Towards a cohesive, holistic view of top predation: a definition, synthesis and perspective
Bibliographic record
Abstract
Research on the ecology of top predators – upper trophic level consumers that are relatively free from predation once they reach adult size – has provided regular contributions to general ecology and is a rapidly expanding and increasingly experimental, multidisciplinary and technological endeavour. Yet, an exponentially expanding literature coupled with rapid disintegration into specialized, disconnected subfields for study (e.g. vertebrate predators versus invertebrate predators, community ecology versus biological control etc.) increasingly means that we are losing a coherent, integrated understating of the role and importance of these species in ecosystems. This process of canalization is likely to hinder sharing of scientific discovery and continued progress, especially as there is a growing need to understand the generality of the top–down forcing, as demonstrated for some members of this group. Here, we propose ways to facilitate synthesis by promoting changes in mentality and awareness among specialists through increased debate and collaboration, conceptual reviews and a series of exemplary case studies. The strategy will rely on the collective contribution by all scientists in the field and will strive to consolidate and formalise top‐order predation as a holistic, cohesive, cross‐taxonomical field of research studying the ecology, evolution and behaviour of apex predators and their capability to exert top–down forcing on lower trophic levels. Synthesis The ongoing global loss of top predators and their recolonization of various regions are causing a rapid upsurge of studies on these species and a consequent fragmentation of this field into disconnected, specialized subcompartments: this will weaken efforts to produce synthetic generalisations of broader ecological interest. Here, we show that top predation provides regular contributions to general ecology, is well grounded in theoretical ecology and is a rapidly expanding and increasingly experimental, multidisciplinary and technological field of research. The novelty of this forum lies in providing a concise synthesis of this area of ecology, in attempting to formalise “top predation” as a specific, inter‐connected area of investigation, and in proposing a marked change of mentality by stressing the need for cross‐taxonomic approaches enabling broader views of the role of predators in ecosystems.
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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 | 0.022 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.012 | 0.009 |
| Science and technology studies | 0.003 | 0.013 |
| Scholarly communication | 0.012 | 0.021 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".