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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.
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Representative terms from entire chapter:
polymerized csm
