Shifting community composition determines the biodiversity–productivity relationship under increasing precipitation and N deposition
Bibliographic record
Abstract
Abstract Questions The relationships between biodiversity and ecosystem functioning (BEF) vary largely across natural ecosystems, with a unimodal, monotonous linear or no relationship. However, it remains unclear how BEF relationships vary under global change. Given future predicted changes in precipitation and nitrogen (N) deposition, it is crucial to determine how precipitation change and N deposition affect grassland biodiversity and productivity, and regulate their relationships. Location A Dry Mixed‐Grass Prairie of western Canada. Methods We established a manipulative field experiment of increased precipitation (water addition with approximately 15% and 30% more monthly precipitation) and N addition (10 g/m 2 ) using a randomized complete block design, including six treatments, each replicated five times (30 plots). We conducted vegetation sampling with a 1 m × 1 m quadrat in each plot from 2016 to 2017, to examine the individual and interactive effects of water and N addition on plant diversity, functional group composition, above‐ and below‐ground productivity, and the diversity–productivity relationships. Results We found a positive linear diversity–above‐ground biomass (AGB) relationship under increased precipitation, which was attributed to the water‐induced increase in the abundance of forbs in the plant community, further promoting the positive effect of plant diversity on AGB. However, N addition caused a negative linear diversity–AGB relationship by increasing AGB and reducing plant diversity. The effects of N on diversity and productivity can be further strengthened under increased precipitation, which was due to the increase of C 3 rhizomatous grasses with high above‐ and below‐ground biomass and the decrease of forbs with high richness. Conclusions Our results suggest that changes in functional group composition determine the plant species’ diversity, productivity, and their relationships under increasing precipitation and N deposition, which has significant implications for understanding and modelling ecosystem productivity in the context of global change.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".