Pyramids of species richness: the determinants and distribution of species diversity across trophic levels
Bibliographic record
Abstract
How species richness is distributed across trophic levels determines several dimensions of ecosystem functioning, including herbivory, predation, and decomposition rates. We perform a meta‐analysis of 72 large published food webs to investigate their trophic diversity structure and possible endogenous, exogenous, and methodological causal variables. Consistent with classic theory, we found that published food webs can generally be described as ‘pyramids of species richness’. The food webs were more predator‐poor, prey‐rich and hierarchical than is expected by chance or by the niche or cascade models. The trophic species richness distribution also depended on centrality, latitude, ecosystem‐type and methodological bias. Although trophic diversity structure is generally pyramidal, under many conditions the structure is consistently uniform or inverse‐pyramidal. Our meta‐analysis adds nuance to classic assumptions about food web structure: diversity decreases with trophic level, but not under all conditions, and the decrease may be scale‐dependent. Synthesis The distribution of species richness across trophic levels has not been evaluated in recent decades, despite improvement in food web resolution and the relevance of biodiversity distribution to ecosystem function. Our meta‐analysis of 72 large, recent food webs, illustrates that published food webs can generally be described as basal‐rich, top‐poor ‘pyramids of species richness’, consistent with classic theory. Although trophic diversity structure is generally pyramidal, under some environmental and ecological conditions the structure is uniform or inverse‐pyramidal. Our meta‐analysis confirms classic theory about food web structure, while adding nuance by describing conditions under which classic pyramid structure is not observed.
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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 | 0.013 | 0.029 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.012 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".