The Relative Importance of Population Size, Colonist Quality, and Colonist Arrival Frequency for Population Success
Bibliographic record
Abstract
Successful population establishment, subsequent population dynamics, and extinction have all repeatedly been shown to be affected by the quantity of initial colonists. However, there are other, less studied factors that could determine population success, including the physiological condition in which colonists arrive (‘quality’), and the frequency with which they arrive (‘arrival frequency’). While all of these factors can individually drive the dynamics and extinction of new populations, we do not understand which has the strongest influence, nor the circumstances under which their relative importance may change. In this thesis, I examined the importance of different combinations of colonizer characteristics for population success, and how their importance varied between species and individuals. In my first experiment, I showed that population size, not arrival frequency, was the primary factor determining the survival and performance of introduced populations of Hemimysis anomala. In my second experiment, I found that the population dynamics of Daphnia pulicaria were only influenced by colonist quality, while the establishment of Skistodiaptomus oregonensis was more strongly influenced by arrival frequency. Finally, I showed that the benefits of increasing colonist quantity and genetic diversity can change based on colonist identity. For some Daphnia pulex colonists, higher quantities or genetic diversities improved their success, while in others there was little effect. I also conducted an additional project that examined the mechanisms driving human-mediated dispersal. Colonization is a shared and integral process across ecological disciplines, and our current understanding of the mechanisms involved is founded on research of both ‘natural’ and ‘human-mediated’ colonization. This project integrates the biological- and human-based processes involved in human-mediated dispersal, and develops a general framework outlining the mechanisms that determine which individuals enter, survive, and exit from human vectors. Overall, my work highlights the necessity of considering multiple colonist characteristics, and pre-arrival processes, to understand, predict, and control colonization, and that the value of particular characteristics is not necessarily consistent across species and individuals.
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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 | 0.004 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".