Spatial factors overcome seasonality in increasing the consumption of allochthonous food resources by fishes from tropical lotic ecosystems
Bibliographic record
Abstract
1. In lotic ecosystems, it is expected higher availability of allochthonous food resources during floods and rainfall events, which may yield a higher consumption of these resources by consumers. However, both the allochthonous input in aquatic ecosystems and seasonality in environmental conditions are locally dependent, thus dietary responses of freshwater consumers to seasonality should also be local-dependent. Herein, we apply a meta-analytical approach to unraveling which environmental variables drive the seasonal relative consumption of allochthonous food resources by fishes from tropical lotic ecosystems.2. We gathered 656 observations of the diet of fish populations (i.e., restricted to the same sampling event) from 83 localities across the tropics during flood and drought periods (hereafter, high-water and low-water periods, respectively). For each locality, we retrieved latitude, channel width, terrestrial biomass, and elevation. Then, we applied meta-regression models using the environmental variables as fixed effects and the proportion of allochthonous food resources in the diet of each observation (%Allo) as the response variable.3. Our models revealed that the diet of fish from tropical lotic ecosystems is mostly autochthonous independently of the hydrological period (high-water or low-water), with the predominance of aquatic invertebrates consumed. Terrestrial biomass and elevation were revealed as the main predictors of increasing allochthony also for both high-water and low-water periods. However, we did not find any relationship between latitude and channel width with allochthony.4. Our results highlight the importance of considering scale dependence for understanding the seasonal relative consumption of allochthonous and autochthonous food resources by fish. The little importance of seasonality when compared to spatial factors (terrestrial biomass and elevation) in increasing allochthony, is probably due to the different effects of seasonality across tropical lotic ecosystems and unseasonal rain in the tropics. Lastly, the non-relationship between channel width and allochthony may be one piece of evidence that the River Continuum Concept is better suited to temperate lotic ecosystems. 5. This study is an initial endeavor to gather fragmented information in a meta-analysis on this subject. Our results give novel insights and may serve as a new big-picture source of knowledge for future local empirical studies, improving the forecasting of the relationship between the factors underpinning the availability of allochthonous and autochthonous food resources and the diet of freshwater consumers.
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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) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".