Ten‐year trends reveal declining quality of seeded pollinator habitat on reclaimed mines regardless of seed mix diversity
Bibliographic record
Abstract
Plant-pollinator interactions represent a crucial ecosystem function threatened by anthropogenic landscape changes. Disturbances that reduce plant diversity are associated with floral resource and pollinator declines. Establishing wildflower plantings is a major conservation strategy targeting pollinators, the success of which depends on long-term persistence of seeded floral communities. However, most pollinator-oriented seeding projects are monitored for a few years, making it difficult to evaluate the longevity of such interventions. Selecting plant species to provide pollinators diverse arrays of floral resources throughout their activity season is often limited by budgetary constraints and other conservation priorities. To evaluate the long-term persistence of prairie vegetation seeded to support pollinators, we sowed wildflower seed mixes into plots on a degraded reclaimed strip-mine landscape in central Ohio, USA. We examined how pollinator habitat quality, measured as floral abundance and diversity, changed over 10 years (2009-2019) in the absence of management, over the course of the blooming season within each year, and across three seed mixes containing different numbers and combinations of flowering plant species. Seeded species floral abundance declined by more than 75% over the study, with the largest decline occurring between the fifth and seventh summers. Native and non-native adventive flowering plants quickly colonized the plots and represented >50% of floral community abundances on average. Floral richness remained relatively constant throughout the study, with a small peak one year after plot establishment. Plots seeded with High-Diversity Mixes averaged two or three more species per plot compared with a Low-Diversity Mix, despite having been seeded with twice as many plant species. Within years, the abundance and diversity of seeded species were lowest early in the blooming season and increased monotonically from June to August. Adventive species exhibited the opposite trend, such that complementary abundance patterns of seeded and adventive species blooms resulted in a relatively constant floral abundance across the growing season. Seeded plant communities followed classic successional patterns in which annual species quickly established and flowered but were replaced by perennial species after the first few summers. Long-term data on establishment and persistence of flower species can guide species selection for future-oriented pollinator habitat restorations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 teacher head, 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".