Bibliographic record
Abstract
G. Moreau, E. S. Eveleigh, C. J. Lucarotti & D. T. Quiring (2006) Ecosystem alteration modifies the relative strengths of bottom-up and top-down forces in a herbivore popu-lation. Journal of Animal Ecology, 75, 853–861. Ecology, like any science, has often found itself split over important issues. The prevalence of top-down and bottom-up forces in ecological communities is an obvious example which has driven heated debate amongst ecologists. Some ecologists have argued that community structure is ultimately set by the top predators, which drive a predictable cascading influence through the rest of the community. Still others have argued that all consumers are ultimately controlled by their resources. Nonetheless, most ecologists would probably agree that it may be more profitable to enrich the debate by refocusing our attention on: (i) outlining the contingencies where top-down/bottom-up control prevail; and (ii) exploring the interactive implications of top-down and bottom-up forces. This contribution is one such paper that begins to consider these emerging aspects of bottom-up and top-down control. As such, this paper is an exciting example of how broadening an old research theme can contribute to fundamental developments in modern ecology. In this paper, Moreau and co-authors explore the role of top-down and bottom-up forests within an interesting applied context. They look at how modern silvicultural practices (e.g. the thinning of a forest stand in Newfoundland) contribute to the survivorship of a herbivore pest (sawfly). In general, they find that forest thinning practices contribute to increased outbreak densities of the sawfly by reducing larval sawfly mortality. One may think that this immediately implies a strong bottom-up influence. However, the authors go on to show that this increased pest influence occurs because the forest thinning drives both bottom-up and top-down processes in a manner that acts to excite sawfly outbreaks. Forest thinning appears to enhance the survivorship of the sawfly, probably by enhancing the quality of the foliage (i.e. bottom-up) and simultaneously reducing the influence of natural predators (the virus, NeabNPV). Further, and importantly, the authors document how the different processes change as a function of forest defoliation level. Their results speak to the dynamic nature of these two opposing processes. These elegant results all unfold because the authors employ both empirical surveys in combination with experimental manipulations, allowing them to tease apart the strength of the different processes.
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 | 0.003 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.176 | 0.082 |
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".