Impacts of climate change on flowering phenology and production in alpine plants: The importance of end of flowering

Agriculture, Ecosystems and Environment 291 (2020) 106795

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Impacts of climate change on flowering phenology and production in alpine plants: The importance of end of flowering

T

Tsechoe Dorjia,b,c,*, Kelly A. Hoppingd, Fandong Menga,b, Shiping Wanga,b,c, Lili Jianga,c, Julia A. Kleine a

Key Laboratory of Alpine Ecology, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Nongke Road No. 6, Lhasa, 850000, Tibet Autonomous Region, China b CAS Center for Excellence in Tibetan Plateau Earth Science, Campus16 Lincui Road, Chaoyang District, 100101, Beijing, China c Naqu Ecological and Environmental Observation and Research Station of Tibet University and Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Lhoma Township, 852076, Tibet Autonomous Region, China d Human-Environment Systems, Boise State University, Boise, ID, 83725, USA e Department of Ecosystem Science and Sustainability, Colorado State University, Fort Collins, CO, 80523, USA

A R T I C LE I N FO

A B S T R A C T

Keywords: Alpine Climate warming OTCs Seasonality Shrub Snow manipulation Tibetan Plateau

Changes in the seasonal timing of plant flowering are hypothesized to alter the number of flowers plants produce, which contributes to reproductive success. However, empirical evidence linking specific aspects of plant flowering phenology to the number of flowers produced is limited, particularly under future global climate change. We used phenology measurements after 2, 3, 6, and 7 years of a fully factorial, climate change field experiment in an alpine meadow pasture on the central Tibetan Plateau to understand: 1) how experimental warming and snow addition affect the date of first and last flowering in related forb and shrub species, Potentilla saundersiana Royle and Potentilla fruticosa L.; and 2) how these changes in the timing of phenological events alter flowering duration and production, as a proxy for reproductive effort. We found that warming significantly advanced the date of first flowering in both P. fruticosa and P. saundersiana, with no other significant effects on flowering duration or production. In contrast to warming, simulated snowstorms delayed the date of first flowering in P. saundersiana, but had no significant effect on P. fruticosa. There were no significant treatment interactions. For both species, flower production increased as the last date of flowering occurred later. These results indicate that as climate change alters alpine plant phenology, advances in the timing of first flowering alone will not necessarily translate to increases in flowering duration and enhanced reproductive effort. Instead, these findings demonstrate the importance of the date of last flowering in mediating plant reproductive effort and success.

1. Introduction Global mean temperature is rising and leading to more frequent extreme weather events, such as snowstorms (Jiang et al., 2012; IPCC, 2013). These climate changes are predicted to be particularly acute in tundra and alpine regions (Jiang et al., 2012; IPCC, 2013; Pepin et al., 2015), where they will alter the timing of phenological events and ecosystem functioning (Ernakovich et al., 2014). Climate warming not only increases temperature, but also reduces soil moisture, which is a key factor affecting growth and reproduction of plants, especially in arid alpine ecosystems (Körner, 2003; Crimmins et al., 2011; Wolkovich et al., 2012; Yang et al., 2018). Snowstorms, on the other hand, increase

soil moisture (Liu et al., 2010; Wipf and Rixen, 2010; Hulber et al., 2011; Tan et al., 2014), and snow can buffer the soil temperature from atmospheric conditions (Brooks and Williams, 2010). The timing of snowmelt has been found to explain variation in the timing of flowering phenology in subalpine, alpine, and arctic systems (Dunne et al., 2003; Borner et al., 2008; Steltzer et al., 2009; Bjorkman et al., 2015). Changes in flowering phenology constitute an important trait, akin to plant height or leaf area index (Jia et al., 2019). Altered flowering phenology is hypothesized to affect reproductive effort (Schwartz, 2003) but empirical evidence linking these two phenomena is limited. The timing of the first and last dates of flowering determines the duration of the flowering period, which is the time span between first

⁎ Corresponding author at: Key Laboratory of Alpine Ecology, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Nongke Road No. 6, Lhasa, 850000, Tibet Autonomous Region, China. E-mail address: [email protected] (T. Dorji).

https://doi.org/10.1016/j.agee.2019.106795 Received 18 May 2019; Received in revised form 16 December 2019; Accepted 18 December 2019 0167-8809/ © 2019 Elsevier B.V. All rights reserved.

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extend their flowering duration in response to warmer temperatures and earlier snowmelt, but this response was not significantly related to soil moisture (Dunne et al., 2003). Similarly, shrubs (mostly deciduous) have generally been found to lengthen their flowering duration under warming in China (Tao et al., 2017). Yet in a synthesis of 253 plant species across 20 tundra sites, late-flowering species’ advancement of first flowering date under warming tended to lead to an overall contraction of community-level flowering duration (Prevéy et al., 2019). On the central Tibetan Plateau, pastoralists observed a trend toward both later flowering and the production of fewer flowers, which they attributed to decreasing rainfall, thus suggesting that water availability, too, could play a key role in regulating these plants’ reproductive responses to climate change (Hopping et al., 2016). The implications of climate-induced shifts in phenology and reproductive effort are likely to not only affect plant community structure, but also biotic interactions (Ernakovich et al., 2014). Livestock grazing in eastern Tibet has been found to advance the timing of flowering and increase flower production via yaks’ effects on canopy height and nitrogen availability (Zhang et al., 2014; Mu et al., 2016). By selectively targeting plants with specific functional traits, small ruminants may also affect vegetation composition and community-level phenology. For example, sheep and goats’ preferential herbivory on forbs reduced floral diversity in Mongolian grasslands (Yoshihara et al., 2008), while sheep preferences for late-flowering plants in alpine pastures in Norway led to an increase in late-flowering species when sheep were removed (Evju et al., 2009). Although graminoids comprise the largest proportion of yak diets, they also consume forb flowers and maximize their consumption of forbs during the summer, when most high-elevation forbs are flowering (Cincotta et al., 1991; Shrestha and Wegge, 2008). These findings from agricultural systems suggest that grazing by domestic yak, sheep, and goats in central Tibet are likely to interact with abiotic factors affecting vegetation phenology, with consequences not only for the vegetation community, but also potentially for herbivore nutrition, due to seasonal changes in forage species’ chemical composition associated with flowering (Johnston et al., 1968). In this paper, we draw on seven years of a fully factorial climate change experiment to understand: 1) how warming (using open top chambers) and spring snowstorms (simulated by adding snow before the start of the growing season) independently and interactively affect flowering phenological events - including the dates of first and last flowering - for two alpine plant species on the central Tibetan Plateau; and 2) how changes in flowering timing alter flowering duration and production. We selected two Potentilla species as our focal species in this study for several reasons. First, these species belong to the same genus, but differ in their life forms: P. saundersiana Royle is a forb, and P. fruticosa L is a shrub. Moreover, these two species are both midflowering, as defined relative to the timing of other species in the experiment (Dorji et al., 2013), but they differ with respect to rooting depth, a key plant trait: P. saundersiana is shallower-rooted, while P. fruticosa is deeper-rooted. Second, these species are both relatively abundant in alpine meadows on the central Tibetan Plateau, which guaranteed a sufficient sampling quantity in terms of number of individuals within each plot. These two plants are also consumed by domestic and wild herbivores, making them good candidates for considering how altered flowering could affect livestock, although their consumption prevented us from monitoring them effectively in plots with yak grazing in the experiment. Third, each of these species experienced significant, interactive effects of warming and snow addition on the timing of their early-season flowering phenology in the first three years of the experiment (Dorji et al., 2013), thus making them interesting candidates for examining longer-term and end-of-season effects. We hypothesized that experimental warming would advance the date of first flowering and delay the last date of flowering of the shrub species P. fruticosa, as documented for other shrub species worldwide (Tao et al., 2007; Elmendorf et al., 2012), and because woody plants are

and last flowering. The flowering period may in turn affect the number of flowers produced, which can be essential for plants’ reproductive success under altered environmental conditions (Forrest and MillerRushing, 2010; Chuine et al., 2013; Richardson et al., 2013). There are additional factors – such as successful pollination, seed set, and germination – that contribute to sexual reproductive success (Billings and Mooney, 1968; Kudo and Hirao, 2006). However, in this paper, we focus on the maximum number of flowers produced as a proxy for sexual reproductive effort, and thus refer to it as such, although we acknowledge that the maximum number of flowers is not the sole contributor to reproductive effort. Given the projections of warming and increased snowstorm frequency and intensity for the Tibetan Plateau (IPCC, 2013), it is imperative to understand how warming and spring snowstorms independently and interactively affect temperature and moisture conditions, and the implications for plant flowering phenology and sexual reproduction. Phenological responses to warming have been examined in experimental studies across many arctic and alpine ecosystems, some of which are used for livestock grazing (Elmendorf et al., 2012; Oberbauer et al., 2013; Prevéy et al., 2019), as well as in ecosystems with other agricultural land uses (Shimono, 2011; Kariyeva and van Leeuwen, 2012; Liu et al., 2013). However, the phenological effects of extreme weather events, such as spring snowstorms, and particularly the interactive effects of warming and snowstorms, have not yet been explored experimentally – despite their relevance for predicting effects on fodder and food production in these systems. Observational and satellite-based studies of snowstorm effects on plant phenology are also lacking, although evidence suggests that green-up on the Plateau could advance in years experiencing extreme snowfall (Klein et al., 2014). While we examined and reported warming and spring snow effects on the timing of budding, flowering, and fruiting of plant species with different functional traits after 2–3 years of experimental treatments (Dorji et al., 2013), this previous study did not examine longer-term phenological responses and their relation to reproductive effort, nor the timing of the end of flowering. This present study, which examines responses after seven treatment years, provides responses over longer time frames than are typically reported. These longer-term experimental findings are critical not only for detecting and understanding key processes that regulate plant phenology in response to a more complex and realistic suite of future climate changes, but are also important for model development and accuracy, as short-term responses have been shown to differ from longer-term experimental outcomes (Wolkovich et al., 2013; Elmendorf et al., 2016). Warming has been found to both advance and delay the date of first flowering in arctic and alpine plants (Sherry et al., 2007; Yu et al., 2010; Lee, 2011; Prevéy et al., 2019). Temperature sensitivity thresholds have also been found to vary for different phenophases (Meng et al., 2016), with fruit set timing being relatively more stable in response to cooling and warming (Jiang et al., 2016). However, the date of last flowering, and therefore the duration of flowering in response to warming, are rarely reported in phenological studies (Bock et al., 2014; Tao et al., 2017), which can lead to an underestimation of the phenological shifts occurring in plant communities (CaraDonna et al., 2014). Flowering duration is important since a longer flowering period can provide more opportunities for plants to reproduce (Dieringer, 1991; Schwartz, 2003; Nagahama et al., 2018). In a study conducted under ambient climate conditions in Norway, most of the plant species that were monitored advanced their first flowering dates following warmer and wetter winters, but for only a few species did this earlier start of flowering also extend the duration of their flowering period (Post and Stenseth, 1999). Elsewhere, warming has been shown to both shorten (Črepinšek et al., 2012) and lengthen (Dunne et al., 2003; Millerrushing et al., 2007) flowering duration, with the direction of response dependent upon location, species, and functional traits (Dunne et al., 2003; Morales et al., 2005; Bock et al., 2014; Tao et al., 2017; Prevéy et al., 2019). Early flowering species, for example, have been found to 2

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air) and moisture (soil) in each plot during the growing season (May 25August 25). Data were logged every 15 min for all sensors (Dorji et al., 2013, 2018; Hopping et al., 2018). We calculated the mean microclimatic conditions for the duration of the entire growing season, during the pre-rainy season, and during the rainy season in each plot each year. Using daily precipitation data from the nearby weather station, we determined the start of the rainy season each year by identifying the first precipitation event that was much higher than average spring precipitation events and which lasted for several days. We also calculated the mean microclimatic conditions for the pre-flowering period (before the date of first flowering) and during flowering (the duration between the first and last date of flowering) for P. saundersiana and P. fruticosa in each plot each year. We used two common plant species, P. saundersiana and P. fruticosa, as focal species for this study. In April 2010, five individuals of each species were selected from the vegetation monitoring subplots of each plot and marked for monitoring flowering phenology and the number of flowers each year (Dorji et al., 2013). For each species, the date of first flowering was the date when any individual (among five marked individuals) flowered for the first time in each plot each year, while the date of last flowering was the date when the last flower among all five individuals of each species was no longer visible in each plot each year (CaraDonna et al., 2014). The mean maximum number of flowers per individual, which we use as an indicator of reproductive effort, was calculated as the average of the maximum number of flowers for each individual within each plot.

generally thought to be temperature limited (Alvares-Uria and Körner, 2007). Conversely, we anticipated that warming would have the opposite effects on P. saundersiana, due to its shallower rooting depth (Hu et al., 2013), which could make it more sensitive to warming-induced reductions in soil moisture (Wolkovich et al., 2012). We hypothesized that snow addition would have less of an effect on P. fruticosa but would delay the first flowering date of P. saundersiana, following results from the first two years of the experiment (Dorji et al., 2013). We expected that changes in flowering timing that increase the flowering duration would correspond to an increase in the maximum number of flowers per individual, which we use as a proxy for reproductive effort. 2. Methods 2.1. Study area Our experiment is located at Namtso village, central Tibet, China (30.72°N, 91.05°E, 4875 m a.s.l) (Fig. S1). The grassland study area is an alpine meadow dominated by Kobresia pygmaea C. B. Clarke, with P. saundersiana and P. fruticosa also commonly found. Data from a nearby weather station installed in 2005 indicate that the 12-year mean (2005–2017) annual air temperature is -0.71 °C, and the mean annual precipitation is 407 mm (Dorji et al., 2018). In addition, severe snowstorms occur in central Tibet, with snow deeper than 1.5 m observed in years with anomalously high snowfall (Li et al., 2001). The frequency and severity of these events are projected to increase with climate change (Shen et al., 2015; Wang et al., 2018b).

2.4. Analyses 2.2. Study design Generalized linear mixed effects models (GLME) with ANOVA tests were used to analyze the data. Response variables were: the date (day of year) of first flowering, date (day of year) of last flowering, duration of flowering, and the maximum number of flowers per individual of the two focal species. Treatments (W, S, WS) and years were assigned as fixed effects, while "block" was assigned as a random effect in the models. GLME models were also used to examine the association between phenological events and the mean maximum number of flowers per individual of each species and the relationships between phenological events and microclimate variables. Both "year" and "block" were assigned as random effects to account for repeated measures across years when only treatment effects were tested. We report statistical test results of p < 0.05 and p < 0.01 as representing significant and highly significant results. All analyses and plotting were performed in R versions 3.4.4 and 3.5.3 (R-Development-Core-Team, 2019). The “glmmadmb” function from the “glmmADMB” package (Fournier et al., 2012) was used to perform GLME (Dorji et al., 2013, 2018).

The phenology study reported here is from a fully-factorial climate change and grazing experiment with 8 treatments. Each of the eight treatments was replicated across eight blocks in a randomized block design for a total of 64 plots, each 8 m in diameter (see supplementary information of Dorji et al. (2018) for the experiment layout and Dorji et al. (2018) and Hopping et al. (2018) for additional details of the study design). Within each plot, we randomly assigned five 1-m diameter permanent subplots for treatment application and measurements. The five subplots within each plot served for different measurement and monitoring purposes, such that one subplot was used for microclimate monitoring, one for relatively destructive soil sampling, and the other three for vegetation measurements, including plant phenology and community composition. In this paper, we only include measurements from control (C), spring snow addition (S), warming (W) and warming x snow addition (WS) treatments because yak grazing and trampling prevented us from measuring flowering phenology accurately in the grazing treatment plots (Dorji et al., 2013). The warming and spring snow addition (hereafter “snow”) treatments were applied to the five permanent subplots. The snow was added to subplots before most plant species turned green each year (Dorji et al., 2018). The added snow was equivalent to 1.22 ( ± 0.18 SD) m of fresh snow fall (Hopping, 2015; Dorji et al., 2018) and was within the range of reported snowstorms that occur in central Tibet (Li et al., 2001). Warming was achieved by using open top chambers (OTCs). The OTCs we used, including materials, size, and shape, are ITEX (International Tundra Experiment) standard in order to be comparable to studies conducted with this methodology globally (Walker et al., 2006; Oberbauer et al., 2013; Elmendorf et al., 2015). We installed OTCs right after the snow treatment was completed and removed OTCs from experimental plots at the end of the growing season each year (Dorji et al., 2018).

3. Results 3.1. Microclimate conditions The air temperature (mean growing season air temperature) in control plots was significantly higher in 2010 relative to other years (Fig. S2a). The soil temperature (mean growing season soil temperature) in control plots was significantly higher in 2010 and 2015 and lowest in 2011 (Fig. S2b). The soil moisture (mean growing season soil moisture) in control subplots was significantly lower in 2010 and significantly higher in 2015 (Fig. S2c). Thus, overall, ambient conditions in 2010 were drier and warmer, while in 2015 they were wetter and relatively cooler. Warming significantly increased air temperatures by 1.25 ℃, on average, and soil temperatures by 1.61 ℃, on average, during the years when phenological measurements were made (Fig. S3a, b). Warming significantly decreased soil moisture by 29.5 % on average, relative to un-warmed subplots (Fig. S3c). During the pre-flowering period, snow

2.3. Data collection We measured 10 cm above- and belowground temperature (soil and 3

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Table 1 Results of generalized linear mixed effects (GLME) models showing the effect of warming, spring snow addition, year, and their interactions on date of first flowering, date of last flowering, flowering duration, and maximum number of flowers per individual for Potentilla fruticosa. Numbers under the response variables are Fstatistics of analyses of variance (ANOVAs) based on the GLME results. Significant effects are indicated by *** (P < 0.001), ** (P < 0.01), * (P < 0.05). 　

Degrees of freedom

Date of first flowering

Date of last flowering

Flowering duration

Maximum number of flowers per individual

Warming Snow Year Warming x Snow Warming x Year Snow x Year Warming x Snow x Year

1,62 1,62 3,62 1,62 3,62 3,62 3,62

7.491** 0.626 6.899*** 0.005 2.017 0.101 0.748

0.043 0.889 11.448*** 0.122 1.798 0.691 0.293

1.74 0.178 7.119*** 0.075 2.331 0.334 0.417

0.059 0.166 4.124** 1.394 0.254 1.491 0.821

addition interacted significantly with warming such that snow increased soil moisture relative to all other treatments, and it also significantly alleviated the warming-associated reduction in soil moisture in warm x snow subplots across all years (Fig. S4). During flowering, however, the snow effect disappeared, and only warming significantly affected soil moisture by drying the soil, regardless of whether snow had previously been added (Fig. S4). 3.2. Interannual variation in phenological events All phenological response variables varied significantly across years (Tables 1 and 2). For both species, the mean first flowering date advanced over the years in control plots, starting 12.0 days earlier on average for P. fruticosa in 2015 (the cool and wet year) than 2010 (the warm and dry year), and 17.8 days earlier for P. saundersiana (Fig. 1). By contrast, the mean date of last flowering ended significantly earlier for P. fruticosa in 2010 relative to other years (Fig. 1). In 2011, which was cool and also relatively wet, flowering ended significantly later for P. fruticosa but earlier for P. saundersiana than in other years (Fig. 2). For P. fruticosa, the early end date of flowering in 2010 led to the shortest mean duration of flowering in control plots that year, while the later end date in 2011 led to the longest flowering duration (Fig. 2). The mean duration of flowering for P. saundersiana was significantly longer in 2014–2015 than 2010–2011 (Fig. 2). Flower production also varied significantly across years in both species (Table 1, Fig. 2). For P. fruticosa, the mean maximum number of flowers per individual was significantly lower in 2010, when the flowering duration was also shortest. For P. saundersiana, the mean maximum number of flowers per individual was lowest in 2011, when flowering duration was shortest, and significantly higher in 2014 and 2015, when flowering duration was longer (Fig. 2).

Fig. 1. Interannual variation in mean date of first and last flowering for Potentilla fruticosa and Potentilla saundersiana in control plots. Within each species, different lowercase letters indicate significant interannual differences for the start (a–d) and end (x–z) of flowering. Error bars represent ± 1 standard error (n = 1 for P. fruticosa in 2010).

addition (Table 1). For P. saundersiana, however, first flowering date was delayed by 1.9 days, on average (Fig. 3c), and the mean maximum number of flowers per individual increased significantly under the snow addition treatment relative to subplots without snow addition (Table 2; Fig. 4). There were no significant interactive effects of warming x snow on any response variables examined for either species. The mean maximum number of flowers per individual in P. fruticosa significantly decreased with warmer air temperatures during the prerainy period, but there were no other significant effects of air temperature on phenological events in either species (Tables S1, S2). Warmer pre-rainy-season and pre-flowering soil temperature, however, tended to advance the end of flowering (i.e. caused it to end earlier) by

3.3. Treatment and microclimate effects on phenology The mean first flowering date advanced for both P. fruticosa (5.6 days earlier) and P. saundersiana (0.9 days earlier; Tables 1, 2; Fig. 3a, b) in warming plots when compared to un-warmed plots. Warming did not affect the other response variables in either species (Tables 1, 2). For P. fruticosa, no response variables were affected by spring snow

Table 2 Results of generalized linear mixed effects (GLME) models showing the effect of warming, spring snow addition, year, and their interactions on date of first flowering, date of last flowering, flowering duration, and maximum number of flowers per individual for Potentilla saundersiana. Numbers under the response variables are Fstatistics of analyses of variance (ANOVAs) based on the GLME results. Significant effects are indicated by *** (P < 0.001), ** (P < 0.01), * (P < 0.05). 　

Degree of freedom

Date of first flowering

Date of last flowering

Flowering duration

Maximum number of flowers per individual

Warming Snow Year Warming x Snow Warming x Year Snow x Year Warming x Snow x Year

1,98 1,98 3,98 1,98 3,98 3,98 3,98

5.722* 12.34*** 87.515*** 1.587 2.378 1.072 0.09

0.867 0.815 5.976*** 0.207 0.537 0.142 0.657

0.105 0.823 41.072*** 1.103 1.873 0.72 0.4

2.336 4.176* 27.124** 0.066 0.236 0.802 0.185

4

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Fig. 4. Significant effect of snow addition on the maximum number of flowers per individual in Potentilla saundersiana across all years. Horizontal black bars show the median for each treatment.

Fig. 2. Interannual variation in the mean duration of flowering and the mean maximum number of flowers per individual for Potentilla fruticosa and Potentilla saundersiana in control plots. Within each species, different lowercase letters indicate significant interannual differences in flowering duration (a–c) and number of flowers (x–z). Error bars represent ± 1 standard error (n = 1 for P. fruticosa in 2010).

increased the mean maximum number of flowers per individual in P. fruticosa (0.04 more flowers per 1 % increase in soil moisture, on average; Tables S1) and the duration of flowering in P. saundersiana (0.56 days longer per 1 % increase in soil moisture, on average; Tables S2). 3.4. Associations between flowering phenology and number of flowers per individual For both species, the mean duration of flowering contracted significantly when flowering started later and expanded significantly when flowering ended later (Tables 3, 4, Fig. S5). The mean maximum number of flowers per individual of both species increased significantly when the date of last flowering occurred later (Fig. S6) and when the duration of flowering was longer (Tables 3, 4, Fig. S7). However, the date of first flowering did not significantly affect the mean maximum number of flowers per individual in either species (Tables 3, 4). 4. Discussion 4.1. Abiotic effects on first and last date of flowering Observational studies in ecosystems with wild and domestic grazing indicate that interannual variation in the timing of early-season plant phenological events are due mostly to variations in environmental conditions, such as temperature and timing of snowmelt (Post and Stenseth, 1999; Elmendorf et al., 2016; Luna, 2016; Tao et al., 2017), although photoperiod may also be a strong constraint on early-flowering alpine and tundra species (Ernakovich et al., 2014; Prevéy et al., 2019). We found that the steady advancement in both P. fruticosa’s and P. saundersiana’s first flowering date each year generally tracked the timing of the start of the rainy season, as well as the increasingly wet soil moisture conditions each year. These patterns support the understanding that soil moisture plays a critical role in regulating Tibetan grassland vegetation dynamics under climate change (Yang et al., 2018). In addition, changes in soil nutrients may also affect plant phenology (Huang et al., 2018), which deserves further investigation in future studies. Both species’ date of first flowering was latest in 2010, which was the driest and warmest year during the study period, with among the

Fig. 3. Significant treatment effects on mean date of first flowering for Potentilla fruticosa and Potentilla saundersiana across all years. Vertical black bars show the median for each treatment.

an average of 3.2 and 1.3 days per degree for P. fruticosa and P. saundersiana, respectively (Tables S1, S2). Higher soil moisture before flowering significantly delayed the date of last flowering for P. fruticosa (1.4 days later per 1 % increase in soil moisture, on average; Tables S1), while higher soil moisture during the flowering period significantly 5

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Table 3 Results of generalized linear mixed effect models (GLME) showing the effects of date of first and last flowering and duration of flowering on the maximum number of flowers per individual, as well as date of first and last flowering on duration of flowering for Potentilla fruticosa. “Block” and “year” were assigned as random effects in the GLME models. Significant effects are indicated by *** (P < 0.001), ** (P < 0.01), * (P < 0.05). 　

Maximum number of flowers per individual

Flowering duration

Date of first flowering Date of last flowering Flowering duration

2.44 - 0.01x −3.46 + 0.02x *** 0.59 + 0.02x ***

196.69 - 0.95x *** −172.95 + 0.99x ***

events on the Tibetan Plateau will likely be influenced by the timing and amount of snowfall, and that plant species as well as vegetative and reproductive phenology may differ in their responses to an increase in spring snowstorms. In contrast to the first date of flowering, which was not significantly associated with any microclimate variables, the last date of flowering did not respond significantly to the treatment manipulations but occurred significantly earlier with higher soil temperatures during the pre-rainy season and pre-flowering period (both species) and significantly later with higher soil moisture during the pre-flowering period (P. fruticosa) across all treatments. These results point to the importance of early-season conditions for regulating the end, rather than the start, of flowering and support previous findings that the timing of distinct plant reproductive events may differ in their responses to microclimatic conditions and warming (CaraDonna et al., 2014; Li et al., 2016; Meng et al., 2016). Overall, the range of ambient soil moisture conditions and the magnitude of change in the first and last dates of flowering across years were each larger than experiment treatment effects on soil moisture and flowering date. This indicates that the climatic conditions imposed by our treatments may not have pushed the vegetation beyond the interannual climate variability to which they are exposed under ambient conditions in this semi-arid environment. While this suggests that the reproductive phenology of these species may be relatively insensitive to the soil moisture reductions associated with the moderate climate warming scenario that we simulated (Hopping et al., 2018), the system may also be vulnerable to crossing thresholds of more extreme drought, such as those experienced in 2010, which could cause a more significant contraction of the flowering period, with negative consequences for reproduction.

most severe growing season drought conditions since 1961 (Hopping et al., 2018). Extreme climate conditions can alter plant physiological processes (Feller and Vaseva, 2014), and since severe droughts are typically stressful for plant growth and reproduction (Signarbieux and Feller, 2011), the drought in 2010 may have delayed the first date of flowering, shortened the flowering duration, and reduced flower production, particularly in P. fruticosa. However, despite the significant differences in the start of flowering across years and the qualitative trend toward delayed flowering under drier conditions, we did not find that any microclimate variables significantly predicted the first date of flowering in either species across the experimental treatments. Contrary to other studies that have found congruence between experimental and observational phenology results (Dunne et al., 2003; Prevéy et al., 2019), we found that the qualitative delay in the start of flowering that we observed in drier years ran counter to P. saundersiana’s delayed flowering under snow addition (which increased soil moisture) and both species’ advanced flowering under experimental warming (which reduced soil moisture). However, our result of advanced flowering phenology under experimental warming is consistent with the finding that warming advances phenological events in general (Sherry et al., 2007; Yu et al., 2010; Lee, 2011; Prevéy et al., 2019), and in tundra shrubs and forbs in particular (Elmendorf et al., 2012; Oberbauer et al., 2013), as well as our previous findings for P. fruticosa (Dorji et al., 2013). It also supports our hypothesis that P. fruticosa, the deeper-rooted shrub, would advance flowering under warming due to lower sensitivity to warming-induced soil moisture reductions, but not our hypothesis of delayed flowering under warming for P. saundersiana, the shallower-rooted forb. The snow addition treatment, which simulated severe spring snowstorms predicted under future climate change scenarios, delayed the first date of flowering in P. saundersiana, but had no significant effects on P. fruticosa, as we hypothesized based on our previous findings from the first years of the experiment (Dorji et al., 2013). The pulse of additional water from snow addition did not cause these two species to flower earlier, which aligns with findings elsewhere that the timing of snowmelt, more than soil moisture, affects the timing of flowering (Post and Stenseth, 1999; Dunne et al., 2003; Bjorkman et al., 2015). This could be due to physical and mechanical effects of snowpack, which blocks solar radiation needed for plants to photosynthesize (Walker et al., 1999; Dunne et al., 2003; Wipf, 2010). On the southeastern Tibetan Plateau, persistent snow cover with a snow addition treatment also significantly delayed seedling emergence for several species (Wang et al., 2018a). These results suggest that phenological

4.2. Potential biotic effects on flowering phenology Biotic interactions may also play a role in the phenological responses to treatments that we observed. For example, production and cover of the early-flowering, dominant species, K. pygmaea, declined significantly with warming in our study plots (Dorji et al., 2018; Hopping et al., 2018). Decreased competition from the dominant species under warming may have led to favorable conditions for earlier flowering of P. fruticosa and P. saundersiana, since changes in plant species interactions can alter phenology (Diez et al., 2012; Wolf et al., 2017). Unlike warming, snow addition advanced the first flowering date

Table 4 Results of generalized linear mixed effect models (GLME) showing the effects of date of first and last flowering and duration of flowering on the maximum number of flowers per individual, as well as date of first and last flowering on duration of flowering for Potentilla saundersiana. “Block” and “year” were assigned as random effects in the GLME models. Significant effects are indicated by *** (P < 0.001), ** (P < 0.01), * (P < 0.05). 　

Maximum number of flowers per individual

Flowering duration

Date of first flowering Date of last flowering Flowering duration

1.59 - 0.004x −1.74 + 0.01x * 0.59 + 0.01x *

174.19 - 0.88x *** −155.88 + 0.92x ***

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5. Conclusion

and increased growth of K. pygmaea (Dorji et al., 2013, 2018), therefore making it possible that increased competition from K. pygmaea in snow addition plots may have caused P. saundersiana to flower later (Liu et al., 2017; Panchen and Gorelick, 2017). Conversely, the deeperrooted P. fruticosa, which was not significantly affected by the snow treatment, may have been buffered from these competitive effects due to its ability to access different sources of water early in the growing season (Hu et al., 2013). These results suggest that the effects of increased snow before the start of the growing season are species-specific, and response patterns likely depend on specific traits (Wipf, 2010; Wipf and Rixen, 2010) and potentially on biotic interactions. However, the mechanisms underlying these potential interactions require more direct investigation. Future studies should thus consider the role of both biotic and abiotic factors and how they interact when examining plant phenological responses to climate change. Grazing could also interact with climate variables to affect plant phenology and reproduction, given results from theoretical models as well as empirical studies of grazing effects on reproductive phenology on the eastern the Tibetan Plateau (Zhang et al., 2014; Mu et al., 2016). Our previous findings indicate that yak grazing affects plant community properties (Dorji et al., 2018) and nutrient cycling (Hopping, 2015; Hopping et al., 2018). The decrease in plant diversity and increase in nitrogen availability with yak grazing in this experiment (Hopping, 2015; Dorji et al., 2018), coupled with findings elsewhere that plants may advance their phenology in response to biodiversity loss (Wolf et al., 2017) and with nitrogen addition (Zhang et al., 2014), suggest that grazing with climate change may interactively or additively lead to further shifts in the timing of plant activity during the growing season. However, the direct effects of grazing on plant phenology may vary depending on the type and rate of grazing (Yamamura et al., 2007), and not all species’ phenology will necessarily be affected by grazing (Diaz et al., 1994). Additional study of how grazing will impact vegetation phenology in this rangeland system is therefore needed, along with an understanding of how phenological shifts under climate change will in turn affect herbivores (Van der Wal et al., 2000) in this pastoral system.

Our findings demonstrate that climate-induced advances in the timing of first flowering alone do not necessarily control subsequent reproductive outcomes. Instead, the date of last flowering emerged as being a more important determinant of flowering duration and the maximum number of flowers produced per individual in both of our focal study species. Overall, the warming and snow addition effects on flowering phenology were smaller in magnitude and in the opposite direction of interannual differences observed under a variable ambient climate. The results presented here indicate the need for studies to consider a more complete set of phenological events, including the first and last date of each event, the relationship between these events and flowering duration, as well as the rate of flower production throughout the entire flowering period when evaluating the impact of climate change on plant performance. Moreover, exploring the biotic mechanisms involved, such as plant traits, biotic interactions, and how they mediate or enhance responses to abiotic conditions, are also necessary to have a more comprehensive understanding of how plant reproductive phenology will respond to climate change. Financial support This work was jointly supported by the Strategic Priority Research Program of Chinese Academy of Sciences (No. XDA2005010405) awarded to L.J and T.D., National Natural Science Foundation of China (31770524), the second Tibetan Plateau Scientific Expedition and Research Program (STEP) (2019QZKK0608) and Ngari degraded grassland monitoring project (from the Institute of Forestry Survey and Design, Tibet Autonomous Region-TAR of China) awarded to T.D.; NSFUSA#OISE-1015691and NSF-USA Graduate Research Fellowship awarded to K.A.H.; National Natural Science Foundation of China (41731175) awarded to S.W. and L.J.; NSF-USA #SBE-0624315 awarded to J.A.K. Acknowledgments

4.3. Last date of flowering regulates number of flowers produced

We thank the Nam Co Multi-Sphere Observation station of the Institute of Tibetan Plateau Research, Chinese Academy of Sciences for hosting our research activities. We also thank B. Roskilly, T. Tarchen, L. Dev, L. Barry, H. Chmura, H.-F. Mok, P. Shrestha, J. Pan, C. Morgan, and students from Tibet University for their assistance with field work in the experiment.

It has been suggested that changes in plant flowering phenology could alter reproductive effort (Bernier, 1988; Schwartz, 2003), but the connection between these traits has rarely been investigated. Our study showed that the first date of flowering was not significantly associated with the number of flowers produced in either species, indicating that earlier flowering alone does not guarantee an increase in flower production. Rather, delays in the last date of flowering and a longer flowering duration were associated with significant increases in the maximum number of flowers per individual in both species. In addition, when soil moisture was higher during the flowering period, the maximum number of flowers per individual and flowering duration increased significantly in P. fruticosa and P. saundersiana, respectively, whereas higher air temperatures in the pre-rainy period significantly reduced the maximum number of flowers per individual in P. fruticosa. Despite the importance of microclimatic controls on the date of last flowering, flowering duration, and flower production in both species, warming and snow treatments did not significantly affect any of these variables. This indicates that warming significantly affected the date of first flowering independently from the date of last flowering, as also shown in arctic tundra species (CaraDonna et al., 2014). On the eastern Tibetan Plateau, a reciprocal transplant study indicated that the timing of fruiting was relatively more stable than other phenological events (Jiang et al., 2016). Although speculative, this suggests that the date of last flowering may be less plastic in its response to climate change in order to maintain a relatively stable fruiting stage (Jiang et al., 2016).

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