Flowering phenology in subalpine meadows: Does climate variation influence community co‐flowering patterns?
Bibliographic record
Abstract
Climate change is expected to alter patterns of species co-occurrence, in both space and time. Species-specific shifts in reproductive phenology may alter the assemblages of plant species in flower at any given time during the growing season. Temporal overlap in the flowering periods (co-flowering) of animal-pollinated species may influence reproductive success if competitive or facilitative interactions between plant species affect pollinator services. We used a 33-year data set on flowering phenology in subalpine meadows in Colorado, USA, to determine whether interannual variation in snowmelt date, which marks the start of the growing season, affected co-flowering patterns. For two of four species considered, we found a significant relationship between snowmelt timing and composition of the assemblage of co-flowering plants. In years of early snowmelt, Lathyrus lanszwertii var. leucanthus (Fabaceae), the species we investigated in most detail, tended to overlap with earlier-flowering species and with fewer species overall. In particular, overlap with the flowering period of Lupinus polyphyllus var. prunophilus, with which Lathyrus leucanthus shares pollinators, was significantly reduced in early-snowmelt years. The observed association between timing of snowmelt and patterns of flowering overlap could not have been predicted simply by examining temporal trends in the dates of peak flowering of the dominant species in the community, as peak flowering dates have largely shifted in parallel with respect to snowmelt date. However, subtle interspecific differences in responsiveness of flowering time, duration, and intensity to interannual climate variation have likely contributed to the observed relationship. Although much of the year-to-year variation in flowering overlap remains unexplained by snowmelt date, our finding of a measurable signal of climate variation suggests that future climate change may lead to altered competitive environments for these wildflower 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 | 0.000 | 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".