Species‐Specific Variation in Germination Rates Contributes To

Received: 7 October 2019 | Accepted: 8 April 2020 DOI: 10.1111/1365-2745.13408

RESEARCH ARTICLE

Species-specific variation in germination rates contributes to spatial coexistence more than adult plant water use in four closely related annual flowering plants

1Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY, USA Abstract 2School of Biological Sciences, University of 1. Spatial partitioning is a classic hypothesis to explain plant species coexistence, but Queensland, Brisbane, Qld, Australia evidence linking local environmental variation to spatial sorting, demography and 3Department of Biology, Grinnell College, Grinnell, IA, USA species' traits is sparse. If co-occurring species' performance is optimized differ- 4Department of Ecology and Evolutionary ently along environmental gradients because of trait variation, then spatial varia- Biology, University of Kansas, Lawrence, tion might facilitate coexistence. KS, USA 2. We used a system of four naturally co-occurring species of Clarkia (Onagraceae) to 5National Lab for Agriculture and the Environment, USDA/ARS, Ames, IA, USA ask whether distribution patchiness corresponds to variation in two environmental variables that contribute to hydrological variation. We then reciprocally sowed Correspondence Aubrie R. M. James Clarkia into each patch type and measured demographic rates in the absence of Email: [email protected] congeneric competition. Species sorted in patches along one or both gradients, Funding information and in three of the four species, germination rate in the ‘home’ patch was higher National Science Foundation, Grant/Award than all other patches. Number: DEB-1256288 and DEB-1256316 3. Spatially variable germination resulted in the same three species exhibiting the Handling Editor: Shurong Zhou highest population growth rates in their home patches. 4. Species' trait values related to plant water use, as well as indicators of water stress in home patches, differed among species and corresponded to home patch attributes. However, post-germination survival did not vary among species or between patch types, and fecundity did not vary spatially. 5. Synthesis. Our research demonstrates the likelihood that within-community spatial heterogeneity affects plant species coexistence, and presents novel evidence that differential performance in space is explained by what happens in the germination stage. Despite the seemingly obvious link between adult plant water-use and variation in the environment, our results distinguish the germination stage as important for spatially variable population performance.

KEYWORDS demographic performance, diversity, germination, interspecific trait variation, plant coexistence, plant communities, spatial heterogeneity

1 | INTRODUCTION consequences on plants in the absence of competition (Adler et al., 2013; Chesson et al., 2004). Studies of plant communities have Of persistent interest in studies of community diversity is how en- demonstrated the relationship between water-use traits, spatial dis- vironmental variation can give rise to species coexistence. In the- tribution and variation, but often focus on dramatic or large-scale ory, spatial heterogeneity can foster coexistence among species in topographic variation in the environment (Dawson, 1990; Lamont, different patches in a community (Pacala & Tilman, 1994), provided Enright, & Bergl, 1989; Richards, Stock, & Cowling, 1995; but see that each species' performance is differentially optimized along Lanuza, Bartomeus, & Godoy, 2018). Studies of finer-scale envi- some gradient (or gradients) in the environment (Hart, Usinowicz, ronmental variation (i.e. within communities) have shown that wa- & Levine, 2017; Tilman & Pacala, 1993). In plant communities, en- ter-use physiology is tightly related to plant performance (Chesson vironmental variation is classically an important mechanism for et al., 2004; Rosenthal, Ludwig, & Donovan, 2005) and even coex- diversity maintenance, and co-occurring plants often exhibit differ- istence (Angert, Huxman, Barron-Gafford, Gerst, & Venable, 2007; ential performance and success according to spatial variation in hy- Angert, Huxman, Chesson, & Venable, 2009; Gremer et al., 2013) in drology. One way to frame the relationship between hydrology and herbaceous plant communities, but are not explicitly spatial—they plant coexistence is hydrological niche segregation (or HNS: Araya do not focus on how variation in space might contribute to varia- et al., 2011; Silvertown, Araya, & Gowing, 2015). Studies of plant tion in performance and coexistence. Still other studies have shown HNS suggest three main responses to hydrological variation in space that plant occurrence or abundance and spatial variation in soil or or time that can affect coexistence: spatial partitioning, which al- hydrology are related to each other (Reynolds, Hungate, Chapin, & lows for source–sink dynamics, where species mutually persist in an D'Antonio, 1997; Silvertown, Dodd, Gowing, & Mountford, 1999), environment due to sources in different patches; water partitioning; but do not investigate the role of plants' water-use traits in these and/or the temporal storage effect. relationships. All three components of HNS implicate variation in plant In this work, we describe the relationship of spatial aggregation water-use traits as a means to minimize interspecific competition, but with two axes of environmental variation—soil texture and proxim- a critical line of evidence to establish trait-based spatial coexistence ity to woody plants—in four herbaceous, sympatric plant species in is to link environmental gradients, plant performance and interspe- the genus Clarkia (family Onagraceae; C. cylindrica ssp. clavicarpa cific trait variation to each other (Adler, Fajardo, Kleinhesselink, & (Jeps.) Lewis & Lewis, C. speciosa ssp. polyantha Lewis & Lewis, Kraft, 2013). In the case of plant communities, spatial coexistence C. unguiculata Lindl., C. xantiana ssp. xantiana A. Gray) in the Kern may be relevant for diversity maintenance if (a) the environment is River Canyon (Kern County, CA, USA; from here: C. cylindrica (C), spatially variable, (b) such variation corresponds to where species C. speciosa (S), C. unguiculata (U), C. xantiana (X)). All four Clarkia co- occur in communities and (c) species performance is highest where flower at the end of the growing season in southern California, after they are most common. If these three criteria are met, then either or many other annuals, have senesced. Within this period, species have both of the major spatial coexistence mechanisms, the spatial storage been observed to flower either early in the season (C. cylindrica and effect (i.e. environment-competition covariance, ∆I) and growth-den- C. unguiculata; Eisen & Geber, 2018) or later in the season (C. speciosa sity covariance (∆K) may affect diversity maintenance (Barabás, and C. xantiana). D’Andrea, & Stump, 2018; Chesson, 2000; Ellner, Snyder, Adler, The first axis of environmental variation we measure is in & Hooker, 2019; Snyder & Chesson, 2004). For both mechanisms, edaphic conditions: soil texture and penetration resistance. Soil tex- demonstrating that spatial partitioning can affect plant coexistence ture is an important aspect for plant water relations; in arid environ- requires measures of species' population growth rates in response ments especially, soil penetration resistance (soil hardness) increases to variation in the environment in the absence of competition. This as soils become finer (Eckhart et al., 2010; To & Kay, 2005), which is because each mechanism is defined in terms of covariance: the can lead to water stress for plants by decreasing water infiltration covariance of population performance with either competition or and soil aeration (Alizai & Hulbert, 1970; Barnes & Harrison, 1982; density. Because of this, accurate estimates of how spatial storage Kinraide, 1984; Sperry & Hacke, 2002). There is some evidence that or growth-density covariance contribute to coexistence first require plant occurrence corresponds to soil textural gradients, including measures of population performance along environmental gradients in the Clarkia system (Beals & Cope, 1964; Eckhart et al., 2017). As independently of competition or density. To further understand the with many Clarkia, these four Clarkia co-occur in multi-species com- specific role of water-use traits in spatial coexistence (as for the role munities more often than they occur alone in their range of overlap of any trait; Adler et al., 2013; Chesson, 2000), we must also demon- (Eisen & Geber, 2018; Lewis & Lewis, 1955). Previous research in strate that plant demographic performance in the absence of com- this system suggests that soil texture is an important axis of varia- petition varies along environmental gradients that (a) are meaningful tion for Clarkia spatial coexistence. In a laboratory environment, the for plants' water economies and (b) correspond to plant water-use two late-flowering species differed in their performance in response traits (Adler et al., 2013; Chesson, 2000). to soil texture, where C. speciosa germinated better in fine-grained Though the literature is replete with examples of how plants soils and C. xantiana in coarse-grained soils (Eckhart et al., 2017). partition space according to aspects of the environment or their These results matched predictions based on where C. xantiana and water-use traits, none have demonstrated the demographic C. speciosa occur naturally at the scale of the landscape (Eckhart JAMES et al. Journal of Ecolog y | 3 et al., 2017). Other research of C. xantiana has shown that its fine- demographic performance. Furthermore, it is unclear whether spa- scale patch occupancy is predicted by soil texture in communities tial heterogeneity affects the composition of Clarkia neighbour- (Kramer, Montgomery, Eckhart, & Geber, 2011). Regional variation hoods or the spatial components of their coexistence. In this study, in precipitation is also related to C. xantiana water status (Eckhart we determine the potential for Clarkia spatial coexistence via HNS et al., 2010), and predictive of plant fitness across a range edge by (a) assessing variation in the edaphic conditions and distance (Geber & Eckhart, 2005); both the water status and fitness of this from woody plants in communities where the four species occur, species have been shown to vary according to parent rock, where (b) determining whether such variation in the environment corre- fine-textured soil negatively predicts C. xantiana fitness (Eckhart sponds to spatial clustering in communities, (c) estimating demo- et al., 2011). graphic performance of Clarkia which have been reciprocally planted Soil texture may only matter for late-flowering species, as water in each patch type in the absence of congeneric competition and becomes extremely scarce during seasonal dry-down. In the earlier then (4) determining whether species-level differences in water-use part of the season, a more meaningful aspect of the environment explain their occurrence in different patch types. We also quantify for hydrological relations may be plant proximity to a shrub or tree. the abundance of annual plants other than Clarkia in each patch to In arid ecosystems, woody plants can act as nurse plants (Banuet understand whether and how patch differences in community com- et al., 1991; Barton & Teeri, 1992; Franco & Nobel, 1989; Turner, position may exacerbate water scarcity by the time Clarkia flower Alcorn, Olin, & Booth, 1966): herbaceous plants growing under nurse late in the season; this is a kind of priority effect that has proven to plants have been shown to experience reductions in evapotranspi- be important for coexistence in similar annual plant systems (Godoy ration, lower competition for soil water (Belsky, 1994; Holmgren, & Levine, 2014; Wainwright, Wolkovich, & Cleland, 2011; Young, Scheffer, & Huston, 1997), and higher seedling survival (Fuller, 1914; Chase, & Huddleston, 2001). Jong & Klinkhamer, 1988; McLeod & Murphy, 1989) and herbaceous If spatial variation is relevant for Clarkia coexistence, then we production (Frost & McDougald, 1989). That said, adaptations that predict that species will assort on the landscape, and species' growth allow growth in the shade should also constrain a plants' ability to tol- rates in the absence of other Clarkia should be highest in their ‘home’ erate dry conditions (Holmgren et al., 1997; Smith & Huston, 1989). patches (i.e. where they are naturally most abundant). If this assorting Because of this, the potential to grow under a nurse plant is contin- is related to hydrological niche and water use, Clarkia should exhibit gent on plants' tolerances to either shade or low moisture. Though it species-level differences in water-use traits (phenology/flowering has not been formally characterized in this Clarkia system, the ear- time and SLA) and how they experience water stress while flower- ly-flowering C. unguiculata is almost exclusively observed growing in ing (as measured by midday stem water-use potential/Ψmid and leaf 13 shady environments (especially under woody plants) in the Kern River delta-13 carbon discrimination ratio/δ C ratio, Table 1). We predict Canyon, whereas the other three Clarkia species tend to grow outside that water stress will increase as seasonal dry down proceeds, and woody canopies (A.R.M. James, pers. obs.). as such, late-flowering plants will experience more water stress than Thus far, research in the Clarkia system has not examined the those that flower early. This should be reflected in differences in 13 role of community-scale environmental heterogeneity on congeners' midday stem water potential and leaf δ C ratio, both indicators of

TABLE 1 Water-use traits or indicators and interpretations for their relationship to plant water use

Trait or indicator Explanation

Trait: days until Flowering is the last stage of the life cycle for Clarkia plants before senescence. In the Clarkia system, early flowering maximum flowering can be an escape strategy because it limits (or eliminates) the plants' exposure to terminal drought (Kooyers, 2015; density (flowering McKay, Richards, & Mitchell-Olds, 2003) time) Trait: SLA (mm2/g) SLA is an indicator of how costly a leaf is to grow and maintain (Pérez-Harguindeguy, Díaz, Garnier, Lavorel, & Cornelissen, 2016). SLA increases with water availability, and a lower SLA indicates a lower growth rate due to water stress (Wellstein et al., 2017). Lower SLA also indicates longer leaf lifespan and is associated with nutrient conservation in nutrient-poor environments (Wright, Reich, & Westoby, 2001) 13 Indicator: delta-13 This value is a proxy for and corresponds to a plants' water-use efficiency (WUE). Higher (more positive) values of δ C carbon discrimination commonly correspond to higher WUE, meaning that carbon is assimilated efficiently with respect to the amount of 13 ratio (δ C) water transpired in the process(Gebrekirstos, van Noordwijk, Neufeldt, & Mitlöhner, 2010) and can indicate drought 13 13 avoidance (Kooyers, 2015). δ C is an indicator of plant water status (Bchir et al., 2016). We interpret high δ C values for a species in its home patch as indicating higher water stress (Hartman & Danin, 2010)

Indicator: midday stem Ψmid indicates a plant's water status in the most challenging diurnal conditions it typically experiences (Klepper, 1968). water potential (Ψmid) As such, it is a metric of plant water stress (Pérez-Harguindeguy et al., 2016). As the ability to maintain function at low Ψmid reflects plants' physiological adaptation to water stress (Gebrekirstos, Teketay, Fetene, & Mitlöhner, 2006). Ψmid is frequently used in agricultural systems for and examining water stress and/or timing irrigation (Choné, Van Leeuwen, Dubourdieu, & Gaudillère, 2001; Girona et al., 2006; Marino, Caruso, Ferguson, & Marra, 2018; Wijewardana et al., 2019) but has also been used to examine wild plants' water stress (i.e. Colom & Vazzana, 2001).

We interpret high (more positive) values of Ψmid as an indicator of low water stress in Clarkia home patches 4 | Journal of Ecology JAMES et al. hydrological stress they must endure in their home patches (Table 1). the aggregation metric (i.e. N = 4 per species; as described, these Finally, we also predict that SLA will differ among species: it should data are aggregation metrics from the three Clarkia communities be lowest for early-flowering plants under the canopy (i.e. when in 2016 and one Clarkia community in 2017) to determine whether and where we expect water stress to be lowest) and highest for species were aggregated. Because this index of aggregation does not late-flowering plants in open areas with fine-grained soil (when and indicate where each species population is aggregated in space, we where water stress should be highest, Table 1). confirmed our results by mapping count data using ArcGIS 10.6.1 (ESRI, 2019, Figure 1).

2 | MATERIALS AND METHODS 2.3 | Environmental variation 2.1 | System 2.3.1 | Soil texture and penetration resistance Clarkia (Onagraceae) is a genus of approximately 40 winter annual flowering plant species largely endemic to the western portion of To characterize soil texture, we collected the taproot and a cylindri- North America. The Clarkia species in the Kern River Canyon co- cal 10 × 15 cm soil sample of surrounding soil of 12–15 individuals occur most commonly at moderate elevations in grasslands, pine- from each Clarkia species at each of the three sampled sites. After oak woodlands and chaparral habitats in the foothills of the Sierra separating the roots from the soil, we followed the soil-texture Nevada Mountains in southern California (Lewis & Lewis, 1955). analysis protocol outlined in Kramer et al. (2011). First, we dried soil Clarkia is a genus of winter annuals: they germinate with late winter samples in a drying oven at 70°C for 48 hr. After drying, we bulked rains, grow throughout the spring, flower over the course of May and samples by pooling three soil samples from each species at each site. June and senesce in mid-late summer. Water relations throughout This gave us four–five soil texture replicates per site, per species the summer are likely critical for the fitness of Clarkia species, as (N = 12–16 per species). We sieved each bulked soil sample through flowering and fruiting individuals are subject to terminal drought in a 2-mm sieve to remove gravel, and then machine-sieved samples mid- to late-summer when most other winter annuals have senesced. through 1-, 0.5-, 0.106- and 0.053-mm sieves (Eckhart et al., 2010; Kramer et al., 2011). We weighed the amount of soil in each sieve size. As in Kramer et al. (2011), we did not separate silt and clay soil 2.2 | Spatial clustering fractions because they represented less than a 5% soil fraction of the total sample. We used centred and scaled soil texture propor- To assess patchiness, we estimated spatial clustering of each spe- tions from each sample to run a principal component analysis (PCA) cies of Clarkia in communities where all four Clarkia species natu- of species' patch soil types to determine the extent to which vari- rally occur in February 2016 and February 2017. In 2016, we set up ation in soil texture explained patch types. Horn's parallel analysis semi-permanent transects in three Clarkia communities (China was conducted to decide the number of principal components to Gardens [0.48 ha, 35°32′18.18″N, 118°38′58.52″W]; Kingsnake retain in our PCA. [0.55 ha; 35°31′45.68″N, 118°39′34.52″W]; and Democrat [0.30 ha; To confirm the relationship between the soil texture and penetra- 35°31′50.94″N, 118°37′38.20″W]). At each site, we laid transects tion resistance in the Clarkia system, we measured soil resistance to 7 m apart and stretched across the site from the lowest elevation to penetration with a soil penetrometer (Spectrum SC-900, Spectrum the highest. Along each transect, we placed –0.5 m2 quadrats every Technologies) at the experimental site where we measured plant 10 m. In 2016, we counted the number of each species' seedlings in demography, Kingsnake. We measured both maximum penetration each quadrat at all three sites in late February, after all species had depth and soil penetration resistance at the surface and at 2.5, 5, germinated (N: China Gardens, 69; Democrat, 58; Kingsnake, 101). 7.5 and 10 cm below the surface in 41 evenly spaced locations on In 2017, we only counted the seedlings at China Gardens in the early 16 June 2018 (N = 11 locations in the C. cylindrica patch; N = 10 for spring due to time constraints and because Kingsnake had been ma- the other three patches). This date was at the very end of the Clarkia nipulated for an experiment. growing season and the very driest conditions that Clarkia experi- We measured spatial clustering for each species in each site ence as adult plants; all Clarkia in the community were fruiting at this using the variance and mean of count data to describe the patchiness time. Therefore, these penetration resistance estimates represent of a population (Chen, Shiyomi, Hori, & Yamamura, 2008; Shiyomi the hardest soils that Clarkia experience in their growing season. & Yoshimura, 2000). Population aggregation is described by the Some very hard soils did not yield quantitative pressure read- equation ( 2 −m)∕m2, where 2 and m are the variance and mean ings, so we also recorded the maximum depth we could insert the of the sample population, respectively. By this measure, a randomly penetrometer for each measurement. We analysed patch-level dif- distributed population would have equal mean and variance, as in a ferences in soil penetration resistance using two ANOVAs: (a) the random Poisson distribution, and population aggregation would be maximum depth of penetration by patch type and (b) soil resistance zero (Chen et al., 2008; Shiyomi & Yoshimura, 2000). We then ran to penetration by depth and patch type. For the latter, we ran model a one-sided t test for each species using our four measurements of selection using AIC estimates to determine the best model of soil JAMES et al. Journal of Ecolog y | 5

FIGURE 1 Heat maps of Clarkia seedling occurrence and abundance from transects surveyed in 2016. Each row corresponds to a site, and each column corresponds to a Clarkia species. Point colour corresponds to species (yellow, C. cylindrica; green, C. unguiculata; red, C. speciosa; purple, C. xantiana) and point size corresponds to the count of seedlings in plots (seedlings per ½ m2). Small, gray points represent surveyed plots with no Clarkia individuals of that species. Shaded areas in between points represent interpolated abundance between surveyed plots, where darker hues indicate high abundance; high and low ranges vary between sites depending on minimum and maximum observed seedlings in plots (‘Count’) resistance to penetration, where the most complex model included method for each location. To determine which classes to use in an interaction of the terms. identifying woody plant canopies, we compared chosen classes to the original four-band imagery. The chosen canopy classes were then used to extract cells that best represented the canopies in 2.3.2 | Distance from woody plants each location, and the raster-to-polygon command was used to convert the canopy rasters to polygons. We calculated the dis- We estimated the distance between the canopy of woody plants tance from each plot to the nearest canopy using the Near com- and plots in each of the three sites using ArcGIS 10.6.1 (ESRI, mand. Because we determined proximity to woody plants from 2019). First, we used the GPS Tracks App (version 3; Morneault, aerial imagery, we did not identify the shrubs and bushes to spe- 2016) to record the latitude and longitude of each plot from the cies. However, the dominant woody plants of the area (and at the semi-permanent transects (Figure 1). We then identified woody Kingsnake site) are oak trees Quercus douglasii and Q. wislizenii, plant canopies at our sites using remotely sensed imagery avail- pine trees Pinus sabiniana and Ceanothus shrubs Ceanothus sp., able from the California Department of Fish and Wildlife (CDFW, Rhamnaceae. 2019). Aerial imagery from the 2016 USDA National Agriculture We used zero-inflated statistical models to predict pres- Imagery Program (NAIP) was downloaded in a geo-tiff file format ence and abundance of each species as a function of distance and processed using an iso-cluster unsupervised classification from woody plants. We used zero-inflated negative binomial 6 | Journal of Ecology JAMES et al. regressions to predict presence and abundance of C. cylindrica, C. in the absence of congeneric competition, we report demographic speciosa and C. unguiculata as a function of distance from woody rates from only these 128 control plots. plants. For C. xantiana, we used a zero-inflated Poisson regression In October 2017, we secured eight, evenly spaced cabone craft- to predict presence and abundance a function of distance from ing rings (5 cm in diameter, CSS Industries, Inc.) in each plot using woody plants. two, 4-cm long fence staples on each side. Two rings per plot were assigned to one of the four species (two focals per species/eight focal plants total in each plot). We sowed 25 seeds into each cab- 2.3.3 | Abundance of annuals other than Clarkia one ring as the ‘focal plants’ from which we estimated germination, survival to reproduction and fecundity. Sown seeds had been col- To compare the abundance of non-Clarkia annual plants between lected from various Clarkia communities in the range of sympatry patches, we counted grasses and forbs in a 10 cm diameter around of the four Clarkia species in 2017, mixed together to homogenize the focal Clarkia location at the same time we assessed Clarkia ger- and randomly counted out for planting into this experiment. We mination in experimental plots at Kingsnake (see below). This was also buried 160 seed bags with 50 seeds each into each patch type done irrespective of if or how many Clarkia had germinated in the to estimate seed survival (10 bags per species per patch type). focal rings. The total counts of grasses and forbs from all 10 cm focal In late February—early March of 2018, when seedlings had just rings (eight in total) were summed for a plot-level estimate of grasses started growing two true leaves, we counted the seedlings in the and forbs (i.e. grass or forb per 0.06 m2). cabone rings in each ring to measure germination. We then thinned We analysed grass and forb counts separately. For each, we to one focal Clarkia seedling in the cabone ring, selecting the ger- used the patch-level count as the response variable in a gener- minant that was growing closest to the centre of the ring. We chose alized linear regression with the negative binomial family, using to count and thin seedlings at this time to balance the necessities patch type as the explanatory variable. To determine whether of (a) surveying as early as possible to minimize the possibility of patches were significantly different from each other in grass or post-emergence mortality and (b) surveying as late as possible to forb abundance, we used a combination of post-hoc tests: first, maximize our confidence in species identification, and that we had estimated marginal means for estimating the differences between counted all potential germinants. In other transplant experiments groups, and second, a Tukey test to determine which patch pair- of C. xantiana, where germination was recorded monthly from wise differences of grass and forb abundances were significant January through May, 97% of germination occurred by the end of

(r package EMMEAnS, Lenth, 2019). February (M.A. Geber, unpubl. data). In November 2018, we recovered buried bags to attempt germination of the remaining seeds for an estimate of seed survival. We 2.4 | Performance measures emptied the contents of the bags into a tea ball strainer and cleaned in a 1% bleach solution and counted the number of seeds. We then 2.4.1 | Experimental design applied a cold treatment (20°C) to seeds in sealed Petri dishes with wet filter paper, exposed them to a 24-hr light treatment for 5 days, To estimate performance in the absence of congeneric competition, and counted germinated seedlings. Remaining seeds were cut lon- we installed plots across a site where all four species naturally occur, gitudinally, placed in 1% tetrazolium solution in 96-well plates and Kingsnake, in 2016. This was part of a larger project to estimate how assessed for stain (indicating viability) after a 24-hr dark treatment. competition varies between all four species of Clarkia across spa- Seed survival was recorded as successful if either it germinated or tial variation and with respect to pollinator-mediated interactions. stained red with the tetrazolium treatment. Our experimental design was a common garden experiment of pair- Previous research has demonstrated that Clarkia reproduc- wise competition plots with focal plants sown into a background tive competition (mediated by shared pollinators) in this sys- of neighbours to estimate pairwise interaction coefficients (after tem is nontrivial and can affect outcomes of Clarkia interactions Godoy & Levine, 2014; Kraft, Godoy, & Levine, 2015; Wainwright, (James, 2020). However, testing spatial coexistence requires an Hillerislambers, Lai, Loy, & Mayfield, 2019). We modified this design estimate of plant performance in the absence of competition be- by first splitting the site into four patch types according to where tween focal species. Because interactions during pollination can each of the species was most abundant (Figure 1). We placed 160 affect plant–plant interactions (as in Lanuza et al., 2018), we sup- experimental plots (640 plots total), each 1 m2 in area in each patch plemented one fruit from each focal plant with conspecific pollen type. Space was limited; as such, plots were placed roughly 0.25 m to eliminate the effects of competition introduced by pollinators. apart from each other in groups of four, where groups of four were At the end of the growing season, we counted all focal plant fruits roughly 0.5 m apart from each other. In 2016 and 2017, we cleared and collected supplemented fruits to estimate seed production each plot of all Clarkia at the end of the growing season. Of the 640 from each focal plant in June–July of 2018. Fecundity, or esti- 1-m2 plots in the experiment, we chose 128 plots (32 per patch type) mated per-plant seed production, was calculated as the product to receive no experimental background Clarkia seeding density. of the seed count from the supplemented fruit and the number of Because this study is concerned with the performance of Clarkia fruits on the plant. JAMES et al. Journal of Ecolog y | 7

2.4.2 | Demographic and population growth The nine Clarkia communities we sampled were chosen to maximize rate analysis variation in flowering schedule: three communities comprised of the early flowering species (C. cylindrica and C. unguiculata), three of the To understand whether vital rates of each Clarkia varied according late-flowering species (C. xantiana and C. speciosa) and three of all to patch type, we ran model selection on each rate we investigated species (Table S1). (germination, fecundity, seed survival and survival to reproduction), Flowering phenology was determined using models of daily where the most complicated model included plant species, the patch flowering abundance. We gathered flower abundance data by vis- type it was grown in, and their interaction as fixed effects. We did not iting each Clarkia community on 9-day rotation (one site per day; use random effects because including them resulted in overfit, singu- Table S1). Before flowering began, we placed four, 20-m long, lar models. If the most complex model had the lowest AIC for a vital semi-permanent transects where Clarkia plants were abundant into rate, it would indicate that each species' performance in that rate de- each of the nine communities. Along these transects, we haphaz- pends on patch type, and that species perform best in different patch ardly placed a ½-m2 quadrat on either side of the transect line and types. We note that estimated germination rates are not confounded counted the number of flowers of each species in the quadrat at by emergence of voluntary seedlings from the seed bank. Voluntary 4-m intervals. We counted open flowers in the same way on the seedlings emerging from the seed bank would have been detectable same four transects for every community on survey days (Table S1). in cabone rings whenever the focal species planted in the ring dif- To assess Clarkia phenology, we estimated the date of peak fered from the ‘resident’ species that dominated that part of the site. flowering. Early dates of peak flowering indicate an early phenol- Across the 1,024 cabone rings in the 128 plots included in this study, ogy, and later dates of peak flowering indicate a later phenology. We only 9 (or <1%) had seedlings of non-focal species. first summed all flowers counted in all quadrats of each species for For each demographic rate, the model with the lowest AIC each survey day. We then fit a set of candidate models to these data. was the model we used to calculate species' patch-level popula- Models were built with and without a second-order quadratic term tion growth rates. Parameter estimates were generated using the for date to use for model selection; the most complicated model in-

EMMEAnS package in r (Lenth, 2019). We used generalized linear mod- cluded an interaction of this quadratic function of date and species els with the binomial family to model germination, seed survival and identity. Including the quadratic function in our models allowed for survival to reproduction, and fecundity with the negative binomial detecting a hump shape in flower abundance through time (increase family. and then decrease in floral abundance as the season progressed). We use a simple equation of annual plant population growth We used a generalized linear model with a negative binomial dis- to determine population growth rates of each species of Clarkia tribution to estimate flowering abundance through time for each

Nt+1 when grown in each patch: = (1 − gi)si + giFivi which relates species; we did not include a random effect of site because these Nt germination (g), seed survival (s), fecundity (F) and survival from models were singular and overfit. We calculated model AIC to de- germination to fruiting (v) of species i to predict its population termine the best-fit model of flowering abundance, and using this growth (Levine & Hillerislambers, 2009). We computed the popu- model, we extracted the model-estimated date of peak flowering lation growth rate for each species in each patch type using the es- abundance for each species. timates from the models described above as parameter values. We parameterized the population growth equation by converting the log-odds averages of seed survival (si), germination (gi) and survival 2.5.2 | SLA to reproduction (vi) rates to probabilities, using these probabilities and per-plant fecundity (Fi) estimates as parameter values for each In the summer of 2017, we sampled fresh leaves from each species of species in each patch type. plant in the three communities of interest for estimating SLA. In each community, we collected leaves from 12 to 15 individuals from each species in their home patch types. We removed one or two turgid, 2.5 | Plant water-use traits and indicators green leaves from each plant, pressed them flat against a piece of paper alongside a sticker of known diameter, and took a photo (iP- 2.5.1 | Flowering phenology hone 8S) of the leaf. We used ImageJ to estimate the area of the leaf (in mm2, ImageJ 1.x, Schneider, Rasband, & Eliceiri, 2012), using the Depending on the year, Clarkia in the Kern River Canyon begin flow- sticker as a reference for size. Leaves were dried in a drying oven for ering in the last week of April or first week of May. Flowering tapers 48 hr at 65°C and weighed to the nearest 0.01 g. SLA was calculated in second or third week of June. To gather information about the by taking the ratio of the measured area and the corresponding dry flowering phenology of the four Clarkia species, we surveyed flo- mass of the sample in mm2/g. We log-transformed SLA values and ral densities in nine different Clarkia communities from 4 May to 8 used them as the response variable in a mixed effects linear model, June in 2017. We chose to sample in this window of time based on using site as a random effect. We estimated pairwise species dif- previous knowledge of Clarkia flowering schedules in the area and ferences in SLA estimated marginal means using the Tukey method observation over the course of the season (M.A. Geber, pers. obs.). (package EMMEAnS, Lenth, 2019). 8 | Journal of Ecology JAMES et al.

2.5.3 | Midday stem water potential 3 | RESULTS

In the summer of 2017, we measured midday stem water potential 3.1 | Spatial clustering and environmental variation

(Ψmid) of each Clarkia species in three communities where all species naturally occurred (China Gardens, Kingsnake and Mill Creek Three species were spatially aggregated (Clarkia cylindrica t3 = 15.14,

[0.58 ha; 35°32′15N, 118°36′49W]). We chose to measure midday p ≪ 0.001; C. speciosa t3 = 6.02, p = 0.009; C. unguiculata t3 = 8.33, stem water potential instead of leaf water potential because the pet- p = 0.003; Figure S1). Though mean aggregation of the fourth spe- ioles of at least one of the species of interest, C. xantiana, collapse cies, Clarkia xantiana, was well above zero (and therefore aggregated before readings can be taken using a pressure chamber (Eckhart on average), the SE was large and it was not significantly aggregated et al., 2010). (t3 = 1.18, p = 0.32; Figure S1). This result is due to extremely low We sampled the three sites for plants from each species in counts of C. xantiana in 2016 in both China Gardens (total: 1 seed- each community (N = 137 plants: 34 C. cylindrica; 36 C. speciosa; ling) and Kingsnake (total: 2 seedlings). Despite the statistical results, 31 C. unguiculata and 36 C. xantiana). Samples were collected from all four species clearly occur separately from each other, including plants where they were most abundant (i.e. their home patch, C. xantiana (Figure 1). In the 2017 China Gardens survey, C. xantiana Figure 1) between 1:00 p.m. and 2:30 p.m. over the course of 10 was much more abundant, had an estimated aggregation value of sampling periods during peak flowering for each species. To mea- 25.3 and occurred in the same area of China Gardens as in 2016. sure Ψmid, we haphazardly selected a plant with at least one open flower and one fresh leaf. We then cut the stem with a razor blade at either 5 cm (C. cylindrica and C. speciosa) or 10 cm (C. unguiculata 3.2 | Soil texture and penetration resistance and C. xantiana) from the top of the main stem. We cut at different heights from the top because of differences in plant architecture: The first two principal components in the PCA of soil texture had ei- C. cylindrica and C. speciosa have more congested inflorescences genvalues >1, and Horn's parallel analysis retained two components (i.e. shorter internodes on racemes) than C. unguiculata and C. xan- (two components had adjusted eigenvalues >1). PC1 accounted for tiana. We used a pressure chamber (PMS Instruments) to measure 48.7% of variation in the data, and loadings revealed that soil from

Ψmid within 1 min after cutting. Data are reported in megapascals different patches segregated along coarse- and fine-grained soil (MPa), where more negative values indicate lower stem water po- (Figure 2). PC2 accounted for 28.8% of the variation in the data, and tential (greater water stress). We used a linear mixed-effects approach to model Ψmid, setting species as the fixed effect and site as the random effect. We estimated pairwise species Ψmid differences in estimated marginal means using the Tukey method (package EM-

MEAnS, Lenth, 2019). 2

2.5.4 | Water-use efficiency 2 1 m m

In the summer of 2016, we collected leaves for estimating the u m106 water-use efficiency of each Clarkia species. Turgid, green leaves 0 were collected from three plants per species at the same three

53 sites listed above on the same day during the growing season um

m Patch type m1

(when all species were flowering) and dried in a drying oven for e in –1 C f 48 hr at 65°C. Leaves were then ground with a mortar and pestle

Standardized PC2 (28.8% explained var.) S

U m m and analysed using a Thermo Delta V isotope ratio mass spec- 5 X trometer linked to a NC2500 elemental analyzer at the Cornell University Stable Isotope Laboratory. Carbon isotope ratios are –2 –3 –2 –1 01 reported as corrected isotope delta value against the Vienna 13 Standardized PC1 (48.7% explained var.) Pee Dee Belemnite reference scale in units permille (δ C, ‰) with a sample run standard deviation of 0.16‰. We used a gen- FIGURE 2 Principal component analysis of soil particle size 13 eral linear model to compare δ C isotope ratios. As with stem distribution between patch types, where particle size bins are water-use potential, we used a linear mixed-effects model with 2 mm–1 mm (‘mm2’); 1 mm–0.5 mm (‘mm1’); 0.5 mm–106 µm (‘um106’); 106 µm–53 µm (‘um53’); <53 µm (‘fine’). Soil texture Clarkia species as a fixed effect and site as a random effect. distinguishes Clarkia speciosa (coral squares) from Clarkia xantiana Pairwise species differences of estimated marginal means were (purple diamonds) patches, but not Clarkia cylindrica (yellow circles) calculated using the Tukey method (package EMMEAnS, Lenth, and C. unguiculata (slate stars) patches. C. speciosa patches have 2019). higher proportions of small particle sizes than C. xantiana JAMES et al. Journal of Ecolog y | 9 loadings generally distinguished the gravel fraction from the rest of significantly predicted where C. speciosa occurred, where the log- the soil texture fractions (Table S2). odds probability of occurring significantly increased with distance Soil texture distinguished two species strongly. PC1 and PC2 from woody plants (log-odds = −0.92, Figure 3). Finally, distance differentiate the soil textures of C. speciosa and C. xantiana patch from woody plants did not significantly predict the presence/ab- types, where C. xantiana patches had coarser soils than C. speciosa, sence of C. cylindrica or C. xantiana. and a higher fraction of gravel. The other two species patch types, C. unguiculata and C. cylindrica, were highly variable and not distin- guishable in a PCA plot (Figure 2). 3.4 | Abundance of annuals other than Clarkia A one-way ANOVA of maximum depth of soil penetration as described by patch type was statistically significant (F3,37 = 4.3, Counts of grasses and forbs varied among patches. Tukey pair- p = 0.01), and a Tukey HSD post-hoc comparison revealed maximum wise comparisons of grass counts among patch types revealed depth of soil penetration in the C. speciosa patch type was shallower that the C. cylindrica and C. unguiculata patches had lower grass on average than other patch types (C. speciosa patch: 8.9 cm ± 0.56 abundance (respectively, 38.9 ± 5.3 SE and 29.9 ± 4.7 SE per SE; C. cylindrica patch: 11.07 cm ± 0.51 SE; C. unguiculata patch: 0.06 m2) than the C. speciosa and C. xantiana patches (68.3 ± 10.5 11.43 cm ± 0.56 SE; C. xantiana patch: 10.92 cm ± 0.56 SE), confirm- SE and 82.4 ± 11.26 SE per 0.06 m2, respectively; Figure S3), ing that the finer soils of that subsite are harder to penetrate, at least but differences between the two groups were not significant. in the driest part of the growing season (Figure S2). This trend was Pairwise comparisons of forb abundance reveal that forb counts also true in the analysis of penetration resistance: the best model were highest in the C. speciosa patch (36.4 ± 9.01 SE per 0.06 m2) of soil penetration resistance (in MPa) included the additive effects and similar among the rest of the patches (C. cylindrica 6.0 ± 1.57 of patch type and depth (Table S3); a two-way ANOVA and corre- SE; C. unguiculata 6.5 ± 1.91 SE and C. xantiana 11.3 ± 3.21 SE per sponding Tukey HSD post-hoc comparison of soil penetration resis- 0.06 m2; Figure S3). tance by patch type shows that the soils of the C. speciosa patch had significantly higher penetration resistance than the other three patches (F3,177 = 10.2, p < 0.001, mean soil penetration resistance by 3.5 | Plant performance in each patch type patch: C. speciosa, 0.63 MPa ± 0.06 SE; C. xantiana, 0.35 MPa ± 0.05 SE; C. cylindrica, 0.26 MPa ± 0.05 SE; C. unguiculata, 0.20 MPa ± 0.05 3.5.1 | Vital rates SE). The best-fit model for each vital rate (germination, fecundity, seed survival and survival to reproduction) differed. The lowest 3.3 | Distance from woody plants AIC model of germination included an interaction between species and patch type (Table S4). Post-hoc estimates of germination The presence/absence of each species as a function of distance in this model reveal that three of the four species (C. speciosa, from woody plants shows that C. unguiculata abundance declined as C. unguiculata and C. xantiana) exhibited highest germination in a function of distance, where the intercept was 9.1 plants per 0.5 m2, their ‘home’ patches (i.e. where they are naturally most abun- and an increase in distance of a meter corresponded to a decrease dant; Table 2, Figure S4). The fourth species, C. unguiculata, ex- of 0.64 times its abundance. Distance from woody plants also hibited the highest germination rates in the C. cylindrica patch.

(A) (B)

FIGURE 3 Clarkia species count data as a function of distance from a woody plant (in metres). Count data are from (C)(D) the 2016 surveys of Clarkia abundance (see Figure 2.1). Gray points are observed count data. Lines and ribbons are model predictions and standard errors of the predictions, respectively. Distance from woody plants significantly B positively predicted the presence of Clarkia speciosa and C negatively predicted Clarkia unguiculata count 10 | Journal of Ecology JAMES et al.

TABLE 2 Estimates of demographic rates and population growth rates of each species in each patch. Bolded values of population growth rates are the highest values for each species. Each rate is reported as the best-fit model-estimated M ± SE. Seed survival and survival to reproduction do not vary by species, patch, or their interaction, and accordingly have one value across all species X patch combinations; they are only listed once

Survival to Clarkia species Patch log(PGR) Germination Fecundity Seed survival reproduction

C. cylindrica C. cylindrica 2.28 0.043 ± 0.005 461 ± 125.8 0.47 ± 0.006 0.55 ± 0.03 C. speciosa 1.60 0.021 ± 0.004 C. unguiculata 0.48 0.0053 ± 0.002 C. xantiana 1.49 0.018 ± 0.004 C. speciosa C. cylindrica 0.23 0.01 ± 0.002 167 ± 93.2 C. speciosa 0.79 0.022 ± 0.004 C. unguiculata −0.47 0.002 ± 0.001 C. xantiana 0.27 0.011 ± 0.003 C. unguiculata C. cylindrica 1.83 0.041 ± 0.004 296 ± 106.1 C. speciosa 1.34 0.024 ± 0.004 C. unguiculata −0.07 0.0033 ± 0.001 C. xantiana 1.68 0.035 ± 0.005 C. xantiana C. cylindrica 0.91 0.030 ± 0.004 145 ± 48.6 C. speciosa 0.45 0.016 ± 0.003 C. unguiculata −0.03 0.0073 ± 0.002 C. xantiana 1.49 0.058 ± 0.006

(A) (B) In fact, all four species exhibited lowest germination in the C. 2.5 unguiculata patch; germination of any species in this patch was 2.0 lower by an order of magnitude than all other germination in all 0.5 1.5 patches.

1.0 Speciosa The best-fit model for fecundity included only species as ex- Cylindrica 0.0 planatory variable, and the next-best fit model with almost equiv- 0.5 alent AIC included only the intercept (ΔAIC = 0.58; Table S4). 0.0 Estimated fecundity from the model with the lowest AIC was CSUX CSUX (C) (D) highest by far in C. cylindrica (461 seeds per plant ± 125.8 SE), fol- 2.0 log(PGR) lowed by C. unguiculata and C. speciosa; it was lowest in C. xantiana 1.5 (145 seeds ± 48.6 SE, Table 2). In the case of both seed survival 1.5 and survival to reproduction (germination to fruiting), the best-fit 1.0 1.0

model included only the intercept, indicating that these two rates Xantiana Unguiculata 0.5 did not differ among species or patch types (estimated seed sur- 0.5 vival: 0.47 ± 0.006 SE and survival to reproduction: 0.55 ± 0.03 SE, 0.0 0.0 Table S4). CSUX CSUX Patch type

Plant performance in each patch type by species. Each 3.5.2 | Population growth rates FIGURE 4 panel is a different species, each bar is the estimate for log(population growth rate) in the patch type. Gray indicates positive population Three of the four species, C. cylindrica, C. speciosa and C. xantiana, growth rate (replacement or more), black indicates negative growth all had the highest population growth rates in their home patches rates (decline). All species but one (C. unguiculata, panel C) exhibit the (Table 2, Figure 4). The fourth species, C. unguiculata, exhib- highest population growth rates in their home patches ited the highest population growth rate in the C. cylindrica patch. Furthermore, in all cases but one, the log of the population growth 3.6 | Variation in water-use traits and indicators rate was greater than zero, indicating that with one exception (C. speciosa planted into C. unguiculata patch type), all four species The four Clarkia species varied in the two traits we measured, can persist in all patch types in the absence of competition. flowering phenology and SLA. Flowering abundance, which we JAMES et al. Journal of Ecolog y | 11

(A) (B) used to predict the date of maximum floral density (phenology),

) was best predicted by an interaction of species and a second-order

( quadratic function of date (Table S5). This best-fit model shows C. unguiculata was the earliest (peak flowering at 10 days); followed by C. cylindrica (17 days), C. speciosa (22 days) and C. xantiana (26 days; Reported as days after 5 May; Figure 5, Panel A). Species (C) (D) also differed in mean SLA values. Pairwise comparison of species ) SLA values indicate that C. unguiculata had the highest SLA, then (

δ C. cylindrica, followed by the late species C. speciosa and C. xan- ψ tiana, which were statistically indistinguishable from each other (Figure 5, Panel B; Table 3). Clarkia also experienced different water stress in their home FIGURE 5 Flowering phenology, SLA, stem midday water patches, which is reflected in both of the hydrological indicators we potential and 13C carbon isotope discrimination (a proxy for water- δ measured. Clarkia unguiculata exhibited the highest midday stem use efficiency) of each of the four Clarkia species. Points and lines in panels B, C and D represent means and 95% confidence intervals; water potential in its home patch, which was significantly higher letters indicate statistically similar values. (A) Model predictions than the other three species in their home patches (Figure 5, Panel of Clarkia abundance through time, where coloured lines are the C; high to low: C. xantiana, C. cylindrica and C. speciosa; Table 3). estimated abundance and gray ribbons indicate standard error of Clarkia speciosa exhibited significantly lower Ψmid values than the model estimates (data not shown). (B) SLA for each species. (C) Stem other three species (Table 1, Figure 5, Panel C). In addition, spe- midday water potential for each species. C. unguiculata is under the cies differed in their 13C ratios, where the two early-flowering least water stress in its home patch and C. speciosa was under the δ most water stress. (D) delta-13 carbon isotope discrimination values species, C. cylindrica and C. unguiculata, had lower (more negative) 13 for each of the four species. Water stress was lower for early- δ C ratios than their late-flowering counterparts, reflecting lower flowering species compared to the late-flowering species water-use efficiency (Tables 1 and 3; Figure 5, Panel D). The val- 13 ues for δ C ratios within these two groups were not significantly different.

TABLE 3 Trait/indicator values for each species when sampled in its own patch type. For date at maximum flowering abundance, we report both the model estimated maximum flower abundance 4 | DISCUSSION and corresponding date of predicted maximum flowering abundance. Dates are reported as days after 5 May. For phenology, In this work, we sought to describe the potential for trait-based, hy- standard errors are reported for floral abundance (the object of drological niche-related spatial coexistence in four co-occurring spe- prediction), but not the date (across which we generated floral abundance estimates) cies of winter annual forbs in Clarkia (Onagraceae). We first asked whether variation in soil texture and canopy cover, both important Trait of for plant water relations, dictated where Clarkia occurred within indicator (units) Species Estimate SE communities. We then used a reciprocal transplant experiment in Maximum C. cylindrica 1117/17 days 469.78/NA one of these communities to ask if such environmental variation flowering C. speciosa 262.7/22 days 107.02/NA abundance/ corresponded to demographic outcomes for Clarkia species in the date at C. unguiculata 738.9/10 days 281.40/NA absence of competition. Finally, we asked whether traits related to maximum C. xantiana 242.4/26 days 98.29/NA water-use could help explain species performance along these small- abundance scale environmental gradients. SLA (g/mm2) C. cylindrica 1.8E + 04 2.2E + 03 C. speciosa 8.6E + 03 2.2E + 02 C. unguiculata 2.4E + 04 2.1E + 03 4.1 | Plant water-use traits and water stress C. xantiana 5.1E + 03 2.2E + 02 correspond to patch attributes Midday C. cylindrica −1.65 0.08 stem water C. speciosa −1.88 0.08 We found that co-occurring Clarkia species do sort according to both potential, Ψmid soil texture and association with woody plant canopy, and that spe- (MPa) C. unguiculata −0.67 0.08 cies' trait values and the water stress they experienced were con- C. xantiana −1.63 0.07 13 sistent with where plants occur along these gradients. Importantly, δ carbon C. cylindrica −33.3 0.30 however, the water stress that species experienced was a function discrimination C. speciosa −30.9 0.30 (‰, water-use of the time of year as well as spatial location. C. unguiculata −32.7 0.30 efficiency) Canopy proximity was important for only one of the early flow- C. xantiana −31.5 0.30 ering species, where proximity to woody plants predicted where 12 | Journal of Ecology JAMES et al.

C. unguiculata, the earliest flowering species, both occurred and unguiculata patch versus the other patches that are in open sun. was most abundant. SLA values may reflect this: C. unguiculata Assessing soil moisture at germination would also be informative— exhibited the highest SLA, indicating lower cost of leaf produc- despite the fact that soil grain size and canopy cover distinguished tion, shorter leaf life span and lower water stress due to growing Clarkia patches, we still do not know how soil moisture levels vary 13 in the shade (Table 1). Though their δ C ratios were statistically by patch and through time. Given our results, soil moisture should indistinguishable, the two early-flowering species also had large be especially relevant at times when roots are actively trying to differences in Ψmid values, where it was evident that C. cylindrica penetrate the soil. Finally, though we did not measure soil mois- experienced higher water stress in its home patch than C. unguic- ture content, it could be relevant for a full picture of patch hy- ulata. This could be explained by the fact that sun exposure, even drology: penetration resistance also declines with soil moisture in the earlier part of the season, causes higher water stress for C. (Bradford, 1986), but we only measured the relationship of pene- cylindrica in its home patch. The difference in Ψmid values could tration resistance and soil texture. also be a function of the later flowering time of C. cylindrica compared to C. unguiculata, perhaps after some amount of seasonal dry down. Taken together, these results suggest a trade-off re- 4.2 | Population growth rates are spatially variable lated to sun exposure and shade exposure that allows these two because of germination species to maintain similar carbon assimilation rates where they co-flower, where C. unguiculata is light-limited and C. cylindrica is Strikingly, we found that home patches conferred higher popula- water-limited. tion growth rates in three of the four species. This result is at As predicted, soil texture was most important for the late-flow- least consistent with the theoretical requirements for spatial ering species, where C. xantiana occurred in coarser soils and C. spe- coexistence: that species perform best either (a) in areas where ciosa in much finer soils, an established trend in these two species they are most abundant (growth-density covariance) or (b) where (Eckhart et al., 2017; Kramer et al., 2011). This makes sense in light they experience the highest competition (environment–com- of the fact that soil texture determines how difficult it is for plants to petition covariance; Chesson, 2000; Snyder & Chesson, 2004). obtain water in arid environments (Alizai & Hulbert, 1970; Barnes & Interestingly, studies of plant coexistence tend to focus on the Harrison, 1982; Kinraide, 1984; Sperry & Hacke, 2002), which is par- seed bank and other means of temporal variation in germination ticularly relevant when C. speciosa and C. xantiana are in flower. The (Angert et al., 2009; Baskin, Chesson, & Baskin, 1993; Chesson low Ψmid values of C. speciosa illustrate that it was under the high- et al., 2004; Gremer, Kimball, & Venable, 2016; Venable & est water stress, which is attributable to flowering in the drier part Lawlor, 1980, but see Pake & Venable, 2008), but this result sup- of the summer and occurring in soils with smaller particle size and ports longstanding theory that spatial variation can be another greater resistance to penetration than the C. xantiana patch (Eckhart means for plant species coexistence at the community scale. et al., 2010). Counter to our predictions, even in the face of the most This result is also relevant in applying coexistence theory to extreme water stress (as measured by Ψmid), C. speciosa exhibited natural plant systems: experimental studies in coexistence often 13 SLA values and δ C ratios similar to C. xantiana. It is possible this average over local spatial variation to estimate population growth species has some yet unmeasured physiological means by which to rates or competitive interactions in communities (e.g. Angert maintain its water status in extreme conditions; the functional roles et al., 2009; Bimler, Stouffer, Lai, & Mayfield, 2018; Godoy & of SLA, stomatal regulation and related traits deserve more study in Levine, 2014; Kraft et al., 2015; Petry, Kandlikar, Kraft, Godoy, & this system. Levine, 2018; Siefert, Zillig, Friesen, & Strauss, 2018; Wainwright Finally, the early–late distinction was most striking in species' et al., 2019), but our study illustrates that local spatial varia- 13 δ C ratios (a proxy for water-use efficiency), where it was clear that tion may be relevant for maintaining diversity at the scale of the late-flowering species (C. speciosa and C. xantiana) had much higher community. 13 δ C ratios than their early-flowering counterparts. This makes sense Even though the adult water-use traits and water stress in- in light of annual rainfall patterns of the area: the severity of sea- dicators we measured corresponded to variation in the environ- sonal dry-down significantly increases as C. cylindrica and C. unguic- ment, variable population growth rates were driven by spatial ulata decline in abundance and C. speciosa and C. xantiana increase in variation in the germination stage. There was no evidence that abundance. Efficient water economies are thus more critical for the this result was driven by accumulated seeds in the seed bank later-flowering species. before the experiment, either: we weeded Clarkia out of all plots Though we found differences among patches in patch soil for 2 years before the experiment, preventing seed rain, and texture and canopy cover, these are certainly not the only abi- germination of voluntary, non-target Clarkia species in the focal otic components of the environment that are important for cabone rings was exceedingly rare. Post-germination survival plant competition, performance and hydrology (for reviews, see and reproduction, the life-history stages most relevant to the Silvertown et al., 2015; Aschehoug, Brooker, Atwater, Maron, & water-use traits and indicators that we measured, did not vary Callaway, 2016). For example, it remains unknown how canopy according to patch; as such, they seem to have little bearing on cover contributes to carbon, nitrogen or litter levels in the C. spatial coexistence in this group of species. This may be a reason JAMES et al. Journal of Ecolog y | 13 to conclude that adult hydrological niche is unrelated to spatial Clarkia in the C. speciosa and C. xantiana home patches might coexistence in these species. On the other hand, there is empir- experience higher water stress not only due to seasonal dry ical and theoretical evidence that seed dormancy and differen- down, but priority effects in competition for water (Godoy & tial germination can set the stage for the selective environment Levine, 2014; Wainwright et al., 2011). Such potential competitive plants experience post-germination, thus determining the selec- dynamics might aggravate the water stress Clarkia experience in tive environment for post-germination plant traits (such as SLA those patches and may be integral to quantify how surrounding and phenology; Donahue, Rubio de Casas, Burghardt, Kovach, annuals change water availability to understand Clarkia interac- & Willis, 2010; Evans & Cabin, 1995; Venable & Lawlor, 1980). tion dynamics later in the season (a potential means of Higher Therefore, though we did not find evidence linking post-germi- Order Interactions; Bimler et al., 2019; Mayfield & Stouffer, nation plant traits and spatial variation in population growth in 2017). our 1-year study, it is possible that variable germination rates in Finally, because we measured plant species' average trait val- space and through time can shape how plants use water through- ues and related them to where plants occur in communities, we are out their lives. Follow-up research modelling this idea may help unable to quantify the extent to which variation in adult water-use us tease apart why, though plant trait values seem to match the traits contributed to individual demographic performance, nor the patches they grow in and suggest hydrological niche segregation extent to which the measurements we took are plastic responses (Silvertown et al., 2015), they do not drive trends in fecundity or to the environment (which could be important for coexistence; population growth. Muthukrishnan, Sullivan, Shaw, & Forester, 2020). However, if While we observed that germination rates were highest for traits do matter for spatial coexistence of Clarkia, our findings three of the four Clarkia in their home patches, the fourth patch suggest that traits in the germination phase of life, often an over- remains a mystery. One of our most unexpected results was how looked phase in trait-based community ecology, may be more rel- poorly all species, including C. unguiculata, performed in the C. un- evant to spatial coexistence than traits in the adult phase (Huang guiculata patch. The poor performance of C. cylindrica, C. speciosa et al., 2016). Because we investigated differences in adult plant and C. xantiana may be explained by either poorly timed or insuffi- traits, we have yet to identify a mechanism to explain spatially cient cues to germination: work in other arid systems confirms that variable germination. A partial explanation is almost certainly that for many annual plants, seed dormancy is conditional on tempera- species have different abilities to emerge from depth; as stated, ture, light or precipitation (Baskin et al., 1993; Chesson et al., 2004; previous research has shown that unlike C. speciosa, C. xantiana Dwyer & Erickson, 2016; Huang, Liu, Bradford, Huxman, & can germinate from depth, which is likely important in its home- Lawrence Venable, 2016; Juhren, Went, & Phillips, 1956). This patch coarse-grained soils (Eckhart et al., 2017). Spatially variable would not explain, however, C. unguiculata's low germination in its germination may also be a function of variable soil microbial com- own patch type. In 2017–2018, rainfall was much lower than aver- munities. Recently, microbial communities have been shown to af- age (California Department of Water Resources, 2018); it is possi- fect coexistence dynamics in plant communities (Ke & Wan, 2019; ble that any moisture the area did receive was intercepted by the Siefert et al., 2018). As such, a promising line of investigation is canopy in the C. unguiculata patch and as a result, seeds did not to determine the extent to which soil microbial communities may receive enough moisture to cue germination. Despite the unclear vary according to soil texture or patch vegetative properties (de mechanism, it is clear that Clarkia did not germinate well in the C. Vries et al., 2012; Štursová, Bárta, Šantrůčková, & Baldrian, 2016; unguiculata patch type in this study. Follow-up work investigating Xue, Carrillo, Pino, Minasny, & McBratney, 2018), as well as plant Clarkia germination through time (i.e. multi-year dormancy) could species-specific association at the seedling stage (e.g. due to nutri- illuminate how variability in germination rates through space and ents released into the soil during germination, as in Torres-Cortés time might interact with each other to determine plants' coexis- et al., 2018). tence dynamics in this system. It is also possible that certain water-use trait values only con- fer advantages in competition; in this case, we would have been 4.3 | Spatial variation is important for studying plant unable to detect the importance of certain trait values because coexistence in the field we were interested in performance in the absence of competition. For example, phenology has been demonstrably important for an- As attempts to apply coexistence theory in the field become more nual plant interactions and coexistence (Godoy & Levine, 2014; commonplace, our study is important in demonstrating the effect Wainwright et al., 2012). Now that there is evidence that Clarkia that environmental variation can have on plant demographic per- species perform best where they are most abundant in this sys- formance. However, seeing the way through to actually quantify- tem, future work can test for environment–competition covari- ing spatial coexistence in the field is as yet unclear—the theory that ance by assessing the effects of interspecific competition between we need to do so is not mature enough for application in systems these plant species in different patches (Adler et al., 2013; see like the Clarkia system, although we are inching closer (e.g. Ellner also Eckhart et al., 2017). In particular, the data we present on et al., 2019). Nevertheless, the results of this study decidedly patch-level differences in grass and forb abundance suggest that demonstrate that quantifying the contributions of growth-density 14 | Journal of Ecology JAMES et al. covariance and the spatial storage effect to plant coexistence will be Alizai, H. U., & Hulbert, L. C. (1970). Effects of soil texture on evapora- tive loss and available water in semi-arid climates. Soil Science, 110, a fruitful endeavour. 328–332. https://doi.org/10.1097/00010694-197011000-00006 In addition to laying the groundwork for eventually testing the Angert, A. L., Huxman, T. E., Barron-Gafford, G. A., Gerst, K. L., & theory of plant spatial coexistence in Clarkia, we also add nuance Venable, D. L. (2007). Linking growth strategies to long-term pop- to ideas of trait-based mechanisms of spatial coexistence in an- ulation dynamics in a guild of desert annuals. Journal of Ecology, 95, nual plants: whereas adult water-use traits do seem to correspond 321–331. https://doi.org/10.1111/j.1365-2745.2006.01203.x Angert, A. L., Huxman, T. E., Chesson, P., & Venable, D. L. (2009). to where a species performs best, it was in fact germination that Functional tradeoffs determine species coexistence via the storage drove differential plant performance in space. Consequently, it effect. Proceedings of the National Academy of Sciences of the United is likely that spatial trends in germination are important for de- States of America, 106, 11641–11645. https://doi.org/10.1073/pnas. termining the competitive environment of plants, the selective 0904512106 Araya, Y. N., Silvertown, J., Gowing, D. J., McConway, K. J., Linder, H. P., environment of plants or both. Importantly, we have provided ev- & Midgley, G. (2011). A fundamental, eco-hydrological basis for niche idence that community-scale variation is another potential means segregation in plant communities. New Phytologist, 189, 253–258. for plant demography and community diversity maintenance, and https://doi.org/10.1111/j.1469-8137.2010.03475.x should be carefully considered when applying coexistence theory Aschehoug, E. T., Brooker, R., Atwater, D. Z., Maron, J. L., & Callaway, R. M. (2016). The mechanisms and consequences of interspecific in the field. competition among plants. Annual Review of Ecology, Evolution, and Systematics, 47, 263–281. ACKNOWLEDGEMENTS Banuet, A. V., Crevenna, A. B., Briones, O., Ezcurra, E., Rosas, M., Nunez, The authors would like to thank Eric Brandt, Noel Graham, Aidan H., … Vazquez, E. (1991). Spatial relationships between cacti and nurse shrubs in a semi-arid environment in central Mexico. 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M., & Teeri, J. A. (1992). The ecology of elevational positions of the Cornell Statistical Consulting Unit provided guidance for the in plants: Drought resistance in five montane pine species in south- eastern Arizona. American Journal of Botany, 80, 15–25. https://doi. statistical methods. Thank you to Nathan Kraft and members of his org/10.1002/j.1537-2197.1993.tb13762.x laboratory, who all encouraged this investigation into the relation- Baskin, C. C., Chesson, P. L., & Baskin, J. M. (1993). Annual seed dor- ship between Clarkia traits and coexistence. Two anonymous re- mancy cycles in two desert winter annuals. The Journal of Ecology, 81, viewers also provided insightful comments that greatly improved the 551–556. https://doi.org/10.2307/2261533 Bchir, A., Escalona, J. M., Gallé, A., Hernández-Montes, E., Tortosa, I., manuscript. NSF DEB-1754299 to M.A.G. and NSF DEB-1256316 to Braham, M., & Medrano, H. (2016). Carbon isotope discrimination 13 V.M.E. supported this work. 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