Similarities between invaders and native species: Moving past Darwin's naturalization conundrum
Bibliographic record
Abstract
Abstract Darwin's naturalization conundrum states that successful invaders must be closely related to native species to possess the traits to tolerate that environment, but distantly related enough to possess traits allowing exploitation of underutilized niches, thereby minimizing competition. Although influential, this hypothesis is based on several simplistic assumptions. In particular, the relationship among phylogenetic relatedness, similarity, and competition is more complex than assumed and changes with spatial and phylogenetic scale. Competitive interactions are determined by limiting similarity and trait hierarchies associated with separate traits. Successful invaders thus need to be similar to native species in some respects, but different in others. This combination of similarities and differences is unlikely to be conserved. Further, many invasive species are represented in their novel range by genotypes with extreme trait values or plasticity relative to the species mean. Selection for these genotypes may alter the similarity between invasive and native species, thus obscuring the relationship between competition and phylogenetic relatedness. As environmental filtering and competition often act on different spatial scales, approaches assessing how individual traits relate to invasion at these scales (species pools vs local community) may improve our understanding of the relationship between similarity and invasion.
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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 | 0.002 |
| 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".