Evaluating the definition and distribution of spring ephemeral wildflowers in eastern North America
Bibliographic record
Abstract
Abstract The herbaceous layer accounts for the majority of plant biodiversity in eastern North American forests, encompassing substantial variation in life history strategy and function. One group of early season herbaceous understory species, colloquially referred to as “spring ephemeral wildflowers,” are of particular ecological and cultural importance. Despite this, little is known about the prevalence and biogeographic patterns of the spring ephemeral strategy. Here, we used georeferenced and dated observations from the Global Biodiversity Information Facility (GBIF) to define the phenological strategies of 559 herbaceous, vascular, understory plant species in eastern North America from a composite species list encompassing 16 site-level species lists ranging from Georgia to southern Canada. Specifically, we estimated activity periods from regional observations (primarily consisting of citizen scientist iNaturalist observations) and classified species as ephemeral if they completed all aboveground activity (including leafing, flowering, fruiting, and senescence) prior to an estimated date of canopy closure derived from remote-sensed data. We then evaluated the richness of these species at the landscape scale using estimates of biogeographic and environmental drivers aggregated for 100 km x 100 km grid cells. Importantly, our spatially-explicit approach defines each species’ spring ephemerality along a continuous scale (which we call the Ephemerality Index, EI) based on the proportion of its range in which it senesces before canopy closure (with EI = 0 indicating a species that is never ephemeral and EI = 1 indicating a species that is always ephemeral). We found that 18.4% (103 species) of understory wildflowers exhibited spring ephemerality in at least part of their range, with only 3.4% of all species exhibiting ephemeral behavior in all parts of their range. Ephemeral species had higher overall richness and composed a higher proportion of understory biodiversity in low-elevation areas with intermediate spring temperatures and elevated spring precipitation. Spring ephemerals peaked in both absolute species richness and relative proportion at mid latitudes. These biogeographic patterns deserve further study in other regions of the world and to uncover mechanisms behind these patterns. Using our new metric, our results demonstrate that the spring ephemeral strategy is not a discrete category, but rather a continuum that can vary across species’ ranges.
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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) | 0.000 | 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".