Community‐level effects of co‐occurring native and exotic ecosystem engineers
Bibliographic record
Abstract
Summary 1. Non‐indigenous ecosystem engineers can substantially affect native biodiversity by transforming the physical structure of habitats. In the Great Lakes–St. Lawrence River system, introduced dreissenid mussels (Dreissena polymorpha and D. bugensis) and the native benthic macroalga Cladophora act as ecosystem engineers by increasing substratum complexity and providing interstitial habitat for benthic macroinvertebrates. 2. We manipulated the topography and perimeter‐to‐area ratio of patches of dreissenid mussels in a series of colonisation experiments conducted at two sites in the St. Lawrence River. Experimental substrata were variably colonised by Cladophora, prompting us to examine (i) how the topography of Dreissena patches affects benthic macroinvertebrate diversity and (ii) the extent to which the effects of Dreissena are altered by the presence of another habitat‐modifying organism (Cladophora). 3. The results of our first experiment suggested that a patchy distribution of dreissenid mussels is an important driver of benthic diversity at small spatial scales. The results of our second and third experiments suggested that a native habitat engineer, Cladophora, modifies the impact of Dreissena on benthic macroinvertebrate communities. 4. While macroalgal blooms have been linked to the large‐scale impacts of Dreissena on light and nutrient availability, Dreissena shells inhibited Cladophora growth at our experimental scale. These findings demonstrate that the interactions between habitat‐modifying species can complicate efforts to predict the community‐level effects of an invasion.
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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 | 0.001 |
| 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 | 0.001 | 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".