Deciduous trees leaf out in the spring beginning with bud burst. Proximally, the timing of that process is triggered by temperature, but natural selection on bud burst timing may have acted in local populations through additional factors, such as frost damage, insect herbivores and fungal pathogens. Valley Oak, Quercus lobata Née, is a deciduous California endemic tree species that shapes the ecosystems where it is found. We examined the phenology of spring bud burst in trees collected from 674 maternal families across the species range, grown in two replicate common gardens. We found significant differences among the families for timing of bud burst, and also found that onset of bud burst differed between gardens, presumably due to climate. The differences among families were associated with the climate of origin where the trees were collected suggesting that some extent of genetic differentiation in bud burst is due to local adaptation. Given predicted changes in climate in California for the future, understanding patterns of bud burst will help inform the selection of seed sources for reforestation efforts.
Phenology, the timing of events in a tree's annual life cycle, is critical for the fitness of the tree. Resulting from complex interactions between the environment and genetically controlled responses, phenology determines the length of the growing season and possibly the annual growth as well (e.g., Polgar and Primack 2011). Selection by many factors, such as frost damage, herbivory and foliar pathogens, can shape the timing of bud burst. Newly emerged leaves are generally highly sensitive to frost, such that selection associated with cold temperatures has shaped the timing of bud burst in several tree species (Vitasse et al. 2013; Augspurger 2009). In addition, several studies have reported damage by herbivores when leaves first emerge, indicating a relationship between phenology and levels of herbivore damage (Visser et al. 2006; Pearse et al. 2015; Wood and Pidgeon 2015). Finally, foliar pathogens, such as powdery mildew, have also been implicated in causing selection on the timing of leafing out in oaks (Dantec et al. 2015). In some cases, selection acts in opposition. For example, early emergence may create more risk of frost but may also result in less powdery mildew (Dantec et al. 2015). Additionally, selection to increase the number of days for leaves to photosynthesize through earlier bud burst may be countered by selection to avoid early frost. Thus, the combination of these factors will affect growth in plants, which is an important component of fitness.
The extent to which geographical patterns of bud burst timing are genetically or environmentally influenced is key to discussions of assisted migration (Aitken and Bemmels 2016). When seeds are moved and planted into a new location, they carry the genetic information that adapted them to their home environment. The timing of bud burst in their new habitat will have a profound impact on their fitness going forward, particularly because the timing of bud burst and flowering is linked developmentally in reproductive oak trees. Understanding how the climate where an acorn is collected impacts the timing of bud burst in a new planting location will help inform seed transfer guidelines. Moreover, in a changing climate, knowing the relationship between climate of origin and timing of bud burst will allow for more nuanced seed transfer guidelines that take into account not only the current climate at a planting location, but also population data that are modeled based on predicted future climates (e.g., see Browne et al. 2019).
Valley Oak, Quercus lobata Née, is an iconic oak species, endemic to California (Pavlik et al. 1995). It is mainly distributed around the California central valley and is found as far south as the Transverse Ranges, and north past Redding (Griffin and Critchfield 1972). A winter deciduous tree, Valley Oak begins to leaf out in the early spring, though the extent of marcescence (the retention of dead leaves) varies within the species and populations (Sork and Wright unpublished data; Karban 2007). It is considered a foundational species and dominates the habitats where it is found. In addition, oaks are an important cultural and nutritional resource for Native American peoples (Anderson 2007).
To assess genetic differences and phenotypic variation among Valley Oak maternal families collected from localities (provenances) for a variety of traits, we established a provenance test in 2014 (Delfino Mix et al. 2015), using 2-yr old seedlings planted into two contrasting field sites: the Institute of Forest Genetics (IFG), Placerville, CA and the Chico Seed Orchard (Chico), Chico, CA. Every year since planting, we have recorded spring leaf emergence as a measure of tree phenology through weekly surveys of tree buds. We have observed significant genetic differentiation and phenotypic plasticity in a range of leaf traits and progeny height (MacDonald 2017), as well as climate-associated relative growth rates (Browne et al. 2019). Here, we focus on differences in phenological patterns within the species by addressing the following questions: (1) Is there genetic variation for the timing of bud burst in a common garden study? And (2) Is the timing of bud burst associated with climate of origin? We then discuss the genetic and environmental basis for this timing in oak management and restoration projects.
Methods
Establishment of the Test- Acorn Collection, Planting Sites
In 2012, acorns were collected from 674 maternal trees at 95 different sites across the species range. Over 11,000 acorns were germinated at the USDA-Forest Service, PSW Institute of Forest Genetics in Placerville, CA (IFG) (38.740, –120.738) (see Fig. S1 in Browne et al. 2019 for a map). Details of the collections, germination and early growth are given in Delfino Mix et al. (2015). Nearly 7000 seedlings were planted in the field during the winter of 2014/2015 at two replicate sites: IFG and the USDA Forest Service Chico Seed Orchard (Chico) in Chico, CA (39.708, –120.780). Trees were irrigated each summer at both field sites. Weeds were controlled with a combination of herbicide and mechanical control.
Collection of Bud Burst Data
At the beginning of each growing season (approximately February 1), trees were scored weekly for their leaf development (see Appendix S1 for sample sizes at each site and year). During each survey, we assigned each tree a score ranging from 0 (no sign of bud burst) to 5 (leaves fully unfolded), following the bud burst stages identified by Derory et al. (2006), who correlated differential transcriptome expression patterns with bud burst stages in Quercus petraea (Matt.) Liebl.
Climate Data
For each of the maternal family collection locational coordinates (GPS data were taken when acorns were collected), we obtained estimated historical climate data from the Basin Characterization Model (Flint et al. 2013) using the 1951 to 1980 30-yr average data. We extracted data for the following climate variables: bioclim_01 through bioclim_19, AET (actual evapotranspiration) and CWD (climatic water deficit) ( https://worldclim.org/data/bioclim.html; Flint et al. 2013). Analysis revealed strong correlations among temperature and precipitation variables. We selected a set of climate variables to analyze that had correlations < 0.80 among variables: bioclim_02 (mean diurnal range), bioclim_04 (temperature seasonality), bioclim_05 (maximum temperature of the warmest month), bioclim_06 (minimum temperature of the coldest month), bioclim_13 (precipitation of the wettest month), bioclim_14 (precipitation of the driest month), bioclim_15 (precipitation seasonality), and AET (actual evapotranspiration). Only two sets of climate variables correlated with each other highly: bioclim_04 and bioclim_05 (r = 0.705) and bioclim_13 and AET (r = 0.775) (Appendix S2).
Data Analysis
For each tree at each site and year, we calculated the date that the first sign of bud burst was observed. Often that was Stage 1, but if the tree was developing quickly, it could have been a higher stage. That date was scored as number of days from January 1 and was used as the bud burst response for subsequent analyses. Chico and IFG had two differences that we accounted for in our analysis. At Chico, the trees were planted in three different planting areas across the site. In addition, there were multiple observers each year recording data. At IFG, however, there was a single planting area, and one primary observer.
To assess whether the maternal families varied for date of first bud burst and to account for possible effects of observer and planting area in Chico, we used a mixed model GLM (PROC MIXED in SAS 9.4, SAS Institute, Cary, NC; Littell et al. 1996), with year considered a fixed effect, and observer, planting area and maternal families as random effects. We included observer as a nested effect within year, as the observers differed each year. From this analysis, we estimated the Best Linear Unbiased Predictors (BLUPs) for each maternal family and used those values for subsequent analyses. At IFG, a similar mixed model was run, but it did not include planting area or observer, simply year and maternal family, because there was only one primary observer and one planting area.
For both analyses, the “covtest” option was selected, giving a test of the significance of the random effects using a Wald Score. In addition, we confirmed the Wald Score results using a chi-square test of the differences between Log-Likelihood scores for models with and without the random effect of maternal family. The P-value, derived from a chi-square distribution with a degree of freedom = 1, was divided by two to make it a two-tailed test (Littell et al. 1996).
To estimate associations between parental climate and timing of bud burst in the two field sites, a multiple regression model selection was used, with the LASSO selection procedure (Efron et al. 2004). We ran models separately for each site, using BLUPs obtained for maternal families in the mixed model described above as observations for the maternal families in the experiment. BLUPs controlled for variation among observers, planting areas and years, and therefore represent the constitutive bud burst patterns of the maternal families. We included the selected climate variables described above, as well as the latitude, longitude, and elevation of the parental trees. To facilitate comparison among variables, we calculated standardized estimates for the predictors using the “stb” option in the model statement. For raw maternal family means and BLUPs as well as the complete data set see Appendices S3, S4 and S5 stored in FigShare ( https://doi.org/10.6084/m9.figshare.14524338).
To test for a significant difference between planting sites and years and their interaction, we used a simplified mixed effect model, with the fixed effects of site and year, and the random effect of maternal family. Because the other sources of variation (planting area and observer) were not balanced between the two sites, we did not include them in the analysis. This model provides a conservative estimate of the effects of site and year, because not all sources of variation are included in it. However, the effects that were included in the model accounted for a sufficiently large portion of the variation that including any additional effects in the model would not change the interpretation of the results.
Results
The calendar day of initiation of bud burst ranged from 38–155 across the two sites and years (January 1 = day 1). At IFG, bud burst started later than Chico, with dates that ranged from 42 to 155, with an average of 94.1 (±0.14 SE) and 99.2 (±0.18 SE) in 2018 and 2019 respectively, while at Chico they ranged from 38–130 with an average of 91.3 (±0.21 SE) and 87.8 (±0.19 SE) in 2018 and 2019. We found significant variation in the timing of bud burst between sites and years, as well as an interaction between the two (Table 1, Fig. 1). Our comparison of variation in bud burst among the maternal families revealed a significant result for both the Wald Score test, as well as the Log-Likelihood Ratio Test at both sites, suggesting significant genetic variation among maternal families was observed for this trait (Table 2).
Table 1.
Generalized Mixed Models for Date of First Bud Burst and the Fixed Effects of Year and Site. The model included the random effect of maternal family, which is more completely analyzed in Table 2.
Fig. 1.
Least squared means from a GLMM of the interaction between site and year from a model that included maternal family as a random effect.
Table 2.
Generalized Mixed Models for Date of First Bud Burst. A. Chico. This model includes the fixed effect of year, and the random effects of maternal family, section and observer. B. IFG. This model includes the fixed effect of year and the random effect of maternal family. An asterisk (*) indicates results were confirmed using a Log-Likelihood Ratio Test (see Methods).
To assess whether differences among families were associated with climate of origin, we used multiple regression with the LASSO model selection technique, and we identified five climate variables, as well as elevation and longitude of the maternal trees that were associated with the date of first bud burst (Table 3, Fig. 2). Two of these were associated with precipitation (Bioclim_13 and 14 – precipitation of the wettest month and precipitation of the driest month, respectively), and two were associated with temperature (Bioclim_02 and 05 – diurnal range and maximum temperature in the warmest month). Evapotranspiration was also associated with bud burst, but only at the Chico site (Table 3, Fig. 2).
Table 3.
Lasso Regression Model Selection Results for Each Site. Chico adjusted R2 = 0.2778; IFG adjusted R2 = 0.3408.
Fig. 2.
Scatter plots of the average date of first bud burst for each maternal family of Quercus lobata grown in two replicate common gardens at each planting site and year for each source site variable (each marker represents the average of one family). A. Bioclim 5: Max Temperature of Warmest Month, B. Bioclim 13: Precipitation of Wettest Month. IFG is shown in open triangles, Chico is solid circles. 2018 is in black, and 2019 in grey. Linear regression lines: larger dashes show IFG, smaller dashes show Chico. 2018 is shown in black, and 2018 is shown in grey.
Discussion
Our experiment demonstrates that variation in the timing of bud burst in Valley Oak is due to genetic differentiation. We found significant associations with climate, as well as the elevation and longitude where the trees came from, but not the latitude of their home origin, which indicates that local temperatures may have played a greater role in phenology than daylength. Differences among maternal families when grown in a common garden were statistically significant, which demonstrates a genetic basis to bud burst timing. A number of other studies have looked at the timing of bud burst in deciduous tree species grown in common gardens. Papper and Ackerly (2021, this issue) studying phenological variation in Blue Oak (Quercus douglasii Hook & Arn.) trees in a common garden found a strong, significant effect of both the planting environment and genetics. Alberto et al. (2011) documented significant heritability for bud burst in a European study of Q. petraea with 10 populations sampled across an altitudinal gradient, looking at 1-yr old seedlings growing in a greenhouse environment. In another study of seven tree species, Vitasse et al. (2013) observed strong evidence for genetic differences in bud burst, while Pearse et al. (2015) tested family effects in Q. lobata and also found evidence for genetic differences.
We found that the timing of bud burst was associated with climate, as well as the elevation and longitude of origin, which are likely to be surrogates for climate variables. Alberto et al. (2011) also found that trees from warmer sites had earlier bud burst, as did Papper and Ackerly (2021, this issue). Higher elevation has been associated with later bud burst in a number of studies of trees grown in common gardens (Deans and Harvey 1995; Vitasse et al. 2009; Firmat et al. 2017). In addition, we found that trees from warmer environments had earlier bud burst, consistent with a number of other studies that have shown increased temperature of origin is associated with earlier bud burst (Alberto et al. 2011; Sampaio et al. 2016; Dewan et al. 2020).
Our data provide evidence that bud burst timing varies with the environment. We found that trees growing in Chico burst bud earlier in the year on average than trees growing at the higher-elevation, colder IFG site in both years. There is an approximate difference in elevation between the two sites of 770 m and 2.8 and 11.3 d between the average bud burst date for the two sites in 2018 and 2019 respectively. Vitesse et al. (2013) found similar results, with leafing out date later at higher elevation planting sites for seven trees species. Koenig et al. (2021, this issue) examined bud burst date in Valley Oak over a 30-yr period, and found that warmer temperatures were associated with earlier bud burst. Studies that used artificial warming to examine the impact of increased temperatures on phenology have found that warmer temperatures are associated with earlier leafing out dates (Morin et al. 2010; Fu et al. 2013; Fu et al. 2016; Dewan et al. 2020; Faticov et al. 2020). Thus, in addition to the genetic basis of bud burst timing, the environment can influence when leaves emerge.
Valley Oaks are threatened by climate change, wildfires and land use changes (Tyler et al. 2006; Sork et al. 2010). As such, they are often the focus of reforestation projects where acorns must be chosen for use in reforestation planting. Several factors can be considered in this choice. The first is climate of origin. Climate models predict increasing temperatures throughout California (Thorne et al. 2017), thus selecting trees adapted to a warmer climate may increase the success of reforestation projects. Given that such trees are likely to break bud earlier than locally-derived seedlings, they may benefit from a longer growing season than local genotypes. Although multiple studies have shown that earlier bud burst is associated with earlier fall leaf senescence in Eastern US and European deciduous trees (Keenan and Richardson 2015; Zani et al. 2020), our observations of Valley Oak saplings in the two common gardens indicated that overall bud break was earlier and marcescence was longer for all provenances at the warmer site (Wright and Sork unpublished data). Thus, the timing of bud burst seems to have both a genetic basis associated with maternal site and a degree of plasticity shaped by the temperature of the planting site. In terms of phenology, the biggest risk of planting progeny derived from warmer sites into cooler sites for the sake of future warmer climates would be the possibility of damage from a late frost in the spring, as well as being more vulnerable to early-season herbivory (Pearse et al. 2015). The extent of these problems would need to be assessed. A potential additional problem may be early flowering as the progeny become reproductive adults, given the fact that bud burst and flowering are developmentally linked. Such early flowering may be asynchronous with the rest of the population and result in lower acorn production (see Koenig et al. 2012). Given the long flowering season of Valley Oaks (typically early February through early April; Lentz and Sork unpublished data) and the fact that restored populations may include individuals from many localities, the possible risk of asynchronous bud burst and flowering in human-managed populations may be less a concern relative to the benefits of genotypes adapted to warmer conditions. Nonetheless, projects considering assisted migration can keep these risks in mind. Phenology is clearly an important and complex trait to consider when selecting seeds for reforestation projects.
Acknowledgments
We acknowledge the native peoples of California as the traditional caretakers of the oak ecosystems sampled for this project. We thank Annette Delfino Mix, Robin Scibillio, and Lisa Crane for their care of the two test sites; R. Boynton, E. Estrada, J. Fucigna, J. Garcia, P. Munson, C. Raether, R. Schafer, K. Shaprio, K. Spratt, A. Sullivan, J. Vang, and E. Wilkerson for field assistance. This work was funded in part by the USDA Forest Service as well as CALFIRE agreement 8CA04059. Any use of product names is for informational purposes only and does not imply endorsement by the U.S. Government. The findings and conclusions in this publication are those of the authors and should not be construed to represent any official USDA or US Government determination or policy.
