The evolutionary species pool hypothesis and patterns of freshwater diatom diversity along a pH gradient
Bibliographic record
Abstract
Abstract Aim To interpret the unimodal relationship between diatom species richness and lake pH within the context of the evolutionary species pool hypothesis (SPH). We test the following primary prediction arising from the SPH: the size of the potential species pool (PSP) will increase along a gradient representing the historical commonness of different pH environments (pH commonness). To do this we assume that the present‐day spatial dominance of near‐neutral pH conditions compared with acidic and alkaline conditions reliably mimics the relative spatial availabilities of historical pH conditions among freshwater lakes. We also determine whether local richness represents a constant proportion of PSP size along the pH commonness gradient. Location Two hundred and thirty‐four lakes distributed over a 405,000 km2 region of the north‐eastern United States of America. Methods Sediment diatom morphospecies lists and pH data were acquired from the US Environmental Protection Agency's Environmental Monitoring and Assessment Program (EMAP) website. Using 248 morphospecies that occurred in at least 10 of the 234 lakes, four different measures of PSPs were calculated along the pH gradient. Local species richness was equated with the number of species occurring within the lake. Alpha diversity was equated with the average species richness of lakes with similar pH values. A combination of statistical methods were employed, including correlations, quadratic regression and piecewise regression. Results PSP size increased significantly with pH commonness for all four measures of PSP size, thus supporting the primary prediction of the evolutionary SPH. Local richness comprised a larger proportion of the PSP within acidic lakes than within circumneutral lakes. Alpha diversity and lake species richness both increased significantly with pH commonness, but the former did so in a two‐step fashion. We test and reject several alternative contemporary time‐scale explanations for our findings. Main Conclusions Our findings are consistent with the hypothesis that diatom taxonomic richness is presently lower within acidic and highly alkaline lakes than in circumneutral lakes owing to the limited opportunity in space and/or time for the evolution of suitably adapted species. Whereas ecological processes can explain why certain species are excluded from particular habitats, e.g. acidic lakes, they cannot account for why so few species are adapted to those habitats in the first place.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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 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".