Limitations and strengths of indicators for evaluating the nitrogen status of forest ecosystems
Bibliographic record
Abstract
Anthropogenic nitrogen (N) deposition has increased N availability in many forest ecosystems. In contrast, global changes such as elevated atmospheric CO 2 , longer growing season under warming, and increased precipitation may stimulate plant growth, intensifying biotic demand for N. These diverging trends influence the N status of forests, reflecting the balance between N supply and demand and indicating whether a forest is in a state of N limitation, transition phase, or N saturation. Numerous direct and indirect indicators are used to evaluate forest N status. However, an overview of their effectiveness for N status assessments, which require established threshold values between different phases, is limited. Here, we review N status indicators and their threshold values to evaluate their effectiveness in revealing changes in forest N status. In addition, we assess whether indicators provide insights into forest health conditions such as defoliation, nutritional status, species richness of the forest understory, the prevalence of diseases, and forest growth dynamics. The N status indicators included are categorized as tree-related (N content of foliage, foliage or nutrient ratios particularly N:P, natural 15 N abundance (δ 15 N) of foliage and wood), soil-related (soil C:N, inorganic N concentrations, N transformation rates, δ 15 N of soil, enrichment factor), and ecosystem-related (litterfall N flux, nitrate leaching, and N 2 O emissions). Our synthesis suggests that while most indicators are useful to assess N availability, the majority lack clearly defined thresholds to identify N saturation and N limitation. Similarly, we found that the majority of indicators cannot be used for assessing forest health conditions. As most indicators assess specific components of the forest N cycle, a comprehensive assessment of forest N status requires combining indicators to evaluate changes in multiple N cycling processes. This review guides the selection of indicators for assessing forest N status by evaluating their effectiveness in detecting N saturation or limitation, reflecting forest health conditions, responsiveness to N deposition, and the required research effort.
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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 | 0.061 | 0.149 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".