Richness, phylogenetic diversity, and abundance all have positive effects on invader performance in an arid ecosystem
Bibliographic record
Abstract
Abstract In search of generalities in biological invasions, it is sometimes forgotten that invader success can be a function of both the diversity of the invaded community and the relatedness of the invader relative to community residents. Both qualities are likely to be especially important in stressful ecosystems, and identifying the species and community attributes that influence biological invasions can help direct management efforts in a sensitive ecosystem like those in arid regions. Pink Morning Glory, Ipomoea carnea Jaq. (Family: Convolvulaceae), is an annual vine native to Central and South America and is invasive in Egypt. We examined the performance of I. carnea at different densities in assembled communities of Egyptian annual native species. The native plant communities were manipulated to represent gradients of species richness and phylogenetic diversity and relatedness to I. carnea. We quantified the performance of I. carnea in these communities and examined the contribution of resident species richness, phylogenetic diversity, and phylogenetic relatedness to invader resistance. Our findings revealed that there was a positive relationship between invader performance and its mean phylogenetic distance to the resident species. Furthermore, species‐rich communities with more distantly related species positively contributed to invader performance in contrast to the classic biotic resistance hypothesis. Beyond these positive relationships, a positive density‐dependent effect of I. carnea on its performance was observed. We conclude that facilitative interactions are potentially important drivers promoting the successful invasion of the nonnative species I. carnea in water‐limited and harsh ecosystems. These results suggest that perhaps contrary to understanding from temperate systems, communities with a higher diversity of species could be more likely to be invaded by arid‐adapted species that are distantly related to natives. Thus, policy and management in arid regions should carefully consider reviewing the importation of nonnative species that are phylogenetically distinct and adapted to arid conditions and prioritizing their control once they are established.
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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 | 0.000 | 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".