Functional differentiation accompanies taxonomic homogenization in freshwater fish communities
Bibliographic record
Abstract
The addition of nonnative species and loss of native species has modified the composition of communities globally. Although changes in β-diversity have been well documented, there is a need for studies incorporating multiple time periods, more than one dimension of biodiversity, and inclusion of nestedness and turnover components to understand the underlying mechanisms structuring community composition and assembly. Here, we examined temporal changes in functional dissimilarity of fish communities of the Laurentian Great Lakes and compared these changes to those of taxonomic dissimilarity by decade from 1870 to 2010. Jaccard-derived functional dissimilarity index was used to quantify changes in functional β-diversity within communities, between all possible pairs of communities, and using a multiple-site index among all communities. β-diversity was partitioned into components of nestedness and turnover, and changes were examined over time. Similar to patterns in taxonomic dissimilarity, each community functionally differentiated from the historical community of 1870, with Lake Superior changing the most (~24%) and Lake Ontario the least (~14%). Although communities have become taxonomically homogenized, functional β-diversity among all communities has increased over time, indicating functional differentiation. This is likely due to functional similarity between the communities being historically high (i.e., ~88% similar in 1870). The higher taxonomic relative to functional turnover indicates that the species being replaced between communities are functionally redundant, which could occur given the harsh environmental conditions of the region and/or as a result of the recent glacial history of the region. High functional nestedness across communities reflects dispersal limitations, with smaller communities being functional subsets of large communities closer to source populations. The functional differentiation observed is likely due to nonnative species with functional traits unique to the region establishing or the loss of functionally redundant native species; however, it is important to note that patterns of homogenization were periodically observed through time. Our study demonstrates the possible factors regulating diversity in the Laurentian Great Lakes fish communities, that patterns of taxonomic and functional β-diversity are dynamic over time and vary in the magnitude and direction of change, and that taxonomic diversity should not be used to predict changes in functional diversity.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".