How climate change affects the seasonal ecology of insect parasitoids
Bibliographic record
Abstract
1. In the context of global change, modifications in winter conditions may disrupt the seasonal phenology patterns of organisms, modify the synchrony of closely interacting species and lead to unpredictable outcomes at different ecological scales. 2. Parasites are present in almost every food web and their interactions with hosts greatly contribute to ecosystem functioning. Among upper trophic levels of terrestrial ecosystems, insect parasitoids are key components in terms of functioning and species richness. Parasitoids respond to climate change in similar ways to other insects, but their close relationship with their hosts and their particular life cycle – alternating between parasitic and free‐living forms – make them special cases. 3. This article reviews of the mechanisms likely to undergo plastic or evolutionary adjustments when exposed to climate change that could modify insect seasonal strategies. Different scenarios are then proposed for the evolution of parasitoid insect seasonal ecology by exploring three anticipated outcomes of climate change: (i) decreased severity of winter cold; (ii) decreased winter duration; and (iii) increased extreme seasonal climatic events and environmental stochasticity. 4. The capacities of insects to adapt to new environmental conditions, either through plasticity or genetic evolution, are highlighted. They may reduce diapause expression, adapt to changing cues to initiate or terminate diapause, increase voltinism, or develop overwintering bet‐hedging strategies, but parasitoids' responses will be highly constrained by those of their hosts. 5. Changes in the seasonal ecology of parasitoids may have consequences on host–parasitoid synchrony and population cycles, food‐web functioning, and ecosystem services such as biological pest control.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".