Ecological and evolutionary response of phytoplankton to rising CO2
Bibliographic record
Abstract
Atmospheric CO2 concentration has risen to a landmark high of 400 ppm, a level not seen on earth for the past million years, and is expected to continue to increase over the course of this century. Besides its indirect effect on climate, this change will directly affect all photosynthetic organisms, including phytoplankton, through an increased availability of carbon. Through laboratory and field experiments, I investigated the ecological and evolutionary response of phytoplankton communities to rising atmospheric CO2. The rise in atmospheric CO2 is occurring at the same time as increases in the availability of a number of nutrients. In a series of mesocosm experiments in a lake, I found that elevated CO2 can act synergistically with increased nutrient availability to increase phytoplankton growth. Elevated CO2 could thus exacerbate the effect of traditional drivers of eutrophication. Major taxonomic groups of phytoplankton differ in their ability to take up and utilize CO2. In an experiment with six species of phytoplankton belonging to three major taxa (cyanobacteria, diatoms and chlorophytes), I found that these physiological differences lead to predictable changes in community dynamics. Chlorophytes, the type most limited by current CO2 levels, benefit from rising CO2 at the expense of cyanobacteria. The applicability of these findings to natural systems was confirmed in the series of mesocosm experiments. In these experiments, the increase in the frequency of chlorophytes with rising CO2 was observed at both high and low nutrient levels. The increased growth rate with the addition of nutrients and CO2, the physiological differences between major groups of phytoplankton and the associated changes in community compositions may be altered by evolutionary change after sufficiently long exposure of these organisms to elevated CO2. I tested for the probability of evolutionary change in response to elevated CO2 by exposing the previous six species and Chlamydomonas reinhardtii to elevated CO2 for over 750 generations. I found no evidence of evolutionary change, which indicates that predictions of the ecological impact of rising CO2 on phytoplankton based on the current physiology of phytoplankton will remain valid even after hundreds of generations. As phytoplankton are the base of most aquatic food webs and important drivers of the global carbon cycle, this work provides a crucial element for predicting the future state of aquatic systems and global geochemistry undergoing global change.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".