Reservoir ecosystems support large pools of fish biomass
Bibliographic record
Abstract
Abstract Humans increasingly dominate Earth’s natural freshwater ecosystems, and many freshwater fisheries resources are imperiled and at-risk of collapse. Yet despite this, the productive capacity of intensively modified freshwater ecosystems is rarely studied. We digitized, and provide open access to, a legacy database containing empirical fish biomass from 1,127 surveys on 301 USA reservoirs. In parallel, we developed a slate of reservoir classification schemas that were deployed to better understand distributions of biomass and secondary production. By fusing these data products, we generated a predictive capacity for understanding the scope of fisheries biomass and secondary production across all USA reservoirs. We estimate total potential fish total standing stock in USA reservoirs is 3.4 billion (B) kg, and annual secondary production is 4.5 B kg y -1 . In southern USA alone, total standing stock and secondary production are 1.9 B kg and 2.5 B kg y -1 , respectively. We also observe non-linear trends in reservoir fish production and biomass over time, indicating that these ecosystems are quite dynamic. Results demonstrate that reservoirs represent globally relevant pools of freshwater fisheries, in part due to their immense spatial and limnetic footprint. This study further shows that reservoir ecosystems play major roles in food security, and fisheries conservation, even though they are frequently overlooked by freshwater scientists. We encourage additional effort be expended to effectively manage reservoir environments for the good of humanity, biodiversity, and fishery conservation. Significance Statement Globally, many freshwater fishes and fisheries resources are imperiled and at-risk of collapse. However, previous research overwhelmingly focuses on freshwater fisheries in natural rivers and lakes. This study provides evidence that novel and reconciled ecosystems, such as reservoirs, hold massive pools of freshwater fisheries biomass and may have higher ecological value than previously thought. While dams are patently ecological catastrophes, ecosystem services including secondary fish production provided by reservoirs are nonetheless substantial. Indeed, in many locations (e.g., arid regions), reservoirs are the only remaining fisheries resource. We suggest considerable conservation management is warranted for reservoir fisheries worldwide. Data Deposition Code is available on GitHub ( https://github.com/caparisek/res_biomass_USA ; DOI 10.5281/zenodo.8316696). All data and reservoir classifications are available on Zenodo (DOI 10.5281/zenodo.8317007). Furthermore, data will also be deposited in the Environmental Data Initiative repository upon acceptance of this manuscript.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".