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Coarse- versus fine-grained water stress in Arabidopsis thaliana (Brassicaceae)¹

Department of Ecology and Evolutionary Biology, University of Connecticut, Storrs, Connecticut 06226 USA

Received for publication December 19, 2003. Accepted for publication September 21, 2004.

	ABSTRACT

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION LITERATURE CITED

 
The effects of coarse vs. fine-grained variation in water regime on 13 accessions of Arabidopsis thaliana were compared and it was found that the scale of environmental variation can lead to differences in which traits are affected and in the magnitude and direction of effect. Coarse-grained (between individual) variation was studied by comparing plants that received high or low amounts of water on a daily basis. Fine-grained (within individual) variation was distributed across the coarse-grained treatments; plants in the fine-grained treatment received the same amount of water per week as the corresponding high and low coarse-grained treatments; however, in the fine-grained treatments, plants received their entire weekly water allotment over 2 days. The number of leaves produced, days to bolting, length of bolt, number of basal and lateral branches, and survival to 30 days after bolting were measured and analyzed by ANOVA. Plants grown in high water generally produced more leaves, taller main axes, more branches and had increased survival, relative to those in low water. Bolting date showed a significant genotype specific effect of water level. Plants grown under fine-grained variation in watering had taller main axes relative to constant water. There were significant interactions between both types of variation for bolting date, main axis height, and survival. Principal components for all traits were loaded such that the components themselves were also independently affected by genotype, water level, variability of water level (grain), and level-by-grain interactions in ways that were largely predicted by their component traits. Overall, the effects of fine-grained variation were subtler than those of coarse-grained variation: fewer traits responded, and the magnitude of the responses was smaller. Nevertheless, the responses to fine-grained variation are distinct from those of coarse-gained variation, differing with respect to which traits respond and in the direction of response, and must therefore be treated as independent sources of environmental variation.

Key Words: Arabidopsis • environmental grain • environmental heterogeneity • heterogeneous environments • plasticity • reaction norm evolution • scale of variation

	INTRODUCTION

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION LITERATURE CITED

 
In an exploration of the role of plasticity as an adaptive evolutionary mechanism, we must consider two questions: Is there genetically controlled variation in a given plastic response? Do some variants have increased fitness? The answer to the first question has generally been an unequivocal "yes." In their reviews, Bradshaw (1965) and Schlichting (1986) compiled clear evidence for genetic variation in (i) which traits are plastic, (ii) the environmental conditions to which there are responses, and (iii) the amounts and directions of the plastic response.

The theoretical framework for understanding how the nature of environmental variation affects adaptive evolutionary processes was outlined by Levins (1962 , 1963 , 1968 ) and by Bradshaw (1965) . Levins (1962) showed that the optimal response to environmental variation would depend not only on the fitness in each environment, but also on the patterns of environmental occurrence and the organism's ability to anticipate such occurrences. Levins (1968) identified three key aspects of environmental variation: frequency, conditional probability, and grain. Frequency is the relative occurrence of a given environment, i.e., whether it is rare or common. Conditional probability refers to the organism's ability to anticipate a given environmental change. The grain of an environmental factor refers to the number of different states of that factor that an organism will encounter during its lifetime (Levins, 1962 ). If a particular environmental component is stable over a sufficiently large space or for a sufficiently long time that an organism experiences only that state (e.g., wet or dry), the environmental factor is said to be coarse-grained. If the state of the environmental factor is constant over only a small area or is ephemeral, then the organism is likely to encounter several states of that factor in its lifetime, and the environment is considered to be fine-grained.

Remarkably, Levins' framework has been largely overlooked in studies of plasticity. There have been numerous studies of theoretical models and substantial experimental research that have specifically examined either fine- or coarse-grained variation. However, there has been little empirical research comparing responses to coarse-grained variation with those to fine-grained variation of the same environmental factor, and even less on the interaction between the two. While our understanding of the effects of coarse-grained variation is steadily developing, experimental results that did not detect responses to such variation may be due to a misunderstanding of the scale of variation appropriate to the organism. An inappropriate scale of variation might also lead to significant results that contradict those that would have been found at other scales (Stratton, 1994 ).

Adaptive plastic responses to coarse-grained environments are predicted to occur via fixed developmental pathways, whereas the responses to fine-grained environments are likely to be reversible when (a) the cost of state transitions is negligible (Lloyd, 1984 ; Bradshaw and Hardwick, 1989 ; Schlichting and Pigliucci, 1998 , Table 9.1), or (b) there is little cost to being a "generalist" (Kassen and Bell, 1998 ; Stratton and Bennington, 1998 ). Consider the example of a plant found in well-drained soils over a range of mean rainfalls. Plants from coarse-grained wet and dry climates (i.e., always wet or always dry) are less likely to respond via adaptive plasticity to a shift in the overall mean rainfall because genetic variation for plasticity would be selectively neutral or perhaps even costly (Bradshaw, 1965 ; Levins, 1968 ) in a constant environment. Plants from a fine-grained, seasonal environment (i.e., two states over the lifetime of the plant) may have a threshold developmental response, for example, with distinct leaf morphologies in wet and dry seasons (Winn, 1996 ). Fine-grained within-season variation (e.g., daily or hourly) is likely to elicit flexible responses such as the opening and closing of the stomates, or up- and down-regulation of metabolic functions in response to available moisture. In spite of the fine-grained nature of natural rainfall, most studies examining variation in water availability have been largely done in a coarse-grained experimental design (Nienhuis et al., 1994 ; Pigliucci et al., 1995 ; Meyre et al., 2001 ).

In this study, we examined the effects of variation in water availability on traits in a variety of accessions of Arabidopsis thaliana. We chose water availability as our variable because it is known to vary in both a coarse-grained (geographic scale) and fine-grained (rainfall dependent) manner. Furthermore, patterns of coarse- and fine-grained variation in water availability are not necessarily independent (e.g., drier climates may also have less predictable rainfall patterns), making this an appropriate system for studying interactions between coarse and fine-grained variation.

	MATERIALS AND METHODS

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION LITERATURE CITED

 
A total of 13 distinct genotypes of Arabidopsis thaliana were used to investigate the effects of fine- and coarse-grained variation on plastic responses. We included 10 "ecotypes" from various geographic regions, a standard laboratory genotype (Columbia-0), and two mutants, viridicaulis (vc-1; abnormal cuticular wax layer) and salt over sensitive (sos-3; hypersensitive to sodium and lithium stress), each in the Columbia background, which might be expected to have distinct responses to water availability (Appendix 1, see Supplemental Data accompanying online version of this article). All genotypes were grown from stocks that had been inbred from single seeds to insure genetic uniformity (Arabidopsis Biological Resource Center, Columbus, Ohio). A. thaliana has been widely used as a model organism for general studies and plant biology because it lends itself to ready cultivation and it has a short growth cycle, less than 6 weeks under some conditions. As a result, there is an expansive body of literature on the physiology and genetics of this plant. There are numerous well characterized mutant strains available, including several that have a direct effect on water metabolism. The reproductive biology of A. thaliana makes it an exceptional candidate for the study of evolutionary mechanisms. It is a naturally self fertilizing plant and therefore can be easily bred to produce lines of genetically identical individuals, which are also commercially available. Finally, A. thaliana is broadly distributed throughout the northern hemisphere across a range of environments that vary in temperature, average rainfall, variability of rainfall and numerous other parameters. Inbred lines from many of these sites are also readily available. By using numerous lines, we can generate a model "population" consisting of distinct yet well defined genotypes each of which has a potentially unique fitness under a given set of environmental conditions.

Treatments
Plants were grown in Pro-Mix general purpose peat-based growing medium (Premier Horticulture, Dorval, Quebec) in 5 cm pots in an antiquated walk-in environmental chamber (approximately 10 m² growing area) with 14-h light/10-h night with fluorescent lighting. Because temperature and humidity regulation was minimal, one pot without a plant was included in each group of 24 plants and weighed daily to evaluate changes in the rate of evaporation. Subsequent watering was adjusted to compensate for within chamber variation. Water was delivered to individual pots using a Repipet dispenser.

Water amounts were varied to produce coarse- and fine-grained conditions. Plants in coarse-grained treatments received the same amount of water daily. Coarse-grained, high water (CGH) received 5 mL/d and had soil that was always wet. Soil for coarse-grained, low water (CGL; 2 mL/d) treatments was dampened and dried on a daily basis. Plants in fine-grained treatments received variable amounts of daily water. The fine-grained, high-water plants (FGH) were watered heavily early in the week (2 days, 10 mL/d), and lightly thereafter (5 days, 3 mL/d): soil was wet early in the week, and from damp to dry later. The fine-grained, low-water plants (FGL; 2 days, 7 mL/d) had damp soil early in the week, but were consistently dry for the last part of the week (5 days without watering). Thus "high" plants received a total of 35 mL/wk, and "low" plants 14 m/wk. Plants were kept in plastic trays; however, drainage was negligible.

Replicates were arrayed in three blocks to account for microenvironmental variation within the chamber. Each block was initially planted with four replicates of each of the 52 genotype-by-treatment combinations (13 genotypes and four treatments), however only seedlings that survived one week post germination were used in this study, giving us at least 3 replicates for all genotype-by-treatment combinations except one (499 plants total). This number did decrease over the course of the experiment due to plant mortality. Each plant was watered individually, assuring independence of the experimental units.

Data collection
Data were collected for two groups of traits. Some traits were measured at a fixed time after planting to measure rates of vegetative and reproductive development: leaves were counted at 28 days after planting, and main axis height and lateral branch number (branches produced on the main axis) were recorded 52 days after planting. Additionally, each plant was checked daily for the first appearance of a bolting main axis.

The second group of traits was measured 30 days after bolting. These measures provide information on production that is less dependent on the maturity of the plant. They include the number of leaves, the main axis height, numbers of both lateral and basal branches (branches initiated from the basal rosette, including the main axis). We also scored whether or not plants survived, that is, had leaves or branches that were at least 50% living at 30 days after the first appearance of the main axis. Fruits typically are mature about 21 days after the first appearance of the main axis (unpublished data), making a 30-day survival a reasonable proxy for reproductive success.

Analyses
The correlation matrix (PROC CORR, SAS, 1996 ) of the measured characters was examined for instances of high intercorrelation. The correlation matrix for all traits showed collinearity for the two lateral branch numbers (52 days post planting and 30 days post bolting; r = 0.76). We excluded lateral branch number (52 days post planting) from further analyses. Correlations among the remaining traits did not exceed 0.56.

Data were analyzed by ANOVA for all traits according to the model y = genotype, level, grain, genotype x level, genotype x grain, level x grain, and block (within level x grain) where level is coarse-grained water amount and grain refers to fine-grained variation in water amount. The three-way interaction was excluded as it never approached significance. All variables were normally distributed, and no transformations were necessary. MANOVA was used to evaluate contrasts between genotypes.

Because the traits remaining are biologically interrelated, we further reduced the data set using principal components analysis (PCA; PROC PRINCOMP, SAS, 1996 ). PCA was carried out for the entire data set, giving us a single set of components and facilitating a comparison among genotypes or among treatments. These components describe the orthogonal relationships underlying the phenotypic values, including those due to the biological processes that determine phenotypic expression. The residuals for each component reflect the weight and direction of the contribution of each individual plant's combined trait values to that component, and these can be analyzed in the same manner as the traits themselves. The residuals were all normally distributed and were used as dependent variables in ANOVA (PROC GLM, type III sum of squares; Tukey-Kramer post hoc analyses; SAS, 1996 ) (for other applications see Pigliucci et al., 1997 ; Kristjánnson et al., 2002 ).

Survival to 30 days after bolting was analyzed using probit regression (Systat, 2000 ). Probit regression, a form of log-linear regression, is used to analyze binary data such as survival, which violate normality.

	RESULTS

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION LITERATURE CITED

 
All measured traits (except 52 d main axis height) showed significant effects of genotype (i.e., variation among ecotypes; Table 1). However, mutants were not significantly different from Columbia. All traits except 52-d main axis height and survival showed significant main effects of water level (high vs. low). Plants grown in high water generally produced more leaves, taller main axes, and more branches and later bolting, relative to those in low water (Table 2). Bolting date had a significant genotype x water level interaction, indicating that effects of water level were genotype specific. A significant main effect of grain was detected for the bolting date 30-d-post-bolting main axis height and survival. Plants grown with increased variation in watering had taller main axes, relative to constant water.

View larger version (13K): [in this window] [in a new window]   Fig. 1. Plot of the mean number of days to bolting vs. the mean main axis height at 52 days after planting for each of the four treatment groups. Variable watering leads to a significant increase in main axis height in the low water treatments, but not in the high water treatments. Constant watering leads to earlier bolting in low water treatments, but delays bolting in the high water treatments. CG = coarse-grained, FG = fine-grained; H = high water, L = low water

	DISCUSSION

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION LITERATURE CITED

The potential to evolve an adaptive plastic response depends on the presence of a differential response to environmental variation within a population, especially with respect to fine-scale variation. Differences among populations (our ecotypes) will only allow adaptive evolution in response to geographic-scale environmental variation, e.g., variation on a scale comparable to that of the distribution of our ecotypes. We observed only limited genotype-specific variation in response to either fine- or coarse-scale variation. Thus, at least in this sample of Arabidopsis populations, there is limited potential for adaptive evolution of plastic responses for individual characters such as bolting date and main axis height to water level or patterns of variability.

Interaction of water level and grain
Three traits showed significant interactions between level and grain. Bolting date is particularly interesting because introducing variation in water delivery has opposite effects at the two watering levels. Increased variation led to faster bolting at high water, but delayed bolting at low water (Fig. 1). The strongest interaction between level and grain was for survival. The relative survival in three treatments was 60%, but the combination of low and variable water treatments (FGL) synergistically increased mortality. Survival was reduced to only 32%, far less than would be predicted from simply adding the effects of low water to those of variable water.

Plants in fine-grained low conditions (FGL) were actually somewhat larger than their counterparts in coarse-grained low, but the mortality data make it clear that a size increase was not a universal benefit. We speculate that plants in the FGL treatment may be receiving conflicting signals for overall growth rate. Perhaps plants are responding to an inappropriate environmental cue, confounding the pulse of water delivered (maximum water) with an expectation of more water (mean water).

Evolution of plasticity
The overall lack of genotypic variation for plasticity (i.e., only a single genotype x environment interaction for bolting date) was surprising. However, several previous studies of A. thaliana have also found relatively uniform responses of ecotypes to coarse-grained variation in water (Pigliucci et al., 1995 ; Callahan et al., 1999 ; Kolodynska and Pigliucci, 2003 ). Nienhuis et al. (1994) found genotype x environment interactions for water use efficiency; however, they varied ambient relative humidity, not water regime. We might speculate that canalization of responses is due to a history of similar strong selection pressures for response to variation in water; in fact, all ecotypes tested were originally collected from well-drained substrates.

Although there have been a number of theoretical explorations of evolution in heterogeneous vs. homogeneous environments (e.g., Levene, 1953 ; Levins, 1962 ; Haldane and Jayakar, 1963 ; Gillespie, 1974 ; van Tienderen, 1991 ; Brown and Pavlovic, 1992 ), there are few experimental studies that explicitly compare the effects of coarse- and fine-grained variation of different variables (see review by Alpert and Simms, 2002 ), and fewer still that compare scales of variation in the same variable. In studies that have compared coarse- vs. fine-grained variation, plants consistently respond differently to spatial vs. temporal environmental variation. Wijesinghe and Hutchings (1999) found that the clonal herb Glechoma hederacea had significantly greater total biomass and greater ramet number in heterogeneous soil nutrient environments where the patch size is large (25 x 25 cm) versus when patch size is small (12.5 x 12.5 cm), when the quality of patches differed substantially. Similarly, Day et al. (2003a , b) found that heterogeneous nutrient supply produced greater early root, shoot, and total plant biomass and lower mortality for Cardamine hirsuta. Kolodynska and Pigliucci (2003) showed that flooding (i.e., constant watering) vs. watering to saturation every other day affected all traits but bolting time in 47 accessions of Arabidopsis thaliana. Mkumbira et al. (2003) found that some traits of cultivated cassava were highly sensitive to location by season effects, that is, heterogeneity across plots over time. Juenger and Bergelson (2002) found significant genotype by environment interactions for large-scale variables (hail) but not for fine-scale variables (water and nutrient availability, local competition) in the annual wildflower, Ipomopsis laxiflora.

The results of those studies, as well as those here, show that both the mean and scale of the variability of environmental factors can be important determinants of phenotypic expression. Bradshaw (1965) and Levins (1968) also identified frequency and predictability as important determinants of the optimal response to a given environment, yet the literature addressing these variables is also limited (see Scheiner and Yampolsky, 1998 , and papers by Bell and co-workers (Bell, 1997 ; Bell and Reboud, 1997 ; Reboud and Bell, 1997 ; Kassen and Bell, 1998 ) for experimental investigations). Although there are expectations associated with the costs or benefits of plasticity in relation to mean and scale of variability, as well as frequency and predictability, there is little explicit theory related to how these might interact to determine phenotypic response and little experimental evidence on which to build such a theory. For example, an adaptive response to a rare, unpredictable, or fine-grained condition may be detrimental when the organism is subject to such a condition for the duration of its lifetime. Clearly, the body of knowledge amassed on the effects of coarse-grained and predictable environmental variation has made significant contributions to our understanding of plasticity and phenotypic evolution. We argue that extending our understanding to both the scale and distribution of environmental variation may be a key step in developing a cohesive theory of the evolution of adaptive plasticity.

	FOOTNOTES

 
¹ The authors thank Tracy Gartner, Cynthia Jones, and the anonymous reviewers for their considerable input into tightening and strengthening this presentation.

² Author for correspondence (kengelmann{at}ncsu.edu .)

³ Current address: Department of Genetics, North Carolina State University, Raleigh, NC 27612 USA

	LITERATURE CITED

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION LITERATURE CITED

 
Alpert P. E. L. Simms 2002 The relative advantages of plasticity and fixity in different environments: when is it good for a plant to adjust?. Evolutionary Ecology 16: 285-297[CrossRef][ISI]

Bell G. 1997 Experimental evolution in Chlamydomonas. I. Short-term selection in uniform and diverse environments. Heredity 78: 490-497[CrossRef][ISI]

Bell G. X. Reboud 1997 Experimental evolution in Chlamydomonas. II. Genetic variation in strongly contrasted environments. Heredity 78: 498-506[ISI]

Bradshaw A. D. 1965 Evolutionary significance of phenotypic plasticity in plants. Advances in Genetics 13: 115-155

Bradshaw A. D. K. Hardwick 1989 Evolution and stress—genotypic and phenotypic components. Biological Journal of the Linnean Society 37: 137-155

Brown J. S. N. B. Pavlovic 1992 Evolution in heterogeneous environments: effects of migration on habitat specialization. Evolutionary Ecology 6: 360-382[CrossRef][ISI]

Callahan H. S. C. L. Wells M. Pigliucci 1999 Light-sensitive plasticity genes in Arabidopsis thaliana: mutant analysis and ecological genetics. Evolutionary Ecology Research 1: 731-751[ISI]

Day K. J. M. J. Hutchings E. A. John 2003 The effects of spatial pattern of nutrient supply on the early stages of growth in plant populations. Journal of Ecology 91: 305-315[CrossRef]

Day K. J. M. J. Hutchings E. A. John 2003 The effects of spatial pattern of nutrient supply on yield, structure and mortality in plant populations. Journal of Ecology 91: 541-553[CrossRef]

Gillespie J. H. 1974 The role of environmental grain in the maintenance of genetic variations. American Naturalist 108: 145-151[CrossRef][ISI]

Haldane J. B. S. S. D. Jayakar 1963 Polymorphism due to selection of varying direction. Journal of Genetics 58: 237-242[ISI]

Juenger T. J. Bergelson 2002 The spatial scale of genotype by environment interaction (GEI) for fitness in the loose-flowered gilia, Ipomopsis laxiflora (Polemoniaceae). International Journal of Plant Sciences 163: 613-618[CrossRef]

Kassen R. G. Bell 1998 Experimental evolution in Chlamydomonas. IV. Selection in environments that vary through time at different scales. Heredity 80: 732-740[CrossRef][ISI]

Kolodynska A. M. Pigliucci 2003 Multivariate responses to flooding in Arabidopsis: an experimental evolutionary investigation. Functional Ecology 17: 131-140[CrossRef][ISI]

Kristjánsson B. K. S. Skúlason D. L. G. Noakes 2002 Morphological segregation of Icelandic threespine stickleback (Gasterosteus aculeatus L). Biological Journal of the Linnean Society 76: 247-257[CrossRef]

Levene H. 1953 Genetic equilibrium when more than one ecological niche is available. American Naturalist 87: 331-333[CrossRef][ISI]

Levins R. 1962 Theory of fitness in a heterogeneous environment. I. The fitness set and adaptive function. American Naturalist 96: 361-373[CrossRef][ISI]

Levins R. 1963 Theory of fitness in a heterogeneous environment. II. Developmental flexibility and niche selection. American Naturalist 47: 75-90

Levins R. 1968 Evolution in changing environments. Princeton University Press, Princeton, New Jersey, USA

Lloyd D. G. 1984 Variation strategies of plants in heterogeneous environments. Biological Journal of the Linnean Society 21: 357-385[CrossRef]

Meyre D. A. Leonardi G. Brisson N. Vartanian 2001 Drought-adaptive mechanisms involved in the escape/tolerance strategies of Arabidopsis Landsberg erecta and Columbia ecotypes and their F1 reciprocal progeny. Journal of Plant Physiology 158: 145-1152[CrossRef][ISI]

Mkumbira J. N. M. Mahungu U. Gullberg 2003 Grouping locations for efficient cassava evaluation in Malawi. Experimental Agriculture 39: 167-179[CrossRef][ISI]

Nienhuis J. G. R. Sills B. Martin G. King 1994 Variance for water-use efficiency among ecotypes and recombinant inbred lines of Arabidopsis thaliana (Brassicaceae). American Journal of Botany 81: 943-947[CrossRef][ISI]

Pigliucci M. P. J. DiIorio C. D. Schlichting 1997 Phenotypic plasticity of growth trajectories in two species of Lobelia in response to nutrient availability. Journal of Ecology 85: 265-276[CrossRef]

Pigliucci M. J. Whitton C. D. Schlichting 1995 Reaction norms of Arabidopsis. I. Plasticity of characters and correlations across water, nutrient and light gradients. Journal of Evolutionary Biology 8: 421-438

Reboud X. G. Bell 1997 Experimental evolution in Chlamydomonas. III. Evolution of specialist and generalist types in environments that vary in space and time. Heredity 78: 507-514[CrossRef][ISI]

SAS. 1996 SAS user's guide. SAS Institute, Cary, North Carolina, USA

Scheiner S. M. L. Y. Yampolsky 1998 The evolution of Daphnia pulex in a temporally varying environment. Genetical Research 72: 25-37

Schlichting C. D. 1986 The evolution of phenotypic plasticity in plants. Annual Review of Ecology and Systematics 17: 667-693[CrossRef][ISI]

Schlichting C. D. M. Pigliucci 1998 Phenotypic evolution: a reaction norm perspective. Sinauer Associates, Sunderland, Massachusetts

Stratton D. A. 1994 Genotype-by-environment interactions for fitness of Erigeron annuus show fine-scale selective heterogeneity. Evolution 48: 1607-1618[CrossRef][ISI]

Stratton D. A. C. C. Bennington 1998 Fine-grained spatial and temporal variation in selection does not maintain genetic variation in Erigeron annuus. Evolution 52: 678-691[CrossRef][ISI]

Systat. 2000 Systat, version 10. Systat Software Inc., Richmond, California, USA

van Tienderen P. H. 1991 Evolution of generalists and specialists in spatially heterogeneous environments. Evolution 45: 1317-1331[CrossRef][ISI]

Wijesinghe D. A. M. J. Hutchings 1999 The effects of environmental heterogeneity on the performance of Glechoma hederacea: the interactions between patch contrast and patch scale. Journal of Ecology 87: 860-872[CrossRef]

Winn A. A. 1996 The contributions of programmed developmental change and phenotypic plasticity to within-individual variation in leaf traits in Dicerandra linearifolia. Journal of Evolutionary Biology 9: 737-752[CrossRef][ISI]

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