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Seed weight variability of antelope bitterbrush (Purshia tridentata: Rosaceae).


Plants can regulate reproductive output by controlling propagule number and/or size. Seed weight can vary up to 20-fold in a species (Gross, 1984; Hendrix, 1984; Thompson, 1984). Much of the variation in seed weight within a species or population occurs within individual plants (52-98% Hendrix and Sun, 1989; 26-53% Marshall et al., 1985; 51.5% Mehlman, 1993; 62% averaged over 39 species, Michaels et al., 1988; 61% Obeso, 1993a). There is some discussion as to whether this variation is an adaptive response to environmental heterogeneity (McGinley et al., 1987), or an inability to maintain constant seed weights as environmental conditions change throughout seed filling (Winn, 1991). Seed weight is affected both by genetic and environmental differences; it is at least partially a plastic character, influenced by the environment of the parent plant and maternal ovaries during fruit filling (Lloyd, 1980; McGinley et al., 1987; Roach and Wulff, 1987).

Plasticity of seed weight has been demonstrated in numerous studies using annuals and herbaceous perennials. Seed weight has been shown to vary with differences in both the internal and external environments of the maternal plant. Internal variables include: (1) number of flowers per inflorescence (Winn and Werner, 1987); (2) pollen quality (Johnston, 1992); (3) timing of flower production (Cavers and Steel, 1984; Hendrix, 1984; Hendrix and Sun, 1989; Thompson and Pellmyr, 1989; Winn, 1991); (4) position in a fruit, inflorescence or along a flowering stalk (Schaal, 1980; Obeso, 1993a; Mazer et al., 1986; Winn, 1991; Stanton, 1984), and (5) plant size (Hendrix, 1984; Hendrix and Sun, 1989). Average seed size per plant varies with external environmental differences such as: (1) nutrient concentration (Stephenson, 1984; Schmitt et al., 1992; Wulff and Bazzaz, 1992; Aarssen and Burton, 1992); (2) population density (Lee and Bazzaz, 1980; Marshall et al., 1985; Matthies, 1990); (3) defoliation (Bentley et al., 1980); (4) light intensity (Schmitt et al., 1992); (5) habitat type (Winn and Werner, 1987); (6) mycorrhizal infection (Koide et al., 1988) and (7) temperature (Alexander and Wulff, 1985).

Plasticity of seed weight in woody perennials is not well described or known. Compartmentalization in woody species can result in the isolation to affected branches of factors such as defoliation (Obeso, 1993b). For example, by removing variable proportions of leaves subtending developing fruits, Stephenson (1980) showed that branches in Catalpa speciosa filled and matured fruit independently of each other; those with more leaves removed produced smaller seeds. Whole-plant-level variation in propagule size can also occur in woody plants. Vaccinium angustifolium shrubs produced larger berries on moist sites than those on drier sites (Pritts and Hancock, 1984). As in other perennials the effect of age on reproduction in woody plants is not well known. In Vaccinium corymbosum, though average berry weight was not affected by age, the total proportion of biomass allocated to reproduction quickly increased with age and then declined (Pritts and Hancock, 1985).

The study of seed-weight plasticity in the woody shrub, antelope bitterbrush (Purshia tridentata) has an important practical application since it is an important browse species for overwintering ungulate populations (Griffith and Peek, 1989) and the decline of antelope bitterbrush populations in much of its range in the intermountain region has been of concern (Rickard and Sauer, 1982; Updike et al., 1990). Restoration efforts do not ordinarily consider the quality of seeds gathered for dissemination even though in other species there is evidence to suggest that larger seeds grow into seedlings that are better competitors and are better able to survive to reproductive maturity (Black, 1958; Dolan, 1984; Marshall, 1986). This may also be true for antelope bitterbrush: results from an associated study suggest that seedlings from heavier antelope bitterbrush seeds are more likely to emerge than those from lighter seeds (Shatford, 1997).

In this study I partitioned seed weight variation among different habitats and antelope bitterbrush shrubs as well as tested the effect of livestock grazing and shrub size on seed weight. I also tested the correlation of the following factors with seed weight: (1) basal diameter and aboveground shrub volume, both of which are correlated with age (McConnell and Smith, 1963); (2) shrub health, as reflected by the proportion of dead branches; (3) browse intensity; (4) shrub density, and (5) soil characteristics. Knowledge of factors associated with seed weight in antelope bitterbrush will enable the collection of seed that may better facilitate management and restoration of local populations.


Antelope bitterbrush is a widely distributed shrub of deep, well-drained soils in western North America (Nord, 1965; Stubbendieck et al., 1992). It is found from southern British Columbia southward along the E side of the Cascade Mountain range and the Sierra Nevada to central California and E to Montana, Wyoming and Colorado (Hitchcock et al., 1961). In British Columbia it is generally found at low elevations (approximately 300 - 400 m), while farther S it is found only at higher elevations (above 1000 m in California: Nord, 1965).

Antelope bitterbrush has perfect flowers which are borne singly on short lateral shoots (Hitchcock et al., 1961). The flower produces a single fruit, an indehiscent, single-seeded achene. Antelope bitterbrush roots are associated with nodules containing the nitrogen-fixing actinomycete Frankia. While this may enable it to exist in nitrogen depauperate habitats, it does not result in appreciable nitrogen inputs into the ecosystem (Dalton and Zobel, 1977).

The branching architecture of antelope bitterbrush enables it to withstand high levels of browsing (Bilbrough and Richards, 1993). It is a preferred food source for insects (Furniss and Krebill, 1972) and small mammals, principally yellow pine chipmunk (Tamias amoenus), cache up to 80% of the antelope bitterbrush seed crop (Vander Wall, 1994). In our study sites chipmunks are not abundant (W. F. Klenner, pers. comm.) and seeds are removed by nocturnal small mammals (Shatford, 1997).


Antelope bitterbrush seeds were collected in 1994 from 10 sites: nine sites in the S Okanagan River valley, British Columbia, Canada, and one site in northern Washington state [ILLUSTRATION FOR FIGURE 1 OMITTED]. All sites are in the altitudinal range of 300 to 500 m above sea level and are on the E side of the valley. Grazing histories range from little or no use to intermittent year-round grazing by horses and cattle (Table 1). Grazing histories were assessed based on historical records and the memories of former ranchers who could recall stocking regimes back to the 1930s. Seven of the sites were on sandy soils, and three were on a floodplain with large rocks and shallow but richer soil (Table 1).



Seed collection. - At each site 12 or 13 small (approximately 1 m high) and 12 or 13 large (approximately 2 m high) antelope bitterbrush shrubs were randomly chosen along haphazardly placed transects. Fruits from these shrubs were collected at peak fruit production (late June) by shaking branches and gathering fruits falling onto a polyethylene tarp spread underneath the shrub. Husks were removed manually. Thirty or 50 seeds were randomly selected from each shrub and individually weighed to the nearest 0.1 mg. Unfilled seeds, which appeared black, elongated and shriveled, were not included, whereas small but otherwise filled seeds were.

Descriptive statistics. - Frequency distributions of seed weight were examined and skewness and kurtosis were calculated (PROC UNIVARTATE: SAS Institute Inc., 1990a). Measures of skewness and kurtosis were tested for significance only for sample sizes over 150 (Sokal and Rohlf, 1981). Because of great within-shrub variation in seed weight, coefficients of variation of seed weight from each shrub were calculated and compared. Coefficient of variation was used instead of standard error as a measure of variance because the latter was significantly correlated with seed weight (r = 0.30, n = 240, P [less than] 0.0001). Differences in coefficient of variation in seed weight between sites were analyzed using nonparametric tests.

The effect of two categorical variables on seed weight, shrub size (small vs. large), and grazing history, were tested using ANOVA. Information on grazing history (Table 1), was used to divide the ten sites into three categories: little or no grazing, some grazing, and heavy grazing. In a second ANOVA that excluded shrub size and grazing history, components of seed weight variation were partitioned among sites, shrubs and within shrubs.

Correlation of shrub characters with seed weight and variability. - The association of antelope bitterbrush health and size with seed weight and seed weight variability was tested using correlation analysis. Health was estimated by the proportion of dead branches (to the nearest 10%) on a shrub. Age of antelope bitterbrush shrubs was estimated with two non-destructive measures: basal diameter and the volume of aboveground biomass. Basal diameter was measured with a DBH tape, and has been shown to be correlated with age in antelope bitterbrush (McConnell and Smith, 1963). Volume of an individual shrub was calculated as an inverted cone ([Pi] [r.sup.2] h/3), the shape most approximate to that of antelope bitterbrush. Radius was calculated as half the average of two perpendicular measurements of diameter. The impact of browsing on seed weight was tested by correlation of seed weight and the number of twigs, of a random sample of 20, that had been browsed during the winter before seed production.

Correlation of site characters with seed weight and variability. - The association of a number of environmental variables with average seed weight at a site (the average of shrub averages) was also tested with correlation analysis. To test whether the density of two invasive weeds, knapweed (Centauria diffusa) and cheatgrass (Bromus tectorum), was associated with average seed weight, at least 40 randomly placed Daubenmire plots (20 x 50cm) (Daubenmire, 1959) were used to sample densities at each site. In addition, percent cover of bare soil was estimated in the same way, using Daubenmire's scale of cover classes as well as one class for cover of less than I percent. Though bare soil increased with grazing intensity, it was also an independent measure of disturbance because it reflected soil excavation by burrowing rodents. To determine whether intraspecific competition at a site affected seed weight, the correlation between seed weight and antelope bitterbrush shrub density was tested. Density was measured with haphazardly placed line-intercept transects across each site (Brower et al., 1989) and was calculated as the number of shrubs intercepted by the 1-cm-wide tape per unit length (10 m). Lastly, the correlation between seed weight and various measures of soil chemistry were tested. From each of the nine sites from British Columbia, five soil samples from the top 20 cm of soil were analyzed for percent nitrogen, percent carbon, magnesium (meq/100g), potassium (meq/100g), and cation exchange capacity (meq/100g). Because of restrictions on bringing soil across the border, the WA site was not included. Tables of correlation coefficients were subjected to the Bonferroni test (standard and sequential) (Rice, 1989), to control the experiment-wide Type I error. Transformations of the data were performed when necessary.


Descriptive statistics. - Weight of individual seeds varied over 9-fold, from 5 to 48 mg [ILLUSTRATION FOR FIGURE 2 OMITTED], and averaged 26.42 [+ or -] 0.07 mg (SE). Antelope bitterbrush produced more small seeds than would be expected from a normal distribution of seed weights (skewed to the left: [g.sup.1] = -0.13, t = -4.59, P [less than] 0.001, n = 8040). The distribution, however, was not kurtotic ([g.sup.2] = -0.013, t = -0.23, P [greater than] 0.5, n = 8040).

The range of weights for individual seeds at each site was almost as great as across the whole population. Only two sites had normally distributed seed weights (BW and ELO; Table 2). Of the five sites that had significantly skewed distributions, four produced more light seeds than expected from a normal distribution (WT, KB, OS and GR) while only one produced more heavy seeds than expected (WA; Table 2). The three remaining sites produced more heavy and light seeds than would be expected from a normal distribution (BO, KL and CWS: platykurtotic distribution).

Seed weight differed significantly among sites (Table 3) and among shrubs at a site. Most of the variation (63.15%) in seed weight, however, was within individual shrubs. Different sites accounted for 7.74% of the variation in seed weight, and different shrubs accounted for 29.11%.

Variability of seed weights differed among shrubs; coefficient of variation values ranged over four-fold [ILLUSTRATION FOR FIGURE 3 OMITTED]. Average seed weight per shrub ranged two-fold, from 16 to 37 mg. Average seed weight was normally distributed across shrubs ([g.sup.1] = 0.27, t = 1.69, P [greater than] 0.05; [g.sup.2] = -0.14, t = -0.44, P [greater than] 0.05; n = 241).


Correlation of shrub characters with seed weight and variability. - The proportion of dead branches was not associated with the average weight of seeds produced (Kendall [Tau]-b correlation coefficient = 0.018, P = 0.44, n = 215). In addition, small and large antelope bitterbrush shrubs produced seeds of similar weights (Table 3). Neither basal diameter nor aboveground volume were associated with average seed weight (Kendall [Tau]-b correlation coefficient = 0.020 and 0.016, P = 0.77 and 0.81, n = 219 and 236, respectively).

Shrub diameter, volume or the proportion of dead branches were also not correlated with the variability of seed weights (Kendall [Tau]-b correlation coefficient = 0.05, -0.009 and 0.06, P = 0.29, 0.83 and 0.19, n = 219, 236 and 215, respectively). Seed weight variability was correlated with degree of browsing (Kendall [Tau]-b correlation coefficient = 0.24, P = 0.0001, n = 232). This is reflected by differences in the distribution of individual seed weights of the 16 most heavily browsed plants as compared with that of the 17 plants that [TABULAR DATA FOR TABLE 3 OMITTED] were not browsed at all (Kuiper 2-sample test (SAS Institute Inc., 1990b): Ka = 1.85, P = 0.027, [n.sup.1] = 515 and [n.sup.2] = 525 seeds) [ILLUSTRATION FOR FIGURE 4 OMITTED].

Site differences in proportion of browsed twigs were not correlated with average seed weight (Kendall [Tau]-b correlation coefficient = -0.023, P = 0.93, n = 10). However, sites differed both in the proportion of twigs that were browsed on antelope bitterbrush shrubs (One-factor ANOVA, F = 24.3, P [less than] 0.0001, [R.sup.2] = 49.6%) and in the coefficient of variation of seed weights (Kruskal-Wallis test, [X.sup.2] = 66.2, P [less than] 0.0001). The median coefficient of variation and the median number of twigs that were browsed were significantly correlated among sites [ILLUSTRATION FOR FIGURE 5 OMITTED].

Correlation of site characters with seed weight and variability. - The environment surrounding antelope bitterbrush shrubs did not affect the weight of seeds produced. Grazing history of a site did not affect seed weight (Table 3). Proportion of bare ground at a site was not associated with average seed weight (Kendall [Tau]-b correlation coefficient = -0.16, P = 0.53, n = 10). Similarly, the density of cheatgrass or knapweed was not associated with seed weight (Kendall [Tau]-b correlation coefficient = -0.33 and 0.13, P = 0.18 and 0.59, respectively, n = 10). Competition between shrubs was also not a factor in seed production, as shrub density was not associated with seed weight (Kendall [Tau]-b correlation coefficient = -0.27, P = 0.28, n = 10).

In addition, soil properties were not strongly associated with average seed production in antelope bitterbrush. The strongest relationship was between mean seed weight and cation exchange capacity ([ILLUSTRATION FOR FIGURE 6 OMITTED], Kendall [Tau]-b correlation coefficient = 0.54, P = 0.046, n = 9), in which on average larger seeds were produced by shrubs at sites with higher cation exchange capacity. However, this relationship was not significant when a Bonferroni adjustment was made (with the five soil properties being studied, a P of 0.01 or less (for the initial P of a sequential Bonferroni, and for the P of a standard Bonferroni) was necessary for significance at the 0.05 level). Percent carbon or nitrogen at a site was not significantly correlated with average seed weight (Kendall [Tau]-b correlation coefficient = 0.44 and 0.39, P = 0.095 and P = 0.14, respectively; n = 9). Similarly neither magnesium nor potassium were correlated with average seed weight (Kendall [Tau]-b correlation coefficient = 0.22 and 0.17, P = 0.40 and 0.53, respectively; n = 9).


Though average seed weight differed significantly among antelope bitterbrush shrubs, none of the factors measured was associated with these differences. Whereas average seed weight remained constant among shrubs that had been browsed at different intensifies, seed weight variability differed. Antelope bitterbrush individuals that had been more heavily browsed produced more variably weighted seeds, that is more heavy seeds and many more light seeds. In antelope bitterbrush, flowers are initiated from buds originating from short shoots situated on 1-2 and 3-yr-old long shoots (Bilbrough and Richards, 1991). Overwinter browsing removes parts of 1-yr-old twigs. Bilbrough and Richards (1993) have shown that simulated browsing of one twig on a bitterbrush shrub results in no compensatory new growth on that twig. In contrast, removal of much of a shrub's 1-yr-old branches results in compensatory new growth with the production of more new long shoots as compared to shrubs that were not browsed at all. Production of more long shoots after winter browsing is most likely at the expense of flower production: in heavily browsed antelope bitterbrush shrubs, all remaining buds produced twigs, whereas in the control shrubs only 20 percent of the buds produced twigs, the other 80 percent producing flowers (Urness and Jensen, 1982). This is corroborated by observations of antelope bitterbrush by Garrison (1953). Hence, it is likely that the heavily browsed antelope bitterbrush shrubs in this study produced proportionally fewer flowers and therefore seeds, than unbrowsed, or lightly browsed shrubs.

Why would these fewer seeds be more variably weighted than seeds from unbrowsed shrubs? From Bilbrough and Richards (1993) results, it is clear that both branch autonomy and sink/source relationships (Sprugel et al., 1991) exist in antelope bitterbrush shrubs. Heavily browsed shrubs would mobilize photosynthate to regrow browsed long shoots and developing seeds should be able to access some of those resources; fewer flowers and seeds on heavily browsed sections of the shrubs should result in larger seeds. At the same time, sections that were not heavily browsed would not be strong enough sinks for the mobilization of photosynthate, and there would be fewer leaves for the production of photosynthate for local fruit and seed development, potentially resulting in smaller seeds. In birch (Betula pubescens), greater intensity of simulated browsing resulted in heavier and fewer seeds, but not more variable seed weights (Bergstroem and Danell, 1987). In contrast, natural browsing resulted in more variable seed weights in the herbaceous perennial Ipomopsis aggregata (Paige and Whitham, 1987). Though average seed weights did not differ between control Ipomopsis aggregata plants and those that had regrown from experimentally as well as naturally clipped plants, standard error of seed weight from naturally browsed plants (0.41) was greater than four times the standard error of the other two groups (0.06 for experimentally clipped, 0.09 for unclipped controls). It is well-known that ungulates are selective browsers (Bryant et al., 1991; McKell, 1989). Perhaps the nonrandom selection of shoots or plants by browsers results in the observed variability in seed size. These hypotheses need to be tested, and could be interesting for further research.

The proportion of variation in seed weight that was attributable to site, shrubs, and within-shrub, was remarkably similar to that found in other species. In a large multi-species and habitat study, Michaels et al. (1988) listed 38% as the average proportion of variation in seed weight attributable to different plants within a population. Michaels et al. (1988) did not partition the variation attributable to different sites; hence, the total found in this study (7.74 + 29.11 = 36.7%) was very close to their average. Most of the variation in seed weight was attributable to variation within individual shrubs (63.3%) which is virtually identical to that found in other species (mean within-plant variation in seed weight for 29 species = 62%; Michaels et al., 1988). In addition, the average weight of antelope bitterbrush seeds collected in this study was similar to the average weight from 72 bulk collections taken by Susan B. Meyer from 1981-1990 across the entire antelope bitterbrush range [28.34 [+ or -] 0.37 (SE)]. The slightly lower average weight in the present study may be attributable to the inclusion of small but filled seeds as these seeds were excluded from the bulk collections (S.B. Meyer, pers. comm.).

Differences in seed weight among individual antelope bitterbrush shrubs may be a proximate response to different amounts of resources during seed filling, or might be attributable to genetically predetermined meristems of different sizes (Sinnot, 1921). Perhaps individuals that produced heavier seeds had access to greater resources such as water or nutrients. Variation in nitrogen supply could be affected by variation in Frankia nodulation (Righetti and Munns, 1982). Differences among shrubs in mean seed weight were not associated with any of the measured shrub characters. Neither shrub health nor size (an estimate of age) were associated with average seed weight. This contradicts a number of studies which show a positive relationship between plant size and seed weight (Schaal, 1980; Michaels et al., 1988).

Associations between seed weight, percent carbon, cation exchange capacity and percent nitrogen were not significant but given the small number of sites (nine), the power of the tests was low (Dallal, 1986). There was a 70-84% chance of accepting the null hypothesis, when it should have been rejected. Habitat differences have been shown to affect seed weight, but the nature of the effect has not been isolated (Winn and Werner, 1987). The near significance of the relationship between seed weight and cation exchange capacity suggests that this may be an important area for future research. A higher cation exchange capacity indicates that the soil has in it more organic matter (Hausenbuiller, 1978). The effect of increased organic matter is varied; increased soil structure with implications for water retention and root growth might be even more important than increased chemical reactivity as expressed by cation exchange capacity (Hausenbuiller, 1978). Antelope bitterbrush is able to sequester nitrogen through nitrogen fixation of Frankia root nodules (Righetti and Munns, 1982). Perhaps that explains why percent nitrogen at a site was not more strongly associated with seed weight; site nitrogen may not be important as a nitrogen supply to antelope bitterbrush shrubs. In controlled greenhouse studies with other species, added nutrients have often resulted in bigger seeds (Stephenson, 1984; Aarssen and Burton, 1990; Schmitt et al., 1992; Wulff and Bazzaz, 1992). Larger seeds commonly grow into larger seedlings that have a better chance of surviving to reproductive maturity (Black, 1958; Dolan, 1984; Marshall, 1986; Wulff, 1986). It is not known whether this is also true for antelope bitterbrush, though preliminary results in a companion study suggest that seed size in antelope bitterbrush is associated with greater percent emergence (Shatford, 1997).

Of the shrub and site characters measured in antelope bitterbrush, none were directly related to seed weight, and as such could not be used as indicators. Across most sites, soil characteristics might be a better indicator of seed weight than is found in this study. Nonetheless, seed weights were much more variable on the same shrub than among sites and shrubs. Therefore, the current practice of eliminating small seeds from bulk collections may already assist in selecting the best seeds for restoration purposes when considering seed size as the primary determinant of seed quality. The failure of some restoration efforts may in part be attributable to variation in other components of seed quality, such as mineral content (Krannitz, in press), or because of the potential importance of local adaptation to a particular site (Shatford, 1997). The importance of all of these variables to seedling establishment and adult reproduction in antelope bitterbrush is an area of future research that will provide the knowledge essential to the restoration of antelope bitterbrush populations.

Acknowledgments. - This study would not have been possible without the cooperation of landowners and neighbors who permitted access to the sites: Osoyoos Indian Band (BW, RG, OS, WT, ELO), Blake Kennedy and George Kennedy (KL, KB), Puget Properties Inc. (WA), BC Environment (BO), and Canadian Wildlife Service (CWS). I gratefully acknowledge Jeff Shatford for his tireless efforts at collecting and processing the seeds along with field assistants Phyllis Gabriel and Jolene Kruger. Jeff also provided the data on soil texture. Sabrina Taylor diligently measured the seed weights. Browsing data were collected by Samantha Hicks and analyzed by Samantha and Randi Mulder. Marilyn Fuchs, Samantha Hicks, and two anonymous reviewers improved an earlier version of the manuscript. I thank Pain Whitehead for drawing figure 1. Funding for this project was generously provided by grants from the Vancouver Foundation and Habitat Conservation Fund, and by operating grants from Environment Canada. Employment Canada partially funded field assistant salaries.


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Author:Krannitz, Pam G.
Publication:The American Midland Naturalist
Date:Oct 1, 1997
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