Intrinsic time dependence in the diversity–invasibility relationship
Bibliographic record
Abstract
Contrasting patterns in the diversity-invasibility relationship have intrigued ecologists for many years, and are now known as the "invasion paradox." Experiments usually detect negative relationships, while field surveys find them to be positive. It is widely believed that the paradox is driven by differences in spatial scale, but this is challenged by field surveys that find positive relationships at all spatial scales. If factors that determine invasion dynamics change during the invasion process, the paradox may be partially driven by differences in temporal scale. Here we used simulation (cellular automata) models to explore the generality of temporal change in the diversity-invasibility relationship. The probability of invaders colonizing an area was inversely related to the density of natives, creating a negative native-exotic correlation when invaders first arrived. Over time, native and exotic populations were both shaped by the same post-introduction processes (disturbance, dispersal, and recolonization), shifting their correlation to positive. The rate of temporal change in the diversity-invasibility relationship was mainly dependent upon the fecundity of invaders. Greater fecundity meant that invaders spread through the landscape faster and were subject to post-introduction processes sooner. We propose a unified conceptual model where the diversity-invasiblity relationship is a function of both spatial and temporal scales.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.008 |
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; both teacher heads agree on what is shown here.
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".