Modern Wheat Varieties as a Driver of the Degradation of Spanish Rainfed Mediterranean Agroecosystems throughout the 20th Century
Bibliographic record
Abstract
The high grain yield of modern varieties (MV) respond to the increase in fossil-based inputs, and the widespread belief that they are more productive than old varieties (OV) is biased. This belief focuses only on marketable biomass, without considering the consequences on agroecosystem sustainability of the reductions in other portions of NPP. Additionally, field comparisons of OV and MV were normally conducted under industrialized farming conditions, which is detrimental for OV performance. Both trials carried out in this study comparing wheat OV and MV show that, under Mediterranean rainfed conditions and traditional organic management, aerial and belowground biomass production of OV is higher than that of MV, without significantly decreasing yield and enabling a better competition against weeds. From the data of our trials, bibliographic review and information from historical sources, we have reconstructed the NPP and destinations of biomass of Spanish wheat fields (1900–2000). Varietal replacement entailed the reduction in residues and unharvested biomass (UhB), which involved soil degradation in rainfed cereal fields and undermining heterotrophic trophic webs. Our results suggest that OV can increase the sustainability of rainfed Mediterranean agroecosystems at present through the improvement of soil quality, the reduction of herbicides use, and the recovery of biodiversity.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| 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".