Phenological responses to climate in the Alberta native flora: Herbarium specimens reveal differential responsiveness between species in mesic and xeric habitats
Bibliographic record
Abstract
The field of phenology focuses on investigating the timing of biological events and phases of life cycles. In the face of projected and ongoing climate change, there is a growing interest in detecting the effects of climate change on plant phenology. This research focuses on using herbarium specimens to examine whether 14 native plant species in Alberta have adjusted to changes in temperature and precipitation over the past century. I hypothesize that the soil moisture to which plants are exposed might affect their phenological responses and investigate: if herbaria collections contain evidence of phenological responses to climate in species of the Alberta flora, and if the responses are dependent on the typical moisture regime of their habitat. Plants from mesic and xeric habitats are compared in terms of phenological responses to air temperature and precipitation. The taxonomic relationships between the species were taken into account, by selecting a total of 14 species representing seven different angiosperm orders (one pair of species for each order). For each selected species, the preserved specimens available at three major Albertan herbaria collections were included in the study, if showing more than 50% of flower buds in anthesis (defined as peak flowering). The peak flowering date of each specimen, combined with the average temperature (or total precipitation) of the species’ mean flowering month and the three months prior, allowed the use of a regression model for the estimation of a species’ phenological responsiveness. The linear multiple regression analysis has revealed a significant responsiveness to temperature for six species from xeric habitats and one species from mesic habitats. My results suggest that species from xeric habitats have an average phenological responsiveness to temperature significantly more pronounced than species from mesic habitats. This tendency might be explained by the thermal properties of mesic habitats. The results indicate that for some species there is a set of environmental cues, as opposed to only one parameter, that governs flowering timing. The elucidation of the ecological implications involving plants phenological responses is key for the development of effective ecosystem conservation programs in the context of global climate 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".