Effects of Agricultural Stressors on Growth and an Immune Status Indicator in Wood Frog (<i>Lithobates sylvaticus</i>) Tadpoles and Metamorphs
Bibliographic record
Abstract
Abstract Like many amphibians, wood frog (Lithobates sylvaticus) populations have likely declined or experienced local extirpations as a result of habitat alterations. Despite this, wood frogs are still present and breeding in altered landscapes, like the agricultural Prairie Pothole Region of central Canada, and are exposed to a variety of anthropogenic impacts. As tadpoles, water contamination can have negative effects on growth, development, and immune systems. To investigate the potential effects of agricultural land use on tadpole growth and immune system stress, we used boosted regression trees to model body mass, body condition, and neutrophil to lymphocyte ratios, a measure of immune stress, against 32 variables including water quality, wetland habitat, and landscape-level measures. Developmental stage strongly influenced all 3 endpoints, and body mass was negatively influenced by higher levels of total dissolved solids (>600–700 mg/L) and at the first sign of pesticide detection (>0.01 proportion pesticides detected of those screened). While correlative, these data suggest that tadpoles developing in agricultural environments may experience survival and reproductive disadvantages if they metamorphose at smaller body sizes. Given the potential impacts this can have on adult frogs and frog populations, these results provide an impetus for further field-based investigation into the effects that pesticides, and especially total dissolved solids, may have on tadpoles. Environ Toxicol Chem 2021;40:2269–2281. © 2021 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC. Abstract A graphical summary illustrating the effects of certain water quality variables on tadpole mass (including metamorph mass, but metamorphs are not illustrated). Concentrations of total dissolved solids greater than approximately 600 to 700 mg/L and proportion of pesticides detected >0.01 were associated with lower mass. Ammonia concentrations of approximately 0.5 to 0.75 mg/L and wetland surface area between 4000 and 6000 m2 had small positive effects on mass. TDS = total dissolved solids; Prop. = proportion; DN-Amm = dissolved nitrogen-ammonia; SA = surface area.
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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 | 0.000 | 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) | 0.001 | 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".