Acta
Oecologica, 36(1), 1-9.
Liakoura, V., Bornman, J. F., and Karabourniotis, G. (2003). The ability of abaxial
and adaxial epidermis of sun and shade leaves to attenuate UV‐A and UV‐B
radiation in relation to the UV absorbing capacity of the whole leaf methanolic
extracts. Physiologia Plantarum, 117(1), 33-43.
Ling, F., and Zhang, T. (2003). Impact of the timing and duration of seasonal snow
cover on the active layer and permafrost in the Alaskan Arctic. Permafrost and
Periglacial Processes, 14(2), 141-150.
Linkosalo, T., and Lechowicz, M. J. (2006). Twilight far-red treatment advances leaf
bud burst of silver birch (Betula pendula). Tree Physiology, 26(10), 1249-1256.
Liu, Q., Fu, Y. H., Zhu, Z., Liu, Y., Liu, Z., Huang, M., ... and Piao, S. (2016). Delayed
autumn phenology in the Northern Hemisphere is related to change in both climate
and spring phenology. Global Change Biology, 22(11), 3702-3711.
Liu, Q., Fu, Y. H., Zeng, Z., Huang, M., Li, X., and Piao, S. (2016). Temperature,
precipitation, and insolation effects on autumn vegetation phenology in temperate
China. Global Change Biology, 22(2), 644-655.
Lee, D. W., and Downum, K. R. (1991). The spectral distribution of biologically active
solar radiation at Miami, Florida, USA. International Journal of Biometeorology,
35(1), 48-54.
54
Lee, D. W., O’Keefe, J., Holbrook, N. M., and Feild, T. S. (2003). Pigment dynamics
and autumn leaf senescence in a New England deciduous forest, eastern USA.
Ecological Research, 18(6), 677-694.
Madronich, S., Zeng, J., and Stamnes, K., (1997) Tropospheric ultraviolet-visible
radiation model, Version 3.9a, February 1997.
Maxwell, K., and Johnson, G. N. (2000). Chlorophyll fluorescence—a practical guide.
Journal of Experimental Botany, 51(345), 659-668
Mazzella, M. A., and Casal, J. J. (2001). Interactive signalling by phytochromes and
cryptochromes generates de‐etiolation homeostasis in Arabidopsis thaliana. Plant,
Cell and Environment, 24(2), 155-161.
McKenzie, R. L., Seckmeyer, G., Bais, A. F., Kerr, J. B., and Madronich, S. (2001a).
Satellite retrievals of erythemal UV dose compared with ground‐based
measurements at northern and southern midlatitudes. Journal of Geophysical
Research: Atmospheres, 106(D20), 24051-24062.
McKenzie, R. L., Johnston, P. V., Smale, D., Bodhaine, B. A., and Madronich, S.
(2001b). Altitude effects on UV spectral irradiance deduced from measurements at
Lauder, New Zealand, and at Mauna Loa Observatory, Hawaii. Journal of
Geophysical Research: Atmospheres, 106(D19), 22845-22860.
Mattila, H., Valev, D., Havurinne, V., Khorobrykh, S., Virtanen, O., Antinluoma, M.,
... and Tyystjärvi, E. (2018). Degradation of chlorophyll and synthesis of flavonols
during autumn senescence—the story told by individual leaves. AoB Plants, 10(3),
ply028.
Matsuda, R., Ohashi-Kaneko, K., Fujiwara, K., and Kurata, K. (2008). Effects of blue
light deficiency on acclimation of light energy partitioning in PSII and CO2
assimilation capacity to high irradiance in spinach leaves. Plant and Cell Physiology,
49(4), 664-670.
Matsuda, R., Ohashi-Kaneko, K., Fujiwara, K., Goto, E., and Kurata, K. (2004).
Photosynthetic characteristics of rice leaves grown under red light with or without
supplemental blue light. Plant and Cell Physiology, 45(12), 1870-1874.
McCree, K. J. (1981). Photosynthetically active radiation. In: Lange OL, Nobel PS,
Osmond, CB, Ziegler H (Eds.) Physiological Plant Ecology I. Responses to the
physical environment, Springer-Verlag Berlin, Heidelberg, pp 41– 55.
Meng, Y., Li, H., Wang, Q., Liu, B., and Lin, C. (2013). Blue light–dependent
interaction between cryptochrome2 and CIB1 regulates transcription and leaf
senescence in soybean. The Plant Cell, 25(11), 4405-4420.
Menzel, A. (2002). Phenology: its importance to the global change community.
Climatic Change, 54(4), 379-385.
Miao, Y. X., Wang, X. Z, Gao, L. H., Chen, Q. Y., and Mei, Q. U. (2016). Blue light is
more essential than red light for maintaining the activities of photosystem II and I
55
and photosynthetic electron transport capacity in cucumber leaves. Journal of
Integrative Agriculture, 15(1), 87-100.
Middleton, E. M., and Teramura, A. H. (1993). The role of flavonol glycosides and
carotenoids in protecting soybean from ultraviolet-B damage. Plant Physiology,
103(3), 741-752.
Mølmann, J. A., Junttila, O., Johnsen, Ø., and Olsen, J. E. (2006). Effects of red, far‐
red and blue light in maintaining growth in latitudinal populations of Norway
spruce (Picea abies). Plant, Cell and Environment, 29(2), 166-172.
Morales, L.O., Brosché, M., Vainonen, J., Jenkins, G.I., Wargent, J.J., Sipari, N.,
Strid, Å., Lindfors, A.V., Tegelberg, R. and Aphalo, P.J., (2013). Multiple roles for
UV RESISTANCE LOCUS8 in regulating gene expression and metabolite
accumulation in Arabidopsis under solar ultraviolet radiation. Plant Physiology,
161(2), 744-759.
Morales, L. O., Tegelberg, R., Brosche, M., Keinänen, M., Lindfors, A., and Aphalo, P.
J. (2010). Effects of solar UV-A and UV-B radiation on gene expression and phenolic
accumulation in Betula pendula leaves. Tree Physiology, 30(7), 923-934.
Muleo, R., Morini, S., and Casano, S. (2001). Photoregulation of growth and
branching of plum shoots: physiological action of two photosystems. In Vitro
Cellular and Developmental Biology-Plant, 37(5), 609-617.
Murchie, E. H., and Lawson, T. (2013). Chlorophyll fluorescence analysis: a guide to
good practice and understanding some new applications. Journal of Experimental
Botany, 64(13), 3983-3998.
Murray, M. B., Cannell, M. G. R., and Smith, R. I. (1989). Date of budburst of fifteen
tree species in Britain following climatic warming. Journal of Applied Ecology 26(2),
693-700.
Myking, T., Heide, O. M. (1995). Dormancy release and chilling requirement of buds
of latitudinal ecotypes of Betula pendula and B. pubescens. Tree Physiology, 15(11),
697–704.
Olson, M. S., Levsen N., Soolanayakanahally, R. Y., Guy, R. D., Schroeder R. W.,
Keller, S. R., and Tiffin, P. (2013). The adaptive potential of Populus balsamifera L.
to phenology requirements in a warmer global climate. Molecular Ecology, 22(5),
1214–1230.
Onda, Y., Yagi, Y., Saito, Y., Takenaka, N., and Toyoshima, Y. (2008). Light induction
of Arabidopsis SIG1 and SIG5 transcripts in mature leaves: differential roles of
cryptochrome 1 and cryptochrome 2 and dual function of SIG5 in the recognition of
plastid promoters. The Plant Journal, 55(6), 968-978.
Osada, N., Murase, K., Tsuji, K., Sawada, H., Nunokawa, K., Tsukahara, M., Hiura, T.
(2018). Genetic differentiation in the timing of budburst in Fagus crenata in relation
56
to temperature and photoperiod. International Journal of Biometeorology, 62(9),
1763–1776.
Peñuelas, J. and Iolanda F. (2009). Phenology feedbacks on climate change. Science
324(5929), 887-888.
Pescheck, F., and Bilger, W. (2019). High impact of seasonal temperature changes on
acclimation of photoprotection and radiation-induced damage in field grown
Arabidopsis thaliana. Plant Physiology and Biochemistry, 134, 129-136.
Phoenix, G. K., Gwynn‐Jones, D., Callaghan, T. V., Sleep, D., and Lee, J. A. (2001).
Effects of global change on a sub‐Arctic heath: effects of enhanced UV‐B radiation
and increased summer precipitation. Journal of Ecology, 89(2), 256-267.
Polgar, C., Gallinat, A., and Primack, R. B. (2014). Drivers of leaf‐out phenology and
their implications for species invasions: insights from Thoreau's Concord. New
Phytologist, 202(1), 106-115.
Price, M. V., and Waser, N. M. (1998). Effects of experimental warming on plant
reproductive phenology in a subalpine meadow. Ecology, 79(4), 1261-1271.
Primack, R. B., Laube, J., Gallinat, A. S., and Menzel, A. (2015). From observations to
experiments in phenology research: investigating climate change impacts on trees
and shrubs using dormant twigs. Annals of Botany, 116(6), 889-897.
Primack, R. B., and Miller-Rushing, A. J. (2012). Uncovering, collecting, and
analyzing records to investigate the ecological impacts of climate change: a template
from Thoreau's Concord. BioScience, 62(2), 170-181.
Rai, N., Neugart, S., Yan, Y., Wang, F., Siipola, S. M., Lindfors, A. V., Winkler, J. B.,
Albert, A., Brosché, M., Lehto, T. and Morales, L.O. (2019). How do cryptochromes
and UVR8 interact in natural and simulated sunlight? Journal of Experimental
Botany, 70(18), 4975-4990.
Renner, S. S., and Zohner, C. M. (2019). The occurrence of red and yellow autumn
leaves explained by regional differences in insolation and temperature. New
Phytologist, 224(4), 1464-1471.
Rice, K. E., Montgomery, R. A., Stefanski, A., Rich, R. L., and Reich, P. B. (2018).
Experimental warming advances phenology of groundlayer plants at the boreal‐
temperate forest ecotone. American Journal of Botany, 105(5), 851-861.
Rinne, P., Saarelainen, A., Junttila, O. (1994a). Growth cessation and bud dormancy
in relation to ABA level in seedlings and coppice shoots of Betula pubescens as
affected by a short photoperiod, water stress and chilling. Physiologia Plantarum,
90(3), 451–458.
Rinne, P., Tuominen, H., Junttila, O. (1994b). Seasonal changes in bud dormancy in
relation to bud morphology, water and starch content, and abscisic acid
concentration in adult trees of Betula pubescens. Tree Physiology, 14(6), 549–561.
57
Richardson, A. D., and O’Keefe, J. (2009). Phenological differences between
understory and overstory. In Phenology of ecosystem processes, Springer, New
York, NY, pp. 87-117.
Rizzini, L., Favory, J.J., Cloix, C., Faggionato, D., O’Hara, A., Kaiserli, E., Baumeister,
R., Schäfer, E., Nagy, F., Jenkins, G.I. and Ulm, R., (2011) Perception of UV-B by the
Arabidopsis UVR8 protein. Science, 332(6025), 103-106.
Robertson, G. W. (1966). The light composition of solar and sky spectra available to
plants. Ecology, 47(4), 640-643.
Robson, T. M., Hartikainen, S. M., and Aphalo, P. J. (2015). How does solar
ultraviolet‐B radiation improve drought tolerance of silver birch (Betula pendula
Roth.) seedlings? Plant, Cell and Environment, 38(5), 953-967.
Robson T. M., Rasztovits, E., Aphalo, P. J., Alia, R., Aranda, I. (2013). Flushing
phenology and fitness of European beech (Fagus sylvatica L.) provenances from a
trial in La Rioja, Spain, segregate according to their climate of origin. Agricultural
and Forest Meteorology, 180, 76–85.
Robson, T. M., and Aphalo, P. J. (2019). Transmission of ultraviolet, visible and near-
infrared solar radiation to plants within a seasonal snow pack. Photochemical and
Photobiological Sciences, 18(8), 1963-1971.
Rozema, J., Van de Staaij, J., Björn, L. O., and Caldwell, M. (1997). UV-B as an
environmental factor in plant life: stress and regulation. Trends in Ecology and
Evolution, 12(1), 22-28.
Sæbø, A., Krekling, T., and Appelgren, M. (1995). Light quality affects photosynthesis
and leaf anatomy of birch plantlets in vitro. Plant Cell, Tissue and Organ Culture,
41(2), 177-185.
Sellaro, R., Crepy, M., Trupkin, S. A., Karayekov, E., Buchovsky, A. S., Rossi, C., and
Casal, J. J. (2010). Cryptochrome as a sensor of the blue/green ratio of natural
radiation in Arabidopsis. Plant Physiology, 154(1), 401-409.
Semerdjieva, S. I., Sheffield, E., Phoenix, G. K., Gwynn‐Jones, D., Callaghan, T. V.,
and Johnson, G. N. (2003). Contrasting strategies for UV‐B screening in sub‐Arctic
dwarf shrubs. Plant, Cell and Environment, 26(6), 957-964.
Siipola, S. M., Kotilainen, T., Sipari, N., Morales, L. O., Lindfors, A. V., Robson, T. M.,
and Aphalo, P. J. (2015). Epidermal UV‐A absorbance and whole‐leaf flavonoid
composition in pea respond more to solar blue light than to solar UV radiation.
Plant, Cell and Environment, 38(5), 941-952.
Smith, H. (1982). Light quality, photoperception, and plant strategy. Annual Review
of Plant Physiology, 33, 481–518.
Smith. H. & Morgan. D.C. (1983) The function of phytochrome in nature. In
Encyclopedia of Plant Physiology Vol. 16 (Ed. W. Shropshire Jr. and H. Mohr),
Springer-Verlag, Berlin, Pp 491-517.
58
Solanki, T., Aphalo, P. J., Neimane, S., Hartikainen, S. M., Pieristè, M., Shapiguzov,
A., ... and Robson, T. M. (2019). UV-screening and springtime recovery of
photosynthetic capacity in leaves of Vaccinium vitis-idaea above and below the snow
pack. Plant Physiology and Biochemistry, 134, 40-52.
Solar, A., Colarič, M., Usenik, V., and Stampar, F. (2006). Seasonal variations of
selected flavonoids, phenolic acids and quinones in annual shoots of common
walnut (Juglans regia L.). Plant Science, 170(3), 453-461.
Stafford, H. A. (1991). Flavonoid evolution: an enzymic approach. Plant Physiology,
96(3), 680-685.
Stamnes, K., Tsay, S. C., Wiscombe, W., and Jayaweera, K. (1988). Numerically stable
algorithm for discrete-ordinate-method radiative transfer in multiple scattering and
emitting layered media. Applied Optics, 27(12), 2502-2509.
Stinchcombe, J. R., Weinig, C., Ungerer, M., Olsen, K. M., Mays, C., Halldorsdottir,
S. S., Purugganan, M. D., Schmitt, J. (2004). A latitudinal cline in flowering time in
Arabidopsis thaliana modulated by the flowering time gene FRIGIDA. Proceedings
of the National Academy of Sciences 101(13), 4712–4717.
Štroch, M., Materová, Z., Vrábl, D., Karlický, V., Šigut, L., Nezval, J., and Špunda, V.
(2015). Protective effect of UV-A radiation during acclimation of the photosynthetic
apparatus to UV-B treatment. Plant Physiology and Biochemistry, 96, 90-96.
Strømme, C. B., Julkunen‐Tiitto, R., Krishna, U., Lavola, A., Olsen, J. E., and
Nybakken, L. (2015). UV‐B and temperature enhancement affect spring and autumn
phenology in Populus tremula. Plant, Cell and Environment, 38(5), 867-877.
Takahashi, S., and Badger, M. R. (2011). Photoprotection in plants: a new light on
photosystem II damage. Trends in Plant Science, 16(1), 53-60.
Taulavuori, K., Hyöky, V., Oksanen, J., Taulavuori, E., and Julkunen-Tiitto, R. (2016).
Species-specific differences in synthesis of flavonoids and phenolic acids under
increasing periods of enhanced blue light. Environmental and Experimental Botany,
121, 145-150.
Teissier du Crois, E., Le Tacon, F., Nepveu, G., Pardé, J., Timbal, J. (1981) Le hêtre.
Département des Recherches Forestières, INRA, Paris, p 613.
Terfa, M. T., Solhaug, K. A., Gislerød, H. R., Olsen, J. E., and Torre, S. (2013). A high
proportion of blue light increases the photosynthesis capacity and leaf formation
rate of Rosa× hybrida but does not affect time to flower opening. Physiologia
Plantarum, 148(1), 146-159.
Thum, K. E., Kim, M., Morishige, D. T., Eibl, C., Koop, H. U., and Mullet, J. E. (2001).
Analysis of barley chloroplast psbD light-responsive promoter elements in
transplastomic tobacco. Plant Molecular Biology, 47(3), 353-366.
Tsunoyama, Y., Ishizaki, Y., Morikawa, K., Kobori, M., Nakahira, Y., Takeba, G.,
Toshinori, Y., Shiina, T. (2004). Blue light-induced transcription of plastid-encoded
59
psbD gene is mediated by a nuclear-encoded transcription initiation factor, AtSig5.
Proceedings of the National Academy of Science 101(9), 3304–3309.
Turnbull, T. L., Barlow, A. M., and Adams, M. A. (2013). Photosynthetic benefits of
ultraviolet-A to Pimelea ligustrina, a woody shrub of sub-alpine Australia.
Oecologia, 173(2), 375-385.
Uemura, S. (1994). Patterns of leaf phenology in forest understory. Canadian Journal
of Botany, 72(4), 409-414.
Urban, O., Klem, K., Ač, A., Havránková, K., Holišová, P., Navrátil, M., ... and
Tomášková, I. (2012). Impact of clear and cloudy sky conditions on the vertical
distribution of photosynthetic CO2 uptake within a spruce canopy. Functional
Ecology, 26(1), 46-55.
Urban, O., Janouŝ, D., Acosta, M., Czerný, R., Marková, I., Navratil, M., Pavelka, M.,
Pokorný, R., Šprtová, M., Zhang, R. and Špunda, V., (2007). Ecophysiological
controls over the net ecosystem exchange of mountain spruce stand. Comparison of
the response in direct vs. diffuse solar radiation. Global Change Biology, 13(1), 157-
168.
Vaartaja, O. (1959). Evidence of photoperiodic ecotypes in trees. Ecological
Monographs, 29(2), 91–111.
Victorio, C. P., Leal‐Costa, M. V., Schwartz Tavares, E., Machado Kuster, R., and
Salgueiro Lage, C. L. (2011). Effects of supplemental UV‐A on the development,
anatomy and metabolite production of Phyllanthus tenellus cultured in vitro.
Photochemistry and Photobiology, 87(3), 685-689.
Vitasse, Y. (2013). Ontogenic changes rather than difference in temperature cause
understory trees to leaf out earlier. New Phytologist, 198(1), 149-155.
Vitasse, Y., and Basler, D. (2014). Is the use of cuttings a good proxy to explore
phenological responses of temperate forests in warming and photoperiod
experiments? Tree Physiology, 34(2), 174-183.
Vitasse, Y., Delzon, S., Dufrêne, E., Pontailler, J. Y., Louvet, J. M., Kremer, A., and
Michalet, R. (2009). Leaf phenology sensitivity to temperature in European trees:
do within-species populations exhibit similar responses? Agricultural and forest
meteorology, 149(5), 735-744.
Vitasse, Y., François, C., Delpierre, N., Dufrêne, E., Kremer, A., Chuine, I., and
Delzon, S. (2011). Assessing the effects of climate change on the phenology of
European temperate trees. Agricultural and Forest Meteorology, 151(7), 969-980.
Wang, Y., Gao, L., Shan, Y., Liu, Y., Tian, Y., and Xia, T. (2012). Influence of shade on
flavonoid biosynthesis in tea (Camellia sinensis (L.) O. Kuntze). Scientia
Horticulturae, 141, 7-16.
Wargent, J. J., Elfadly, E. M., Moore, J. P., and Paul, N. D. (2011). Increased exposure
to UV‐B radiation during early development leads to enhanced photoprotection and
60
improved long‐term performance in Lactuca sativa. Plant, Cell and Environment,
34(8), 1401-1413.
Waterman, M. J., Bramley-Alves, J., Miller, R. E., Keller, P. A., and Robinson, S. A.
(2018). Photoprotection enhanced by red cell wall pigments in three East Antarctic
mosses. Biological Research, 51(1), 49.
Way, D. A., Montgomery, R. A. (2015). Photoperiod constraints on tree phenology,
performance and migration in a warming world. Plant, Cell and Environment,
38(9), 1725–1736.
Welling, A., and Palva, E. T. (2006). Molecular control of cold acclimation in trees.
Physiologia Plantarum, 127(2), 167-181.
Wesołowski, T., and Rowiński, P. (2006). Timing of bud burst and tree-leaf
development in a multispecies temperate forest. Forest Ecology and Management,
237(1-3), 387-393.
Wilkinson, D. M., Sherratt, T. N., Phillip, D. M., Wratten, S. D., Dixon, A. F., and
Young, A. J. (2002). The adaptive significance of autumn leaf colours. Oikos, 99(2),
402-407.
Ylianttila, L., Visuri, R., Huurto, L., and Jokela, K. (2005). Evaluation of a Single‐
monochromator Diode Array Spectroradiometer for Sunbed UV‐radiation
Measurements. Photochemistry and Photobiology, 81(2), 333-341.
Young, A. J. (1991). The photoprotective role of carotenoids in higher plants.
Physiologia Plantarum, 83(4), 702-708.
Zeuthen, J., Mikkelsen, T. N., Paludan‐Müller, G., and Ro‐Poulsen, H. (1997). Effects
of increased UV‐B radiation and elevated levels of tropospheric ozone on
physiological processes in European beech (Fagus sylvatica). Physiologia
Plantarum, 100(2), 281-290.
Zhang, Q., Li, H., Li, R., Hu, R., Fan, C., Chen, F., Wang, Z., Liu, X., Fu, Y., and Lin,
C. (2008). Association of the circadian rhythmic expression of GmCRY1a with a
latitudinal cline in photoperiodic flowering of soybean. Proceedings of the National
Academy of Sciences, 105(52), 21028–21033.
Zhang, Y. J., Yang, Q. Y., Lee, D. W., Goldstein, G., and Cao, K. F. (2013). Extended
leaf senescence promotes carbon gain and nutrient resorption: importance of
maintaining winter photosynthesis in subtropical forests. Oecologia, 173(3), 721-
730.
Zohner, C. M., Benito, B. M., Svenning, J. C., and Renner, S. S. (2016). Day length
unlikely to constrain climate-driven shifts in leaf-out times of northern woody
plants. Nature Climate Change, 6(12), 1120.
