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Secondary defense responses of White spruce (Picea glauca) and arctic lupine (Lupinus arcticus) to changes… Sharam, Gregory John-David 1997

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SECONDARY DEFENSE RESPONSES OF WHITE SPRUCE (PICEA GLAUCA) AND ARCTIC LUPINE (LUPINUS ARCTICUS) TO CHANGES IN HERBIVORY AND SOIL NUTRIENT CONCENTRATIONS by Gregory John-David Sharam B.Sc, Dalhousie University, Halifax, 1994 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in THE FACULTY OF GRADUATE STUDIES (Department of Botany) We accept this thesis as conforming to the required standard THE UNIVERSITY OF BRITISH COLUMBIA February 1997 © Gregory John-David Sharam, 1997 I n p r e s e n t i n g t h i s t h e s i s i n p a r t i a l f u l f i l m e n t o f t h e r e q u i r e m e n t s f o r a n a d v a n c e d d e g r e e at t h e U n i v e r s i t y o f B r i t i s h C o l u m b i a , I a g r e e t h a t t h e L i b r a r y s h a l l m a k e i t f r e e l y a v a i l a b l e f o r r e f e r e n c e a n d s t u d y . I f u r t h e r a g r e e t h a t p e r m i s s i o n f o r e x t e n s i v e c o p y i n g o f t h i s t h e s i s f o r s c h o l a r l y p u r p o s e s m a y b e g r a n t e d b y t h e h e a d o f m y d e p a r t m e n t o r b y h i s o r h e r r e p r e s e n t a t i v e s . I t is u n d e r s t o o d t h a t c o p y i n g o r p u b l i c a t i o n o f t h i s t h e s i s f o r f i n a n c i a l g a i n s h a l l n o t b e a l l o w e d w i t h o u t m y w r i t t e n p e r m i s s i o n . D e p a r t m e n t o f T h e U n i v e r s i t y o f B r i t i s h C o l u m b i a V a n c o u v e r ; C a n a d a . D a t e ' fek> D E - 6 ( 2 / 8 8 ) Abstract White spruce {Picea glauca, Voss) contains an antifeedant (camphor) which deters snowshoe hares (Lepus americanus Erxleben), a generalist herbivore, from feeding on it. Spruce was used as a model species to test the sometimes conflicting predictions of the Optimal Defense, and the Carbon: Nutrient Balance (CNB) theories of plant defense. The Optimal Defense theory predicts that plants will produce inducible defenses, this concentration being a function of the intensity of herbivore attack, and soil fertility. The CNB theory predicts that changes to the carbon: nutrient ratio will alter the relative amount of available carbon in the plant, and thus, the amount of defensive investment. Twig samples of white spruce were collected from small (0.5-1 m tall), medium (2-3m), and large (6-10m) trees growing in areas which have had Herbivore Exclusion, Fertilization, and Herbivore Exclusion + Fertilization treatments for 9 years. Twig samples were also collected from a group of medium-sized trees on Control and Fertilized areas that had been exposed to low and high levels of simulated herbivory. Medium and large trees were also sampled repeatedly during a period of fifteen months to examine yearly patterns of defensive investment. Medium and large trees on Herbivore Exclusion and Fertilization treatment areas had reduced defenses, with additively reduced defenses on the Herbivore Exclusion + Fertilization treatment area. Small tree defenses did not vary between treatment areas. Medium-sized trees exposed to low ii levels of simulated herbivory decreased defenses within the same year as treatment, and increased defenses the year after treatment. Medium-sized trees exposed to high levels of simulated herbivory had reduced defenses in both the same and the year following treatment. A yearly defense cycle was detected, with a minimum in June-July, and a maximum in December-January. Results suggest that spruce trees defend both optimally and as a response to carbon: nutrient limitation. A modified CNB theory is proposed that addresses problems in the original CNB theory, and has better predictive abilities. The defensive content (spartein) of arctic lupines {Lupinus arcticus S. Watts) was also investigated. No variation in defenses was found between lupines on different treatment areas. Spartein concentration was found to cycle on a daily basis, with a maximum at 2 am and a minimum from 10 am to 6 pm. The results of the lupine study are included in an appendix. iii Table of Contents Abstract Table of Contents i v List of Figures . v i List of Tables v j i Acknowledgment v ' " 1.0 General Introduction to Chemical Defense Theory 1 1.1 Introduction 1 1.2 Definitions 1 1.3 Evolutionary Optimality Theories 2 Optimal Defense Theory (OD) 4 Resource Availability 6 1.4 Physiological Theories 9 Nutrient Stress 10 Carbon: Nutrient Balance Theory 11 Reallocation and the Moving Target 12 1.5 The Study Species and its Defense 13 1.6 Hypotheses 14 2.0 Materials and Methods 17 2.1 The Study Area 17 2.2 The Kluane Boreal Forest Ecosystem Project 20 2.3 Field Site 20 2.4 The Species 21 2.5 Manipulations of Spruce Trees 21 2.6 Sample Collection 22 2.7 Quantitative Analysis of Camphor 23 2.8 Quantitative Analysis of Nitrogen 25 2.9 Statistical Analysis 25 3.0 Results 26 3.1 Camphor Concentrations 26 Main Treatments 26 Yearly Cycle 26 Size Class 27 3.2 Nitrogen Concentrations 27 iv 3.3 Water Content 28 4.0 Discussion 37 4.1 Main Treatments 37 Standard Optimal Defense Theory 39 Modified Optimal Defense Theory.: 40 Carbon: Nutrient Balance Theory 41 Limiting Resource Theory.. 42 Integration of Optimal Defense and Limiting Resource Theories 44 Support for Multiple Pathways in the Literature 45 Problems With the Optimal Defense/ Limiting Resource Theory 46 4.2 Large and Small Tree Classes, and the Yearly Cycle 48 Large Tree Class 48 Small Tree Class 48 Yearly Cycle 48 4.3 Limitations of this Study 50 5.0 Conclusion 52 Appendix: Experiments with Lupines 53 Bibliography 60 V List of Figures Figure 1: Resource Availability model, the effect of defense 7 investment on realized growth rate. Figure 2: The modified Resource Availability model, the effect of 9 defense investment on realized growth rate. Figure 3: May of Yukon Territory, Alaska, and British Columbia, 18 showing location of the study site. Figure 4: Camphor concentrations of medium sized (2-3 m) spruce 32 trees on treatment areas and exposed to simulated and extreme herbivory. Figure 5: Camphor concentrations of medium (2-3 m) and large (6- 33 10 m) spruce trees over fifteen months. Figure 6: Camphor concentrations of small (0.5-1 m), medium (2-3 34 m), and large (6-10 m) trees on main treatment areas. Figure 7 : Nitrogen concentrations of medium (2-3 m) spruce trees 35 on main treatment areas and exposed to simulated and extreme herbivory. Figure 8: Growth rates of spruce trees measured over a six year 51 period. Figure 9: Spartein concentrations of dried lupine samples over a 59 48 hr period. vi List of Tables Table 1: Hypotheses of the Standard and Modified Optimal Defense 16 theory and the Carbon: Nutrient Balance theory. Table 2: Summary of ANOVA for camphor concentrations on main 29 treatment grids. Table 3: Summary of Bonferri-Dunn test for variation of treatment 29 camphor concentrations from control mean. Table 4: Summary of ANOVA for yearly camphor concentrations of 30 large trees. Table 5: Summary of ANOVA for yearly camphor concentrations of 30 small trees. Table 6: Summary of ANOVA for camphor concentrations of large 30 trees on main treatment grids. Table 7: Summary of ANOVA for camphor concentrations of small 31 trees on main treatment grids. Table 8: Summary of ANOVA for nitrogen concentrations on main 31 treatments grids. Table 9: Hypotheses of the Standard and Modified Optimal Defense 36 theories, Carbon Nutrient Balance theory for Camphor in White Spruce, and Experimental Results. Table 10: Predictions made by the Limiting Resource Theory. 43 Table 11: Predictions of the Standard and Modified Optimal Defense 54 theories, and the Carbon: Nutrient Balance theory for Spartein concentrations in Lupines. Table 12: Summary of ANOVA for spartein concentrations in lupines. 57 Table 13: Summary of ANOVA for nitrogen concentrations of lupines. 57 vii Acknowledgment I wish to thank my supervisor Dr. Roy Turkington for his support, encouragement, patience, and constant anecdotes. I am indebted to him for allowing me to work in the Yukon and to find my own way in science. I also wish to thank my committee members, Dr. A.R.E. Sinclair, and Dr. Neil Towers. Dr. Ljerka Kunst was of immense assistance for the use of her laboratory and equipment. Thanks to Samantha Hicks, Pippa Secomb-Hett, Sam Skinner, Steve Montgomery, Karen Hodges, Elizabeth Gillis, Clive Wellham and Christie Spence for help in the field, creative criticism of my ideas, and keeping me sane. v i i i 1 1.0 General Introduction to Chemical Defense Theory 1.1 Introduction Plant defensive theories can be divided into two general groups: evolutionary and physiological. Evolutionary defense theories are optimality models predicting tradeoffs between defense and growth or reproduction. Physiological theories argue that defensive investment is the fortuitous result of general physiological changes in response to the environment. If nitrogen becomes limiting to the plant, carbon-based defenses will be produced with the excess carbon. These two theories make slightly different predictions, allowing us to test which model has the better predictive abilities with regard to plant defensive investment. 1.2 Definitions A defense is any characteristic of a plant that reduces its consumption by herbivores. The ambiguity of this definition is important, as defense from herbivores can often be the product of a suite of characters, not simply the result of one chemical or morphological structure (Bryant, 1981; Hruska, 1988; Hay and Kappel, 1994, Scogings, 1995). Defenses can include physical characteristics such as thorns, burrs, high fiber content, chemical defenses, or even a low nutritional content. Evolutionary theories generally consider simply whether a plant should defend or not (van der Meijden et al., 1988; Clark and Harvell, 1992; Karban and Niiho, 1995). Many studies, however, attempt to identify a specific trait that acts as a defense. Physiological-based theories of defense require some information about the defense (i.e. carbon- or nitrogen-based) in order to make predictions. A plant defensive chemical is any chemical that functions as a defense. Defensive chemicals can deter feeding, cause a toxic effect that deters further feeding, interferes with digestion, or kills the animal. These compounds may have both defensive and non-defensive metabolic functions (e.g. Baldwin etal., 1994; Hjaltenefa/., 1994). Plant defenses are of two general types; constitutive and induced. A constitutive defense has a genetically programmed allocation strategy, that is unalterable by environmental factors. In contrast, the concentration of inducible defenses Is wholly or partially controlled by the environment. These defenses can be "induced" by environmental factors to be produced de novo, or their concentration and allocation may be altered from a preexisting level. A plant could conceivably have both a baseline constitutive level of defense due to evolutionary constraints, and an inducible defense that is initiated when the environment changes (Tuomi and Fagerstrom, 1991). 1.3 Evolutionary Optimality Theories Evolutionary theories of plant defense are based on the assumption that defenses deter herbivores, and are a cost to the plant. Grime (1977) first clearly articulated the two prevalent themes in optimal defense theories: (1) probability of attack, and (2) the alternative strategies of growth and defense. These two themes influence most current optimality models. Grime theorized that, in broad terms, stress tolerating (S) plants are long lived, have a higher probability of being attacked and should defend themselves. Ruderal (R) and competitive (C) plants, on the other hand, are generally short-lived, grow on fertile soil, and should devote their resources to growth rather than defense. High soil fertility allows ruderals and competitors to regrow after attack, thus reducing the need for initial investment in defense. Probability of attack can be seen as a subset of the growth:defense theory. Given that a plant is stress tolerant, it should defend itself, and do so as a function of its probability of being attacked. The concept of growth vs. defense has expanded beyond R,C and S strategists to include comparisons between similar species and even within a single species, van der Meijden et al. (1988) examined defense and regrowth characteristics of several closely related biennials, finding the two characters to be inversely correlated. Price (1991) and Hunter and Schultz (1995) have recently rearticulated this theory as the Plant Vigor hypothesis and the Active Defense theories respectively, stating that vigorously growing plants need not defend, as they can easily regrow tissue lost to herbivory. Feeney (1977) used the idea of probability of attack in his "Apparency Hypothesis". He proposed that the largest determinant of plant defense is the probability of its being attacked (apparency), which is, in turn, a function of several variables, including plant abundance, distribution, size, and cover. For example, plants with long life spans should defend more than those with shorter ones. Flowers which are larger, more abundant, or longer lived, should be 4 better defended, as they are more likely to be found by a foraging herbivore. While on a large scale, this theory is intuitively appealing it may not be an important determinant of chemical defensive investment. Coley (1983) did not detect any differences between ruderal and stress tolerant tropical lowland trees; two groups which are relatively similar but differ greatly in both spatial and temporal apparency. Growth rate, however, was positively correlated to nutritional content, and negatively correlated to defensive investment (growth vs. defense). Optimal Defense Theory (OD) The probability of attack theory and Feeney's (1977) apparency hypothesis have been expanded to produce a group of theories know as optimal defense theories. These theories describe the maximization of defensive characteristics in space and time, while simultaneously minimizing costs of defense. There are two classes of optimal defense theories; the optimal constitutive and optimal inducible defense theories. Both predict that a plant should more heavily defend structures that are more important, heavily attacked, or costly for the plant to produce (spatial optimization). Allocation to defense should also depend on biomass (size escape), the current defense level, the effectiveness of the defense and the reproductive state of the plant. The constitutive theory predicts greater defense at periods when herbivore attack is more likely, i.e. before size escape, or at certain times during the day or year. The inducible defense theory predicts that a plant should increase its 5 defensive investment when triggered by the attack of a herbivore (Clark and Harvell, 1992). Much theoretical work has been devoted to determine which theory is optimal under a variety of conditions (Grover, 1995; Thompson, 1988). Computer modeling indicates that the best strategy depends on the predictability of attack, how sustained the attack is, and the time lag before induction of the defense (Lundberg et al., 1994). In the case of an unpredictable and sustained attack, and a short time lag defense (shorter than the duration of attack), the inducible defense is more appropriate. Other theories, however, show that inducible defenses are more appropriate when the defensive compounds are effective deterrents (Reichardt et al., 1990). Thus, optimal defense theories predict that plants should have inducible defenses, and that when attacked, they should use them. Plants should also have higher levels of constitutive defense during times or seasons of high attack, when they are small and more easily completely consumed, and in areas of the plant that are most susceptible or have historically been attacked more often. The concept of costs is critical to defensive investment ideas. To model defenses using evolutionary ideas, there must be some inherent cost to defense. If a defense had no cost, then a plant could produce an infinite amount of it in all of its tissues. Costs can be defined as either proximal or ultimate. Proximal cost is measured in energy, nutrients, water, or time used in defense production. Ultimate cost is the reduction in lifetime breeding success due to proximal costs. It is generally assumed that proximal costs result in ultimate costs. Defensive costs may be less than their proximal costs, however, because the defensive compounds or structure may have uses unrelated to defense, e.g. a photosynthetic thorn. Even if an ultimate cost is very small, it can still provide significant selective pressure to drive adaptation, and thus, the evolution of optimal allocation of defenses (Mole, 1994). Resource Availability Coley et al. (1985) used an optimal defense model to predict rates of growth and defense within a single species in their Resource Availability theory. In this theory, growth and defense are seen as the two sinks for a plant's resources. Thus, the cost of defense is a reduction in growth. Coley et al. (1985) proposed that allocation to defense will inversely correlate with soil nutrient supply and thus growth rate. Higher defensive investment by plants growing at low resource levels is argued to occur for three reasons. First, those plants at a low nutrient supply, have a lower growth rate than those at a high nutrient supply, and so have a lower regrowth potential should herbivory occur. Thus, these plants should increase defensive investment to 'protect what they have'. Second, a given amount of biomass removal (absolute value) represents a larger proportion of the total plant biomass for a slow growing plant than for a faster growing plant (Fig. 1). Third, a given percent reduction in growth rate caused by the reallocation of energy from growth to defense, represents a greater absolute growth reduction for a fast growing plant than for a slow 7 growing plant. To maximize absolute growth rate, the fast growing plant should defend less than a slower growing plant (Fig. 1). Realized growth rate maximal growth rate Low maximal growth rate Low Defense investment -> High Figure 1. Effect of defensive investment on realized growth rate. Arrows indicate the maximum realized growth rate for a given maximal growth rate (modified from Coley et al., 1985). Realized growth rate (dC/dT) is calculated from the formula G*C*(1-kDa) - (H-mDb) where: G* (g/gd) = the maximum inherent growth rate permitted by the environment (g new growth/g existing biomass*day) C* (g) = the plant's biomass at t=0 D (g/g) = defensive investment (g defenses/ g biomass) H (g/d) = the maximum potential herbivore pressure (no defenses) k,a,m,b = constants g Thus, the term (1-kDa) is the percentage reduction in growth from reallocation of energy to defense. The term (H-mDD) is the reduction in realized growth due to herbivory. There are two inherent assumptions in this model, both of which may be unfounded when considering defenses within a single species. First, as species composition changes from low to high fertility areas, maximum growth rate is assumed to increase. Within a single species, however, this may not be true, or the increase in growth rate may be very small. The arctic lupine (Lupinus arcticus S. Wats) does not detectably increase its growth rate when fertilizer is added to the soil (Graham, 1994; Arii, 1996). Second, because the term that describes reduction in realized growth due to herbivory is subtracted from growth rate, the model assumes that a fixed amount of biomass is removed by herbivores. However, herbivores are unlikely to consume a fixed amount or proportion of plant biomass grown on different nutrient concentrations (Price, 1991; de Jong, 1995). Some fertilized herbaceous individuals are consumed more than unfertilized individuals of the same species in the Kluane boreal forest (John & Turkington, 1995, 1997). Thus, with a small or insignificant increase in G* (the maximum inherent growth rate), and a large increase in H (the maximum potential herbivore pressure) with increasing nutrient supply, in order to maximize realized growth rate (dC/dT), defensive investment should be increased with increasing soil fertility (Fig 2.). 9 Realized growth rate Defense investment Figure 2. Maximum realized growth rate at low and high nutrient supply (arrows indicate maxima), given that growth rate does not significantly increase with nutrient supply, and there is a large herbivory increase. Thus, the resource availability theory makes two predictions. First, the prediction made by Coley et al. (1985) that plants will invest more in defenses when growing in low nutrient soils. Second, if optimal foraging by herbivores is assumed, the modified Resource Availability theory predicts that plants will invest more in defenses when growing in high nutrient soils. 1.4 Physiological Theories Bryant etal. (1983), Coley (1983) and Tuomi et al. (1984) have proposed a number of physiological explanations for plant defenses. In these theories, defense is considered to be a fortuitous consequence of some larger metabolic reaction due to changes in environmental conditions. 10 Nutrient Stress The Nutrient Stress Hypothesis (NSH) was proposed by Tuomi et al. (1984) as a method by which plants could increase defensive levels after herbivore attack without the need for inducible defenses. They expanded on a suggestion made by Bryant etal. (1983) that plants using carbon-based defenses will increase their defensive load if carbon is in excess. Plants using nitrogen-based defenses, will decrease their defensive investment at high C:N ratios. Tuomi et al. (1984) theorized that after defoliation by a herbivore, plant nitrogen in leaves would be lost to the herbivore, creating a carbon excess and an increase in defensive chemical concentrations. This theory has several unresolved problems. First, logic dictates that if the leaves have been removed, and roots unaffected, there should be an excess of available nitrogen, not carbon. Second, the assumption that leaf nitrogen is the major source of available nutrients for metabolism and growth is incorrect (Chapin, 1980). Most inorganic nutrients and nitrogen are provided de-novo from the roots (Chapin, 1980). Finally, Tuomi et al. (1984) are assuming that the leaves remaining after an attack greatly increase their photosynthetic rate so as to provide surplus carbon. In heavily or completely defoliated plants, this could not occur, because most leaves are operating close to their maximal rates of photosynthesis already (Laetch and Fretdse, 1982). This theory, without proper physiological support is not useful, though it is the basis for several theories that purport to have predictive value. 11 Carbon: Nutrient Balance Theory Expanding on the work of Tuomi et al.(1984), Bryant et al. (1983,1987) proposed a modified Carbon:Nutrient balance theory. They assert that when a plant is defoliated, root hairs die, limiting the nitrogen intake of the plant. The plant is thus nitrogen limited, and can produce defenses with its excess carbon. Implicit with this theory are the assumptions that root damage will also cause increases in defenses, shading will cause decreases, and the effects will be more pronounced on nutrient poor soils where the plant is already somewhat nutrient limited. Bryant et al. (1983) and Jonasson et al. (1986) support this theory, reporting decreases in defenses with shading and fertilization in both green aspen and paper birch. Hunter and Schultz (1995) also reported that fertilization mitigated the effects of defoliation, and that insect herbivores preferred fertilized to unfertilized plants. Hjalten etal. (1994), however, found that herbivores preferred plants that had been previously attacked, implying a decrease in defense after attack. Baldwin et al. (1994) argues against the CNB theory using the higher levels of nitrogen based defenses in partially defoliated tobacco plants as evidence, invoking instead the Optimal Defense theory. Tuomi and Fagerstrom (1991) have responded to the criticism of the CNB theory that its predictions closely mirror those of Optimal Defense Theory by stating that the one defining feature of his theories from the ODT is the response to fertilization. They assert that fertilized plants, being given all the nutrients they need, should be healthier, more vigorous, and more able to 12 defend themselves when attacked. He assumes here that a healthier plant will be affected less by the costs associated with defensive investment. The CNB theory, however predicts a decrease in defensive investment with increased fertilization. In all cases, the CNB theory predicts a positive correlation between carbon: nutrient ratio and defensive investment. This is equivalent to a negative correlation between nitrogen concentration and defensive investment, an easily testable hypothesis. Reallocation and the Moving Target Bryant etal. (1987), while proposing modifications of the Carbon: Nutrient Balance theory also proposed a theory to account for increases in the quality of woody forage when grazed by moose. Several researchers (e.g. Machida, 1979) have found that when moose feed on woody plants, the remaining plant material increases its forage quality rather than decreasing as it does when grazed by insects or hares. Jonasson et al. (1986) asserted that the removal of whole twigs from the plant allows the resources from the entire root system to be concentrated into the few remaining branches, thus eliminating any carbon surplus and chemical defenses, while increasing available nitrogen in the leaves. This theory can be seen as a special case of the CNB. Alder and Karban (1994) theorized that plants may not actually have to "invest" in defense. A plant can avoid defense costs by simply changing ontogeny to one no less efficient, but that has better defense. In the moose 13 browsing example, the plant has shifted to a new form involving a higher root:shoot ratio. The remaining above ground biomass is not less efficient (per gram) than the original plant, but it has a higher nutrient uptake potential, and thus will be more vigorous and be more able to defend itself. A more plausible example is the reversion of browsed willow to a juvenile, highly defended form when it grows back (Bryant and Wieland, 1985). The reallocation theory is inconsistent with the Carbon: Nutrient Balance theory as proposed by Bryant et al. (1983). While it makes similar predictions to the optimal defense theory, it is not as amenable to testing, as "vigor" is a difficult quality to measure. Alder and Karban's (1994) theory is easy to test, by observing a major change in growth form. It does not, however, give any sort of mechanistic explanation or provide any predictive ability. 1.5 The Study Species and its Defense White spruce (Picea glauca) was chosen as a study species because it is a winter forage for hares in the boreal forest, and its defensive chemistry is known. Sinclair et al. (1988) reported that hares in feeding trials avoided camphor, a compound present in spruce trees. Alkaloids were not found to affect feeding preferences of hares. Camphor is present in greater concentration in naturally grown trees than in nursery grown trees (Rodgers et al., 1993). The feeding of spruce grouse is inversely related to camphor concentration (Mueller 1993). 14 Camphor (C1 0H1 6O) is an oxygenated monoterpene, one of a group of compounds composed primarily of carbon, hydrogen and oxygen, with little or no nitrogen. 1.6 Hypotheses The standard optimal defense hypothesis makes the following two predictions (Table 1): (1) When attacked, the plants will increase defensive investment in proportion to the severity of attack. Growth will decrease with increased defensive investment, as resources are channeled out of growth and into defense. (2) When fertilized, the plant will decrease its defensive investment, and divert nutrients into new growth. Thus, growth rates should increase, consistent with the classical Resource Availability arguments. The modified resource availability (p. 9) version of the optimal defense hypothesis makes the following two predictions. (1) When attacked, the plant will increase defensive investment and its growth will be reduced in proportion to the severity of attack, as in the standard optimal defense hypothesis. (2) When fertilized, the plant will increase defensive investment, and thus, decrease growth. 15 The carbon:nutrient balance theory makes the following three predictions. (1) When attacked, the plant will increase its defensive investment. Plant nitrogen concentration will decrease. (2) When fertilized, the plant will decrease its defensive investment and nitrogen concentration will increase. (3) At higher intensities of attack, the plant will increase its defensive investment, nitrogen concentrations will decrease, but fertilization will prevent any increase in defense investment. 16 Table 1. Predictions of the Standard and Modified Optimal Defense theory, and the Carbon: Nutrient Balance theory. Symbols represent the levels of Defense, Nitrogen concentration, and Growth, increase (+), decrease (-), and no change (0) in response to treatments, relative to controls. Optimal Defense Carbon Nutrient Stan Reso Availabilit dard urce y Theory Modified Resource Availability Theory Balar ice Herbivory Fertilization Camphor Growth Camphor Growth Camphor %N2 Natural - Contra Natural + - + + - - + Excluded1 - - + - + - + Excluded + + + 0 0 - - + + Artificial2 - + + + — Artificial + 0 0 Extreme3 - + + + + + ~ Extreme + 0 0 1. Herbivores Excluded is equivalent to periods of low herbivore numbers, or when absent. 2. Artificial Herbivory simulates the effects of a large population of herbivores. 3. Extreme Herbivory simulates the effects of a very large population of herbivores, or the effect of a herbivore on a small plant. 4. Growth predictions at Artificial and Extreme levels of Herbivory were not tested. 5. The Standard Resource Availability theory predicts that fertilized plants will invest less in defense than the unfertilized Artificial and Extreme Herbivory plants, but will invest more than controls. 6. The Modified Resource Availability theory predicts that fertilized plants will invest more in defense than the unfertilized Artificial and Extreme Herbivory plants. 2.0 Materials and Methods 2.1 The Study Area This study was part of the Kluane Boreal Forest Ecosystem Project, carried out near Kluane Lake, Yukon Territory. The study site (60° 5' N, 137° 5'W) is located at Km 1695 Alaska highway, 48 km north of Haines Junction. Kluane lake is located in the Shakwak Trench, a wide glacial valley in the southwest Yukon. The trench runs northwest-southeast, bounded on the west by the St. Elias mountains, and on the east by the Kluane hills. Elevation generally varies between 910m and 960 m across the study area, with a low of 860m at Kluane Lake (Douglas, 1974). The soil is comprised of various glacial tills, characterized as glacial aluvisoils. These soils are fast draining, and poor in nutrients. The thick layer of till overlays a bedrock of schists and low grade metamorphic shales. The water table is high (1-4 m below surface) and patchy, with distinct highs in early spring from snow melt and late summer/fall due to rising lake water levels. Permafrost is not found below the subalpine (2000m) (Anonymous, 1987). The climate is subarctic/semi-arid, characterized by short, cool summers, and long, cold winters. The mean air temperature at Kluane Lake in July is 12.6° C and -21.5° C in January. Haines Junction is frost free for an average of 21 days per year, but this can vary from 12 to 45 days. Mean annual precipitation at Kluane Lake is 223.9 mm (70% rain, 30% snow). The first snow fall can be as early as the beginning of September, and snow is often still on the ground in the middle of May (Webber, 1973). Figure 3. Map of Yukon Territory, Alaska, and British Columbia showing location of the study site (North America inset). 19 Three plant communities dominate the low altitude areas of the southwest Yukon. The most abundant is a canopy forest dominated by white spruce (Picea glauca Moench), with an understory of mixed shrubs and perennial herbaceous plants. A second type of canopy forest is dominated by trembling aspen {Populous tremuloidies Michx.) and balsam poplar (Populous balsamiferous L), with an understory of predominantly herbaceous plants. This community is generally found in wetter areas. The herbaceous plant community is composed mainly of five species: a grass (Festuca altaica Trin.), arctic lupine (Lupinus arcticus S. Wats), anemone (Anemone parviflora Michx.), bluebells (Mertensia paniculata (Ait.) G.Don), and yarrow (Achillea millefolium var. borealis L). The third community is dominated by various willow (Salix spp.) and birch species (Betula spp.); this community may be in dynamic equilibrium with the white spruce forest and represent an alternative stable state for the area. The dominant herbivore in the boreal forest is the snowshoe hare (Lepus americanus Erxleben). The hare population cycles in density from 63-125 per km^ with a period of eight-ten years. At the low point in the cycle, hares have little impact on the vegetation, but at the high, they consume significant portions of the available biomass. The most recent population high was in 1989-90. My studies were conducted during the summers of 1995 and 1996, during the increase phase of the hare population. 20 2.2 The Kluane Boreal Forest Ecosystem Project The aim of this project was to examine the linkages between the various components of the boreal forest ecosystem, using the ten year hare cycle as a , natural perturbation to the system. Both top-down and bottom-up hypotheses of vertebrate community dynamics were tested in a series of manipulative experiments over a ten year period. To test bottom-up control by plants on herbivores, food was added both in the form of rabbit chow, and by fertilizing the forest to increase available plant mass. Top-down control by predators on herbivores was tested by excluding predators (both ground and avian) from large areas of the forest. In addition, hares were excluded by fencing to examine their effects on the herbaceous community. The areas on which these long term manipulations had been applied were appropriate for testing both the effects of soil quality and herbivore attack on plant chemical defense. 2.3 Field Site As part of the Kluane Boreal Forest Ecosystem Project, undisturbed areas of the boreal forest near Kluane lake, Yukon Territory, Canada were fenced to exclude hares and fertilized in a 2 X 2 factorial design. Control (unfenced and unfertilized) and Fertilized Treatment blocks were 1 km2-Herbivore Exclosure and Herbivore Exclosure + Fertilization treatments were 4 ha. Fences were erected and ammonium nitrate fertilization was applied at a rate of 25g/m2 in May 1987. NPK fertilizer was used in May 1988 at a rate of 17.5 g N/m2, 5 g P/m2 2.5 g K/m2. Half of this rate was applied in 1989, and in 1991, and the full rate was applied in 1990, and in 1993. No fertilization was carried out in 1992, and ammonium nitrate was again applied in 1994 at 25g/m2. Fertilizer was applied aerially, and ground checked to ensure it was evenly spread. 2.4 The Species White Spruce (Picea glauca) grows ubiquitously across the southwest Yukon. It is a long-lived, slow growing, climax species that provides cover for a variety of animals. Spruce is a stress tolerating plant (sensu Grime (1977,1979)), and is predicted to heavily defend itself. During the highest densities of hares in the hare cycle, the needles and bark of standing trees and terminal shoots of small trees are eaten. Fallen spruce trees are readily consumed by hares. The yearly growth of spruce occurs from terminal buds which are formed one year and grow the next. A ring is left on each twig where the tree stops growing for the winter. It is thus easy to accurately delineate and sample the two or three year's previous growth using growth rings as markers. 2.5 Manipulations of Spruce Trees In addition to natural herbivory by hares on the four treatment grids, two levels of simulated herbivory were imposed on 100 2-2.5 m tall trees randomly selected within the Control and Fertilized treatment grids. The first level was 22 termed "Artificial Herbivory", and involved the removal of 10-15% of the trees' green biomass by clipping the terminal 1-2 years growth from each branch using yearly growth rings as references. This level of herbivory was designed to simulate an intense attack from a herbivore such as might be experienced at the peak in the hare cycle. The second level, "Extreme Herbivory" involved the removal of 80-90% of the green biomass (80-90% of each tree branch), including the apical meristem tissue. It was decided to remove parts of branches instead of removing needles because needle removal is time consuming, and difficult to accomplish without heavily damaging the wooden stem. Each tree was tagged, numbered, and its position noted for further sampling. 2.6 Sample Collection The distal 10-15 cm (the previous years growth) were cut from 100 randomly selected 2-3 m tall trees (medium size class) and the 200 simulated herbivory trees on each of the four treatment grids. Five or six branches were sampled from each tree, and care was taken to sample around each tree. Samples were frozen to -20UC in a freezer, packed with "cold blocks", and transported by air to University of British Columbia where they were kept frozen at -30° C until analyzed. Because some samples were frozen for up to six months before analysis, a test was carried out to determine if the camphor concentration changed after extended storage. Spruce material from the same sample was analyzed for camphor immediately upon return to UBC, and again six months later. Samples were collected in early May, June, July and August of 1995 and in late May and June of 1996. Twenty adult trees (6-10 m tall -Large tree class) and ten very young trees (0.5-1 m tall - Small tree class) were sampled as above on each treatment area. Ten medium and large trees were also selected on untreated areas of the boreal forest and sampled each month for 15 months beginning in May 1995. 2.7 Quantitative Analysis of Camphor Frozen samples were thawed for 4 hours to room temperature. Wet spruce material was chopped using a coffee grinder for 20-25 seconds, to fit through a 1.2 mm screen, weighed (approx. 6 - 6.5g) and placed in a 75 ml test tube. Wet samples were used instead of dry, because camphor will volatilize at the temperatures required to oven-dry samples, and because drying at room temperature may allow plant tissue to metabolize camphor. An L-bomeol internal standard (0.500 mg) was added to each sample. (The L-borneol standard was produced by dissolving 0.500 g of L-borneol in 100 ml of methylene chloride and adding 100 uL aliquots of the resulting mixture to each sample.) Samples were extracted for 72 hours with 25 ml of methanol and the test tubes capped with parafilm. The methanol was then decanted and the sample washed twice with 5 ml of methanol. Three and a half ml of the resulting 35 ml extract was blown dry with air for 48 hours, yielding a red/black resin. Aerator pumps were used to blow air through pipettes into the samples. Once the solvent was evaporated, the samples were left to stand for an additional 24 24 hours. This extra time was required to ensure that no water remained in the samples, as the cyanide column used in the gas chromatograph can easily be poisoned by water. The resin was extracted with 3 ml of 1:1 hexane:methylene chloride for 24 hours. The sample were then briefly heated with an air gun, the liquid layer decanted, and the remaining dark red resin was washed three times with 2 ml of methylene chloride. One ml of the resulting yellow/green liquid was then blown dry as above for 36 hours. The sample was dissolved in 250 uL of 1:1 hexane:methylene chloride and 1 uL was injected for gas chromatographic analysis. Quantitative analysis of camphor was carried out on a Hewlett-Packard 5880A Gas Chromatograph using a cyanide capillary column (30 m X 0.25 mm) and a flame ionization detector. Individual samples were injected at a 1:100 split, and temperature programmed at 100 °C for 20 minutes, rising to 240 °C over the following 20 minutes and holding at 240 °C for a further 30 minutes. Peak areas were determined using an HP chemstation integrator. Peak identities were confirmed by retention time comparison and co-injection with authentic material. Retention times were determined by injecting pure sample into the GC and recording the time from injection to exit into the detector. When a sample is run, the peak recorded at the same retention time of the pure material is assumed to be the same compound as the pure material. To check this, a small amount of the pure material is added to the sample and run again on the GC. If the peak that is assumed to represent the pure material increases in size, the identity of the peak is confirmed. 2 5 Excess chopped spruce from each sample was weighed wet, then dried and reweighed. The wet/dry ratio was used to calculate the theoretical dry mass for each sample that was extracted (because extractions were carried out on wet material). Camphor concentration was calculated using the L-borneol internal standard for both wet and dry weights. 2.8 Quantitative Analysis of Nitrogen Spruce samples were analyzed for total nitrogen content using the macro-Kjeldahl digestion method. Excess dried, ground samples from camphor analysis (0.5g) were digested on a Tecator block digestor at 400°C with a sulfuric acid, hydrogen peroxide, and selenium solution. Nitrogen content of digested samples was then determined colorimetrically on a Tecator auto analyzer. 2.9 Statistical Analysis The data was tested for both normality and equal variation between sample populations. Camphor and nitrogen concentrations of medium sized trees were compared by 2 -factor ANOVA, Bonferroni-Dunn control test and t-tests. Nitrogen concentrations were regressed on camphor concentrations. Water content was regressed on wet and dry camphor and nitrogen concentrations. Large tree and very small tree classes were compared among themselves by 2-factor ANOVA. 26 3.0 Results 3.1 Camphor Concentration Main Treatments Camphor concentrations differed greatly between treatment grids (Fig. 4; Table 2). Fertilized trees had significantly lower levels of camphor than unfertilized trees. Herbivory treatments significantly affected camphor concentrations. Trees on grids where hares had been excluded had significantly lower levels of camphor than controls. Trees exposed to Artificial Herbivory had a 70% decline in camphor levels within the same season, but camphor concentrations increased the following year to be significantly higher than trees exposed to natural levels of herbivory. Extreme herbivory trees had the lowest camphor levels both within the same year as the damage was imposed, and the following year (Table 3). Trees on Herbivore Exclusion + Fertilization areas had significantly lower levels of camphor than Fertilized trees (t-test; p=0.043). Artificial and Extreme Herbivory treatments the year after clipping did not have significantly different camphor concentrations compared to these treatments plus Fertilization (t-test; p=0.856 and p=0.784 respectively) Yearly Cycle Camphor levels varied significantly throughout the year (Tables 4 & 5), with a peak in December-January and a minimum in June-July. A dramatic decrease in camphor levels was observed to coincide with spring "green-up" of 27 the trees. The medium tree class (2-3m) displayed a qualitatively larger seasonal variability than the larger tree class (6-1 Om) (Fig. 5). Small tree October data were not included for analysis due to small sample size (n=3). Size Class The large size class trees (6-1 Om) were found to respond in a similar way to the medium size class (2-3m) on the main treatment grids (Fig. 6). Large trees contained significantly less camphor on Fertilized, Herbivore Excluded and Fertilized + Herbivore Exclusion grids (Table 6). The small tree class (0.5-1m) was not found to vary between main treatment grids (Table 7), maintaining a consistently high concentration of camphor (Fig. 6). 3.2 Nitrogen Concentrations Nitrogen concentrations of medium sized trees varied significantly in response to fertilization and herbivory (Table 8). Nitrogen levels increased by 40% in fertilized trees (t-test; p=5.0X10"6) compared to controls. Similar increases were observed in response to Simulated and Extreme levels of herbivory (t-test; p=3.2X10'4 and p=2.7X10"4 respectively). There was no detectable interaction effect on nitrogen concentrations between herbivory and fertilization (Table 8, Fig. 7). 28 3.3 Water Content Water content did not vary significantly with camphor or nitrogen concentrations. Water content did vary significantly during the yearly cycle (ANOVA; p=0.045), with a 5-8% increase during the summer months. This increase was not sufficient to account for camphor yearly variation. 29 Table 2. Summary of ANOVA for camphor concentrations on main treatment grids. Bold values are significant at p=0.05. Source dF SS F-ratio Probabil Fertilization 1 56.258 2.356 0.042 Herbivory 2 42.153 14.568 0.00005 Fertilization * Herbivory 2 2.369 0.978 0.068 Error 586 0.628 Table 3. Summary of Bonferri-Dunn test for variation of treatments from the control mean. Test conducted for camphor concentrations on main treatment grids (Control, Fertilized, Herbivore Exclusion and Fertilized and Herbivore Exclosure) and exposed to Artificial and Extreme simulated herbivory. Bold values are significant at p=0.05. Comparison of Control with: F-ratio Probability Fertilized 0.256 0.0214 Herbivore Exclosure 0.124 0.0397 Herbivore Exclosure + Fertilized 0.564 0.0184 Artificial Herbivory (same year) 0.987 0.0014 Extreme Herbivory (same year) 0.997 0.0011 Control (next year) 0.045 0.9581 Artificial Herbivory (next year) 0.547 0.0124 Artificial Herbivory + Fertilization (next year) 0.612 0.0139 Extreme Herbivory (next year) 0.864 0.0021 Extreme Herbivory + Fertilization (next year 0.754 0.0034 30 Table 4. Summary of ANOVA for yearly camphor concentrations of large (6-10 m tall) trees. Bold values are significant at p=0.05. Source dF SS F-ratio Probability Between 14 0.014 2.747 0.042 Within 135 0.024 Error 150 0.038 Table 5. Summary of ANOVA for yearly camphor concentrations of medium (6-10 m tall) trees. Bold values are significant at p=0.05. Source dF SS F-ratio Probability Between 14 0.042 2.839 0.037 Within 128 0.071 Error 143 0.113 Table 6. Summary of ANOVA for camphor concentrations of large (6-10 m tall) trees on main treatment grids (Control, Fertilized, Herbivore Exclusion and Fertilized and Herbivore Exclosure). Bold values are significant at p=0.05. Source dF SS F-ratio Probability Fertilization i 0.025 4.215 0.002 Herbivory 2 0.365 3.108 0.008 Fertilization * Herbivory 2 0.869 1.256 0.013 Error 75 1.056 31 Table 7. Summary of ANOVA for camphor concentrations of small (0.5-1 m tall) trees on main treatment grids (Control, Fertilized, Herbivore Exclusion and Fertilized and Herbivore Exclosure). Bold values are significant at p=0.05. Source dF SS F-ratio Probability Fertilization ' 1 ' 1.008 1.235 0.858 Herbivory 2 0.116 4.256 0.786 Fertilization * Herbivory 2 1.236 2.364 0.565 Error 35 2.568 Table 8. Summary of ANOVA for nitrogen concentrations on main treatment grids (Control, Fertilized, Herbivore Exclusion and Fertilized and Herbivore Exclosure) and exposed to Artificial and Extreme simulated herbivory. Bold values are significant at p=0.05. Source dF SS F-ratio Probability Fertilization 1 0.018 1.564 0.048 Herbivory 2 8.693 0.975 0.042 Fertilization * Herbivory 2 4.235 2.468 0.984 Error 75 8.987 32 Figure 4. Camphor concentrations (mean + SE) in medium size class (2-3 m tall) white spruce. Control consists of natural levels of herbivory on an unfertilized site in the boreal forest. "Same year" samples were collected before spring greenup the summer after simulated herbivory treatments were applied. "Next year" samples were collected immediately after greenup the summer after simulated herbivory treatments were applied. 33 Sampling Date Figure 5. Camphor concentrations (mean + SE) of 10 medium size class (2-3m tall), and large size class (6-1 Om tall) trees sampled monthly for 16 months. October 1995 data for the medium size class were excluded due to small samle size (n=3). 34 Control Fertilized Herbivore Herbivore Exclosure Exclosure + Fertilized Treatment Figure 6. Camphor concentrations (mean + SE) of medium • , large 1, and small • trees on main treatment grids. 35 Figure 7. Percent nitrogen (mean + SE) of dried white spruce samples. Control consisted of natural herbivory on unfertilized areas of the boreal forest. 36 Table 9. Predictions of the hypotheses of the Standard and Modified Optimal Defense theory, and the Carbon: Nutrient Balance theory; and experimental results. Symbols represent changes in the levels of Defense, Nitrogen concentration, and Growth, increase (+), decrease (-), and no change (0) in response to treatments, relative to controls. Opt ima l Defense Carbc n nt ;e Resul ts S tandard Resource Avai lab i l i ty Modi f ied Resource Avai lab i l i ty Nutr ie Balani Herbivory Fertilizatior C a m p h o r Growth C a m p h o Growth C a m p h o r % N C a m p h o r Growth % N N a t u r a l - C o n t r o l C o n t r o l N a t u r a l + - + + - - + - + + E x c l u d e d - - + - + - + - 0 0 E x c l u d e d + + + 0 0 + + + + Ar t i f i c i a l - + + + - + + Ar t i f i c i a l + + + 0 0 + + E x t r e m e - + + + + + - — + E x t r e m e + + + + + 0 0 — + 1. Herbivores Excluded is equivalent to periods of low herbivore numbers, or when they are absent. 2. Artificial Herbivory simulates the effects of a large population of herbivores. 3. Extreme Herbivory simulates the effects of a very large population of herbivores, or the effect of a herbivore on a small plant. 4. Growth predictions at Artificial and Extreme levels of Herbivory were not tested. 5. The Standard Resource Availability theory predicts that fertilized plants will invest less in defense than the unfertilized Artificial and Extreme Herbivory plants, but will invest more than controls. 6. The Modified Resource Availability theory predicts that fertilized plants will invest more in defense than the unfertilized Artificial and Extreme Herbivory plants. 37 4.0 Discussion The lack of significant change in the water content of spruce between treatment grids and the lack of correlation between camphor concentration and water content in individual trees indicates that changes in camphor concentration are not due to changes in water content. 4.1 Main Treatments Hypotheses The standard optimal defense hypothesis makes the following two predictions (Table 9): (1) When attacked, the plants will increase defensive investment in proportion to the severity of attack. Growth will decrease with increased defensive investment, as resources are channeled out of growth and into defense. Not Supported (2) When fertilized, the plant will decrease its defensive investment, and divert nutrients into new growth. Thus, growth rates should increase, consistent with the classical Resource Availability arguments. Supported 38 The modified resource availability (p. 9) version of the optimal defense hypothesis makes the following two predictions. (1) When attacked, the plant will increase defensive investment and its growth will be reduced in proportion to the severity of attack, as in the standard optimal defense hypothesis. Not Supported (2) When fertilized, the plant will increase defensive investment, and thus, decrease growth. Not Supported The carbon:nutrient balance theory makes the following three predictions. (1) When attacked, the plant will increase its defensive investment. Plant nitrogen concentration will decrease. Not Supported (2) When fertilized, the plant will decrease its defensive investment and nitrogen concentration will increase. Supported (3) At higher intensities of attack, the plant will increase its defensive investment, nitrogen concentrations will decrease, but fertilization will prevent any increase in defense investment. Not Supported 39 The results of these studies indicate that neither the Optimal Defense (OD) theory nor the Carbon: Nutrient Balance (CNB) theory accurately predict spruce defensive investment. The Optimal Defense theory, and a modified Carbon: Nutrient Balance theory together, predicts defensive investment better than either theory alone, and is applicable to other studies in this field. Standard Optimal Defense Theory The standard Optimal Defense theory predicted decreases in camphor concentration due to herbivore exclusion and fertilization, and camphor increases due to artificial herbivory. It, however, failed to predict the dramatic decreases in camphor concentration within the same growing year as artificial herbivory, and in response to extreme levels of herbivory. This theory accurately predicted an increase in growth rate due to fertilization, but predicted an increase in spruce growth with herbivore exclusion that was not observed (Fig. 7). It is arguable that extreme defoliation is an event that rarely occurs to spruce trees, thus a non-optimal response is expected. Small trees, however, are sometimes observed to be severely defoliated, even to the extreme level applied in this experiment. The lack of significant growth rate increase with herbivore exclosure may be an indication that the cost-benefits analysis of the OD theory is wrong, that trees are not alternating resources between growth and defense. Alternatively, the predicted change in growth rates may be too small to detect. The average concentration of camphor in untreated white 4 0 spruce is 0.15% of dry weight. If one (arbitrary) growth unit is assumed to equal one unit of defense, then a decrease from 0.36% to 0. 32% camphor (dry weight) would cause an increase in growth of 0.04%, well below the detection limit of the growth measurements. The decrease in camphor concentration within the same year as the artificial herbivory treatment, is not predictable using this theory. Modified Optimal Defense Theory The predictions made by the modified OD theory require changing the assumptions of the standard OD theory. It is assumed that when plants are fertilized, herbivores will attack these plants preferentially over unfertilized plants. Thus, fertilized plants were predicted to defend themselves more than unfertilized plants. Nutrients channeled away from growth and into defense would cause a reduction in growth when the plant is fertilized. The decrease in camphor and increase in spruce growth on fertilized grids did not support the modified OD theory. The assumptions made to generate the predictions of this theory may not have been justified. Hares may not attack spruce trees on more fertile soils differentially. Alternatively, it may be advantageous to a tree to allow itself to be attacked as it is more than making up for its lost tissue in new growth. Spruce may not be a good model species for this theory, because once it has reached a size escape, it is in little danger of being entirely consumed by hares, regardless of site fertility and thus, its value as forage. 4 1 Carbon: Nutrient Balance Theory The CNB theory, like the standard OD theory, accurately predicted the decrease in camphor concentrations in response to herbivore exclusion and fertilization and the increase in camphor with artificial herbivory. However, it failed to predict the dramatic drop in camphor concentrations with extreme herbivory, and during the same year as artificial herbivory. Unlike the standard OD theory, the CNB theory makes predictions about nitrogen concentration in spruce instead of growth rates. The CNB theory accurately predicted an increase in nitrogen concentrations with fertilization, but did not predict the lack of response when herbivores were excluded or the increase in nitrogen concentrations at the levels of artificial and extreme herbivory (Fig. 7). The CNB theory is not supported due to these inconsistencies. The carbon.nutrient balance theory as proposed by Bryant et al. (1983) has an obvious flaw that limits its usefulness. By examining this flaw, and correcting it, the results of this experiment can be more clearly interpreted than with Bryant's et al. (1983) version of the CNB. Bryant et al. (1983) proposed that when nitrogen in green photosynthetic tissue is lost to herbivores, the plant's nitrogen supply is reduced. Bryant ef al. (1987) modified this theory, stating that fine rootlets of the plant die disproportionately to the amount of green tissue removed, thus reducing the nitrogen available to the plant. Reduced nitrogen supply increases the carbon : nutrient ratio, and the surplus carbon is used for the production of defensive compounds. 42 Since nitrogen used for growth and metabolism is largely drawn from the roots, not the leaves (Crowler and Ghres, 1992), and disproportionate fine rootlet mortality seems unlikely, the CNB theory appears intractable. In addition, regulatory mechanisms in plants generally limit the uptake of either carbon or nutrients in excess. Leaves rarely photosynthesize at their maximum rate, and are often able to increase the rate of carbon assimilation to maintain a constant C:N ratio when defoliation occurs (Huntly, 1991). Roots, likewise, can vary their uptake rates such that nitrogen is supplied at a constant rate (Glass and Bilsner, 1995). Limiting Resource Theory Due to the poor predictive ability and the logical flaws inherent in the CNB, I propose a new theory, the Limiting Resource Theory (LR). I propose that removal of green biomass, if it has any effect on the carbon : nutrient ratio at all, will decrease the supply rate of carbon, not nitrogen. Thus, this modified CNB theory predicts that when a plant is attacked, the concentration of carbon-based defenses will go down. When fertilized, defensive investment will, likewise, decrease (Fig. 10). Despite the LR theory's intuitive appeal, it does not accurately predict the effect of herbivore removal on camphor concentration. When a herbivore removes green tissue, it should reduce the carbon:nutrient ratio, thus reducing carbon-based defensive investment. The response to fertilization, however, is consistent with the LR theory. At artificial and extreme levels of herbivory, the 43 LR theory also predicts a decrease in defenses, and an increase in nitrogen concentrations. This was supported by the data, except for the camphor concentrations of artificial herbivory trees the year after clipping. The LR theory, however, predicts the large decrease in camphor concentrations during the same year as artificial herbivory. Thus, the LR theory is consistent with the responses of spruce camphor and nitrogen concentrations with respect to fertilization, and artificial and extreme herbivory, except camphor concentrations the year after artificial herbivory. Table 10. The predictions made by the Limiting Resource Theory, at Natural, Excluded, Artificial and Extreme levels of simulated herbivory, and with and without fertilization. Herbivory Fertilization Camphor %N Natural - Control Natural + - + Excluded - - 0 Excluded + + Artificial - + + Artificial + + + Extreme - — + Extreme + — + 4 4 Integration of OD and LR Theories The standard Optimal Defense (OD) theory accurately predicts the response of spruce camphor concentrations to natural and artificial herbivory, and to fertilization. The Limiting Resource (LR) theory accurately predicts camphor and nitrogen concentrations in response to fertilization, for extreme herbivory, and within the same year for artificial herbivory. These theories do not make conflicting predictions concerning fertilization at the natural herbivory treatment level. The results, therefore, suggest that the OD and LR theories make predictions about different aspects in the defense of white spruce. The OD theory predicts responses to herbivory, while the LR theory predicts responses to fertilization, and higher levels of herbivory. Thus, two mechanisms may control camphor production in the plant: a herbivory mediated inducible pathway, and production dependent on availability of excess (free) carbon. A hypothetical description of this bi-mechanistic theory follows: When herbivores are excluded, the inducible pathway "shuts off", and camphor production decreases. Even though green tissue is not being removed, the increase in carbon is not enough to change camphor concentrations. When trees are fertilized, the increase in nitrogen concentration decreases the amount of free carbon, and camphor production decreases. When herbivores are removed and the trees are fertilized, camphor production decreases additively. Artificial herbivory causes a decrease in free carbon (and increase in nitrogen concentration) and, therefore in defense within the same year. When the tree 45 starts growing the next year, the camphor production pathway is induced, and camphor concentrations increase. Extreme herbivory causes a dramatic decrease in free carbon, thus decreasing camphor production within the same year. The year following clipping, the continuing lack of free carbon does not allow the induced pathway to increase the camphor concentrations. Nitrogen concentrations remain high. Support For Multiple Pathways in The Literature Many studies have shown that defensive investment cannot be predicted by any one set of simple rules. The CNB and elements of the OD theory are both supported and refuted in the literature. Bryant et al. (1987a,b), Reichardt etal. (1990b) and Hunter (1995) have shown that herbivory increases defenses, while fertilization decreases defenses and mitigates the influence of herbivore damage, thus supporting the CNB. de Jong (1995) discovered that defense was inversely correlated to growth rate, supporting the OD theory, but not supporting the OD resource availability model (Coley et al., 1985). Mihaliak and Lincoln (1989), likewise, reported evidence supporting an OD defense allocation pattern, but that did not support the resource availability model. Some studies have reported evidence for multiple defense responses and thus multiple control pathways in plants, van der Meijden etal. (1988) discovered that plants responded independently to herbivory and fertilization, thus refuting the CNB and the resource availability model. Hjalten et al. (1994) also reported defoliation, nutrient supply and the plant's history of both were independently 4 6 influential in defensive investment. Karban and Niiho (1995) and Baldwin etal. (1990) reported that defensive chemicals were induced by hormone changes in the plant when attacked. Response to fertilization in these studies, however, seemed to be mediated by some other mechanism. Wainhouse and Ashburner (1996) discovered that lignin defenses in sitka spruce were influenced both by environmental factors and by the trees' genetics. Problems With The OD/LR Theory Despite the close fit of the OD and LR theories to the experimental data, several questions remain. First, the LR theory predicts a reduction in defensive investment when the plant is fertilized. However, no significant reduction in defense is observed at the artificial and extreme levels of herbivory when the trees were fertilized. At the artificial herbivory level, the inducible (OD) response may be more powerful than the LR response. The high level of variability between trees may have also masked any response to fertilizer. The second question deals with nitrogen concentrations at artificial and extreme herbivory. The LR predicts further increases in %N at higher levels of herbivory, and on fertilization treatments. As the amount of green tissue removed increases, the carbon supply decreases, and the nitrogen concentration in the plant should increase. No nitrogen concentrations of simulated or extreme herbivory treatments are higher than the nitrogen concentrations of main treatment fertilized plots. This level of %N may simply represent a maximum nitrogen content possible in the plant. Beyond a certain 4 7 concentration, negative feedback mechanisms often reduce nitrogen uptake rates, and so limit overall plant nitrogen content (Glass and Bilsner, 1995). 4.2 Large And Small Tree Classes, And The Yearly Cycle Large Tree Class (6-1 Om) Defense levels in large and medium trees were not different as predicted by the optimal defense theory. This theory states that large trees that have reached a size escape from hares, will reduce defenses, as they are not needed. Herbivore pressure may still, therefore, be an important influence on large spruce trees, or spruce relative defense levels are set constitutively and may be non-optimal. Large trees should have reached a size escape from hares, thus the Optimal Defense theory predicts that they should not defend anymore. Alternatively, the large trees may have adated to defend themselves from large extinct herbivores such as mastadons. This hypothesis is, however, untestable. The similar response of large and medium trees suggests that the same mechanisms may be at work. However, without treatments of simulated herbivory in the large tree class, as in the medium tree class, neither the OD nor the CNB theory can be supported preferentially, because these theories make the same predictions in response to herbivore removal and fertilization. Small Tree Class (0.5-1 m) The high levels of defense in small trees is predicted by the OD theory. As smaller trees have not reached a size escape, they should defend themselves more than larger trees. The lack of response to herbivore removal 4 8 or fertilization by the small trees may indicate that defense levels are set constitutively when the plant is young. Yearly Cycle The pronounced yearly cycle is consistent with the OD prediction that plants should increase defense when attack is most frequent. Herbivore pressure was not experimentally varied over the course of the year, thus the OD cannot be tested. The May 1995 measurement was made before spring green-up, while the May 1996 measurement was made immediately after spring green-up. This may explain the differences between the two measurements. Spring green-up coincides with a dramatic growth burst in white spruce. This growth burst may cause the yearly camphor concentration cycle. Growth rate is highest in summer, thus camphor production may be reduced by diverting resources to growth. Alternatively, camphor may be "diluted" by rapid growth during the summer. This would require camphor production rate to remain relatively constant and independent of growth rate. The LR theory predicts that with limiting nitrogen, defensive investment should increase. Nitrogen may be limiting during the winter, when biologically mediated nitrification and mineralization rates are slowest. The extremely high concentrations of camphor during the winter months, double those observed during the summer, suggest that there is some other mechanism at work in this situation. The larger seasonal change observed in the 2-3m tree class over the 6-10m tree class is consistent with OD predictions that plants that have not achieved size escape should defend more than those that have reached size 4 9 escape. Alternatively, smaller trees may have larger shifts in growth rate from summer to winter, or may be more physiological responsive to environmental conditions in some other way. This experiment, unfortunately, cannot determine which of these possibilities is the mechanism of seasonal camphor concentration cycling. 4.3 Limitations of this study Several studies have found that responses to herbivory damage were observed only in tissues that had been directly attacked. Branches or twigs that are attacked may undergo changes in ontogeny and defense, while neighboring branches or twigs on the same tree do not (Alder and Karban, 1994; Obesco and Grubb, 1994; Bryant and Weiland, 1985). This response may be mediated by hormones (Baldwin etal., 1994; Hjalten etal., 1994; Karban and Niiho, 1995). In my study, random branches on main treatment grids were sampled, with no knowledge of whether the tree or that specific branch had been previously attacked or not. This may have diluted the actual effects of herbivory. Branches that had been attacked may have defended themselves, while unattacked branches may not have defended themselves. If I sampled both of these branches on a natural herbivory treatment area, I would conclude that the defense response was the average of the previously attacked and unattacked branches, which was lower than the actual response of attacked branches. Simulated herbivory trees were sampled on damaged branches, however, as all branches were clipped. 50 This study, unfortunately cannot differentiate between the CNB (LR) and the OD (resource limitation hypothesis) with respect to fertilization effects under conditions of natural herbivory. The increase in nitrogen content of fertilized trees is suggestive, but does not conclusively support the LR theory. The increase in growth rates of fertilized trees (C.J. Krebs, unpublished data), suggests that the Limiting Resource theory is predicting defensive investment. There is, at this time, no good test to discriminate between these two theories. Figure 8. Growth (mean + SE) of white spruce on treatment areas in the boreal forest. Growth was measured as a ratio of current year (1990-95) growth to growth in 1989. Data from C.J. Krebs (unpublished). 52 5.0 Conclusions Neither the Optimal Defense theory nor the Carbon: Nutrient Balance theory were found to accurately predict changes in camphor and nitrogen concentrations of white spruce in response to herbivory and fertilization. At natural levels of herbivory, both theories predicted equally well, but neither accurately predicted defense responses at higher levels of herbivory. Small tree camphor concentrations on the treatment areas supported the Optimal Defense model, while large tree camphor concentrations did not A modified version of the Carbon: Nutrient Balance theory is proposed. This is called the Limiting Resource theory and was proposed after examining and changing some of the assumptions in the Carbon: Nutrient Balance theory. In conjunction with the Optimal Defense Theory, the Limiting Resource theory accurately predicts the camphor concentrations observed. This suggests that there are two separate mechanisms controlling defense investment in spruce, one in response to herbivory pressure and another in response to soil fertility levels. Other studies have reported evidence that supports the hypothesis, though similar multiple-mechanism hypotheses of defensive investment have not been proposed. This study is important for examining both evolutionary ideas and plant/ herbivore interactions. It has provided insight into patterns of defense investment of spruce in its natural setting and proposed mechanisms of defense control which may provide the basis of future physiological research. 53 Appendix: Experiments with Lupines Study Species Arctic lupine (Lupinus arcticus) is a nitrogen fixing perennial herbaceous plant, common in the white spruce forest understory of the boreal forest. Lupines contain several alkaloids that are toxic to vertebrates (Stefan et al., 1988; Barboni etal., 1994), yet hares consume the leaves and stems. Kinghorn et al. (1980) discovered that the most common alkaloid found in a variety of North American lupines is Spartein. Humans have been poisoned by consuming lupine seeds (Keeler and Panter, 1989), and lupines have been shown to cause crooked-calf disease among domestic cattle (Keeler, 1972; Keeler et al., 1976; Quinton, 1984). Alkaloids are nitrogen based compounds, found as defensive chemicals in a variety of plants. Because, alkaloids are nitrogen-based, the Carbon: Nutrient Balance theory predicts opposite changes from carbon based defenses when plants are fertilized. The Standard and Modified Optimal Defense models remain unchanged (Table 10). Spartein is a metabolic toxin, and the precursor to the highly toxic N-spartein, Lupinine, and cadaverine (Saito et al., 1989). 54 Table 11. Predictions of the Standard and Modified Optimal Defense theories, and the Carbon: Nutrient Balance theory. Symbols represent changes in the levels of the Defense (spartein), Nitrogen concentration, and Growth, increase (+), decrease (-), and no change (0) in response to treatments, relative to controls. Optimal Defense Carbon Nutrient Balance Stan Resc Availabilil dard urce y Theory Modified Resource Availability Theory Herbivory Fertilization Spartein Growth Spartein Growth Spartein %N2 Natural - Contra Natural + - + + - + + Excluded1 - - + - + - + Excluded + + + 0 0 0 Artificial2 - + 4 + + -Artificial + ++ 0 1. Herbivores Excluded is equivalent to periods of low herbivore numbers, or when they are absent. 2. Artificial Herbivory simulates the effects of a large population of herbivores. 3. Extreme Herbivory simulates the effects of a very large population of herbivores, or the effect of a herbivore on a small plant. 4. Growth predictions at Artificial and Extreme levels of Herbivory were not tested. 5. The Standard Resource Availability theory predicts that fertilized plants will invest less in defense than the unfertilized Artificial and Extreme Herbivory plants, but will invest more than controls. 6. The Modified Resource Availability theory predicts that fertilized plants will invest more in defense than the unfertilized Artificial and Extreme Herbivory plants. 55 Field Site This study was conducted in the same area as the studies done with spruce. One square meter plots were fertilized, fenced and clipped in a 2 X 2 X 2 factorial design. Fences were erected, clipping performed and 35-10-5 NPK fertilizer was added in June 1991. In 1992-95, areas remained fenced, clipping was carried out and fertilizer was added at double the 1991 rate. Sampling The leaves and stems of lupines were collected for analysis on June 15, 20, and 25, 1996 from control, fertilized, and fenced and clipped plots, in a 2 X 3 factorial design [ + fertilization X three levels of herbivory: none (inside a fenced area), natural (unfenced) and artificial (clipped)]. Lupines from a large, untreated common patch were also collected every two hours for 48 hours. Two methods were used to fix samples before transport to the University of British Columbia for analysis. The first method involved drying samples in the sun immediately after sampling. The second method involved fixing samples with ethanol. Wet samples (8-1 Og) were weighed, homogenized in a blender with 35 ml of ethanol for 2 minutes, and stored in silex tubes. Extraction of Spartein Samples air-dried in the field were weighed and immersed in 150 ml of water. Ethanol-fixed samples were air-dried for two days, weighed, and immersed in 150 ml of water. After 24 hours, the water was decanted, and the sample washed twice with 10 ml of water. The water was then allowed to evaporate for four days. The resulting gray precipitate was dissolved in 10 ml 56 of water and made basic with 5 ml of 20% ammonium hydroxide. This solution was extracted twice with 50 ml portions of dichloroethane, dried over sodium sulphate, filtered through ashless paper, and evaporated for 48 hours. The resulting white precipitate was dissolved in 1 ml of dichloromethane, of which 0.1 ml was injected for gas chromatographic analysis. Quantitative analysis of spartein was conducted on a Hewlett Packard 5880A Gas Chromatograph using a cyanide capillary column (30 m X 0.25 mm and a flame ionization detector. Individual samples were injected at a 1:100 split, and temperature programmed at 140°C for 35 minutes, then rising and holding at 240° C for 20 minutes. Peak areas were determined using an HP chemstation integrator. Peak identities were confirmed by retention time comparison and co-injection with authentic material. Standards were produced by the sample-addition method. Three different amounts of spartein were added to authentic samples and processed as above. Losses were assumed to be equivalent in both standard and experimental samples. Results No significant differences in spartein or nitrogen concentrations of lupines were detected between treatments (Table 8, 9). A significant daily cycle was observed, with a maximum at 6 am and a minimum at 2 pm (Fig. 8). 57 Table 12. Summary of ANOVA for spartein concentrations of lupines. Source dF SS F-ratio Probability Fertilization 1 67542.56 0.987 0.432 Herbivory 2 4785.34 1.345 0.786 Error 33 29875.43 Table 13. Summary of ANOVA for nitrogen concentrations of lupines. Source dF SS F-ratio Probability Fertilization 1 567.34 4.528 0.987 Herbivory 2 47.897 6.784 0.743 Error 33 345.86 58 Discussion The ability of lupines to fix nitrogen may account for the lack of nitrogen response to treatments. In turn, lack of nitrogen variability confounds the Carbon: Nutrient Balance theory, and changes its predictions to no response to either herbivory or fertilization. Lack of optimal defense by lupine suggests that its defenses may by set constitutively, and are not inducible in response to environmental variation. Alternatively, this may be a case where the cost of defense production is so low, that there is no evolutionary pressure to produce an optimal pattern of defensive investment. The daily cycle observed is consistent but displays a longer minimum phase than those found by other researchers (Keller, 1986; Keller and Patell, 1991; Saito, 1993). These researchers hypothesized that the defensive alkaloids were nitrogen storage compounds. 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