Assessing changes in biomass, productivity, and C and N stores following<i>Juniperus virginiana</i>forest expansion into tallgrass prairie
Bibliographic record
Abstract
An increase in woody plant abundance in regions historically dominated by grasses is a recent land cover change in grasslands worldwide. In tallgrass prairies of North America, this increase in woody plant cover includes the development of dense stands of eastern redcedar (Juniperus virginiana L.). To evaluate the consequences of this ongoing land cover change for ecosystem functioning, we developed allometric equations, using data from Kansas and Oklahoma, to estimate aboveground biomass and productivity in closed-canopy redcedar stands. We then applied these equations to three closed-canopy redcedar stands, 3580 years old, which developed on sites formerly dominated by tallgrass prairie in eastern Kansas. Aboveground plant biomass for these redcedar-dominated sites ranged from 114 100 kg/ha for the youngest stand to 210 700 kg/ha for the oldest. Annual aboveground net primary productivity (ANPP) ranged from 7250 to 10 440 kg·ha1·year1for the oldest and younger redcedar stands, respectively. Estimates of ANPP in comparable tallgrass prairie sites in this region average 3690 kg·ha1·year1indicating a large increase in C uptake and aboveground storage as a result of the change from prairie to redcedar forests. Therefore, the widespread occurrence of redcedars across the woodlandprairie ecotone suggests that this land-cover change may have important consequences for regional net C storage.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 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".