Plant networks are more connected by invasive brome and native shrub facilitation in Central California drylands
Bibliographic record
Abstract
Dominant vegetation in many ecosystems is an integral component of structure and habitat. In many drylands, native shrubs function as foundation species that benefit other plants and animals. However, invasive exotic plant species can comprise a significant proportion of the vegetation. In Central California drylands, the facilitative shrub Ephedra californica and the invasive Bromus rubens are widely dispersed and common. Using comprehensive survey data structured by shrub and open gaps for the region, we compared network structure with and without this native shrub canopy and with and without the invasive brome. The presence of the invasive brome profoundly shifted the network measure of centrality in the microsites structured by a shrub canopy (centrality scores increased from 4.3 under shrubs without brome to 6.3, i.e. a relative increase of 42%). This strongly suggests that plant species such as brome can undermine the positive and stabilizing effects of native foundation plant species provided by shrubs in drylands by changing the frequency that the remaining species connect to one another. The net proportion of positive and negative associations was consistent across all microsites (approximately 50% with a total of 14% non-random co-occurrences on average) suggesting that these plant-plant networks are rewired but not more negative. Maintaining resilience in biodiversity thus needs to capitalize on protecting native shrubs whilst also controlling invasive grass species particularly when associated with shrubs.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".