| Literature DB >> 18665271 |
Elina Mäntylä1, Giorgio A Alessio, James D Blande, Juha Heijari, Jarmo K Holopainen, Toni Laaksonen, Panu Piirtola, Tero Klemola.
Abstract
BACKGROUND: An understanding of the evolution of potential signals from plants to the predators of their herbivores may provide exciting examples of co-evolution among multiple trophic levels. Understanding the mechanism behind the attraction of predators to plants is crucial to conclusions about co-evolution. For example, insectivorous birds are attracted to herbivore-damaged trees without seeing the herbivores or the defoliated parts, but it is not known whether birds use cues from herbivore-damaged plants with a specific adaptation of plants for this purpose.Entities:
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Year: 2008 PMID: 18665271 PMCID: PMC2475509 DOI: 10.1371/journal.pone.0002832
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Figure 1Photos of the real and the artificial larvae.
A) A fifth instar Epirrita autumnata larva on a branch. B) Larval feeding damage on mountain birch (Betula pubescens ssp. czerepanovii) leaves. C) A plasticine larva on a mountain birch branch. D). A beak marking on a plasticine larva indicating a predation attempt by an insectivorous bird.
Figure 2The daily numbers of damaged plasticine larvae found from herbivore (black bars) and control (grey bars) birches.
The X-axis shows the number of days since the start of defoliation by autumnal moth larvae in the herbivore trees. Solid and hatched arrows show the days when the volatile organic compounds (VOCs) and net photosynthesis rate, respectively, were measured.
Results of the generalized linear models on factors affecting the probability of predation event of plasticine larvae.
| Final model | DF | χ2 |
|
|
| 1 | 7.21 | 0.0072 |
|
| 1 | 11.38 | 0.0007 |
|
| 1 | 13.79 | 0.0002 |
The analysis was first based on a full model, from which effects were dropped one by one in order of least significance. The final model is given with the statistically significant (p<0.05) variables. Results for the other factors are given when they were added alone to the final model.
Figure 3The volatile organic compound (VOC) emissions from herbivore (black bars) and control (grey bars) birch branches (ls means+SE from statistical models are shown).
A) six days, n = 14 in both control and herbivore trees, and B) 10–11 days since the start of defoliation by autumnal moth larvae, control: n = 7 and herbivore: n = 6. Compounds: (1) α-pinene, (2) β-myrcene, (3) limonene, (4) β-ocimene, (5) linalool, (6) (E)-DMNT, (7) α-copaene, (8) α-humulene, (9) caryophyllene oxide, (10) (E)-β-caryophyllene, (11) β-bourbonene, (12) cis-3-hexenyl acetate, (13) cis-3-hexen-1-ol+(E)-2-hexenal, (14) nonanal, (15) cis-3-hexenyl butyrate. (*: p<0.05; **: p<0.01; ***: p<0.001).
Spearman's rank correlation coefficients (r S) between individual volatile organic compound emissions in the first measurement (6 days after the start of defoliation) and the total sum of damaged plasticine larvae per tree (n = 28 trees) in both herbivore and control trees.
| Compound | No. | Group | rS |
|
| #6 | homoterpene | 0.576** |
|
| #4 | monoterpene | 0.454* |
|
| #5 | monoterpene | 0.454* |
|
| #11 | sesquiterpene | 0.242 |
|
| #13 | green leaf volatile | 0.224 |
|
| #15 | green leaf volatile | 0.162 |
|
| #1 | monoterpene | 0.160 |
|
| #7 | sesquiterpene | 0.147 |
|
| #12 | green leaf volatile | 0.142 |
|
| #10 | sesquiterpene | 0.093 |
|
| #14 | green leaf volatile | 0.080 |
|
| #3 | monoterpene | −0.012 |
|
| #9 | sesquiterpene | −0.015 |
|
| #8 | sesquiterpene | −0.023 |
|
| #2 | monoterpene | −0.107 |
Column ‘No.’ refers to the number of the compound in Figure 2. Column ‘Group’ indicates into which group of VOCs the compound belongs. (*: p<0.05; **: p<0.01).
Figure 4Scatter plots of three volatile organic compounds (VOCs) and the total sum of damaged plasticine larvae in herbivore (black dots) and control (grey dots) trees (n = 28). A) (E)-DMNT, B) linalool and C) β-ocimene.
Note the different x-axes in the panels.