A common contaminant shifts impacts of climate change on a plant-microbe mutualism: effects of temperature, CO <sub>2</sub> and leachate from tire wear particles
Bibliographic record
Abstract
Abstract Anthropogenic stressors, such as climate change or chemical pollution, affect individual species and alter species interactions. Moreover, species interactions can modify effects of anthropogenic stressors on interacting species - a process which may vary amongst stressors or stressor combinations. Most ecotoxicological work focuses on single stressors on single species. Here, we test hypotheses about multiple stressors (climate change and tire wear particles) and interacting species, and whether species interactions modify responses. We use duckweed and its microbiome to model responses of plant-microbe interactions. Climate change is occurring globally, and with increasing urbanization, tire wear particles increasingly contaminate road runoff. Their leachate is associated with zinc, PAHs, plastic additives, and other toxic compounds. We crossed perpendicular gradients of temperature and CO 2 in a well plate with factorial manipulation of leachate from tire wear particles and presence of duckweed microbiomes. We measured duckweed and microbial growth, duckweed greenness, and plant-microbe growth correlations. We found that tire leachate and warmer temperatures enhanced duckweed and microbial growth, but microbes diminished positive responses in duck-weed, meaning microbiomes became costly for duckweed. These costs of microbiomes were less-than-additive with warming and leachate, and might be caused by leachate-disrupted endocrine signaling in duckweed. We observed reduced greenness at higher CO 2 without tire leachate, suggesting a relative increase in plant nutrient demand, and possibly underlying positive plant-microbe growth correlations in these conditions, as microbes presumably increase nutrient availability. However, with tire leachate, growth correlations were never positive, and shifted negative at lower CO 2 , further suggesting leachate favors mutualism disruption. In summary, while individual stressors of global change can affect individual species, in ecology we know species interact; and in ecotoxicology, we know stressors interact. Our results demonstrate this complexity: multiple stressors can affect species interactions, and species interactions can alter effects of multiple stressors.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".