Pollen richness is not equivalent to plant species richness:
Bibliographic record
Abstract
Many modern climate variables are co-linear, which can complicate our efforts to understand patterns of plant richness. Because climate variables have varied in the past with respect to one another palaeoecological records of species richness could improve models of species richness and help with future biodiversity modeling. Fossil pollen has been used as a proxy for past plant richness but the relationship between pollen and the parent plat community is affected by the low taxonomic resolution of pollen and taphonomic processes (pollen production, transport, deposition and preservation), which may degrade the degree to which pollen accurately represents vegetation communities. By combining pollen data from modern lake sediments (n = 546; n = 167 in British Columbia, Canada) in the Pacific Northwest and a detailed data base (n = 16 071) of plant presence across British Columbia we were able to test whether pollen richness can act as a proxy for regional patterns of plant richness. Ultimately, we find that palynological richness cannot be considered a reliable proxy for inferring plant richness in British Columbia, even though changes in richness have been reported in the literature. Our findings suggest that more work is needed to understand previously reported patterns of pollen assemblage richness through time and in space. The lack of a relationship is ascribed to the process of transport, deposition and preservation of the pollen grains, rather than the taxonomic resolution of pollen with respect to parent vegetation. We suggest alternate measures for assemblages, including functional diversity or phylogenetically based analysis to help link pollen richness to plant community richness.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.004 | 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".