Linking environmental gradients, species composition, and vegetation indicators of sugar maple health in the northeastern United States
Bibliographic record
Abstract
Sugar maple ( Acer saccharum Marsh.) decline has occurred throughout its range over the past 50 years, although decline symptoms are minimal where nutritional thresholds of Ca, Mg, and Mn are met. Here, we show that availability of these elements also controls vascular plant species composition in northern hardwood stands and we identify indicator species of these nutrient thresholds. Presence and abundance of vascular plant species and data on 35 environmental variables were collected from 86 stands in New Hampshire and Vermont (NHVT) and Pennsylvania and New York (PANY). Nonmetric multidimensional scaling ordination was used to determine which variables affected presence and abundance of species; both measures gave similar results. A base cation – acid cation nutrient gradient on axis one accounted for 71.9% (NHVT) and 63.0% (PANY) of the variation in the nonmetric multidimensional scaling ordination. Measures of Ca, Mg, and pH formed the base end and Al, Mn, K, soil acidity, and organic matter the acid end in both subregions. In both subregions, sugar maple foliar Mg and Ca had the strongest association with the base end of axis 1; exchangeable Al in NHVT and foliar Mn in PANY were strongly associated with the acid end. McNemar’s exact test and indicator species analysis were used to determine which species were present in stands that met the nutritional thresholds for Ca, Mg, and Mn foliar chemistry. McNemar’s exact test identified 16 species in NHVT and PANY, 16 additional species in NHVT only, and 12 additional species in PANY only. Indicator species analysis identified a subset of these species with the highest frequency of occurrence. Indicator species could provide land managers with a diagnostic tool for determining where on the landscape sugar maple is “at risk” or likely to remain healthy in the face of stresses.
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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 | 0.000 | 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".