Evidence map›Paper›PMID 40811245›Full record

ArticlePLoS biology2025

Plants respond to herbivory through sequential induction of cheaper defenses before more costly ones.

Jinlong Wan, Jiahui Yi, Xiao Sun, Evan Siemann, Matthias Erb, Wei Huang

Abstract read
In one paragraph

Article in PLoS biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Volatile Organic Compounds ofPlants (Basel, Switzerland) · 2026
    Article
  5. Article
  6. Article
  7. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Jinlong WanWuhan Botanical Garden, Chinese Academy of Sciences, Wuhan, China.
Jiahui YiWuhan Botanical Garden, Chinese Academy of Sciences, Wuhan, China.
Xiao SunSchool of Life Sciences, Henan University, Kaifeng, China.
Evan SiemannDepartment of Biosciences, Rice University, Houston, Texas, United States of America.
Matthias ErbInstitute of Plant Sciences, University of Bern, Bern, Switzerland.
Wei HuangWuhan Botanical Garden, Chinese Academy of Sciences, Wuhan, China.ORCID 0000-0003-3760-6084

Funding

National Key Research and Development Program of ChinaNational Natural Science Foundation of ChinaYouth Innovation Promotion Association of Chinese Academy of Sciences
6 · The paper itself

Abstract

Plants encounter natural antagonist threats of varying intensity and respond by activating multiple defense traits. Due to the fitness costs associated with producing defense traits, plants are expected to activate less costly traits first, reserving more costly defenses for potentially more severe damage ("cheaper first hypothesis"), but evidence to date is scarce. Here, we tested this hypothesis by measuring six putative defense traits in the annual plant Ambrosia artemisiifolia. We found that all traits were effective against insect herbivores, but production of three of them more strongly reduced plant growth, suggesting higher growth costs. When plants were attacked by insect herbivores, less costly traits were induced first, even at the lowest levels of damage, while more costly traits were activated only after higher damage thresholds. This cost-dependent sequential pattern was consistently observed in plants when challenged by 12 different herbivore species from three insect orders. These findings demonstrate that plants can employ the "cheaper first" sequential induction defense strategy, potentially allowing them to reduce defense costs and maximize fitness. Our study provides new insights into how plants fine-tune their defense responses under variable antagonistic pressures.

Indexed as

HerbivoryPlant Defense Against HerbivoryAnimalsInsecta

Identifiers

PMID40811245
PMCPMC12352644

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.