Seasonal Forest Resources Support Fish Biomass in Floodplain Lakes of an Amazonian Tributary
Bibliographic record
Abstract
ABSTRACT The Flood Pulse Concept is a foundational ecological theory that emphasizes the critical role of lateral connectivity between a river channel and its floodplain. Many tropical rivers inundate the surrounding floodplain in the flood stage, thereby receiving large amounts of terrestrial organic matter that can be decomposed by microbes and directly consumed by animals. This dynamic could simultaneously drive down oxygen concentrations while also supporting fish production. We used two lines of evidence to investigate the fate of terrestrial organic matter during the low‐ and high‐water seasons in the Juruá River, Amazonas, Brazil: spot measurements of dissolved oxygen and isotopic measurements (δ 13 C, δ 15 N) of fishes and food source pathways originating from C3 and C4 plants, phytoplankton, and periphyton. Dissolved oxygen concentrations were low (mean ≤ 3.0 mg/L) throughout the floodplain during high water, while higher values (mean = 6.5 mg/L) were evident during low water, suggesting variable rates of ecosystem respiration, production and atmospheric exchange across seasons. Most fish species, including the commercially and culturally important pirarucu ( Arapaima sp.), had a strong dependence on terrestrial C3 plants during the falling‐water season (median source proportions 34%–77%), while fishes shifted to rely on the phytoplankton pathway (median proportions 11%–82%) during low water. Our results demonstrate that terrestrial C3 plant resources are channeled into the food web through detritivorous fishes, such as bodó ( Liposarcus pardalis ), and frugivorous fishes, such as pacu ( Mylossoma aureum ). During high water, a dispersed food web takes shape as fish move into the flooded forest, driven by terrestrial resources and accompanied by low oxygen conditions. During low water, a concentrated food web emerges in the remaining oxbow lakes, consistent with fast‐growing algal resources.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".