Use of stable isotopes for assessing urbanization impacts on freshwater fishes
Bibliographic record
Abstract
Continued urban development is inevitable with ongoing human population growth. Urbanization has profound negative impacts on aquatic environments and the organisms that occupy those environments. Urbanization results in habitat stressors including sedimentation, alterations to flow, increases in water temperature, changes in riparian habitat, and changes in the food supply of freshwater systems. In the face of continuing urbanization there is an urgent need to employ effective and practical tools to evaluate the impacts on freshwater fish populations and to better understand the implications of urban development for lotic aquatic ecosystems. Stable isotope analyses (δ 13 C, δ 15 N, δ 18 O δ 34 S and δ 2 H) are useful and cost-effective tools that can help highlight and evaluate urbanization impacts on fish populations. Here we review recent developments in stable isotope-based methods for studying urbanization impacts on freshwater fish populations. We identified and review published studies that have implemented stable isotopes to evaluate urban impacts, discuss promising stable isotope-based approaches that have not been commonly applied to the assessment of urban impacts, and highlight the advantages and limitations of the various approaches. In particular, we show how stable isotope analyses can help address both the ecological and physiological impacts of urban development on freshwater fishes in hopes of inspiring more frequent use of the approaches in urbanization studies. We elucidate how stable isotopes can be used to understand the impacts of urbanization on the feeding ecology, habitat and thermal occupancy, and field metabolic rates of freshwater fishes. It was found that stable isotope-based approaches are underutilized to examine the impacts of urbanization on freshwater fishes. We suggest such approaches can be applied more frequently in freshwater environments globally to help assess and actively mitigate the negative impacts of urbanization on 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 | 0.001 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 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".