Presence of a resident species aids invader evolution
Bibliographic record
Abstract
Abstract Interactions between phytoplankton species shape their physiological and evolutionary responses. Yet, studies addressing the evolutionary responses of phytoplankton in changing environments often lack an explicit element of biotic interactions. Here, we ask (1) how the presence of a locally adapted phytoplankton species will affect an invading phytoplankton species' evolutionary response to a physiologically challenging environment; (2) whether this response is conserved across environments varying in quality; and (3) which traits are associated with being a successful invader under climate change scenarios. In a conceptual first step to disentangle these broad questions, we experimentally evolved populations of fresh‐ and seawater phytoplankton in a novel salinity (the freshwater green algae Chlamydomonas in salt water, and the marine Ostreococcus in freshwater), either as mono‐cultures (colonizers) or as co‐cultures (invaders: invading a novel salinity occupied by a resident species, for example, Chlamydomonas invading salt water occupied by resident Ostreococcus ) for 200 generations. We superimposed a temperature treatment (control (22°C), mild warming (26°C), drastic warming (32°C), and fluctuating (22°C/32°C) warming) as a representative aspect of climate change with the potential to ameliorate or deteriorate existing environmental conditions. Invaders had systematically lower extinction rates and evolved overall higher growth rates, as well as broader salinity and temperature preferences than colonizers. The invading species' evolutionary responses differed from those of colonizers in a replicable way across environments of differing quality. The evolution of small cell size and high reactive oxygen species tolerance may explain the invaders' higher fitness under the scenarios tested here.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| 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".