Temporal dynamics of taxonomic homogenization in the fish communities of the Laurentian Great Lakes
Bibliographic record
Abstract
Abstract Aim As a result of the loss of native species and the spread of non‐native species, fish communities are becoming increasingly homogenous globally. In the Laurentian Great Lakes, 21 native fish species have been extirpated from one or more lakes as a result of habitat alteration and destruction, overexploitation and invasive species since the 1800s. Over the same time period, 30 non‐native species became established in at least one lake as a result of authorized and unauthorized introductions. This study examines temporal changes in taxonomic dissimilarity over 15 time periods spanning the last 150 years. Location Laurentian Great Lakes, North America. Methods Changes to the Great Lakes fish fauna were summarized in species lists by decade from 1870 to 2010. Taxonomic dissimilarity between and within communities was calculated using Jaccard's dissimilarity coefficient; the relative contribution of turnover (species replacement) and nestedness (species loss) to total taxonomic dissimilarity was also calculated. To test whether the Great Lakes have homogenized, we conducted a regression on multiple‐site dissimilarity values over time. Results Native species richness in the Great Lakes exhibits a latitudinal gradient that reflects post‐glacial history and current climate. We demonstrate that the establishment of non‐native species and extirpation of native species has changed fish communities in each of the Great Lakes, with communities in Lake Superior differentiating the most (~23%) and in Lake Ontario the least (~12%) since 1870. Multiple‐site dissimilarity ranges between ~50% and 53% per decade, and communities have become ~5.9% more similar over time since 1870. Main Conclusions Species introductions and extirpations have changed community composition, resulting in the fish communities becoming significantly more similar to one another over time and, thus, homogenized. As a result, ongoing management should prevent range expansion of native and non‐native species to preserve the current distinctiveness of the Great Lakes fish communities.
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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 | 0.000 | 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".