Spatial factors overcome seasonality regulating the consumption of allochthonous food resources by fishes from tropical lotic ecosystems
Bibliographic record
Abstract
Abstract In lotic ecosystems, a higher availability of allochthonous food resources is expected during floods and rainfall events, which may yield a higher consumption of these resources by consumers. However, allochthonous input and seasonality in environmental conditions are locally dependent. Thus, dietary responses of freshwater consumers to seasonality should also be locally dependent. Herein, we applied a meta‐analytical approach to identify the spatial and seasonal environmental variables associated with the relative consumption of allochthonous food resources by fishes from tropical lotic ecosystems in different seasons. We gathered 566 observations of the diet of fish populations (i.e., restricted to the same sampling event) from 38 studies conducted in 70 localities across the tropics during flood and drought periods (hereafter, high‐water and low‐water periods, respectively). We retrieved latitude, seasonal channel width, elevation and two proxies for allochthonous input for each locality: terrestrial biomass (without considering seasonality) and the normalised difference vegetation index (NDVI; considering seasonality). Then, we applied meta‐regression models using these environmental variables as predictors and the proportion of allochthonous food resources in each consumer's diet (%Allo) as the response variable. Our models revealed that the diet of fishes from tropical lotic ecosystems is mostly autochthonous‐based, independent of the hydrological period (high‐water or low‐water), and aquatic invertebrates were the most consumed food items. Terrestrial vegetation biomass and elevation predicted increasing allochthony in the diet of tropical fishes for high‐water, but only terrestrial biomass predicted allochthony at low‐water periods. We found no relationship between latitude, channel width or NDVI with allochthony. Our study highlights the importance of considering the hierarchical level of biological organisation and fish trophic guilds for understanding seasonal patterns of relative consumption of allochthonous and autochthonous food resources by fishes. We also argue that variations in seasonality across the tropics are likely to have undermined its influence on allochthony in fish diets. The absence of a non‐relationship between channel width and allochthony provides evidence that the River Continuum Concept is better suited to temperate lotic ecosystems. Our results provide novel insights and the big‐picture of seasonal pattern in the diets of tropical fishes for use in future local empirical studies, improving forecasting of the relationship between the factors underpinning the availability of allochthonous and autochthonous food resources, and the diet of freshwater fishes.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.009 | 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 teacher head, 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".