Assessing the functional importance of large‐bodied invertebrates in experimental headwater streams
Bibliographic record
Abstract
Recent theoretical advances in food web ecology emphasize the importance of body size disparities among species for the structure, stability and functions of ecosystems. Experimental confirmations of the functional importance of large species, independent of their trophic position, are scarce. We specifically examine the multiple ecological roles of large invertebrates from two distinct trophic levels in headwater streams. We experimentally manipulated the presence of large predatory invertebrates (two Perlid stoneflies) or detritivores (a limnephilid caddisfly and a Pteronarcys stonefly) in a two‐by‐two design in stream channels open to immigration/emigration of smaller biota. We assessed treatment effects on the trophic structure of the benthic invertebrate community, dynamics of basal resources (benthic algae and leaf litter of cedar and alder), and stability of litter decomposition rates against an experimental pulse perturbation (fine sediment input). The presence of the large invertebrates was associated with a ten‐fold decrease in the biomass of invertebrate filterers whereas other trophic groups were unaffected by the large species. The biomass of benthic algae was lower and the rate of mass loss of alder litter was higher in channels lacking the large predators, thus revealing trophic cascades operating along both algal‐based and detritus‐based food chains. The large predators had no detectable effect on the decomposition of cedar whereas both cedar and alder disappeared faster in the presence of the large detritivores. Furthermore, the large predators and large detritivores interactively influenced the decomposition of the cedar–alder mixture through a litter diversity effect and the variability of the rate of alder decomposition after a pulse of fine sediment. Because the large invertebrates affected multiple ecosystem properties, and as their absence was not rapidly compensated for by small immigrant species, our findings support the notion that large species could be critically important in controlling ecosystem structure and functioning.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".