Risk of Facilitated Invasion Depends Upon Invader Identity, Not Environmental Severity, Along an Aridity Gradient
Bibliographic record
Abstract
Positive interactions can drive the assembly of desert plant communities, but we know little about the species-specificity of positive associations between native shrubs and invasive annual species along aridity gradients. These measures are essential for explaining, predicting, and managing community-level responses to plant invasions and environmental change. Here, we measured the intensity of spatial associations among native shrubs and the annual plant community—including multiple invasive species and their native neighbors—along an aridity gradient across the Mojave and San Joaquin Deserts, United States. Along the gradient, we sampled the abundance and species richness of invasive and native annual species using 180 pairs of shrub and open microsites. Across the gradient, the invasive annuals Bromus madritensis ssp. rubens ( B. rubens ), B. tectorum , B. diandrus, Hordeum murinum , and Brassica tournefortii were consistently more abundant under shrubs than away from shrubs, suggesting positive effects of shrubs on these species. In contrast, abundance of the invasive annual Schismus spp. was greater away from shrubs than under shrubs, suggesting negative effects of shrubs on this species. Similarly, native annual abundance (pooled) and native species richness were greater away from shrubs than under shrubs. Shrub-annual associations were not influenced by shrub size or aridity. Interestingly, we found correlative evidence that B. rubens reduced native abundance (pooled), native species richness, and exotic abundance (pooled) under, but not away from shrubs. We conclude that native shrubs have considerable potential to directly (by increasing invader abundance) and indirectly (by increasing negative impacts of invaders on neighbors) facilitate plant invasions along broad environmental gradients, but these effects may depend more upon invader identity than environmental severity.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".