Direct and indirect effects of landscape structure on a tri‐trophic system within agricultural lands
Bibliographic record
Abstract
Although several studies have examined the influence of landscape structure and agricultural intensification on species abundance and diversity, few have addressed how these impact populations across multiple trophic levels. We investigated the effects of landscape structure on the tri‐trophic interactions between a bird host (the Tree Swallow Tachycineta bicolor (Vieillot)), its blowfly ectoparasites ( Protocalliphora Hough), and their parasitoid wasps ( Nasonia Ashmead) across 13 spatial scales, along a gradient of agricultural intensification covering 10,200 km 2 in southern Québec, Canada. We showed that the three taxa responded to landscape structure at distinctive spatial scales that are relative to their size rather than their trophic rank. This response, however, differed according to habitat type. The three organisms responded to the amount of intensive cultures (maize, soybean and other cereals) at smaller spatial scales than to the amount of extensive cultures (hayfields and pastures). Although the number of Tree Swallow fledglings, the number of Protocalliphora sialia Shannon & Dobroscky pupae and the number of P. sialia pupae parasitized by Nasonia sp. per nest were negatively affected by agricultural intensification, our data do not support the prediction that organisms at the higher trophic levels are more susceptible to habitat degradation. Here, ectoparasites at the second trophic level were disproportionally affected by agricultural intensification; the abundance of P. sialia decreased by 80% along the gradient of agricultural intensification compared to a 20% and 35% reduction in the number of Tree Swallow fledglings and in the level of parasitism by Nasonia sp., respectively. Our work highlights the importance of designing protocols that take spatial aspects of trophic interactions into account when studying the impact of habitat loss and fragmentation on populations and communities, as these interactions dictate local biodiversity and community function. Furthermore, our results highlight the importance of considering multiple landscape parameters when identifying the functional spatial scales of an organism, as a failure to do so could lead to an underestimation of the area it uses.
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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) | 0.000 | 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".