The role of cyanobacteria in Southern California salt marsh food webs
Bibliographic record
Abstract
Abstract Understanding wetland food webs is critical for effective habitat management, restoration and conservation. Microalgae are recognized as key food sources for marsh invertebrates but the importance of different groups under various conditions is rarely examined. We tested the hypothesis that faunal utilization of microalgae, and cyanobacteria in particular, is significant in Southern California created and natural salt marshes but varies with habitat type (creek bank versus marsh interior) and season (spring versus autumn). We used stable isotope analysis and mixing models (IsoSource) to compare food webs in adjacent young (created) and mature (natural) salt marshes. Isotopic values of some primary producers, macrofauna, epifauna, and fish demonstrated significant differences between the adjacent salt marshes. δ13C and δ34S values of the benthic microalgal community varied with taxonomic composition (diatoms versus cyanobacteria) and to a lesser extent with season. Depleted δ15N values of benthic diatoms and macroalgae indicated that N2 fixed within algal mats was recycled within the benthic algal community. Marsh fauna, including most major macrofauna taxal, Cerithidea, and Fundulus, also exhibited seasonal differences in isotopic composition, and Cerithidea and selected macrofauna (oligochaetes, polychaetes) from the marsh interior were more enriched in 13C and depleted in 15N than those from the creek bank. In the young marsh, the cyanobacteria contributed a minimum of 17–100% of the primary production in food webs supporting macrofauna, and cyanobacteria contributed at least 40% of the primary production included in Cerithidea and Fundulus food webs. A wider range of primary producers contributed to food webs in the mature marsh. Cyanobacteria were a greater source of trophic support for macrofauna from the marsh interior than the creek bank, whereas Spartina was a more important food source for creek bank macrofauna in both marshes. Insect larvae largely consumed cyanobacteria, whereas polychaetes exhibited greater utilization of Spartina. Phytoplankton was the primary food resource for mussels in both marshes. Although the spatial and temporal complexity of food webs has traditionally been collapsed into the study of relatively simplified food webs, isotope signatures reveal fine‐scale patterns in food web structure that may be used to make more accurate assessments of ecosystem state. Accurate interpretation of marsh trophic structure using natural abundance stable isotopes requires fine‐scale resolution in space and time, a large number of samples, and a high level of taxonomic resolution.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 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".