Herbivore-induced plant defences regulated by the phytohormones jasmonic acid (JA) and salicylic acid (SA) are predicted to influence herbivore population dynamics, in part because they can operate in a density-dependent manner. While there is ample evidence that herbivore-induced plant responses affect individual performance and growth of herbivores, whether they scale-up to regulate herbivore population dynamics is still unclear.
We evaluated the consequences of variation in plant defences and herbivore density on herbivore development, reproduction and density-dependent population growth. We investigated potential mechanisms affecting the strength of herbivore density-dependent processes by manipulating jasmonate expression, quantifying plant defensive traits (phytohormones JA and SA and serine proteinase inhibitors) and adding aphids (Macrosiphum euphorbiae) at different densities to plants to simulate different initial population density and herbivore load. We manipulated jasmonate defences by using genetically modified lines of tomato plants (Solanum lycopersicum) with elevated or suppressed jasmonate-dependent defences. Jasmonate-insensitive plants cannot induce the defences regulated by the JA pathway, while jasmonate-overexpressing plants constitutively express jasmonate-dependent defences.
We found that jasmonate defences provided resistance against aphids and influenced density-dependent processes. Jasmonate-overexpressing plants reduced aphid reproduction, prolonged developmental time, dampened aphid populations across all aphid densities and caused density-independent aphid population growth. Jasmonate-overexpressing plants showed high JA-dependent constitutive levels of resistance and were unable to activate the SA pathway in response to aphid feeding. In contrast, jasmonate-insensitive plants increased aphid reproduction, shortened developmental time, reduced population growth only at high initial densities and promoted strong negative density-dependent population growth. Aphid feeding on jasmonate-insensitive plants did not induce jasmonate-dependent defences, but induced the SA pathway in a density-dependent manner, which resulted in negative density-dependent aphid population growth.
Aphid feeding on jasmonate-insensitive and jasmonate-overexpressing plants differentially activated the salicylate pathway, revealing a negative crosstalk between the defensive phytohormones JA and SA. By muting or enhancing jasmonate-mediated responses and quantifying SA phytohormone induction, we demonstrated that plant defences are a key factor driving not only the performance, but also the density dependence processes and population growth of herbivores.

1 INTRODUCTION

While density-dependent population growth is the core of many ecological theories explaining the abundance and distribution of animal populations, there is still much debate on how herbivore populations are regulated (Harrison & Cappuccino, 1995; Haukioja & Hakala, 1975; Underwood, 2009). Detecting density dependence in herbivore populations can be difficult due to the many factors that limit population growth in a density-dependent manner, including natural enemies, disease, competition and plant nutritional and defensive traits. Density-dependent population growth is particularly important for pest species, such as aphids (Alyokhin, Drummond, & Sewell, 2005; Myers et al., 2005), as the short developmental time and clonal reproduction can lead to exponential population growth (Agrawal, Underwood, & Stinchcombe, 2004; Myers et al., 2005). Therefore, recognizing the factors that drive the strength of density-dependent population growth is crucial for understanding both population dynamics and effective pest management of herbivores (Bommarco, Wetterlind, & Sigvald, 2007; Hassell, Latto, & May, 1989).

There has been great interest in the consequences of plant quality, as determined by plant nutritional and defensive traits, on the strength of density-dependent processes of insect herbivore populations (Haukioja & Hakala, 1975; Helms & Hunter, 2005; Underwood & Rausher, 2000; Ylioja, Roininen, Ayres, Rousi, & Price, 1999). Plant nutritional quality, for instance, may decrease as intraspecific competition between aphids intensifies (Denno, McClure, & Ott, 1995). Resource limitation may cause aphid performance and population growth to rapidly decline, triggering the production of winged morphs (Müller, Williams, & Hardie, 2001) and potentially strengthening density-dependent population growth. It is also broadly recognized that plants change their defensive phenotype upon herbivore damage (Karban & Baldwin, 1997). Aphid feeding, for instance, can trigger the induction of the phytohormones jasmonic acid (hereafter JA) and salicylic acid (hereafter SA); both of which can induce defences that negatively affect aphids (Inbar et al., 1998; Thaler, Fidantsef, Duffey, & Bostock, 1999; Walling, 2000) and thus may be linked to variation in the strength of density dependence. The induction of JA and SA is the core of plant responses to herbivores (Kessler & Baldwin, 2002; Thaler, Humphrey, & Whiteman, 2012). Interplay between phytohormonal pathways may be beneficial to plants if they synergistically increase plant's ability to reduce damage, or detrimental when negative signalling crosstalk occurs, leading to susceptibility to subsequent attack. The study of density dependence population growth of herbivores can be challenging because feedbacks between herbivore density and plant defences occur. Although herbivore-induced plant responses can be dependent on the amount of damage imposed by herbivores, we still lack a mechanistic understanding for how plant defences interact and influence herbivore population dynamics.

Here, we controlled our analyses for resource limitation, so that we could investigate how plant defences contribute to aphid performance and population growth processes without the potential confounding effect of resource availability. Quantifying resource limitation in aphid–plant systems can be challenging, and to overcome this barrier, we used the density of winged morphs as an estimative of resource deterioration. Crowding intensifies resource competition, reducing food availability and triggering wing formation in aphids (Müller et al., 2001). Although plant resistance levels may increase the proportion of winged aphids, in our study jasmonate expression manipulation did not affect aphid wing formation (F_2,215 = 0.572, p = 0.565). Therefore, the number of winged morph aphids can be a strong proxy for resource deterioration in this study. By including resource limitation in our models, we were able to test the effects of plant defences without the influence of resource depletion. We took an experimental approach by conducting herbivore density manipulations, using a model plant in which resistance has been genetically altered to elevate or suppress jasmonate plant defences. Jasmonate-dependent defences regulate several resistance traits, including trichomes, toxins and digestibility reducers (Duffey & Stout, 1996). We used three genetically modified tomato lines that vary in the expression of JA pathway: (a) jasmonate-insensitive—a mutant tomato line (cv. Jai-1; Li, Li, Lee, & Howe, 2002) that does not perceive JA and hence does not induce its defences, conferring low resistance to aphids (Kersch-Becker, Kessler, & Thaler, 2017; Kersch-Becker & Thaler, 2015), (b) wild type—(cv. Castlemart), which can induce JA upon damage and (c) jasmonate-overexpressor—a transgenic line that overexpresses prosystemin, a component in the JA pathway (cv. Prosystemin; McGurl, Orozco-Cardenas, Pearce, & Ryan, 1994), and therefore has constitutively high levels of JA-dependent defences conferring high resistance to aphids (Kersch-Becker et al., 2017; Kersch-Becker & Thaler, 2015). We evaluated the effects of jasmonate-mediated defences on the performance of the potato aphid, Macrosiphum euphorbiae, in terms of fecundity, developmental time and amount of feeding (honeydew production).

We investigated potential mechanisms affecting the strength of herbivore density-dependent processes by manipulating jasmonate expression and quantifying plant defensive traits (phytohormones JA and SA). We also measured serine protease inhibitor (SPIs) activity as a jasmonate-dependent defence marker to demonstrate the differences in constitutive levels of jasmonate defences. Because aphids feed on protein-poor diet (phloem sap) and receive essential amino acids from gut symbionts (Douglas, 2003), they may be insensitive to protease inhibitors (PIs). Nevertheless, studies have shown that PIs are detected in both leaves and phloem sap (Rahbe et al., 2003), suggesting some PIs, including SPIs, may play a role in plant resistance against aphids (Losvik, Beste, Stephens, & Jonsson, 2018; Rahbe et al., 2003).

We hypothesized that jasmonate and salicylate defences independently or jointly mediate the strength of aphid density dependence processes. If jasmonate-based defences are the mechanism by which aphid populations are regulated, then we expect jasmonate-overexpressing plants to suppress aphid populations across all densities, promoting weak density dependence (Hypothesis A, Figure 1). We hypothesized weak density-dependent population growth on jasmonate-overexpressing plants because these plants show high constitutive levels of resistance, but low inducibility. In contrast, jasmonate-insensitive plants have negligible levels of both constitutive and herbivore-induced jasmonate defences; thus, we expect high, but similar population growth across all densities and density-independent population growth may occur. On the wild type, inducible plants, we expect defences to increase with increasing aphid density, promoting density-dependent population growth. However, we expect salicylate defences to regulate aphid density dependence particularly on the plants that do not induce the jasmonate pathway. Through signal conflict (crosstalk) with JA, SA and JA can constrain the induction of each other (Thaler et al., 2012). We expect jasmonate-insensitive plants to compensate for the lack of JA by inducing higher amounts of SA, promoting low population growth at higher aphid densities and causing strong negative density-dependent population growth (Hypothesis B, Figure 1). These plants induce high amounts of methyl salicylate (Kersch-Becker et al., 2017), a compound expressed in response to SA production.

Details are in the caption following the image — **Figure 1**
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Different mechanisms on how plant defences can affect herbivore population growth. (a) Hypothesis A: jasmonate-mediated defences affect aphid population growth. We expect jasmonate-overexpressing plants, which show high levels of constitutive resistance and low inducibility, to suppress aphid population growth across all densities, promoting weak density-dependent or density-independent population growth. In contrast, jasmonate-insensitive plants have negligible constitutive and induced levels of jasmonate defences; thus, we expect high, but similar population growth across all densities and density-independent population growth may occur. On the wild type, inducible plants, we expect defences to increase with increasing aphid density and promoting density-dependent population growth. (b) Hypothesis B: salicylate defences regulate aphid population growth particularly on the plants that do not induce the jasmonate pathway. Through signal conflict (crosstalk) with jasmonic acid, we expect jasmonate-insensitive plants to compensate for the lack of jasmonic acid-based defences by inducing higher amounts of salicylic acid, promoting strong negative density-dependent population growth. Jasmonate-overexpressing plants may not induce salicylate defences because of its high levels of jasmonate-mediated defences

2 MATERIALS AND METHODS

We germinated tomato plants (Solanum lycopersicum L.) in the laboratory, transplanted them to 10-cm pots in a greenhouse and grew them for 4 weeks (four-leaf stage). We grew the plants in commercial potting soil, watered them daily and supplemented the plants with 85 g of fertilizer per week (Jack's professional^® water-soluble fertilizer 21:5:20 N:P:K). Individual aphids came from a laboratory colony of aphids, M. euphorbiae (Thomas, 1878) (Hemiptera: Aphididae) (WU-11-FR clone, Goggin, Williamson, & Ullman, 2001), that were reared on tomato plants (cv. Castlemart) in growth chambers (22°C, 16:8, L:D photoperiod). We used three genetically modified tomato lines that vary in the expression of JA pathway: (a) jasmonate-insensitive—a mutant tomato line (cv. Jai-1) that does not induce JA-dependent defences, (b) wild type—(cv. Castlemart), jasmonate-induced resistance not impaired and (c) jasmonate-overexpressor—a transgenic line that overexpresses prosystemin, a component in the JA pathway (cv. Prosystemin), and therefore, the JA-mediated defences are constitutively induced. The jasmonate-insensitive and jasmonate-overexpressor mutant lines are in the same genetic background as the wild type.

2.1 Effects of jasmonate expression on aphid performance

To test whether jasmonate plant defences affect aphid performance, we measured aphid fecundity and developmental time on the different plant lines (jasmonate-insensitive, wild type and jasmonate-overexpressor). To measure aphid fecundity, we placed two aphid nymphs on the second and third leaf of each plant and enclosed them with a translucent spun polyester sleeve. For trials 1–3, we used 4th instar aphids and standardized their age by following several 1-day-old cohorts and added aphids to plants as they moulted into the 4th instar. For trials 4–5, we transferred and enclosed a single 1-day-old aphid to plants. We checked aphids every 5 days, removing and counting the nymphs produced until aphid death. We carried out five trials in a greenhouse, totalling 32 replicates for jasmonate-insensitive plants, 30 for wild type and 32 for jasmonate-overexpressor plants. We used generalized linear effect model (GLM) with Poisson distribution to analyse the effect of plant lines and trial on the number of nymphs produced by aphids (fecundity). We included the number of aphids (1 or 2) as a covariant in the model. We evaluated aphid developmental time by enclosing a single 1-day-old aphid on the third leaf of each plant with a translucent spun polyester sleeve. We checked the aphid daily until it produced its first nymph, which was our aphid reaching adulthood marker. Therefore, we measured aphid developmental time as the number of days taken to produce the first nymph. We carried out two trials in a greenhouse for a total of 12 replicates for jasmonate-insensitive plants, 10 for wild type and 10 for jasmonate-overexpressor plants. We performed one-way analysis of variance (ANOVA) to test for the effect of JA defences on aphid developmental time. We included trial as a blocking factor. When plant line was significant, we performed Tukey's HSD post hoc test comparisons. The number of nymphs produced by an aphid was not normally distributed; therefore, we square-root transformed the data to meet parametric assumptions; homogeneity of variance was met after transformation.

To evaluate whether jasmonate plant resistance constrains aphid feeding, we collected aphid honeydew. Aphid honeydew excretion can be used as a proxy for the amount of food ingested (Douglas, 2003; Taylor, Parker, & Douglas, 2012). We applied two aphid densities (10 or 100 adult aphids) to the second leaf of 4-week-old jasmonate-insensitive, wild type and jasmonate-overexpressor tomato plants. We carefully placed the entire second leaf inside 500-ml plastic chambers. We lined the entire chamber with previously weighed aluminium foil. Total aphid honeydew production was measured as the difference between the initial and final weight of the aluminium foil after 72 hr of aphid feeding. Because aphids were reproducing over the 72 hr, we calculated aphid per capita honeydew production as the total amount honeydew produced divided by the number of aphids present after 72 hr. We used two-way ANOVA to analyse the effect of plant line and aphid density on per capita aphid honeydew production.

2.2 Effects of jasmonate expression on aphid density-dependent processes

To evaluate whether resource limitation and plant defences strengthen aphid density-dependent processes, we manipulated initial aphid density and jasmonate plant defences and estimated resource limitation. We enclosed each plant with a spun polyester sleeve and randomly assigned them to receive different aphid densities. We initially added 5, 25, 50, 100 or 150 aphids per plant. Following aphid infestation, we allowed the aphids to settle and feed for 3 days. After 3 days, we recorded the number of aphids per plant and used those numbers as our initial density treatment and initial densities varied between 1 and 330 aphids per plant. Short-term density-manipulation experiments have been successfully employed to study density-dependent processes of insects in different systems (Helms & Hunter, 2005; Rotem & Agrawal, 2003; Underwood, 2010; Underwood & Rausher, 2002). We estimated aphid population growth by calculating the daily per capita growth rate of aphids (dN/Ndt) as (ln[N₂] − ln[N₁])/(t₂ − t₁), where N₂ and N₁ are the final and initial aphid densities, respectively, divided by the number of days elapsed between initial (t₁) and final (t₂) counting (ca. 15 days) (Agrawal et al., 2004; Vandermeer, 2010). A negative feedback between density and per capita population growth rate is a necessary condition for the density-dependent regulation of populations (Harrison & Cappuccino, 1995). We carried out six trials in a greenhouse, and the total number of replicates per treatment was as follows: jasmonate-insensitive = 67, wild type = 78 and jasmonate-overexpressor = 72. Visual inspection of the data suggests linearity; therefore, we used generalized linear mixed effect models (GLMM) to analyse the effect of plant lines, initial aphid density (ln-transformed) and their interaction on aphid per capita growth rate and final density (ln-transformed). We included resource limitation (number of winged aphids, ln-transformed) as a covariant and trial as a random effect in the model. We controlled for potential effects of resource limitation on density dependence processes by quantifying the number of winged morphs, a well-known proxy for resource deterioration response in aphids (Müller et al., 2001). Although plant resistance levels may affect the proportion of winged aphids, our JA manipulation did not affect wing formation (F_2,215 = 0.572, p = 0.565). As a result, we were able to use the number of winged morph aphids recorded as an estimative of resource limitation in our analyses. Therefore, we tested the role of plant defences on herbivore population processes without the confounding effects of resource depletion.

2.3 Effects of jasmonate expression and aphid density on plant defences

We assessed the differences in plant defence induction among the three plant lines in response to variation in aphid density by measuring the concentration of phytohormones (JA and SA) and the activity of SPI. We grew plants for 4 weeks in a greenhouse and then infested them with different aphid densities (0, 10, 100, 500). We enclosed the aphids on the youngest fully expanded leaf (leaf 3), and aphids were free to move between leaflets. We quantified SPI activity at 96 hr and phytohormones at 24 hr following aphid infestation. We carried out one trial for SPI and two trials for phytohormones. For each SPI sample, we collected and weighed (100 mg) the third leaflet of the youngest fully expanded leaf, and for phytohormone analysis, we collected and weighed (200 mg) the terminal leaflet of the youngest fully expanded leaf. We then transferred the tissue to 2-ml screw cap tubes containing 900 mg zirconia/silica beads (BioSpec) and immediately immersed it in liquid nitrogen. We stored the samples at −80°C until chemical analysis.

We extracted phytohormones from the tissue and analysed them according to the methods described in Thaler, Agrawal, and Halitschke (2010) and Pan, Welti, and Wang (2008). Briefly, we added 1 ml of extraction buffer and 100 μl internal standard solution (d₄-SA and d₅-JA CDN isotopes, Point-Claire, Canada). We homogenized the samples in a FastPrep (MP Biomedicals) at speed 6.5 for 45 s and then in a centrifuge (Beckman Coulter, Allegra^® X-22R, Fullerton, CA, USA) at 4°C for 20 min at 14,000 rpm. We dissolved samples in 175–200 μl methanol after extraction with dichloromethane and solvent evaporation. We analysed 15 μl on a triple-quadrupole LC-MS/MS system (Quantum access; Thermo Scientific).

To quantify SPI activity, we followed the method described in Bode et al. (2013) for use in a microplate assay. Briefly, we extracted the proteins by adding 1 ml of extraction buffer, homogenized the samples in a Fast prep^® machine and centrifuged. After centrifugation, 500–700 μl of supernatant was transferred to a 1.5-ml tube. We used the Bradford assay (Bradford 1976) for protein quantification. SPI activity was measured by combining 20 μl of reaction buffer (0.1 M TRIS, pH 7.6), 10 μl of 0.25 mg/ml trypsin in 0.1 M TRIS, and 20 μl sample; shaking gently on vortex to mix the ingredients; and incubating at 37°C for 5 min. Then, we added 20 μl of 3.1 mg/ml N-benzoyl-DL-arginine-b-naphthylamide (BANA) in DMSO to each sample in the microplate and incubated for another 20 min at 37°C. We stopped the reaction by adding 100 μl of 2% HCl in ethanol. We then read the absorbance at 540 nm in a BioTek microplate reader (BioTek), to control for the background of each sample. Last, we added 100 μl of 0.06% p-dimethylaminocinnamaldehyde in ethanol to develop the sample. The dye reaction was allowed to proceed for 30 min at room temperature before we measured the total absorbance at 540 nm. A positive control (with trypsin, no sample), soybean trypsin inhibitor standards of six concentrations (0.24, 0.12, 0.06, 0.03, 0.015 and 0.0075 mg/ml in 0.1 M TRIS) and a negative control (including no trypsin and no sample) were run on the same microplate. We determined SPI activity using a standard curve, which was calculated from measurements of the standard solutions.

We analysed the concentration of phytohormones (ln-transformed) and SPI activity using GLMM and GLM, respectively. We included plant line, aphid density and plant line-by-aphid density interaction as independent variables; aphid density was ln-transformed. We used protein concentration per fresh tissue weight as a covariate in the SPI activity model and the amount of Methanol (175–200 μl) per sample as a random effect in the phytohormone analyses. All statistical analyses were performed in JMP 14 (SAS Institute Inc., 2018).

3 RESULTS

3.1 Effects of jasmonate expression on aphid performance

Aphid developmental time was slower on jasmonate-overexpressor plants compared to jasmonate-insensitive and wild type plants (Table 1; Figure 2a). Aphids showed higher fecundity when feeding on jasmonate-insensitive plants, producing 58% more nymphs compared to wild type and 43% more compared to jasmonate-overexpressor plants ( $urn:x-wiley:00218790:media:jane12993:jane12993-math-0001$ = 30.68, p < 0.001; Figure 2b). Aphids feeding on jasmonate-insensitive and wild type plants excreted less per capita honeydew when feeding at higher densities, whereas when feeding on jasmonate-overexpressing plants, honeydew excretion was not affected by aphid density (Table 1; Figure 2c).

Table 1. ANOVAs, GLMs and GLMMs of developmental time (number of days to first nymph), final number of aphids, per capita population growth rate, serine protease inhibitor, salicylic acid and jasmonic acid. Treatments are plant lines (jasmonate-insensitive, wild type and jasmonate-overexpressor) and aphid initial density. Resource limitation (number of winged aphids) was included as a covariate. Final number of aphids, initial density, salicylic and jasmonic acid were ln-transformed, and developmental time was sqr-transformed. F-values and degrees of freedom (df) are shown

Source of variation	Developmental time	Honeydew production	Final no. of aphids	Per capita growth rate	SPI	Salicylic acid	Jasmonic acid
Trial	0.51_(2,28)
Plant line	3.56_(1,28)*	4.24_(2,24)*	18.33_(2,206)***	17.69_(2,206)***	4.68_(2,55)*	0.54_(2,166)	0.99_(2,163)
Aphid initial density		41.84_(1,24)*	323.90_(1,183)***	7.27_(1,193)**	0.28_(1,55)	4.88_(1,166)*	4.20_(1,164)*
Aphid initial density × Plant line		3.94_(2,24)*	4.32_(2,206)*	5.37_(2,206)**	0.63_(1,55)	3.08_(2,165)*	0.54 _(2,163)
Resource limitation			0.62_(1,210)	0.42_(1,209)
Protein per fresh tissue weight					0.25_(2,55)

Abbreviation: SPI: serine protease inhibitor.
* p < 0.05,
** p < 0.01,
*** p < 0.001

3.2 Effects of jasmonate expression on aphid density-dependent processes

We found a significant interaction between plant line and initial aphid density on aphid per capita growth rate, which indicates that plant defensive traits strengthened density-dependent population growth (Table 1; Figure 3a). On jasmonate-insensitive and wild type plants, we found a negative relationship between per capita population growth and aphid initial density, indicating density-dependent population growth (F_1,58 = 13.74, β = −0.021 p = 0.0005, R² = 0.65; F_1,69 = 5.18, β = −0.013, p = 0.026, R² = 0.53, respectively). In contrast, aphids showed density-independent population growth on jasmonate-overexpressor plants, as there was no relationship between per capita population growth and aphid initial density (F_1,63 = 0.891, β = 0.006 p = 0.349, R² = 0.47).

At lower initial densities, the final number of aphids was higher on jasmonate-insensitive plants compared to jasmonate-overexpressor plants. At higher densities, the final number of aphids on all plant lines converged to similar densities (Table 1, Figure 3b), which corroborates our findings that per capita population growth at higher densities was similar across all plant lines.

3.3 Effects of jasmonate expression manipulation and aphid density on plant defences

Serine PIs showed higher activity on jasmonate-overexpressor plants compared to wild type and jasmonate-insensitive plants (Table 1), which demonstrates the high constitutive levels of resistance on jasmonate-overexpressor plants. Aphid density and plant line-by-aphid density did not induce SPI activity (Table 1, Figure 4a).

The plant line-by-aphid density interaction affected the induction of SA (Table 1, Figure 4b). Aphid feeding on jasmonate-insensitive plants increased the induction of SA (F_1,55 = 8.54, p = 0.005). Aphid feeding on wild type and jasmonate-overexpressor plants did not affect the concentration of SA (wild type: F_1,57 = 2.64, p = 0.110; jasmonate-overexpressor: F_1,54 = 0.10, p = 0.765). This result suggests a negative crosstalk between the defensive phytohormones. Aphid feeding increased the JA production across all plant lines (Table 1, Figure 4c). We did not detect an effect of plant line or plant line-by-aphid density on the induction of JA (Table 1).

4 DISCUSSION

Using a density-manipulation experiment, we simulated aphid population growth under high and low population densities, which allowed us to assess the role of plant defences on herbivore population dynamics and evaluate the potential mechanisms involved in herbivore density-dependent population growth. We demonstrated that plant defences can provide resistance against aphids and can strengthen density-dependent processes. Aphids took longer to grow, produced fewer nymphs and consequently showed lower densities when feeding on jasmonate-overexpressing plants compared to jasmonate-insensitive plants (Figures 2 and 3b). Jasmonate-overexpressing plants did not induce the phytohormone SA, dampened aphid population densities across all initial densities and caused a density-independent population growth. In contrast, jasmonate-insensitive plants induced SA, reduced population densities at high initial densities and promoted strong negative density-dependent population growth. Combined, these results suggest a signalling pathway crosstalk and highlight the critical role of plant defences in strengthening density-dependent processes in herbivore populations.

Previous studies have highlighted the importance of host plant quality on density dependence processes (Hunter, Forkner, & McNeil, 2000; Rotem & Agrawal, 2003; Underwood & Rausher, 2002, 2000). By changing birth, death, emigration and immigration rates, plants influence density dependence processes and thus population equilibrium. Plant quality may influence density-dependent population growth of herbivorous insects by increasing food limitation (Abbott, Morris, & Gross, 2008; Denno et al., 1995), changing the impact of predators on prey (Kersch-Becker et al., 2017) and through the negative response associated with induced plant defences (Underwood, 1999). For example, spider mite (Tetranychus urticae) populations showed strong negative density-dependent growth on high-quality host plants (Leonurus cardiaca), whereas on low-quality host plants spider mite population grew in a density-independent manner and this result was attributed to potential differences in herbivore-induced plant responses (Rotem & Agrawal, 2003). Using a density-manipulation experiment, Underwood and Rausher (2002) demonstrated that herbivore-induced resistance caused lower population growth and stronger density dependence on Mexican bean beetle populations compared to soybean varieties with no resistance. However, none of these studies controlled for other potential confounding effects, such as resource depletion.

Although plant traits have the potential to drive population dynamics of herbivores, it remains unclear how plant defences strengthen density-dependent processes in herbivores (Agrawal, 2004; Underwood & Rausher, 2002). It has been hypothesized that high constitutive levels of resistance should not impose negative density dependence (Hunter et al., 2000; Rhoades, 1985; Underwood, 1999). While evidence for a trade-off between induced and constitutive resistance is still evasive, it is often suggested that the level of induced resistance expressed by plants with high levels of constitutive resistance should be lower than those expressed by plants with low levels of constitutive resistance (Karban & Baldwin, 1997). This suggests that herbivores may be always maximally suppressed on highly resistant plants and the negative feedback of herbivore density should be low or non-existent. We provide empirical evidence for this hypothesis by showing that high constitutive levels of resistance caused low population growth regardless of the initial density of aphids and thus did not cause negative density-dependent population growth. In our study, jasmonate-overexpressing plants show high JA-dependent constitutive levels of resistance (Figure 3a, McGurl et al., 1994) and were unable to activate the SA pathway (Figure 3b, Kersch-Becker et al., 2017). Plants with higher levels of resistance are expected to impose their negative effects on herbivores at all times, thus not increasing resistance as densities rise. By lowering aphid fecundity and performance, jasmonate-overexpressing plants do not impose negative density-dependent growth and therefore maintain aphid populations at lower and stable level densities, reducing overall damage to plants. It is likely that jasmonate-mediated defences are involved in suppressing aphid population growth in a density-independent manner in our jasmonate-overexpressing plants, which showed higher level of SPI activity.

In contrast, jasmonate-insensitive plants cannot induce JA-dependent defences and therefore showed low constitutive levels of JA-mediated defences (low SPI activity), but strongly induced the SA pathway. Aphids feeding on these plants are larger in size (Kersch-Becker & Thaler, 2015) and when densities rise aphid per capita honeydew excretion is reduced, suggesting that at high densities aphids are consuming less food. Aphid negative density-dependent population growth on jasmonate-insensitive plants may be intensified in response to depletion of edible resources (Denno et al., 1995) or induction of plant defences (Underwood, 1999). Because we controlled for resource depletion in our models, it is unlikely that reduced food availability explains our results. SA-mediated defences negatively affect aphids (Kersch-Becker & Thaler, 2014; Walling, 2000; Züst & Agrawal, 2016). In our study, SA accumulation in response to aphid density was higher on jasmonate-insensitive plants likely because of signalling crosstalk between JA and SA pathways that occurs on plants with functional JA pathways (Thaler et al., 2012). Although we did not measure SA defence markers downstream from SA accumulation (e.g., gene expression, enzymes), it is likely that SA-dependent defences were up-regulated when SA was induced (Schenk et al., 2000; Schweiger, Heise, Persicke, & Müller, 2014). On jasmonate-insensitive plants, for instance, aphids induce higher amounts of methyl salicylate, a SA-dependent secondary compound, compared to jasmonate-overexpressor plants (Kersch-Becker et al., 2017). Thus, on jasmonate-insensitive plants SA was more strongly induced at higher densities, thus likely mediating the negative density-dependent population growth of aphids. On wild type plants, aphid population also showed negative density-dependent growth, which might be a response to both constitutive and induced resistance expressed by these plants. Our findings differed from Kersch-Becker et al. (2017), and we attributed this variation to differences in field and greenhouse experimental set-up. The greenhouse experiments were carried out throughout the year and performed in smaller enclosures in highly controlled settings.

Our findings indicate that an interplay between jasmonate and salicylate-mediated responses is involved in plant resistance against aphids, adding to a growing body of evidence that although aphids are stealthy herbivores they activate both jasmonate and salicylate responses. Our results provide a mechanistic framework for how plant defences affect herbivore density-dependent processes. The phytohormone signalling cascades interact (pathway crosstalk), and SA cascade is antagonized by the overexpression of the JA cascade and enhanced by the silencing of the JA pathway. By muting (jasmonate-insensitive) or enhancing (jasmonate-overexpressor) jasmonate-mediated responses using genetic manipulations, we showed that SA-related plant defences operate in a density-dependent manner likely strengthening density-dependent processes, whereas JA-dependent defences affect other population attributes. We demonstrated that variation in plant defensive traits not only influences herbivore performance, but is a key factor driving herbivore population processes.

ACKNOWLEDGEMENTS

This study strongly benefited from comments and suggestions by Anurag Agrawal, Alison Power, Suzi Claflin, Chris Stieha and Gui Becker. We thank Rayko Halitsche and Lucas Gonzalez for help with chemical analyses. This project received financial support from National Research Initiative of the USDA Grant 2006-35302-17431, the Department of Ecology and Evolutionary Biology, Andrew Mellon Foundation and the Department of Entomology at Cornell. MFKB was supported by the CAPES/Fulbright fellowship (BEX 2234-08-4). Appropriate permits were obtained for the use of transgenic plants. We have no competing interests relating to this paper.

AUTHORS’ CONTRIBUTIONS

M.F.K.-B. and J.S.T. conceptualized the research; M.F.K.-B. conducted the experiments, collected and analysed the data; M.F.K.-B. wrote the manuscript with J.S.T.

DATA AVAILABILITY

Data available from Dryad Digital Repository: http://doi.org/10.5061/dryad.4nr0843 (Kersch-Becker & Thaler, 2019).

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Citing Literature

Volume88, Issue7

July 2019

Pages 1079-1088

Constitutive and herbivore-induced plant defences regulate herbivore population processes

Abstract

1 INTRODUCTION

2 MATERIALS AND METHODS

2.1 Effects of jasmonate expression on aphid performance

2.2 Effects of jasmonate expression on aphid density-dependent processes

2.3 Effects of jasmonate expression and aphid density on plant defences

3 RESULTS

3.1 Effects of jasmonate expression on aphid performance

3.2 Effects of jasmonate expression on aphid density-dependent processes

3.3 Effects of jasmonate expression manipulation and aphid density on plant defences

4 DISCUSSION

ACKNOWLEDGEMENTS

AUTHORS’ CONTRIBUTIONS

DATA AVAILABILITY

REFERENCES

Citing Literature

Figures

References

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Constitutive and herbivore-induced plant defences regulate herbivore population processes

Abstract

1 INTRODUCTION

2 MATERIALS AND METHODS

2.1 Effects of jasmonate expression on aphid performance

2.2 Effects of jasmonate expression on aphid density-dependent processes

2.3 Effects of jasmonate expression and aphid density on plant defences

3 RESULTS

3.1 Effects of jasmonate expression on aphid performance

3.2 Effects of jasmonate expression on aphid density-dependent processes

3.3 Effects of jasmonate expression manipulation and aphid density on plant defences

4 DISCUSSION

ACKNOWLEDGEMENTS

AUTHORS’ CONTRIBUTIONS

DATA AVAILABILITY

REFERENCES

Citing Literature

Figures

References

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