Latitudinal shift in the timing of flowering of tree species across tropical Africa: insights from field observations and herbarium collections
Bibliographic record
Abstract
Abstract Temporal and spatial patterns in flowering phenology were assessed for eight tropical African tree species. Specifically, the frequency and seasonality of flowering at seven sites in central Africa were determined using field data, graphical analysis and circular statistics. Additionally, spatial variation in the timing of flowering across species range was investigated using herbarium data, analysing the relative influence of latitude, longitude and timing of the dry season with a Bayesian circular generalized linear model. Annual flowering was found for 20 out of the 25 populations studied. For 21 populations located at the north of the climatic hinge flowering was occurring during the dry season. The analysis of herbarium collections revealed a significant shift in the timing of flowering with latitude forE. suaveolens, and with the timing of the dry season forM. excelsa(and to a lesser extentL. alata), with the coexistence of two flowering peaks near the equator where the distribution of monthly rainfall is bimodal. For the other species, none of latitude, longitude or timing of the dry season had an effect on the timing of flowering. Our study highlights the need to identify the drivers of the flowering phenology of economically important African tree species.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".