Canopy gap size influences niche partitioning of the ground-layer plant community in a northern temperate forest
Bibliographic record
Abstract
The Gap Partitioning Hypothesis (GPH) posits that gaps create heterogeneity in resources crucial for tree regeneration in closed-canopy forests, allowing trees with contrasting strategies to coexist along resource gradients. Few studies have examined gap partitioning of temperate, ground-layer vascular plants. We used a ground-layer plant community of a temperate deciduous forest in northern Wisconsin, USA, as a model system to test whether the GPH extends to the relatively species-rich ground layer. We used a well-replicated experimental approach that included a gap opening gradient (five gap sizes, 6, 10, 20, 30 and 46 m diameter, and undisturbed reference areas), a within-gap location gradient (gap edge to center), and a temporal gradient (0, 2, 6 and 13 years after gap creation). The data were observations of ground-layer plant abundance, published plant traits, and a modeled index of understory light environments. We ordinated the plant abundance data and evaluated the relationships of composition, traits and light environment by gap size, location along the forest-gap transect and time, with several approaches such as correlations, descriptivestatistics, non-parametric tests of group differences and indicator species importance values. Ground-layer plant composition and traits differed across gap sizes, within-gap locations and over time. Gaps of all sizes differed in composition from undisturbed areas, and all pair-wise combinations of gap size also differed in composition, except the 6 m from the 10-m gaps. Large gaps (46 m) also displayed within-gap compositional gradients from gap edge to center locations. Compositional differences in gap size were evident 2 years after gap creation and, contrary to our hypotheses, remained different over the 13-year period, even in gaps with crown closure. In contrast to the neutral theory, species functional traits and microenvironmental conditions were related to variation in ground-layer composition. Species with smaller seeds, lower shade tolerance, later bloom times, shorter stature and longer leaves were associated with higher light, more central gap locations, larger gap sizes and greater time since gap creation. The correlation between gap size and ground-layer plant composition and traits provides evidence for gap partitioning by the diverse ground-layer community in this temperate deciduous forest community.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".