Testing the Mechanisms by Which Source‐Sink Dynamics Alter Competitive Outcomes in a Model System
Bibliographic record
Abstract
Dispersal among sites can affect within-site competitive outcomes via source-sink dynamics. Source-sink dynamics are thought to affect competitive outcomes primarily via spatial subsidies: by redistributing individuals from sources to sinks, source-sink dynamics can alter competitive outcomes in both sources and sinks. However, dispersal also can affect competitive outcomes via demography modification, which occurs when dispersal alters the parameters governing species' per capita demographic rates. For instance, dispersal of exploitative competitors might cause extinction of some of the resources for which competition occurs, thereby altering the competition coefficients. I used protist microcosms as a model system to test whether spatial subsidies alone could explain the effects of source-sink dynamics on competitive outcomes. I examined the long-term outcome of exploitative competition among three bacterivorous ciliate protists in microcosms of high enrichment (sources) and low enrichment (sinks) in both the presence and the absence of dispersal. Dispersal altered competitive outcomes. Fitting mathematical models to the population dynamics revealed that spatial subsidies were insufficient to account for the effects of dispersal. Fitting alternative models strongly suggested that demography modification was an important determinant of competitive outcomes. These results provide the first evidence that dispersal does not simply redistribute competitors but can alter their per capita demographic rates.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".