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Emily T. Cox, Rachael L. Olliff-Yang
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Climate change impacts the severity and frequency of droughts in California. As a result, native plants will likely face changes in soil moisture as temperature and weather patterns shift. Lasthenia gracilis (DC.) Greene, commonly known as Needle Goldfields, is a native California wildflower distributed across broad climate gradients from northern to southern California. Therefore, this species is ideal for testing how water availability affects populations from contrasting locations across its range. In a greenhouse experiment, we measured the effects of differing water treatments on the growth and reproductive fitness of this species to explore if there is variation in response between northern and southern populations. We also measured days to germination, germination rate, and days to flowering to further compare responses among the geographically distinct populations. Individuals from most populations exhibited faster growth rates when exposed to more water. The response of reproductive output (number of inflorescences) to the treatments was reduced in populations historically exposed to drought conditions, suggesting that the southern populations have lower population plasticity for this trait. Further, individuals in five out of six populations produced inflorescences later and flowered for longer when exposed to the highest watering treatment, revealing that phenology is significantly impacted by differing water treatments. Studying the effects of limited water availability on growth and reproductive ability in plant populations across a species' geographic range can provide more complete insight into how climate change may impact a species. This study indicates the presence of relative population plasticity in response to drought, which may be important to consider during restoration planning.

Anthropogenic climate change is causing an increase in global average temperatures, sea level rise, changes in precipitation patterns, and disturbances to species interactions (Karl et al. 2009; Kopp et al. 2014; Kharouba et al. 2018; Renner and Zohner 2018; Fawzy et al. 2020; Olliff-Yang et al. 2020). California is experiencing an increase in the frequency, magnitude, and length of droughts with “chronic, long-term hydrological drought” looming at the end of this century (Mann and Gleick 2015; Wuebbles et al. 2017). Furthermore, global temperature increases of 1°C have already been recorded, with business-as-usual scenarios predicting a global average increase of up to 5°C by 2100 (Wuebbles et al. 2017). Both extended drought conditions and increasing temperatures have been correlated with earlier flowering (Cui et al. 2017; König et al. 2017; Papper et al. 2021; Pearson et al. 2021), a potentially detrimental phenomenon to the community composition and ecosystem-level resilience of flowering grassland species (Suttle 2007; Crimmins 2009).

Water stress, especially the prolonged periods without precipitation associated with drought, can disrupt the phenology of plants (Suttle 2007). Phenology is the timing of biological events in a life cycle such as flowering, breeding, and hibernation (Lieth 1974). Variability in phenology has been found to be higher in early-flowering plant families (Mazer et al. 2012), grasses (Munson and Long 2017), and early flowering species (Wainwright et al. 2012). Specifically in mid- to high-latitudes, warming temperatures disproportionately affect the phenology of early-active flowering plants due to higher temperature variability in spring months (Menzel et al. 2006). Changes in phenology can have serious repercussions for both individual plant fitness and entire ecosystems (Cui et al. 2017; Mazer et al. 2012). At an extreme, alterations to the phenology and reproductive ability of species can lead to phenological mismatches — asynchrony with pollinators or a loss of temporal overlap between mutualistic species (Rafferty et al. 2015; Renner and Zohner 2018, Olliff-Yang et al. 2020).

Conversely, some species may benefit from phenological shifts in response to changing environmental factors. For example, species with minimal photoperiod and chilling requirements (time exposed to low temperature required to break dormancy) may actually increase in abundance and distribution due to earlier budbreak (producing green leaves after dormancy) (Polgar and Primack 2011; Koenig et al. 2021). In addition, species that exhibit less phenological shift in response to climate changes have decreased greatly in abundance, a trend observed in over 400 flowering plant species (Willis et al. 2008). Hence, shifting in flowering time may have costs, such as potential mismatch or changed species interactions, and also benefits, such as the ability to track optimal temperatures for growth.

Importantly, there is evidence of adaptive differentiation within a species in response to different amounts of precipitation in the environment (Sultan 1996; Rajakaruna et al. 2003). For example, Sultan (1996) found that the offspring of Polygonum persicaria L. exposed to various environmental stressors, including low soil moisture, demonstrate wide plasticity in their growth responses due to higher provisioning of mass to seedlings, earlier germination time, and other individual parental compensations. Similarly, Rajakaruna et al. (2003) recorded plasticity in Lasthenia californica (DC.) Greene sensu Ornduff (1966, 1993) when exposed to drought conditions and found them to be adaptively differentiated by population for reproductive responses but not for growth responses. This phenotypic plasticity, at the individual and population level, could provide species with a wide geographic range with greater drought tolerance and increased resistance to competition caused by phenology shifts (Nicotra and Davidson 2010; Wainright et al. 2012; Pearse et al. 2020).

The purpose of this study is to determine intraspecific variation to drought stress in a California native herbaceous annual. We are studying this response using Lasthenia gracilis (DC.) Greene (Asteraceae), as a model organism. We chose this species because it is a flowering annual with a large geographic range, genetically-distinct populations (Rajakaruna 2003), and relatively short growth cycle (Rajakaruna and Bohm 1999; Calflora 2018). Flowering time in Lasthenia species is responsive to water availability (Emery 2009), and there is genetic variation within a population of vernal pool species for responses to water depth and season length (Emery and Ackerly 2014). Lasthenia is also used in California restoration projects, making it relevant to future management decision applications (Point Blue Conservation Science 2019). In this study, we test for differences in population-level plasticity of the growth and phenology of an early-flowering native California annual exposed to differing amounts of water. These differences could be adaptive assuming the populations are adapted to their geographic areas of origin. We hope to answer the following questions: 1) Does L. gracilis exhibit plasticity in growth rate, inflorescence number, and flowering time in response to different levels of water, and 2) do plastic responses to water treatments differ based on source location, indicating adaptive differentiation?


Study Species

We investigated the effects of different watering treatments on the growth of individuals from six populations of L. gracilis, a native California wildflower with a range of habitats from northern California to northwestern Baja California (Calflora 2018). Lasthenia is a genus comprised of 18 known species and subspecies occupying a diverse set of habitats (Chan and Ornduff 2000). These include coastal bluffs, open grasslands, oak woodlands, alkali flats, chaparral, pastures, roadsides, desert habitats, and serpentine outcrops (Rajakaruna and Bohm 1999; Rajakaruna 2003). We chose L. gracilis as our model organism because it is a flowering annual with a large geographic range (Fig. 1) with evidence indicating genetically-distinct populations (Rajakaruna 2003, Montalvo et al. 2017). This makes it favorable for investigating adaptive differentiation in the context of drought conditions (Rajakaruna and Bohm 1999; Rajakaruna et al. 2003). This is an obligately outcrossing species, requiring cross-pollination to set seed (Ornduff, 1966). Lasthenia gracilis has a typical bloom period from February to June (Calflora 2018), relatively fast experimental germination (1–2 wk) and short growth cycles (2 mo). Due to hypothesized adaptive differentiation, the suitable temperature range, elevation, amount of precipitation, and morphological characteristics are extremely broad and varied. For instance, the wet season within L. gracilis species range is anywhere from 0 to 8 mo with average temperatures ranging from 21°F to 64°F (Calflora 2018).

Fig. 1.

All California Consortium of Herbaria (CCH) records of Lasthenia gracilis. Black points are herbarium specimen collection locations, grey triangles are seed collection locations for populations used in this study. Collection data were cleaned and georeferenced using methods described in Baldwin et al. (2017).


Study Population Selection

We chose six populations based on latitude, climate moisture deficit (CMD), and seed availability. From north to south the populations are Table Mountain (TM), Henry Coe (HC), Pinnacles (PN), Carrizo Plain (CB), Tejon Mojave (TC), and Anza Borrego (AB) (Appendix 1). Maternal effects were removed from 14 maternal lines by growing one generation in the greenhouse under uniform conditions, and by cross-pollinating individuals by hand. Seeds were collected and pooled from inflorescences that had been cross-pollinated with another individual within the same population and separated to prevent accidental pollen transfer between populations. We pooled 10 seeds each from five maternal lines from each population to germinate for our greenhouse study. We selected populations with at least 13 successfully-germinated seeds during an initial germination trial and excluded populations that did not germinate sufficiently to include enough replicates. Our populations represented a range from arid, southern habitats to wetter, northern habitats (Appendix 1, Fig. 1).

Greenhouse Experiment

To determine the relationship between population and growth response to differing water treatments, we conducted a greenhouse experiment in 1.5″ diameter planting cones of Sunshine Growth 4 Aggregate Mix (Sun Gro Horticulture, McClellan Park, California) at the Oxford Tract greenhouses at the University of California, Berkeley. We controlled temperature, light, and pest exposure. The greenhouse was maintained at a temperature from 64–77°F with a photoperiod of 12 hr of light from overhead high intensity discharge (HID) lights to simulate average temperature of the growing season across California. Neither pesticides nor fertilizer was used during this experiment.

Experimental Methods

Germination. To test the effects of three watering treatments on growth and reproduction, we exposed four individuals from each of the six populations to one of three watering treatments (n = 12 plants per population). As a buffer for replicate loss, we added one extra seed per population, totaling planting 13 individuals from each of the six populations (n = 78 plants total). To do this, we germinated 50 seeds from ten populations (including the six populations listed above) to compensate for variable germination rates between populations. For each population, we pooled ten viable seeds (determined based on color [dark brown to black] and fill [opaque]) from five randomly chosen mother lines. Next, we placed the seeds in Petri dishes with filter paper pre-moistened with 1–5 mL of deionized water. We then placed the dishes in a refrigerator at 2°C until root tips emerged to mimic the cold, dark germination conditions characteristic of winter in California. We selected six populations of the original ten (four not shown) based on successful germination and to optimize the diversity in terms of latitude between populations (Appendices 1, 2).

Planting. We transferred pre-germinated seeds into sterilized cones containing water-saturated Sunshine Growth 4 Aggregate Mix. We prepared containers by cleaning them with a 10% bleach solution and rinsing them with tap water. To prevent soil loss, we placed a jumbo cotton ball in the bottom of each cone and then filled them with Sunshine Growth 4 Aggregate Mix. To facilitate precise seedling transfer, we fully saturated soil by adding tap water, allowing the soil to settle, refilling each cone with approximately one cup of additional soil, and bringing the dry soil to saturation. We also employed bottom watering to keep the soil saturated for the first 17 d of growth, changing the water once a week to prevent algae growth. To prevent breakage due to pinching, we used tweezers to lift one seed at a time into previously-created indents (∼0.5 cm deep) in each cone. To ensure contact between the root hairs and the soil, we gently pushed soil around the seed and moistened the area with 1–5 mL of water. We moved any large pieces of perlite away from the seed with tweezers to prevent desiccation. To randomize placement, we organized the 72 cones (4 individuals exposed to each treatment × 3 treatments × 6 populations) according to a random number generator and labeled them with the population and seed number.

Water treatments. We established three watering treatments that ranged from saturated soil to dry conditions and exposed four individuals from each population to each treatment. Our watering treatments were as follows: Low, 10 mL of tap water once per week; Medium, 10 mL of tap water twice per week; High, 25 mL of tap water twice per week, maintaining soils at saturation. We determined the prescribed watering volumes by observing the moisture level at the surface of several cones (to attain saturation throughout the cone for the highest watering treatment, surface dryness and root moisture for the medium watering treatment, and total dryness between lowest watering treatments) over a month-long pilot study we initiated 2 wk before the greenhouse experiment. Plant water potential measurements were not conducted, however, a similar frequency and watering amounts (scaled to pot size) were used in a previous study that investigated the response to water stress in Lasthenia (Rajakaruna et al. 2003).

At least 13 seeds from each population germinated in the span of 8 d. After germination, seedlings were transferred from the petri dishes to the planting cones. We kept the planted seedlings moist by bottom-watering and spraying the soil surface with approximately 5 mL of water once a day. We stopped moistening the top of the soil 3 d before the watering treatment began and removed the planting cones from bottom-watering tray on the day the watering treatments began (17 d after planting). We continued watering according to this scheme until most individuals reached senescence and stopped producing flowers. The greenhouse experiment was initiated on October 26, 2018 and ran for 101 d. Since four individuals were exposed to each water treatment from each population, our experimental design was balanced.

Table 1.

Means of Growth Responses by Population and Water Treatment. Watering treatments are shown in columns (labeled as “Low”, “Med” and “High”) and rows indicate different populations.


Data Collection

To quantify the effects of differing water treatments, we recorded seedling growth metrics over 101 d. We chose growth rate (cm/d), inflorescence counts, days to flowering (days), peak flowering time (days since planting), and length of longest leaf at first flower (cm) because they represent growth, phenology, and reproductive fitness. We collected data at least two times per week for 12 wk. To find the relationship between differing water treatments and growth, we measured the distance from the top of the soil to the tallest part of the plant (whether it was the apical meristem or the tip of the longest leaf) two times per week using a tape measure. These heights divided by the total number of days during which the plant's height is positively increasing gave the growth rate for that plant. We also measured the length of the longest leaf on the day that each plant opened its first flower, as a measure of relative leaf differences at the time of flowering.

To find the relationship between differing water treatments and reproductive fitness and phenology, we collected inflorescence counts twice a week. Characteristic of Asteraceae, L. gracilis produces a cyme-like head comprised of both disk and ray florets (Keil 2017). To determine days to flowering, we recorded the date that each plant exhibited its first “open inflorescence”, defined as having at least one open ray flower in an inflorescence. We then used this date to determine the number of days until flowering from the date of planting. We counted the number of open inflorescences on each plant every day until most populations, with the exception of PN, TM, and AB, had reached senescence, defined as the point when all inflorescences were counted dead. Plants in PN and AB exposed to the high water treatment (and plants from TM in other treatments) generally continued to flower, although the inflorescences at the end of the study were small and had very few open ray and disk flowers. These daily measurements gave the inflorescence counts and were used to determine the peak flowering time.

Data Analysis

To determine the relationship of the growth and reproduction response variables with both population and water treatment, we employed various methods of statistical analyses in R (R Core Team, R Foundation for Statistical Computing, Vienna, Austria). For each of the seven dependent variables (growth rate, maximum number of inflorescences, length of longest leaf at first flower, flowering start date, flowering peak date, flowering end date, and flowering duration) we performed a two-way analysis of variance (ANOVA), with population and water treatment as fixed predictor variables. We also tested the interaction between population and water treatment on the response variables. Initial height was included as a covariate in the ANOVA models to control for any differences in seedling size at planting. To check the normality of our data we used Shapiro-Wilks tests and examined the histograms of the residuals.

To visually compare the variation in growth responses to drought conditions among populations, we created ordered boxplots, arranged from south to north by latitude (see Appendix 1 for latitudes and longitudes). We plotted the average of the growth rate on the Y axis for individuals from each population grouped by water treatment on the X axis to look for clusters of like responses by population and trends. We repeated this for the maximum number of inflorescences and length of longest leaf at first flower. To visually interpret the phenological responses, we created two horizontal boxplots of the start, peak, and end flowering dates grouped both by population and watering treatment.


Maximum Height

Both population and watering treatments significantly impacted growth variables (height, growth rate for the first 51 d, length of longest leaf at first flower), with no significant interaction (Table 2, Fig. 2). This lack of interaction indicates that the effect of water level on growth and flowering did not differ among populations. Maximum height was significantly affected in a two-way ANOVA test by both population (df = 5, F5,67 = 3.392, P = 0.010) and water treatment (df = 2, F2,70 = 9.047, P = 0.0004) (Table 2). A post-hoc Tukey test indicated that there was a statistically significant difference in maximum heights between the low and high water treatments (P = 0.006) and between the medium and high water treatments (P = 0.009) but not between the low and medium water treatments (P = 0.99). Although the interaction was not significant, plants from TM demonstrated the greatest percent difference in average height and growth rate between the lowest and highest watering treatments (Fig. 1). Most populations produced taller plants with increasing amounts of water.

Table 2.

Results of Two-way ANOVAs Testing Three Dependent Variables ∼ Population + Water Treatment + Population × Treatment + Initial Height. * denotes significant effect (α = 0.05).


Fig. 2.

The average maximum heights (A), growth rates (B), and maximum number of inflorescences (C) ordered by population from south to north and sub-ordered by water treatment. Black indicates low watering treatment; grey indicates medium watering treatment; white indicates high watering treatment. The error bars indicate the standard error of the mean.


Growth Rate Over First 51 Days

Water treatment (df = 2, F2,70 = 8.202, P = 0.0008) and population (df = 5, F5,67 = 3.374, P = 0.010) significantly impacted the growth rates over the first 51 d in a two-way ANOVA test, indicating that the response to increasing amount of water is faster growth (Table 2, Fig. 2). The interaction between population and treatment was not significant. A post-hoc Tukey test indicated that there was a statistically significant difference in growth rates between the low and high water treatments (P = 0.008) and between the medium and high water treatments (P = 0.01) but not between the low and medium water treatments (P = 0.99). The Tukey test also indicated that plants under the highest water treatment showed higher growth rates over all populations.


We found a significant positive relationship between amount of water and reproductive fitness. The maximum number of inflorescences are significantly affected by both population (df = 5, F5,67 = 9.430, P < 0.0001) and water treatment (df = 2, F2,70 = 7.894, P = 0.001) (Table 2), with no significant interaction in a two-way ANOVA test. Within most populations, individuals treated with the highest watering treatment yielded more inflorescences compared to individuals of the same population exposed to drier conditions. Consequently, plants in all populations except one responded to drought conditions by producing fewer inflorescences (Fig. 2). Historical CMD data from the source locations were correlated with reproduction (P = 0.003, correlation = –0.342).


We found that the phenology of L. gracilis (flowering start date, flowering end date, flowering duration, and peak flowering date) showed significant population and water treatment effects, with no significant interactions (Table 3) in our two-way ANOVA tests. Population showed significant effects on flowering start date (df = 5, F5,67 = 3.541, P = 0.008), flowering end date (df = 5, F5,67 = 2.911, P = 0.021), and flowering duration (df = 5, F5,67 = 4.039, P = 0.004). Treatment showed significant effects on flowering end date (df = 2, F2,70 = 8.340, P < 0.001), flowering duration (df = 2, F2,70 = 5.773, P = 0.005), and peak flowering date (df = 2, F2,70 = 4.108, P = 0.022). Flowers from all populations flowered later and longer when treated with more water (Table 4). On average, the peak flowering date was shifted 7 d later when comparing the highest and lowest treatments for all populations. The end flowering date was shifted 14 d later on average when comparing the highest and lowest treatments for all populations. The duration of flowering was shortened by 9 d on average when comparing the highest and lowest treatments for all populations. There is no discernible pattern of phenological shift when the populations are ordered by latitude (Fig. 3A).

Table 3.

The Results of Two-way ANOVAs Testing the Effects of Population + Water treatment + Population x water Treatment + Initial Height on Four Phenology Variables. * denotes significant effect (α = 0.05).


Table 4.

Means of Reproductive Responses by Population and Water Treatment. Watering treatments are shown in columns (labeled as “Low”, “Med” and “High”) and rows indicate different populations.


Fig. 3.

Average duration of flowering and peak flowering date for each population (A) and for each watering treatment (B). The error bars indicate the standard error of the mean.



We found that watering treatments produced significant differences in growth across all populations. In our experiment, plants grew taller and faster with increasing amounts of water when compared to plants of the same population exposed to drought conditions, with the exception of plants from TC and CP. The historical environments of TC and CP populations are on the lower end of average precipitation and highest climate moisture deficits (Appendix 1). Plants from TC and CP could have been allocating more biomass to their root systems, an example of a functional trade-off observed in vascular plants, especially those in desert environments (Michelaki et al. 2019). A future experiment incorporating measurements of pre-drawn water potential and below/aboveground biomass could further investigate this potential drought tolerance strategy. Generally, interaction between population and treatment was not found to be significant for any response variable, so the effect of water level on growth and flowering did not depend on population. Consequently, because L. gracilis grows on a wide range of edaphic environments, the range in growth responses to water level fits a hypothesis of high plasticity in this species (Rajakaruna and Bohm 1999; Rajakaruna et al. 2003).

Plants in all populations produced a significantly higher number of inflorescences when treated with more water, with the exception of one population. Historical CMD data from source location was correlated with reproduction in a weak negative linear relationship (correlation not shown). The negative correlation between historical CMD and inflorescence production indicates that populations from wetter environments tend to exhibit higher levels of reproductive output. Plants from AB, TM, and HC under some water treatments continued flowering after the plants from other populations had reached senescence. Inflorescences produced after we had stopped watering were small, low on the plant, and often consisted of just a few open ray flowers poking through a bud. Since we defined inflorescences as having open ray flowers, these small inflorescences with only ray flowers were counted. This has also been seen in other plant species from arid environments — where more water is available seed production increases (Yu et al. 2021), indicating that our flower data is a proxy for reproductive responses to water availability.

This behavior of producing more inflorescences with more water is consistent with resource cost hypotheses which highlight the inherent trade-offs associated with the allocation of water for reproduction by asserting that this can be costly to vegetative growth and ultimately survival (Galen 2005; Tracey and Aarssen 2014). Namely, L. gracilis from all populations appear to allocate less water and energy to reproduction when resources are limited. However, smaller plants are able to allocate fewer resources to all functions overall (Aarssen and Taylor 1992; Younginger et al. 2017). Therefore, to test for tradeoffs, future studies would need to collect data to compare vegetative and reproductive biomass to explore the trade-offs that occur in this species. We ran a post-hoc correlation of the growth rates and maximum flowers and found the correlation to be significant (P < 0.001), indicating a trade-off between plant height and reproductive fitness. Biomass data would help to further investigate plasticity in reproductive growth parameters in response to varying levels of water.

The severity of the negative impacts on reproductive output caused by drought conditions is related to geographic population. Specifically, individuals from locations that receive lower amounts of precipitation on average (AB, TC, CP, and PN) show less plasticity in reproductive response when comparing the number of flowers produced by plants grown under the lowest watering treatment with the number produced under the highest watering treatment within each populations (Appendix 1). For example, individuals from AB showed an average difference of three fewer inflorescences produced per plant when comparing those grown under the lowest watering treatment to those grown under the highest watering treatment. Individuals from TM, a site which receives about four times the amount of precipitation in the field compared with AB, showed an average difference of 16 fewer inflorescences per plant when comparing those treated with the lowest watering treatment to those treated with the highest watering treatment. Individuals from these historically drier locations (AB, TC, CP, and PN) are able to reach inflorescence numbers closer to their high watering treatment maximums, even when exposed to drought conditions. Since water use efficiency is a known drought adaptation (Hendry and Day 2005), this trend in differential reproductive output correlated with population suggests that plants from these populations are more drought tolerant.

Plants from all populations flowered significantly earlier and for a shorter amount of time when exposed to drought conditions. These two strategies are both drought adaptations. For example, in desert plants, a lack of water has been shown to stimulate flowering of annuals (Rathcke and Lacey 1985; Shavrukov et al. 2017). Phenotypically, this results in earlier flowering dates when annuals are exposed to drought conditions compared to when they are given ample water. However, in our study, there is no discernable pattern of stronger phenological shifts correlated with populations that have historically been exposed to less precipitation, as other studies have shown (Pearson et al. 2021). As per previous population-level drought studies, we anticipated that plants from drier locations flower earlier and reach maturity faster, not “betting” on future water supplies (Aronson et al. 1992; Rajakaruna et al. 2003).

There are a few caveats to consider regarding interpretation of our results. First, our growth measurement method was invasive as it required using our hands to pull the delicate plants up to the measuring tape. This resulted in breakage of two plants and one leaf over the course of the greenhouse experiment. Since we had to touch the plants to measure them, our method increased risk but gave valuable growth response data including maximum height and growth rate. We had extra replicates to replace the affected individuals, but we would shift to a less invasive growth measure such as using above and below ground biomass to quantify growth response in future studies. Furthermore, the cones housing the plants were small, so soil got extremely stripped (lost color) and sometimes caked (desiccated and compacted) by the end of the experiment. Planting in larger pots or implementing micro-tilling (disrupting the soil) could solve this issue.

At any given site, the combination and interaction of countless environmental factors including soil type, temperature, precipitation, local biodiversity, and more have been shown to affect plant growth (Rajakaruna 2003; Rajakaruna et al. 2003; Dierig et al. 2006; Powell et al. 2011). In this project, we investigated the effect of water availability on the growth and reproduction of individuals from six geographically-distinct populations of L. gracilis chosen to represent a range of latitudes across California. Since many other factors besides simply the latitude of a site have been shown to affect plant growth, we see potential for a larger drought study to be conducted over various gradients including climate moisture deficit, elevation, temperature, as well as a comparative study of coastal versus inland plant responses.


This research on the drought response of a species of native California wildflower has applications in management and ecosystem protection in the face of the changing climate. As California faces more severe and frequent droughts (Mann and Gleick 2015; Wuebbles et al. 2017), information about drought responses of native plants can help predict which species will be impacted the most (Gitlin et al. 2006). Additionally, information about population-level plasticity can help inform population selection in restoration projects. Lasthenia gracilis is already included in seed mixtures used for restoration projects and planted along highways by CalTrans because it is good for early cover (Montalvo et al. 2017). Lasthenia spp. is also recommended for use in the rehabilitation of disturbed lands because it can tolerate a wide range of environments (Newton and Claassen 2003). Further understanding of the population-based responses to drought can help fine-tune choice of source population for restoration plans based on changing climatic variables.

Additionally, knowledge of environmental preference by population can inform management decisions like the implementation of assisted migration. Assisted migration, or assisted colonization, is a process through which species that are at risk of extinction are introduced to a predicted more suitable environment (Gallagher et al. 2014; Hällfors et al. 2017). For example, survival of translocated White Spruce seedlings declined when seeds were transplanted from wet origins to dry locations due to differences in cold hardiness (Sebastian-Azcona et al. 2019). Some of these population-level limitations can be investigated before launching restoration and assisted migration projects. As California faces a future of more frequent and intense droughts, translocating more drought tolerant lines in areas experiencing more drought could mitigate the possibility of entire loss of a species due to desiccation. Although our results did not indicate any of the six populations to be significantly different in drought tolerance based on latitude, population responses were not uniform, and further study into drought tolerance is needed.

Similarly, assisted gene flow is a conservation tactic in which more resilient populations are crossbred with at-risk populations at a site (Aitken and Whitlock 2013). At its best, this process yields genetic resilience to environmental factors. However, there is also evidence for the inherent risk of outbreeding depression associated with the crossing of plants from populations insurmountable adaptive differences such as edaphic preferences (Rajakaruna 2003; Montalvo et al. 2017). Knowledge of populations' adaptations to environmental factors such as water availability can help inform decisions to effectively implement conservation management tactics such as assisted migration and assisted gene flow in a vulnerable location. Since water availability significantly impacted growth and reproductive success, site-specific details of water availability should be considered when sowing Lasthenia seeds for restoration to achieve maximum success.


We thank the Ackerly Lab at the University of California, Berkeley for supporting this project. We thank L. McGinnis and P. Mendez, for the helpful writing comments. We also thank our editing group, The Photosynthe-sistas Soil-mates Forever (F. Mahmud, H. Marsh, E. Murphy, A. Sadowski) for their support and friendly reviews. We thank E. Lai, P. Butani, H. Warshawsky, A. Cox, R. Yap, J. Killeen, and A. Alaghatta for assistance in the greenhouse; D. Ru, P. Abramowitz, E. Sun, and J. Singh for help with statistical analysis; and the College of Natural Resources, The California Botanical Society's Paul Silva Student Research Grant, UC Berkeley Undergraduate Research Apprenticeship Program, Mildred E. Mathias Graduate Student Research Grant for financial support. Additional support was provided by the National Science Foundation Graduate Research Fellowship Grant (#1049702) (to R.L.O.-Y.).

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Appendix 1

Summary of location and environmental conditions for chosen study populations of L. gracilis . Temperature and precipitation values are averaged over the typical L. gracilis growing season (February–June). 1 Climate moisture deficit (CMD) incorporates precipitation and evaporation metrics. A higher CMD indicates an area with lower levels of precipitation and higher rates of evaporation.


Appendix 2

Percent germination for 50 seeds per population planted on October 8, 2018. The germination study was run for 18 d. Seeds from populations with sufficient germination (listed below) were immediately used for our greenhouse experiment.

Emily T. Cox and Rachael L. Olliff-Yang "GROWTH RESPONSES OF LASTHENIA GRACILIS TO SIMULATED DROUGHT," Madroño 68(4), 366-376, (23 December 2021).
Published: 23 December 2021
climate change
greenhouse experiment
population plasticity
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