Functional traits associated with the establishment of introduced <i>Phytophthora</i> spp. in Swedish forests
Bibliographic record
Abstract
Abstract Invasive forest pathogens of the genus Phytophthora are threatening ecosystems globally. Phytophthora species are mainly introduced by humans importing infected nursery stock. However, due to the presence of environmental filters, not all introduced Phytophthoras manage to establish and spread. Phytophthoras’ ability to overcome these filters may be linked to functional traits. In northern Europe, the increasing number of reports calls for a better understanding of the invasion process to prevent future outbreaks. We hypothesized that the incidence of invasive Phytophthoras in urban locations would be higher than in remote forests, that there would be a decrease of species richness along the invasion process because of environmental filtering, and that there would be a functional shift among Phytophthora communities between stages of invasion. We compared the species composition of 96 sites from 16 rivers running through areas that constitute a gradient of human influence. We also compared the species composition and functional diversity of Phytophthora communities in eight nurseries and 14 forests, including anthropogenic and natural forests. Phytophthoras were isolated from river water, soil and/or plant tissue. Cultures were identified based on the Internal Transcribed Spacer region. Three Phytophthoras were detected in all environments ( Phytophthora cactorum , Phytophthora plurivora and Phytophthora cambivora ). The incidence of these species was higher in urban locations than in remote forests, suggesting that human activities act as a driver of invasion. Most of the Phytophthoras detected in forests were detected in nurseries. The Phytophthora community in nurseries was richer and more diverse than in forests, pointing to environmental filtering affecting the establishment. Phytophthora communities in nurseries and forests differed in their functional divergence. Traits associated with establishment were the ability to form asexual survival structures and lower cardinal temperatures for growth. Synthesis and applications . Our findings support the view that human activities act as drivers of Phytophthora invasions, and suggest that Phytophthoras able to form asexual structures are more likely to establish in northern Europe. The results increase the capacity to predict the establishment of Phytophthora species in Sweden and expand our understanding of the invasion process of forest pathogens.
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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 | 0.000 | 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) | 0.000 | 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".