Spatiotemporal variation in drivers of parasitoid metacommunity structure in continuous forest landscapes
Bibliographic record
Abstract
Abstract Although landscape spatial structure is known to influence spatial patterns of biodiversity, its effect on insect communities at higher trophic levels such as parasitoids remains poorly understood. This is particularly true in continuously distributed forests in which it can be difficult to identify clear boundaries among habitat patches. Using the metacommunity framework, we evaluate the relative importance of forest landscape structure, non‐environmental spatial structure, and host outbreak status to spatial and within‐season temporal variation in parasitoid communities. We used variation partitioning and metacommunity structure analyses to identify (1) the drivers of the metacommunity structure of parasitoids associated with the spruce budworm ( Choristoneura fumiferana ), and (2) how their relative influence varies through a season. We used a multi‐scale perspective to summarize landscape heterogeneity in regions of increasing size around the community sampling locations. Spruce budworm larvae and pupae were sampled during three periods during the summer 2014 in 18 locations within continuous forest landscapes in Quebec, Canada. Thirty‐two parasitoid wasp and fly species were recorded, 16 of which were found at more than one location. We found that the mechanisms shaping metacommunity structure changed over the course of a single season and that community structure varied among sites. At early and late periods in the season, we found that non‐environmental structure, forest structure, and likely inter‐specific competition were the main mechanisms influencing spatial variation in community structure. These results suggest a competition–dispersal trade‐off. In contrast, at the middle period of the season, environmental filtering by forest structure and stochastic events were found to influence community structure. This period corresponds to the transition between early and late parasitoid communities. Our findings on the role of environmental filtering and forest structure support the idea that forest manipulations have the potential to influence parasitoid populations and hence spruce budworm outbreak dynamics as hypothesized by the “enemies hypothesis.” Moreover, our study highlights the value of considering a multi‐scale approach and temporal variability of species interactions when characterizing the multiple processes shaping spatial metacommunity structure, particularly in continuous environments.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 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 teacher head, 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".