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General discussion
In this Ph.D. thesis various aspects of mast behaviour in the main European forest tree species were explored. The function of weather conditions as triggers and inhibitors of mast years were investigated for Scots pine (Pinus sylvestris L., hereafter pine), Norway spruce (Picea abies [L.] Karst., hereafter spruce), European beech (Fagus sylvatica L., hereafter beech), and sessile and pedunculate oak (Quercus petraea [Matt.] Liebl. and Quercus robur L., hereafter oak; Chapters I and II; Figs. 1-3). The changes in vegetative growth and nutrient concentrations during and after mast years and the resource dynamics mechanisms behind mast years were investigated for beech and oak (Chapter III; Figs. 2, 3). These insights allow a better understanding of the underlying processes of mast behaviour and provide broader knowledge for future forest management strategies as well as for ecological modelling of forest dynamics research questions which include mast related topics. The results of the research questions raised in the general introduction will be discussed.
Measurement methods for mast occurrence and possible future challenges of the focal species apropos generative growth and current climate change will be addressed.
Which weather conditions are triggers for mast years in the focal species and how spatially consistent are these weather conditions at a continental scale?
Pine
Weather conditions leading to mast years could be found for all of the investigated species, except for pine (Chapter I; Fig. 1a). As previously described (Wauters et al. 2001; 2004;
Bisi et al. 2016; Nussbaumer et al. 2016), this species does not show strong annual variability in fruit production and does not synchronise its flowering as consistently as the other focal species (Nussbaumer et al. 2016). According to Geburek et al. (2012) and Pearse et al. (2016) pine shows signs of a non-masting pollen producer and fruit maturation masting species which means that it produces high amounts of pollen every year without necessarily being followed by high fruit production. Pine does not seem to be a masting species sensu stricto and, therefore, is likely to be less dependent on distinct weather conditions to produce seeds than other forest tree species. Thus, the differences found between the regions may be accidental.
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Figure 1 Changes in resource allocation to generative growth in the two years before mast years and impact of weather cues in the two years before mast years and in the mast years for a Scots pine and b Norway spruce in Europe. In grey: weather conditions have no impact in the specific season.
Original artwork by Anita Nussbaumer.
Spruce and beech
For spruce and beech, weather conditions in the two summers before a mast year were the main explanatory factors to drive high fruit production (Figs. 1b, 2). For spruce, a cool (and dry) summer, followed by a warm and dry summer, led to a mast year in the following year.
This is in accordance with earlier findings in the Alps (Bisi et al. 2016), Southern Sweden (Selås et al. 2002), and Norway (Solberg 2004). Weather conditions inducing mast years in beech were generally similar to those of spruce, but two years before mast years, summers
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were wet and cold instead of dry and cold. This has been shown for various regions in Europe before (Piovesan and Adams 2001; Drobyshev et al. 2010, 2014; Hacket-Pain 2015;
Vacchiano et al. 2017; Lebourgeois et al. 2018). Another important weather cue was a warm spring in the mast year which apparently allows successful pollination. This may be similar to the finding of Kasprzyk et al. (2014) that a dry spring is advantageous to trigger beech mast years. The results of this thesis show that spruce and beech mast events are spatially consistent at continental scale. This is in accordance with Koenig and Knops (2000) who found in a global study that species tend to synchronise their flowering over large areas. Our findings are also in agreement with the results from the previous study by Ascoli et al.
(2017) who showed that the North Atlantic Oscillation controls mast occurrence in Norway spruce and European beech over large areas. Both spruce and beech are species which produce relatively low amounts of pollen and do not produce flowers every year (masting pollen producers and flowering masting species; Geburek et al. 2012; Pearse et al. 2016).
Pollen data of the Federal Office of Meteorology and Climatology MeteoSwiss show that pollen production in those species vary strongly between years (MeteoSwiss 2020). Both species seem to be restricted in their ability to produce fruits and might, therefore, need an external trigger to induce the generation of flower buds in the year before flowering.
Oak
In contrast, for oak the only common weather cue was a warm spring in the mast year itself (Fig. 3). This was shown before in some European regions (Poland: Bogdziewicz et al. 2017;
France: Lebourgeois et al. 2018) but results were not spatially consistent. Other studies found i.a. that a dry spring can be a trigger (Kasprzyk et al. 2014) or an inhibitor (Wesolowski et al. 2015) for oak mast years in Poland. It was only recently understood that mast is triggered by a different weather condition mechanism in oak than in species such as beech and spruce (Bogdziewicz et al. 2017; Lebourgeois et al. 2018). This may be the reason why oak species were previously rather neglected in mast research as no consistent weather patterns inducing mast years could be found (but see Sork et al. 1993). Oak is not as dependent on weather conditions as spruce and beech to trigger the generation of flower buds for next year’s fruit production. According to Geburek et al. (2012) and Pearse et al.
(2016), oak species are non-masting pollen producers and fruit maturation masting species.
Therefore, only weather conditions during the pollination period, i.e. an abrupt change from cool to warm and dry weather to synchronise the beginning of flowering (and the absence of frost, heavy rain or hail) are important for successful mast years.
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Do inhibiting environmental or internal factors exist which prevent mast occurrence in the focal species?
In the investigated species, high fruit production in one year showed different impacts on fruit production in the following year (Chapter I). In pine, fruiting levels in the year prior to a mast year were high in all regions, and were more important than any weather cue (Fig.
1a). This is again in accordance with the assumption that pine is not a masting species sensu stricto (Bisi et al. 2016; Nussbaumer et al. 2016). For spruce, fruiting levels were also high in the year before a mast year at continental scale, but this effect was not consistent between the regions. In several regions, fruiting levels were significantly low (Fig. 1b). For beech, fruiting levels in the year before a mast year was not important (Fig. 2). The oak species showed a similar pattern as pine with high fruiting levels in the year before a mast year, although this effect was not present in all regions. This result adds to the support of the assumption that oak species are prepared for fruit production every year (Geburek et al.
2012; Pearse et al. 2016). In contrast to the findings in Chapter I, the temporal analysis of fruit production via superposed epoch analysis in Chapter III showed that fruit production levels were low in the two years before and after the mast year in beech and oak (Figs. 2, 3). In beech, however, fruiting levels were not significantly lower two years before a mast year which is in accordance with the findings that in the last two decades, beech showed an almost two-year mast cycle in various European regions (Nussbaumer et al. 2016; Chapter II of this thesis). The differences between the results in Chapter I and Chapter III for the deciduous species regarding fruiting intensity / fruit biomass production in the two years before the mast year could further be explained by the analysis of two different parameters for mast year definition. In Chapter I, fruiting intensity of the crown condition survey was used which is assessed during summer while in Chapter III, fruit biomass production was analysed which mainly reflects the amount of ripe fruits in autumn. As has been shown in Chapter II (see also next paragraph), these two assessment methods can show different fruiting levels in the same year if trees fail to complete fruit development.
In beech during the very hot and dry summer 2018 in Switzerland, fruit maturation was interrupted and trees aborted their developing beechnuts or empty cupulas. Beech pollen data showed that 2018 was a flowering year with very high pollen loads measured in spring (MeteoSwiss 2020). During the annual crown condition survey of the Sanasilva programme (Level I plots of Switzerland) in early summer, beech fruit development still looked normal (C. Hug, per comment). However, from late July to mid-August, beech trees on the Swiss plateau, the Jura mountains and the eastern Prealps started to turn brown and shed their lea-
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Figure 2 Changes in resource allocation to generative and vegetative growth in the two years before mast years, mast years, and the two years after mast years, and impact of weather cues in the two years before mast years and in the mast years forEuropean beech in Europe. Fruit production can be high or low two years before and after mast years. In grey: weather conditions have no impact in the specific season. Original artwork by Anita Nussbaumer.
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Figure 3 Changes in resource allocation to generative and vegetative growth in the two years before mast years, mast years, and the two years after mast years, and impact of weather cues in the two years before mast years and in the mast years forsessile and pedunculate oak a in Europe. In grey: weather conditions have no impact in the specific season. Original artwork by Anita Nussbaumer.
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ves. At the same time, they stopped fruit development. On the three long-term Level II beech plots of Switzerland other years with similar conditions could be singled out. Years with high pollen loads in spring and low fruiting levels in autumn were present in the 14- and 18-year long litterfall series on two of the three plots. Comparing these 18-years with mast failure with years with high fruiting levels revealed that very high summer temperatures and very low precipitation sums act as an environmental veto for masting in beech (Fig. 2). Other environmental vetoes for masting have been explored before, such as late frost hindering successful pollination in oak (Bogdziewicz et al. 2018; 2019). For beech, however, such an environmental veto has been scientifically described for the first time in this Ph.D. project (Chapter II).
How does vegetative tree growth change when mast years occur?
The investigated deciduous species beech and pedunculate and sessile oak showed very different changes in vegetative tree growth during and after mast years (Figs. 2, 3). For beech, stem growth and leaf production were significantly enhanced in the two years before a mast year. During the mast year, stem growth was significantly reduced in two of the three analysed climate regions (warm temperate region and moderate temperate region). The analysis of different climate regions showed that this effect was not present on the cool temperate plots in the lower parts of the arc of the Alps which is near the distribution limit of beech. Here, leaf production, not stem growth, was reduced. Low leaf production during mast years was also present in the analysis of the three Swiss Level II plots (Chapter II). In contrast, in the warmer and drier two regions leaf production was not reduced. In oak, while stem growth was also enhanced in the year before a mast year, high fruit production during the mast year had no immediate effect on stem growth. This is in contradiction with previous studies which showed evidence for resource matching in both focal oak species (Askeyev et al. 2005; Lebourgeois et al. 2018). In the two years after the mast year, stem growth was reduced in the warm temperate region. While in both species, mass of 100 leaves was reduced during mast years, oak did not show a reduction in total leaf biomass production.
Oak apparently is able to compensate for smaller individual leaf biomass by producing more leaves. In contrast, beech was not able to compensate for the smaller leaves in the cool temperate region.
Leaf carbon (C) concentration during mast years did not differ from years with low fruit production in beech and oak. For beech, it can be assumed that C accumulation takes place in the years before a mast year when leaf production and, consequently, photosynthetic
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capacity is enhanced. This stored C, however, will not be used for fruit production but for vegetative growth, as shown by Hoch et al. (2013), Ichie et al. (2013) and Han and Kabeya (2017). According to their studies, C invested in fruits originate from current leaves. For oak, there are no signs for C accumulation in the years before a mast year as leaf production was not enhanced in those years.
In contrast to previous studies investigating nutrient dynamics during mast years (Han et al.
2011; Müller-Haubold et al. 2015; Jonard et al. 2009), leaf nitrogen (N) and phosphorus (P) concentrations were not reduced in the deciduous focal species and even enhanced in beech, although this effect was mostly site-specific. According to Pearse et al. (2016), N is likely to be the most prone nutrient for resource depletion. The absence of a depletion effect in oak and even an enhancement of N and P concnetrations in beech during mast years suggests that on the investigated plots fruit production is not hampered by limited nutrient supply.
Which resource dynamics mechanisms are involved in fruit and leaf production, and stem growth of the investigated species?
The comparison of the three most abundant European deciduous tree species showed that beech and oak follow different resource dynamics mechanisms. Beech is a species which accumulates resources before a mast year (Isagi et al. 1997; Satake and Iwasa 2000; Masaka and Maguchi, 2001; Monks and Kelly, 2006; Crone and Rapp, 2014; Han et al. 2014; Abe et al., 2016; Pearse et al., 2016; Pesendorfer et al., 2016; Venner et al., 2016; Bogdziewicz et al. 2018, 2020a). It shows resource switching from vegetative to generative growth during mast years (Kelly 1994; Pearse et al. 2016; Bogdziewicz et al. 2020a). In the years after the mast year, there were no signs for resource depletion other than the absence of high beechnut production which is expected due to the assumption that beech seldom shows consecutive mast years (but see Hilton and Packham 2003; Nussbaumer et al. 2016). Resource switching during beech mast years has been described before for various European regions (France:
Lebourgeois et al. 2018; Germany: Eichhorn et al. 2008; South Sweden: Drobyshev et al.
2010). However, we found that for beech in the cool temperate region, resource switching did not happen from stem growth but from leaf production to fruit production. This shows that resource dynamics mechanisms can spatially vary in the same species. The underlying triggers for these mechanisms are likely to be dependent on climatic factors and site characteristics. In oak, resource accumulation was present one year before a mast year, and resource depletion with reduced stem growth occurred in the two years after the mast year (Janzen 1971; Hacket-Pain et al. 2015; Pearse et al. 2016). Thus, oak shows indication for
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the resource storage hypothesis, although resource depletion was absent in the cool temperate region.
Comparison of measurement methods for fruit production
In this Ph.D. thesis, two principal ways of measuring fruit production, qualitative (Chapter I) and quantitative (Chapter II and III) methods, were used. From a scientific point of view, annual fruit production is a continuous variable (Kelly 1994). However, a coarse categorisation often suffices to address forestry and ecological questions.
Qualitative methods include crown condition surveys where fruiting intensity is usually estimated with binoculars or the naked eye. A four-class scale is often applied which is well established in forestry (Rohmeder 1972). In the German part of Europe the terms ‘Leermast’
(=no fruits), ‘Sprengmast’ (= scarce fruits, occurs typically at the forest edge and on single trees outside the forest), ‘Halbmast’ (= half mast) and ‘Vollmast’ (= full mast, tree appearance is dominated by fruits) are established and e.g. implemented in the International Co-operative Programme on Assessment and Monitoring of Air Pollution Effects on Forests (ICP Forests) crown condition survey manual (Eichhorn et al. 2016). These estimations are usually performed during summer and register fruits on trees. Few information on the seed quality can be provided. However, for conifers which, after seed release, do not lose their empty cones for up to several years, this is a reliable way of recognising if a mast year occurred. Furthermore, similar qualitative classes are often used for data from historical sources such as seed prizes, taxes raised to allow swine herders to bring livestock into the forest for foraging, or seed quality estimations (Szabó 2015; Nussbaumer et al. 2016; T.
Ebinger, per comment).
Quantitative measuring methods include collecting methods, such as permanent litterfall traps (e.g. Ukonmaanaho et al. 2016), seed collection with large sheets (Touzot et al. 2018), or manual collection of fruits from the forest floor during the fruit fall season (Bogdziewicz et al. 2020b). In contrast, Nygren et al. (2017) used a remote sensing method by taking photographs of the tree crowns and counting Norway spruce cones. The collecting methods provide information at stand scale while the remote sensing method is used on individual trees. For forest tree species with small seeds the collecting methods cannot be easily applied to define annual fruiting intensity as seeds are light and likely to drift long distances. At the same time, cones can stay on trees for a long time. When using measurements from projects which are not specifically designed for mast behaviour, e.g. the ICP Forests litterfall survey, where seeds and cones are counted as one fraction, information on mast occurrence cannot
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be derived for most conifers. Therefore, pine and spruce had to be excluded from the analyses of Chapter III in this Ph.D. project. An exception from this methodical impediment are conifers where cones fall apart after seed release, such as Abies alba L. (Baltisberger 2009).
Collecting methods represent the amount of fruits at the end of fruit development and can differ from methods applied earlier in the year, such as the crown condition estimates or other remote sensing methods applied to tree crowns (Eichhorn et al. 2016; Ukonmaanaho et al. 2016; Nygren et al. 2017; Touzot et al. 2018; Bogdziewicz et al. 2020b). This could e.g. be seen when comparing the results of Chapter I and Chapter III (see above).
Understanding that mast data can represent a variety of different traits is crucial for interpreting and comparing results. Quantitative data were collected mostly in the last two to three decades (e.g. ICP Forests, UNECE ICP Forests 2016) or in short-term projects which can reduce its informative value. Thinking of fruit production as a continuum may be appealing for investigating quantitative research questions such as resource dynamics and carbon and nutrient cycles (see Chapter III) but can reduce the data range immensely.
On the other hand, qualitative data may suffice to investigate impacts on ecosystems and to detect general trends and mechanisms. Data aggregation of both qualitative and quantitative collection methods, therefore, offer a chance to create large long-term and geographically extended datasets to address future research questions concerning mast behaviour.
Importance of mast behaviour in the focal species in relation to future climates
The current climate change will most likely lead to rising temperatures and shifts in precipitation patterns (IPCC 2013; 2019). Temperatures are very likely to rise throughout all seasons, and precipitation patterns are likely to change with up to 40% less precipitation sums during summer and up to 30% more precipitation sums in winter (IPCC 2013).
Additionally, an increase of extreme weather events is likely to occur (Lorenz et al. 2019),
Additionally, an increase of extreme weather events is likely to occur (Lorenz et al. 2019),