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