Resource–consumer diversity: testing the effects of leaf litter species diversity on stream macroinvertebrate communities
Bibliographic record
Abstract
Summary 1. Understanding relationships between resource and consumer diversity is essential to predicting how changes in resource diversity might affect several trophic levels and overall ecosystem functioning. 2. We tested for the effects of leaf litter species diversity (i.e. litter mixing) on litter mass remaining and macroinvertebrate communities (taxon diversity, abundance and biomass) during breakdown in a detritus‐based headwater stream (North Carolina, U.S.A.). We used full‐factorial analyses of single‐ and mixed‐species litter from dominant riparian tree species with distinct leaf chemistries [red maple (Acer rubrum), tulip poplar (Liriodendron tulipifera), chestnut oak (Quercus prinus) and rhododendron (Rhododendron maximum)] to test for additivity (single‐species litter presence/absence effects) and non‐additivity (emergent effects of litter species interactions). 3. Significant non‐additive effects of litter mixing on litter mass remaining were explained by species composition, but not richness, and litter‐mixing effects were variable throughout breakdown. Specifically, small differences in observed versus expected litter mass remaining were measured on day 14; whereas observed litter mass remaining in mixed‐species leaf packs was significantly higher on day 70 and lower on day 118 than expected from data for single‐species leaf packs. 4. Litter mixing had non‐additive effects on macroinvertebrate community structure. The number of species in litter mixtures (two to four), but not litter species composition, was a significant predictor of the dominance of particular macroinvertebrates (i.e. indicator taxa) within mixed‐species packs. 5. In addition, the presence/absence of high‐ (L. tulipifera) and low‐quality (R. maximum) litter had additive effects on macroinvertebrate taxon richness, abundance and biomass. The presence ofL. tulipiferalitter had both positive (synergistic) and negative (antagonistic) effects on invertebrate taxon richness, that varied during breakdown but were not related to litter chemistry. In contrast, the presence/absence ofL. tulipiferahad a negative relationship with total macroinvertebrate biomass (due to low leaf mass remaining whenL. tulipiferawas present and higher condensed and hydrolysable tannins associated with leaf packs lackingL. tulipifera). Macroinvertebrate abundance was consistently lower whenR. maximumwas present, which was partially explained by litter chemistry [e.g., high concentrations of lignin, condensed tannins, hydrolysable tannins and total phenolics and high carbon to nutrient (N and P) ratios]. 6. The bottom‐up effects of litter species diversity on stream macroinvertebrates and litter breakdown are different, which suggests that structural attributes of macroinvertebrate communities may only partially explain the effects of litter‐mixing on organic matter processing in streams. In addition, stream macroinvertebrates colonising decomposing litter are influenced by resource diversity as well as resource availability. Broad‐scale shifts in riparian tree species composition will alter litter inputs to streams, and our results suggest that changes in the diversity and availability of terrestrial litter may alter stream food webs and organic matter processing.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".