The success of assisted colonization and assisted gene flow depends on phenology
Bibliographic record
Abstract
Global warming will jeopardize the persistence and genetic diversity of many species. Assisted colonization, or the movement of species beyond their current range boundary, is a conservation strategy proposed for species with limited dispersal abilities or adaptive potential. However, species that rely on photoperiodic and thermal cues for development may experience conflicting signals if transported across latitudes. Relocating multiple, distinct populations may remedy this quandary by expanding genetic variation and promoting evolutionary responses in the receiving habitat--a strategy known as assisted gene flow. To better inform these policies, we planted seeds from latitudinally distinct populations of the annual legume, Chamaecrista fasciculata, in a potential future colonization site north of its current range boundary. Plants were exposed to ambient or elevated temperatures via infrared heating. We monitored several life history traits and estimated patterns of natural selection to determine the adaptive value of plastic responses. To assess the feasibility of assisted gene flow between phenologically distinct populations, we counted flowers each day and estimated the degree of temporal isolation between populations. Increased temperatures advanced each successive phenological trait more than the last, resulting in a compressed life cycle for all but the southern-most population. Warming altered patterns of selection on flowering onset and vegetative biomass. Population performance was dependent on latitude of origin, with the northern-most population performing best under ambient conditions and the southern-most performing most poorly, even under elevated temperatures. Among-population differences in flowering phenology limited the potential for genetic exchange among the northern- and southern-most populations. All plastic responses to warming were neutral or adaptive; however, photoperiodic constraints will likely necessitate evolutionary responses for long-term persistence, especially when involving populations from disparate latitudes. With strategic planning, our results suggest that assisted colonization and assisted gene flow may be feasible options for preservation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".