All wet or dried up? Real differences between aquatic and terrestrial food webs
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Ecologists have greatly advanced our understanding of the processes that regulate trophic structure and dynamics in ecosystems. However, the causes of systematic variation among ecosystems remain controversial and poorly elucidated. Contrasts between aquatic and terrestrial ecosystems in particular have inspired much speculation, but only recent empirical quantification. Here, we review evidence for systematic differences in energy flow and biomass partitioning between producers and herbivores, detritus and decomposers, and higher trophic levels. The magnitudes of different trophic pathways vary considerably, with less herbivory, more decomposers and more detrital accumulation on land. Aquatic-terrestrial differences are consistent across the global range of primary productivity, indicating that structural contrasts between the two systems are preserved despite large variation in energy input. We argue that variable selective forces drive differences in plant allocation patterns in aquatic and terrestrial environments that propagate upward to shape food webs. The small size and lack of structural tissues in phytoplankton mean that aquatic primary producers achieve faster growth rates and are more nutritious to heterotrophs than their terrestrial counterparts. Plankton food webs are also strongly size-structured, while size and trophic position are less strongly correlated in most terrestrial (and many benthic) habitats. The available data indicate that contrasts between aquatic and terrestrial food webs are driven primarily by the growth rate, size and nutritional quality of autotrophs. Differences in food-web architecture (food chain length, the prevalence of omnivory, specialization or anti-predator defences) may arise as a consequence of systematic variation in the character of the producer community.
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.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 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 it