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Biochemical Indicators of Air Pollution Effects in Trees: Unambiguous Signals Based on Secondary Metabolites and Nitrogen in Fast-Growing Species ? Clive G. Jones Institute of Ecosystem Studies The New York Botanical Garden Mary Flagler Cary Arboretum Millbrook, NY 12545 James S. Coleman Department of Biological Sciences Stanford University Stanford, CA 94305 ABSTRACT Various perturbations such as air pollution, shading, low nutrients, herbivore and pathogen attack cause stress and damage to plants. Stresses and damage may be distinguished on the basis of their effects on function and structure of the plant respectively, and on the time frame with which they occur. Different stresses may be classified on the basis of their relative or absolute effect on carbon (C) or nutrient acquisition. At the leaf tissue level, stress effects on carbon-based secondary metabolites (CSM) and nitrogen (N) may be predicted from the relative or absolute availability of C and N resources. In addition, stress often results in mobilization of N. The primary determinant of the magnitude and rate of difference in stress response between plant species is the inherent growth rate of plants. Fast-growing species may show plastic, dynamic responses in mobile CSM because allocation to growth takes priority over allocation to these compounds. Slow growers may not show such plastic and dynamic responses. Tissue damage initiates processes of repair and defense, which may result in mobilization of C and N to the site of damage for repair, and polymerization of CSM at the site of damage. A predictive model based on the above factors is presented with different perturbations as dependent variables and mobile and polymerized CSM, total and mobile N and time as independent variables. No single variable has a unique value for particular types of stress or damage, but combinations of two or more variables predict that signals will be distinguishable. If the predictions are correct, they will permit air pollution stress and/or damage to be relatively unambiguously identified. Preliminary data from ozone exposure of a fast-growing species, cottonwood, support the predictions of the model. INTRODUCTION Ideally, a biochemical indicator of air pollution effects in trees should provide an unambiguous, easily measured signal, specific to air pollution and occurring in most species. It is unlikely that such a silver bullet will be found because plants are exposed to multiple, simultaneous abiotic and biotic perturbations that are not distinguishable solely on the basis of which external force is acting on the plant. The end result of 261

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262 these perturbations is partially the effect of the particular stress or damage agent, and partially the result of plant adjustment. The particular nature of the plant response is determined by inherent plant characteristics that differ between species. Nevertheless, we will argue that it is possible to: distinguish between perturbations that are stresses versus those that damage the plant; categorize different stresses in terms of their effects on plant function; categorize the response of plants by applying plant physiological concepts; and categorize plant species on the basis of their inherent growth rates. These concepts can be linked together and used to predict changes in classes of biochemicals that are dynamic and sensitive to changes in plant function in certain species. Our arguments extend and derive from concepts we have presented regarding the nature of physiological and biochemical responses of plants to different stresses (Jones and Coleman, 1 988a). A predictive model will be presented for selected perturbations. We will focus attention on carbon-based secondary metabolites (CSM) and total and mobile nitrogen (N) in leaves. We will then describe a preliminary test of this model, using data from studies on the biochemistry of cottonwood following acute ozone exposure (Jones and Coleman, in prop.~. Of necessity, this short paper will be an outline of these ideas, rather than a detailed exposition. COMPONENTS OF A PREDICTIVE MODEL Distinguishing Stress from Damage Plants are exposed to a diversity of abiotic and biotic perturbations, in addition to air pollution. These perturbations often occur simultaneously and include shading, nutrient and water deficiencies, and herbivore and pathogen attack (Chapin et al., 1987; Jones and Coleman, 1 988a; Mooney et al., 1988~. Distinguishing the outcome of these perturbations on the plant requires that we first understand in what ways the effects of different perturbations to the plant are similar or different. Perturbations can be classified as resulting in stress - defined here as interference with plant function, or damage - defined here as interference with plant structure (cf., Grime, 1979~. The perturbations listed above can result in stress or damage (Fig. 1~. Stress may lead to subsequent damage (Pell, 1979) (e.g., drought may increase susceptibility to herbivores; Mattson and Haack, 1987), and damage may lead to subsequent stress (Baseman and Dickmann, 1985) (e.g., oxidant injury reduces carbon gain and growth; Reich, 1987), but this is not inevitable. Furthermore, certain perturbations cause stress but not damage, but all perturbations causing damage have the potential also to cause stress. Interestingly, air pollution, herbivore and pathogen attack can similarly result in both stress and damage (Norris, 1979; Williams, 1979; Bassman and Dickmann, l9g5; Hawkins et al., 1 986a,b; Tissera and Ayers, 1986; Jones and Coleman, 1 98Sa). Stress and damage tend to occur on different time frames (Grime, 1979; Fell, 1979; Fell and Dan, 1988~. While stress effects may be short (i.e., acute) or long (chronic), effects of damage are usually comparatively short-lived after initial damage (Kimmerer and Kozlowski, 1982; Edwards et al., 1986~. Distinguishing between stress and damage is critical to the use of bioindicators because certain plant biochemicals show different responses, depending on whether stress and/or damage occurs (Jones and Coleman, 1988a). Whole Plant Partitioning of Resources in Response to Stress The overall effect of stress is a reduction in the acquisition of resources - the dominant plant function (Mooney, 1972~. Plants respond to stress by adjusting partitioning of existing and subsequent resources to ameliorate the effects of stress (Bloom et al., 1985; Chapin et al., 1987; Szaniawski, 1987~. For example, when carbon (C)

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263 PERTUR8AT I ONS Stress (affects function Air Pollution Herb ivores Pa thogens Shad ing Low Mineral Nutrients Drough t Figure 1. Some perturbations to plants that may result in stress and/or damage. acquisition is limited by shading or air pollution, plants subsequently partition proportionately more C to shoots (Mooney and Winner, 1988~. This results in a shoot C gain relative to nutrient acquisition, and this C may be used to produce proportionately more leaf area or photosynthetic machinery, which presumably then restores the C balance by increasing photosynthetic capacity. On the other hand, plants exposed to nutrient (N) limitation partition more C to root growth (Robinson, 1986; Hunt and Nicholls, 1986; Mooney and Winner, 1988~. This enables plant roots to grow and explore a greater soil area for resources, and creates a greater surface area for absorption of nutrients and water (Ingestaad and Agren, 1988~. The overall result of adjustment to stress is a balancing of the C:N ratio around some optimal value (Bryant et al., 1983; Bloom et al., 1985; Chapin et al., 1987; Agren and Ingestaad, 1987; Ingestaad and Agren, 1988~. Using this approach, we can derive a primary classification of stresses in terms of their relative effects on C or nutrient acquisition. Thus, air pollution, herbivory and pathogen attack (on leaves) can result in C stress, whereas nutrient limitation results in N stress (Jones and Coleman, 1 98Sa). This primary classification is an essential component of the predictive model. Damage a f f ec ts s tructure Air Pollution Herb ivores Pa thogens Severe Drough t Allocation of Resources within Tissues We can apply the concept of C and nutrient balance at a lower level of organization - the tissues (i.e., leaves) - by applying the resource availability hypothesis (Bryant et al., 1985~. This hypothesis focuses primarily on changes in plant secondary

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264 metabolites (e.g., phenolics, terpenoids) and nutrients such as protein and soluble N. The hypothesis predicts that plants allocate C or N to these compounds as a function of their availability in the environment. In this paper we will restrict our comments to carbon-based secondary metabolites (CSM) (e.g., phenolics, terpenoids) and organic N. Evidence substantiating the general applicability of this hypothesis is now quite considerable (Rhoades, 1983; Bryant et al., 1985; Larsson et al., 1986; Bryant, 1987) and, therefore, we will generalize in the context of selected stresses, rather than present a detailed exemplification. A more detailed treatment examining physical characteristics and a broad suite of chemical changes in leaves is presented in Jones and Coleman (1 988a). When C gain is limited relative to nutrient availability (e.g., air pollution, shading), allocation to CSM is predicted to decline, and leaves become relatively enriched in nitrogen. Nutrient stress is predicted to result in an increase in CSM because of a relative increase in the availability of C, while N concentrations are predicted to decline. Stress-induced Changes in the Form of Nitrogen Nutrient stress results in mobilization of N. with increases in concentrations of amino acids, imino acids, poly- and di-amines (Stewart and Larher, 1980; Erickson and Dashek, 1982; Smith, 1984; White, 1984~. This occurs because nutrient stress induces catabolism of plant protein and subsequent re-translocation of N to shoot tips (Stewart and Larher, 1980~. Plant Determinants of the Magnitude and Rate of Stress Responses Not all plants show dynamic changes in CSM or N following stress. The inherent growth rate of plants has been invoked to explain these differences (Corey et al., 1985~. This concept has three major components. First, fast-growing species that tend to occur in resource-rich environments are predicted to allocate proportionately fewer resources to the production of CSM compared to slow-growing species from resource-poor environments, presumably because the value of individual leaves to a plant decreases as relative growth rate increases. Second, fast-growing species are predicted to make small amounts of mobile CSM with high turnover rates and metabolic costs (e.g., phenolic glycosides, monoterpenes); whereas slow-growers should construct large amounts of relatively immobile CSM with relatively low turnover rates and metabolic costs (e.g., tannins). Third, under conditions of stress, fast-growers should show extensive plasticity in the production of CSM, because allocation to growth is predicted to be: a higher priority than allocation to CSM. For example, a reduction in C gain due to shading reduces mobile phenolics (Waring et al., 1986; Larsson et al., 1986; Bryant et al., 1987; Mole and Waterman, 1988~. On the other hand, allocation to immobile CSM should be a high priority in slow-growers, so there should be less plasticity when these plants are stressed (Lincoln and Mooney, 1984; Bryant et al., 1985; Coley et al., 1985~. Inherent growth rate is thus a critical predictor of the expected response of different plant species to stress. Plant Responses to Damage While stress results in adjustments of the primary plant function of resource acquisition, damage at the tissue level activates processes of repair and defense (McLaughlin and Shriner, 1980; Putritch and Jensen, 1982; Shigo, 1984~. Repair requires C and N to be moved to the site of damage as resources for synthesis of membranes, cell walls, enzymes and other metabolites, and to remove any further damage agents (such as

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265 free radicals) (Lee and Bennett, 1982; Pelt and Dan, 1988~. Consequently, damage results in increases in mobile forms of N (e.g., amino acids, soluble enzymes e.g.; Green and Ryan, 1972) and C (e.g., sugars Craker and Starbuck, 1972; Heath, 1984; Koziol and Whatley, 1984; Guderian et al., 1985; Tallamy and Raupp, 1989~. Defense occurs to prevent subsequent invasion by pathogens or attack by herbivores of vulnerable tissues. A frequent response of plants to damage is the deposition of phenolic materials (e.g., lignin, polyphenolics) into damaged or adjacent tissues (Rhoades, 1979; Deverall, 1982; Daly, 1984; Kemp and Burden, 1986~. This requires mobilization of polyphenolic precursors to the site of damage or in situ biosynthesis, rapidly followed by polymerization (Howell, 1974; Tingey et al., 1975, 1976; Curtis et al., 1976). The recognition that damage can result in local increases in mobile N and polymerized forms of CSM over short time frames (hours, days) is critical to the predictive model. PREDICTING STRESS AND DAMAGE RESPONSES IN FAST-GROWING TREE SPECIES The Model The predicted relationships between stress, damage and the biochemical responses on plants are shown for fast-growing plant species in Table 1, and are based on the previous considerations. The independent variable is the perturbation. Dependent varia- bles are the % polymerized CSM (lignin, polyphenolics), either as absolute values compared to unstressed or undamaged plants, or as a relative value compared to total foliar N; total foliar N. either absolute or relative to total C, % of total N in mobile, low molecular weight forms (amino, imino acids, diamines, polyamides) either absolute or relative to total C; and the duration of the response - short (hours, days) or long (weeks, season, years). Of total leaf C allocated to mobile CSM (e.g., mobile phenolics), and (lignin, polyphenolics), either as absolute values Table 1. Predicted relationships between perturbation, duration of effect of perturbation and foliar biochemistry. Mobile and polymerized CSM can be a To of total C or absolute concentrations or relative to total N. Mobile N can be a oh of total N or absolute concentrations. Alernatively, total and mobile N may be relative to total C. +:increase; -:decrease; O:no change. Duration Mobile Polymerized Total Mobile Perturbation of Effects CSM CSM N N Damage (Air pollution, Hervivores, pathogens) Carbon Stress (Air pollution, shading, prior defoliation by hervivores) Short + Short/ - O Long Mineral Nutrient Stress Long + O o +

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266 It can be seen that each single dependent chemical variable shows increases, decreases or no change, depending on the type of stress. No single type of stress, nor damage, has a unique value for the response of each variable, with the exception of increases in polymerized CSM with damage. However, combinations of two or three variables are predicted to show unique, stress- or damage-dependent signals. example, if the mobile CSM is plotted against the total foliar N (Fig. 2), a clearer separation of the different stresses or damage is obtained. Damage due to air pollution, herbivores or pathogens is distinguished by the high values for mobile CSM and N. and the presence of polymerized CSM. It is probably reasonable to suppose that the specific damage agents of herbivores or Pathogen attack can be distinguished visibly at lea.~t in the case of foliar chewing. mining. Balling or leaf-rollin~ herhivnre~ carbon stress (air pollution, shading) produces high values for N and low values for CSM, and no polymerized CSM is present. Different sources of carbon stress (air pollution, shading, prior defoliation) should be distinguishable if canopy dominant, unshaded trees are sampled and if there are reasonable records of prior defoliation by insects. Nutrient stress has low values for total N and high values for mobile CSM, with no polymerized CSM present. I, ~ ,, On the other hand, For High C, a) _ Q o :E Low Damage Mineral N Stress (Polymerized CSM also present) Carbon Stress Low Total N High Figure 2. Predicted values for, and relationships between, mobile CSM, and total N with different types of stress and damage. The biaxis plot shows separation of carbon stress from nutrient stress and damage.

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267 Our model suggests that one approach to find markers of air pollution effects in forests would be to determine the relative or absolute allocation of foliar C to mobile CSM (e.g., phenol glycosides, low molecular weight phenolics, terpenoids) and polymerized forms of CSM (e.g., polyphenols, tannins, lignins) and the absolute or relative total foliar N and % of total nitrogen in mobile N (polar, low molecular weight such as amino and imino acids, di- and polyamines), for canopy-dominant, fast-growing species. Sampling these predicted changes in allocation over reasonable time periods (2-3 years), or comparing allocation with plants growing under similar conditions at lower pollutant concentrations, may facilitate relatively unambiguous determination of both damage and stress effects due to air pollution. A PRELIMINARY TEST OF THE PREDICTIVE MODEL Jones and Coleman (in prep) exposed saplings of deltoids, to an acute dose of ozone (20 pphm, 5 fur). fast-grower. The ozone dose had no significant effect did not cause visible injury to the leaves that were charcoal-filtered air controls (Coleman et al., 19871. two clones of cottonwood, Populus This species is an indeterminate on the growth of the plant, and chemically analyzed, compared to The concentration of one class of mobile CSM, phenol glycosides, polymerized phenolics, total N and polar (mobile) N were determined in leaves. Although the selected ozone dose had no direct effect on growth, and did not cause visible injury to assayed leaves, both damage and short-term stress to the plant occurred for the following reasons. Leaves older than those assayed frequently showed visible ozone injury. These doses are also known to reduce photosynthetic rates and carbon gain (Reich, 1983), biomass partitioning (Reich and LassoIe, 1985) and water use (Reich and Lassoie, 1984) in poplars. Lastly, both clones showed significant changes in subsequent resistance to insects and diseases (Coleman et al., 1987; Jones and Coleman, 1 98Sb; Coleman and Jones, 1988), indicating changes in structure and/or function in leaves that were not visibly injured. Table 2. Predicted changes in biochemical characteristics of P. deltoides exposed to stress, damage, and both stress and damage when exposed to ozone (20 pphm, 5 hr.~. Abbreviations as in Table 1. Mobile CSM Phenolic Glycosides Polymerized Total Mobile CSM N N Phenolics Damage Only + + + + Stress Only _ 0 + O Damage Damage>Stress + Damage=Stress Stress Stress>Damage + + + + O + + + + + + The model predicts that for this short-term perturbation (Table 2), stress should result in a reduction in the mobile CSM phenol glycosides' an increase in total N. and no change in mobile N. Damage should be indicated by the presence of polymerized CSM

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268 phenolics, an increase in total N and an increase in mobile N. Since both stress and damage occurred in the experiment, we would expect an increase in total N and mobile N and the presence of polymerized CSM phenolics. If stress exceeded damage in intensity, mobile CSM phenol glycosides should decrease. If damage exceeded stress in intensity, mobile CSM should increase and stress would not be detectable from a sample taken at only one time, because the other discriminatory variable, total N. is also predicted to increase with both stress and damage. If damage and stress were both equal in intensity, mobile CSM phenolic glycosides should not have changed. Table 3 shows that mobile CSM phenol glycosides decreased; polymerized phenolics were present; total N increased in both clones, but significantly so, in only one clone; and mobile N increased. The model predicts that the changes in the parameters we measured indicate that indeed both stress and damage occurred. In addition, if the model is correct, stress effects were greater in intensity than damage effects, because mobile CSM phenol glycosides showed an overall decline. Table 3. Leaf characteristics of 2 clones of P. deltoides exposed to an acute ozone close (20 pphm, 5 hr) that had no effect on growth and did not produce visible injury. * p > 0.1; ** p > .0005. Residue phenolics are Folin=Denis positive phenols remaining in the plant after extraction with solvents. Polar N is nitrogen extracted into butanolic or aqueous fractions. Data from Jones and Coleman, 1989. Clone ST109 Clone ST66 O3 CFA O3 CFA Phenol glycosides, 7.44* 10.57 7.89* % DW as glucose equivalents (_ Mobile CSM) 10.71 Residue Phenolics, 0.28 0 0.64 0 oh DW (-- Polymerized CSM) Total N. %DW 1.92 1.81 2.02** 1.68 Polar N. % of 22 12 17 (_ Mobile N) 13 CONCLUSION The above data were measured prior to the development of this model, but were not considered in constructing the predictions of the model. The experiment was by no means a rigorous test of the predictions - for example, we did not measure photosynthetic rates or examine leaves histologically to confirm independently that stress and damage occurred in this particular experiment. Nevertheless, the findings do not contradict the predictions of the model. This is encouraging, and suggests that tests of the model in greenhouse and field chamber experiments, as well as the field, are warranted.

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269 ACKNOWLEGMENTS Contribution to the program, Institute of Ecosystem Studies, The New York Botanical Garden. We thank NSF (BSR-85-16679), The NRC and the Mary Flagler Cary Charitable Trust, for support of CGJ, and EPRI and Hal Mooney for support of ISC. REFERENCES Agren, G.I., and Ingestaad, T. 1987. Root/shoot ratios as a balance between nitrogen productivity and photosynthesis. Plant, Cell and Environ. 10:579-586. Bassman, J.H., and Dickmann, D. 1985. Effects of defoliation in the developing leaf zone of young Populus X euramericana plants. III. Distribution of 14C photosynthate after defoliation. For. Sci. 31:358-366. Bloom, A.J., Chapin, F.S. III, and Mooney, H.A. 1985. Resource limitation in plants - an economic analogy. Annul Rev. Ecol. Syst. 16:363-392. Bryant, J.P. 1987. Feltleaf willow - snowshoe hare interactions: Plant carbon/nutrient balance and floodplain succession. Ecology 68:1319- 1327. Bryant, J.P., Chapin, F.S. III, and Klein, D.R. 1983. Carbon/nutrient balance of boreal plants in relation to verebrate herbivory. Oikos 40:357-368. Bryant, J.P., Chapin, F.S. III, Reichardt, P., and Clausen, T.P. 1985. Adaptation to resource availability as a determinant of chemical defense strategies in woody plants. Rec. Adv. Phytochem. 19:219-237. Bryant, J.P., Chapin, F.S. III, Reichardt, P.B., and Clausen, T.P. 1987. Response of winter chemical defense in Alaskan paper birch and green alder to manipulation of plant carbon/nitrogen balance. Oecologia 72:510-514. Chapin, F.S. III, Bloom, A.J., Field, C.B., and Waring, R.H. 1987. Plant responses to multiple environmental factors. BioScience 37:49-57. Coleman, J.S., and Jones, C.G. 1988. Plant stress and insect performance: Cottonwood, ozone and a leaf beetle. Oecologia 76:57-61. Coleman, J.S., Jones, C.G., and Smith, W.H. 1987. Effects of ozone on cottonwood-leaf rust interactions: Independence of abiotic stress, genotype and leaf ontogeny. Can. J. Bot. 65:949-953. Coley, P.D., Bryant, J.P., and Chapin, F.S. III. 1985. Resource availability and plant antIherbivore defense. Science 230:895-899. Craker, L.E., and Starbuck, J.S. 1972. Metabolic changes associated with ozone injury of leaves. Can. J. Plant Sci. 52: 589-597. Curtis, C.R., Howell, R.K., and Kremer, D.R. injury. Environ. Pollut. 11:189- 194. 1976. Soybean peroxidases from ozone

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