What Are the Drivers of Fatty Acid Production? Analysis of Phylogenetic Signals and Other Key Factors
Bibliographic record
Abstract
Essential fatty acids such as Omega-3s and Omega-6s are key nutrients in supporting individual and ecosystem health. Currently, many essential fatty acids for humans are derived from fish and shellfish; however, growing human populations and declining fish and shellfish populations threaten access to these fatty acids and thus nutritional food security. I predicted that bioprospecting (i.e., the search for chemicals in plants or animals) for essential fatty acids in plants can alleviate some harvesting pressure on aquatic ecosystems and provide new sources of plant-derived essential fatty acids. Understanding the distribution and patterns associated with fatty acid production in plants is the first step to achieving this. Using a meta-analytic approach allowed me to include a wide variety of taxa in the analysis. I used phylogenetic signal analysis to map fatty acid profiles, including both presence and abundance of particular and important groups of essential fatty acids, onto a plant phylogeny encompassing algae, bryophytes, ferns and their allies, gymnosperms, and angiosperms. Additionally, I explored how other factors including cultivation status, tissue, and climate were related to changes in fatty acid production to identify potential drivers of fatty acid production and provide guidance to bioprospecting endeavors. My phylogenetic signal analysis revealed that production of most key fatty acids was randomly or ubiquitously distributed, while the concentration of most key fatty acids (including eicosapentaenoic, docosahexaenoic, and nervonic acid) was significantly clustered in specific clades. Fatty acid content differed significantly between crops and non-crops, as well as among tissues of angiosperms, ferns, and bryophytes for some key fatty acids. Climate (via latitude and global climate deviations) also had significant effects on groups of fatty acids (saturated, unsaturated, mono-unsaturated, and poly-unsaturated fatty acids). In summary, I present new evidence for the roles of phylogeny, climate, cultivation status, and tissue source in the production of key fatty acids in plants using a meta-analytic and phylogenetic signal analysis approach, exploring the evolutionary and environmental contexts that facilitate the production of fatty acids in plants.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".