Urbanized landscapes favored by fig‐eating birds increase invasive but not native juvenile strangler fig abundance
Bibliographic record
Abstract
Propagule pressure can determine the success or failure of invasive plant range expansion. Range expansion takes place at large spatial scales, often encompassing many types of land cover, yet the effect of landscape context on propagule pressure remains largely unknown. Many studies have reported a positive correlation between invasive plant abundance and human land use; increased propagule pressure in these landscapes may be responsible for this correlation. We tested the hypothesis that increased rates of seed dispersal by fig-eating birds, which are more common in urban habitats, result in an increase in invasive strangler fig abundance in landscapes dominated by human land use. We quantified abundance of an invasive species (Ficus microcarpa) and a native species (F. aurea) of strangler fig in plots spanning the entire range of human land use in South Florida, USA, from urban parking lots to native forest. We then compared models that predicted juvenile fig abundance based on distance to adult fig seed sources and fig-eating bird habitat quality with models that lacked one or both of these terms. The best model for juvenile invasive fig abundance included both distance to adult and fig-eating bird habitat terms, suggesting that landscape effects on invasive fig abundance are mediated by seed-dispersing birds. In contrast, the best model for juvenile native fig abundance included only presence/absence of adults, suggesting that distance from individual adult trees may have less effect on seed limitation for a native species compared to an invasive species undergoing range expansion. However, models for both species included significant effects of adult seed sources, implying that juvenile abundance is limited by seed arrival. This result was corroborated by a seed addition experiment that indicated that both native and invasive strangler figs were strongly seed limited. Understanding how landscape context affects the mechanisms of plant invasion may lead to better management techniques. Our results suggest that prioritizing removal of adult trees in sites with high fig-eating bird habitat may be the most effective method to control F. microcarpa abundance.
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 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 | 0.000 | 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) | 0.004 | 0.001 |
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; both teacher heads agree on what is shown here.
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".