Organized Oral Session 44: Impacts of Species Addition and Species Loss on Ecosystem Function in Freshwater Systems
Bibliographic record
Abstract
Understanding the role of species as drivers of ecosystem processes is imperative to preserve, utilize, and sustain ecosystems globally. Addition of species through invasion and loss of species through extirpation or extinction can have profound effects on ecosystem structure and function (Zavaleta et al. 2009). This is especially true for freshwater ecosystems in which a preponderance of native species are threatened with extinction and where nonnative species are frequently introduced (Dudgeon and Smith 2006). Commonly, anthropogenic activities result in the loss of biodiversity and enhance the ability of exotic species to invade and persist in novel habitats (Dudgeon and Smith 2006). Because these activities are expected to increase through time, advances in understanding the consequences of species loss and addition on ecosystem function are needed to guide appropriate management and conservation decisions. The loss and addition of organisms may render habitats functionally impaired (Covich et al. 2004); therefore, understanding the consequences of such change is imperative to manage, mitigate, and restore freshwater ecosystems.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.251 | 0.093 |
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".