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BIOMASS ALLOCATION IN PLANTS: ONTOGENY OR OPTIMALITY? A TEST ALONG THREE RESOURCE GRADIENTS.

K. D. M. MCCONNAUGHAY [1,3]

J. S. COLEMAN [2,4]

(1.) Department of Biology, Olin Hall, Bradley University, Peoria, Illinois 61625 USA

(2.) Department of Biology, Biological Research Laboratories, Syracuse University, Syracuse, New York 13244 USA

Abstract. We examined biomass allocation patterns throughout the entire vegetative growth phase for three species of annual plants along three separate gradients of resource availability to determine whether observed patterns of allocational plasticity are consistent with optimal partitioning theory. Individuals of the annual plant species Abutilon theophrasti, Chenopodium album, and Polygonum pensylvanicum were grown from locally field-gathered seed in controlled greenhouse conditions across gradients of light, nutrients, and water. Frequent harvests were used to determine the growth and allocation (root vs. shoot, and leaf area vs. biomass) responses of these plants over a 57-d period. Growth analysis revealed that each species displayed significant plasticity in growth rates and substantial amounts of ontogenetic drift in root: shoot biomass ratios and ratios of leaf area to biomass across each of the three resource gradients. Ontogenetically controlled comparisons of root: shoot and leaf area ratios acro ss light and nutrient gradients were generally consistent with predictions based on optimal partitioning theory; allocation to roots decreased and leaf area increased under low light and high nutrient conditions. These trends were confirmed, though were less dramatic, in allometric plots of biomass allocation throughout ontogeny. These species did not alter biomass allocation (beyond ontogenetic drift) in response to the broadly varying water regimes. Furthermore, many of the observed differences in biomass allocation were limited to a given time during growth and development.

We conclude that, for these rapidly growing annual species, plasticity in biomass allocation patterns is only partially consistent with optimal partitioning theory, and that these plastic responses are ontogenetically constrained. Further, while these species did adjust biomass allocation patterns in response to light and nutrient availability, they did not adjust biomass allocation in response to water availability, despite dramatic plasticity in growth rates along all three resource gradients. Our results support a developmentally explicit model of plasticity in biomass allocation in response to limiting resources.

Key words: Abutilon theophrasti; allocation; allometry; biomass partitioning; Chenopodium album; leaf area ratio; old-field annuals; ontogeny; plant growth rate; Polygonum pensylvanicum; resource gradients; root: shoot ratio.

INTRODUCTION

How plants respond to variation in the availability of resources in their environment is a central question in plant ecology. Optimal partitioning models and theories suggest that plants respond to variation in the environment by partitioning biomass among various plant organs to optimize the capture of nutrients, light, water, and carbon dioxide in a manner that maximizes plant growth rate (Thornley 1969, 1972, Bloom et al. 1985, Robinson 1986, Hirose 1987, Johnson and Thornley 1987, Szaniawski 1987, Levin et al. 1989, Hilbert 1990, Dewar 1993). For example, plants exposed to reduced sunlight would be predicted to shift resources toward stem and leaf growth, and to pigments associated with light capture, in lieu of increasing the production of root biomass, carbohydrate availability for nutrient uptake, or enzymes (e.g., rubisco) associated with carbon fixation (Bloom et al. 1985). Alternatively, factors that limit the acquisition of below-ground resources relative to light and [Co.sub.2] should have the op posite effects. Thus, plants are predicted to respond to low nutrient availability by shifting the partitioning of carbohydrates to processes associated with nutrient capture in lieu of carbon acquisition (Bloom et al. 1985). The theory surrounding optimal partitioning is generally accepted and a number of studies report adjustments in biomass allocation consistent with it (reviewed in Bloom et al. [1985], Chapin [1991], Jones and Coleman [1991], Mooney and Winner [1991], Reynolds and D'Antonio [1996]). Current debate centers on the mechanism(s) underlying the observed partitioning responses (e.g., Hirose 1987, Hilbert 1990, Chu et al. 1992, Dewar 1993, Luo et al. 1994).

Recently, we suggested that adjustments in biomass allocation as a consequence of normal plant growth and development may be responsible for some or all of the adjustments in biomass allocation cited in support of optimal partitioning theories (Coleman et al. 1994). Remarkably few studies account for the many morphological and physiological changes, including biomass allocation patterns, that occur under the normal course of growth and development before they examine adjustments in biomass allocation in response to fluctuating resource levels (Coleman et al. 1994). Evans (1972) defined the phenomenon of a trait changing in a predictable way as a function of plant growth or development as ontogenetic drift.

A theoretical framework for distinguishing "apparent" plasticity from "true" plasticity

Variable (i.e., plastic) biomass allocation patterns may result from either ontogenetic drift in biomass allocation patterns coupled with plasticity in growth rates ("apparent" plasticity in allocation) or plasticity in biomass allocation patterns themselves ("true" plasticity in allocation; Fig. 1). Whenever biomass allocation patterns exhibit allometric (i.e., non-isometric) growth for some or all of development, biomass allocation traits will exhibit ontogenetic drift (i.e., biomass allocation patterns will vary as plants grow and develop, regardless of environmental conditions; Fig. 1C-F). Only when the relationship between biomass accumulation in various components (e.g., roots vs. shoots) is isometric (i.e., slope of [log] root biomass vs. [log] shoot biomass = 1.0) and linear (i.e., not indicative of complex allometry [Jolicoeur 1989]) can we ignore ontogenetic drift (Fig. 1A, B). In the absence of ontogenetic drift in biomass allocation patterns, any plasticity in biomass allocation traits observed c an be directly attributed to "true" plasticity in biomass allocation patterns, and resulting root: shoot ratio differences will be maintained throughout growth and development (Fig. 1B). Although studies have suggested this pattern of plasticity for root: shoot ratios (Coleman et al. 1989, Coleman and Bazzaz 1992), we do not know of any that have conclusively documented this pattern of plasticity, nor do we know of any published studies that have identified a complete lack of both ontogenetic drift in biomass allocation parameters and true adjustments in allocation (Fig. 1A).

Ontogenetic drift in biomass allocation patterns may obfuscate studies of plasticity in biomass allocation traits (e.g., Coleman and McConnaughay [1995]; Fig. 1C). In the vegetative growth phase of most herbaceous plants, root: shoot ratios are highest in seedlings, and decline over time as plants grow and develop (i.e., slopes of the allometric plot of [log] root vs. [log] shoot mass [greater than] 1.0, as depicted in Fig. 1C-F; Hunt [1990]). Thus, even in the absence of "true" plasticity in biomass allocation, root: shoot ratios would differ for plants growing at different rates when comparisons are made at a common time or plant age but would not differ when comparisons are made at a common plant size or developmental stage (Fig. 1C). Any observed plasticity in root: shoot ratio would result solely from plasticity in growth rates ("apparent" plasticity in allocation). Without a careful study of root and shoot allometry, the data could be misinterpreted.

Root: shoot ratio plasticity may result from both "true" adjustments in biomass allocation and ontogenetic drift (Fig. 1D-F; Coleman et al. [1994]). "True" plasticity in root vs. shoot allocation (as evidenced by unequal slopes in the allometric plot) can offset changes in root: shoot ratios via ontogenetic drift such that adjustments in allocation patterns may not be observed when comparing root: shoot ratios solely as a function of plant age (Fig. 1D; Evans [1972], Rice and Bazzaz [1989]). Evans (1972) reports a study where differences in root: shoot ratios were in the opposite direction when plants were compared at a common age vs. at a common size (Fig. 1E). Perhaps the most common scenario is when ontogenetic drift in allocation patterns may increase or decrease the degree of phenotypic plasticity observed over time (Fig. 1F). A number of examples of this scenario have been reported (Hughes and Evans 1962, Terry 1968, Ackerly et al. 1992, Poorter and Pothmann 1992, Gedroc et al, 1996, McConnaughay and C oleman 1998).

Is biomass allocation in response to limiting resources onto genetic or optimal? Developmental considerations

To date, a handful of studies have explicitly distinguished between allocation changes that result as a normal consequence of plant growth and development (i.e., ontogenetic drift) and "true" adjustments in biomass allocation (i.e., those that require an adjustment in biomass allocation beyond that due to ontogenetic drift). Taken together, these studies suggest that "true" adjustments in biomass allocation occur in response to nutrient limitation (Cromer and Jarvis 1989, Van de Vijver et al. 1993, Hartvigsen and McNaughton 1995, Gedroc et al. 1996), but not necessarily in response to water (Ledig et al. 1970), [CO.sub.2] (Farnsworth et al. 1996, Bernacchi 1997), and light availability (Hughes and Evans 1962, Ledig and Perry 1965, Terry 1968, Ledig et al. 1970, Evans 1972, Corre 1983, Rice and Bazzaz 1989; but see Pearsall 1927, Troughton 1956).

The lack of observed adjustments to biomass allocation with respect to light and [CO.sub.2] availability is particularly interesting when viewed from a developmental context. As previously stated, root: shoot ratios in many herbaceous plant species decline throughout much of vegetative growth and development (Hunt 1990). When resources are limiting, plants grow and develop slowly, retaining the higher root: shoot ratios of less-developed plants. If the limiting resource(s) is water or nutrients, the higher root: shoot ratio of the underdeveloped plant is consistent with optimal foraging behavior; the plant is investing a greater proportion of its biomass in belowground foraging structures, even in the absence of "true" adjustments in allocation (Fig. 1C). If the limiting resource is light or [CO.sub.2], however, the higher root: shoot ratio of the underdeveloped plant is not at all consistent with optimal foraging behavior. In order for such a plant to alter biomass allocation patterns in a manner consistent with optimal partitioning theory, this plant must adjust biomass allocation to an appreciable extent, more appreciably than the scenario depicted in Fig. 1D. Thus, in contrast to classical optimal partitioning models, a more developmentally explicit partitioning model might predict that plasticity in biomass allocation would need to be more dramatic in response to insufficient supplies of light or [CO.sub.2] than of nutrients or water, at least in the vegetative growth phase of most herbaceous species.

In sum, optimal partitioning models predict that plants should adjust partitioning to minimize imbalance in any critical resource (Bloom et al. 1985, Chapin et al. 1987), while the more developmentally explicit model outlined above predicts that "true" adjustments in biomass allocation patterns should be most profound in response to inadequate light or [CO.sub.2] availability and should be negligible or greatly reduced in response to inadequate nutrient or water availability.

Here we examine biomass allocation patterns throughout the entire vegetative growth phase for three species of annual plants along separate gradients of light, nutrient, and water availability. For each species, we examined growth responses to these resource gradients over the entire course of vegetative (pre-reproductive) growth, biomass allocation responses as a function of time and of plant size, and allometric relationships among various biomass components. We asked the following questions: (1) Do plants grown under broadly differing resource conditions adjust biomass allocation patterns, beyond those adjustments that are a consequence of ontogenetic drift, in a manner consistent with optimal partitioning theory?, and (2) Are those responses resource-dependent or species-specific?

MATERIALS AND METHODS

We compared phenotypic expression throughout the vegetative phase of plant growth and development for three fast growing species in environments that vary in resource availability. This was accomplished by performing harvests every other day of plants grown along three separate resource gradients.

Species.--The three old-field annual species, Abutilon theophrasti, Chenopodium album, and Polygonum pensylvanicum, were selected based on apparent differences in morphological plasticity in response to varying nutrient environments. Chenopodium has been shown to have relatively fixed allocation patterns in comparison to Polygonum, which exhibited greater plasticity in allocation and architecture in response to spatially constrained neighborhoods; Abutilon displayed intermediate plasticity (McConnaughay and Bazzaz 1992). These old-field annual species colonize relatively nutrient-rich habitats. They grow rapidly, reaching reproductive maturity within 90 d, and complete their life cycles in [similar to] 5 mo.

Cultivation methods.--We grew each species from seeds obtained from local populations starting in early July 1994 (the natural growing season within the old-field annual community is from May/June through October [McConnaughay and Bazzaz 1987]). Once the first true leaves appeared (1-2 wk of age), individual seedlings were transplanted into 12.7 cm diameter X 12.7 cm deep plastic pots (one seedling per pot) containing 1 L of a 1:1:1 mix of sterilized loam: sand: perlite and placed randomly on 12 greenhouse benches. Day/night temperatures were 27[degrees]C/20[degrees]C [plus or minus] 2[degrees]C. No supplemental lighting was used. General growth conditions, with exceptions outlined below for experimental treatments, were as follows. Plants were watered eight times daily with an automatic watering system, with additional water added as needed to prevent wilting. Nutrient additions began 1 wk following transplanting of seedlings, and were continued weekly while gradually increasing doses as nutrient demands increased, based on known growth rates for these species across a similar nutrient gradient. Nutrients were added in the form of 200 mL of a liquid soluble fertilizer (Peter's 20-20-20: 3.9% [NH.sub.4]-N, 5.8% [NO.sub.3]-N, 10.0% urea-N, 20% [P.sub.2][O.sub.5]-P, 20% [K.sub.2]O-K) such that total nutrient additions over the entire growth period approximated nutrient addition rates of 400 kg N*[ha.sup.-1]*[yr.sup.-1] (Table 1). Note that nutrient applications decreas ed in weeks 6 and 7, concomitant with reductions in plant growth rates, and thus nutrient demand, in these species. Twenty-four harvests (one seedling per species per gradient per level per harvest) were performed beginning 1 wk following transplanting of seedlings, continued every day for 1 wk, and were subsequently performed every other day for 2 wk, then every third day for 3 wk, and finally every fourth day until the end of the experiment in mid-September (57 d after transplanting, at plant age 64-71 d).

Three independent gradients were constructed as follows: First, a light gradient of three light treatments was constructed using neutral shade cloth tents (0.91 X 0.61 m ground area X 1.22 m height); high light (full sun, no shade cloth), medium light (50% full sun), and low light (12% full sun). Each of three greenhouse benches (0.91 X 1.82 m) were divided into three sections, over which the three light treatments were randomly assigned in a split-plot fashion (three plots per light level). Eight seedlings of each of the three species were fully randomized within each plot for a total of 24 seedlings per species per light treatment. Benches were oriented in a single north-south line to reduce shading from adjacent light treatments.

Second, a nutrient gradient of three nutrient treatments was implemented in which pots were randomly placed over three benches under full sun conditions. Twenty-four seedlings of each species were randomly assigned to each of three nutrient levels approximating nutrient addition rates (expressed as nitrogen mass) of 800 kg N*[ha.sup.-1]*[yr.sup.-1] (high nutrients), 400 kg N*[ha.sup.-1]*[yr.sup.-1] (medium nutrients), or 100 kg N*[ha.sup.-1]*[yr.sup.-1] (low nutrients). Nutrient additions were made weekly, in the form of 200 mL of the liquid soluble fertilizer described in Materials and methods: Cultivation methods, above. Weekly doses paralleled nutrient requirements as estimated by plant growth rates (Table 1).

Third, a water gradient of three water treatments was implemented in which pots were randomly placed over three benches under full sun conditions. Twenty-four seedlings of each species were randomly assigned to each of three water levels: high (near or at field capacity; water was added eight or more times a day, via an automatic watering system, to saucers subtending individual pots), medium (100 mL water added per pot whenever soil surface was dry in [greater than or equal to]50% of the pots in that treatment), or low (50 mL water added per pot whenever wilting was observed in [greater than or equal to]50% of the pots in that treatment). Determinations of water status for medium and low water treatments were made at 1500 in the afternoon, daily.

Growth analysis and statistical methods.--As we had no a priori hypotheses regarding the exact timing (i.e., point(s) during growth and development) of resource availability effects on the developmental trajectories of whole-plant growth and biomass allocation, we allocated N = 24 replicates pots to separate, frequently spaced harvests, and analyzed these trajectories using the functional approach outlined by Causton and Venus (1981) and Hunt (1982). This level of replication was found to be adequate to resolve multiple growth and allometric curves in these species previously (Coleman et al. 1993, Gedroc et al. 1996, McConnaughay and Coleman 1998). In most cases, whole-plant growth curves and allocational trajectories over the 60-d growth period were appreciably curvilinear (as determined by sequential polynomial regression), even when biomass variables were transformed to their natural logarithms. The curvilinearity of the allometric relationships examined here is indicative of complex allometry rather than simple allometry and precludes the use of more appropriate model 2 linear regression techniques (Jolicoeur 1989). Therefore, second-order polynomial regression equations were used for comparisons of (1) natural logarithm (In) of total dry biomass vs. time, (2) In root: shoot ratio (RIS, as dry mass) vs. time, (3) In RIS vs. In total dry biomass, (4) In leaf area ratio (LAR, [whole plant leaf area]/[whole plant dry biomass]) vs. time, (5) In LAR vs. In total dry biomass, (6) In total root dry biomass vs. In total shoot dry biomass, and (7) in whole plant leaf area vs. ln total dry biomass. Biomass variables and whole plant leaf area were transformed to their natural logarithms before analysis to meet the assumptions of normality and homoscedasticity associated with model 1 regression techniques. Log-transformed variates and their residuals were judged to be normally distributed and homoscedastic by a combination of histograms, normality statistics, and normal probability plots (DataDesk 4.0 [Velleman 1992]). All curves were fitted using the NLIN program of Statistical Analysis System (Joyner 1985).

These fitted curves were statistically compared using methods described by Mead and Curnow (1983) and Potvin et al. (1990). Briefly, for each species along each gradient, the goodness-of-fit of a single line (all three levels of resource availability lumped together; 72 points per curve) was compared to the goodness-of-fit of three separate lines (one line for each level of resource availability; 24 points per curve). Analysis of variance statistics (F) were computed by hand from type 3 residual sums of squares according to published formulae (Potvin et al. 1990).

RESULTS

Each species displayed significant plasticity in growth rates (Fig. 2) and substantial amount of ontogenetic drift in R/S and LAR (i.e., R/S and LAR varied throughout the 60-d growth period, regardless of resource condition) across each of the three resource gradients (Figs. 3 and 4). Comparisons of root: shoot and leaf area ratios for plants of the same age showed that, in general, allocation to roots increased and leaf area decreased under high light and low nutrient conditions, and that water stress resulted in increased allocation to roots without concomitant increases in leaf area development (Figs. 3 and 4). There were some exceptions to these trends, however; allocation to roots was insensitive to light or water availability for Chenopodium (Fig. 3) and allocation to leaf area was increased early in development in the high water treatment for Polygonum (Fig. 4).

Comparisons of R/S and LAR as a function of plant size reveal that the increased allocation to roots observed for all three species under nutrient stress were limited to the early stages of plant growth, and that as growth proceeded, nutrient stressed Abutilon and Polygonum plants allocated less biomass to roots than those grown at higher nutrient levels (Fig. 5). Increased allocation to roots, for Polygonum under water stress was not apparent when plants were compared as a function of plant size (Fig. 5). In other cases, the degree of plasticity in R/S observed when plants were compared as a function of plant size was greater (Abutilon, light gradient), or lesser (Polygonum, light gradient; Abutilon, water gradient), throughout part or all of the growth period, than that observed when plants were compared as a function of plant age. Similarly, same-size comparisons revealed plastic responses in LAR that were greater than (Polygonum, nutrient gradient), lesser than (Abutilon, light gradient), or in the oppos ite direction of (Polygonum, water gradient in latter part of vegetative plant development) those observed when comparisons were made as a function of plant age (Fig. 6).

Allometric analyses of allocation patterns revealed that, in general, these species altered allocation patterns in response to light and nutrient availability but not in response to broadly varying water availability (Figs. 7 and 8). There were, however, a few exceptions: root: shoot allocation was insensitive to nutrient availability for Abutilon and to light availability for Chenopodium (Fig. 7), and allocation to leaf area development was greater for Polygonum grown under ample water conditions (Fig. 8). Inspection of the allometric plots reveals that shifts in the partitioning programs observed in these species under these regimes were often constricted to a limited portion of growth and development.

DISCUSSION

The results of this study lead to four important points: (1) These species adjusted the partitioning of biomass between shoots and roots and to leaf area development in response to variation in light and nutrient availability in a manner consistent with optimal partitioning models. (2) These species did not adjust biomass partitioning in response to water availability even though growth rates were substantially altered by water treatment. Thus, the optimal partitioning model did not apply to the broad gradient of water availability. (3) Across all gradients for all species, we found that both root: shoot and leaf area ratios were subject to ontogenetic drift (i.e., they varied throughout ontogeny, see Figs. 3-6). (4) Had we not accounted for ontogenetic drift, we would have misjudged the magnitude, duration, and in a few cases the direction of many of the adjustments in biomass allocation patterns made by these species in response to these broadly varying resource gradients.

The decreased allocation to shoots and leaf area production in higher light environments, shown for all three species of old-field annuals, are in agreement with predictions based on optimal partitioning models and the developmentally explicit model we presented earlier. These results are consistent with those for pea (Pearsall 1927) and for forage grasses (Troughton 1956). However, other studies that have accounted for ontogenetic drift have found a lack of plasticity in allocation in response to variable light availability in conifers (Ledig et al. 1970, Steinbrenner and Rediske 1964), weedy annuals (Evans and Hughes 1961, Hughes and Evans 1962, Rice and Bazzaz 1989), and crop plants (Terry 1968, Corre 1983), despite moderate to substantial plasticity in biomass allocation with regard to other environmental conditions in some cases (Terry 1968, Ledig et al. 1970). While none of these studies appears to lend support to optimal partitioning models, the conifer studies reported that root: shoot ratios were in creasing during the early phases of seedling development; thus, for these species, the allocation patterns normally seen during seedling growth and development would favor allocation to light interception for more slowly growing light-limited seedlings (Ledig et al. 1970) and would thus lend further support to the developmentally explicit model of biomass allocation.

Decreased allocation to roots in enriched nutrient environments has been previously observed for a number of species comprising a wide range of growth forms and habits. Such adjustments in allocation have been reported for eucalyptus seedlings (Cromer et al. 1984, Cromer and Jarvis 1989), tropical perennial grasses (Hartvigsen and McNaughton 1995), temperate annual grasses (Van de Vijver et al. 1993), and old-field annuals (Gedroc et al. 1996). The lack of "true" plasticity in root vs. shoot allocation for Abutilon in response to nutrient availability in the present study is not consistent with results reported by Gedroc et al. (1996), though both studies used nutrient gradients of similar breadth (i.e., total nutrient additions for the low and high nutrient treatments were approximately equal) and form (weekly additions of liquid soluble fertilizer). Nutrients were added in gradually increasing quantities (i.e., commensurate with plant growth) in the present study vs. in equal doses in the Gedroc study. Thu s, saturating nutrient availability (i.e., as afforded by a spring pulse or spatial "hot spot") to young Abutilon seedlings may trigger plastic allocation responses while smaller levels of nutrient enrichment may not. The increased allocation to leaf area production in response to increased nutrient availability observed for all three species in the present study is consistent with the result for temperate annual grasses reported elsewhere (Van de Vijver et al. 1993). Adjustments in biomass allocation patterns in response to nutrient limitation were less dramatic than those in response to light limitation for two of the three species (Abutilon, Figs. 7 and 8; Polygonum, Fig. 7), lending further support to the developmentally explicit model we outlined earlier.

There are remarkably few data on plastic allocation responses to water availability in experiments where ontogenetic drift was accounted for in the experimental design. Consistent with predictions based on optimal partitioning theory, increases in allocation to root growth under water-stressed conditions have been reported for loblolly pine seedlings (Ledig et al. 1970) and forage grasses (Troughton 1960). Callaway and DeLucia (1994) report shifts in growth allometries in pines in response to a naturally occurring moisture/temperature gradient. Our results indicate that, at least for these old-field annual forbs, extremes in water availability do not trigger plastic responses in vegetative biomass allocation patterns, contrary to variation in other plant resources. We did not measure physiological water use parameters in this study; perhaps gross differences in water availability in these species are more readily regulated through stomatal responses than by gross adjustments in allocation, or perhaps the dec line in water availability had equivalent effects on photosynthesis and nutrient uptake such that no adjustment would be likely to occur (see Bloom et al. [1985]). Alternatively, water and nutrient limitation may represent different problems for roots; water is delivered to roots via mass flow, while nutrients are delivered via bulk flow in soil water or via the slower diffusion along soil particles, depending on the mobility of the ion (Nye and Tinker 1977). As the less mobile nutrients become limiting, the increased rooting densities required to maintain, nutrient uptake rates (Nye and Tinker 1977) may require increased biomass allocation to root systems.

In general, the results of this experiment are partially consistent with optimal partitioning models of plant growth. However, it should be noted that ontogenetic drift in biomass allocation patterns obscured actual shifts in biomass partitioning. Many actual adjustments in allocation were of different magnitude, duration, or direction than expected based on common-age comparisons of plants grown along broad light and nutrient gradients. Even more significantly, however, some of the observed plasticity in biomass allocation was exclusively due to ontogenetic drift. In fact, ontogenetic drift accounted for nearly all of the plasticity in allocation in response to varying water availability for these three annual species (cf. leaf area allocation in Polygonum).

Understanding the sources of phenotypic plasticity will greatly enhance predictions of plant responses to novel environmental conditions. Optimal partitioning theory is often the basis for models attempting to predict the ecological outcome of anthropogenically induced environmental changes (Sharpe and Rykiel 1991). Clearly, if the basic assumptions of optimal partitioning (i.e., plants can and do shift partitioning in response to environmental cues and these shifts control growth rates) are incorrect (e.g., in response to variation in particular resources such as water) or much more circumscribed than previously thought (e.g., limited to a brief period in plant development), the predictions of these models should be re-evaluated.

ACKNOWLEDGMENTS

We gratefully acknowledge John Gedroc, Lisa Subick, Lisa Walker, and LaShunda Williams for assistance throughout this project, and David Ackerly, Hendrik Poorter, Alan Black, and two anonymous reviewers for their helpful comments on the manuscript. This research was supported by NSF grant IBN-9408120 (to K. D. M. McConnaughay and J. S. Coleman), IBN-9357302 (to J. S. Coleman), a Bradley University Research Excellence Grant (to K. D. M. McConnaughay), and a grant from the Andrew W. Mellon Foundation (to J. S. Coleman), Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

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Manuscript received 31 July 1997; revised 20 October 1998; accepted 22 October 1998.

(3.) E-mail: kdm@bradley.edu

(4.) Present address: Biological Sciences Center, Desert Research Institute, Reno, Nevada 89506 USA.
         Fertilizer addition rates (expressed as mass of nitrogen
          per liter) in a laboratory study of resource allocation
                             in annual plants.
     Nutrient level (g N/L)
Week          Low           Medium  High
 1           0.073           0.291 0.583
 2           0.146           0.583 1.165
 3           0.323           1.292 2.584
 4           0.573           2.293 4.586
 5           0.785           3.141 6.283
 6           0.782           3.129 6.258
 7           0.485           1.938 3.876
Notes: Nutrients were added weekly as 200 mL of liquid
soluble 20-20-20 NPK fertilizer (see Materials and methods:
Cultivation methods for details). Fertilizer additions for light
and water gradients were at the same rate as for the Medium
level of nutrient gradient.
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