Warming alters cascading effects of a dominant arthropod predator on microbial community composition in the Arctic
Bibliographic record
Abstract
ABSTRACT Warming is expected to increase abundances of wolf spider, the top predator in soil communities in the Arctic, but we have little understanding on how increased wolf spider density under warmer conditions affects soil microbial structure through trophic cascades. We tested the effects of wolf spider density and warming on bacterial and fungal community structure in litter through a fully factorial mesocosm experiment in Arctic tundra over two summers. Replicated litter bags were deployed at the soil surface and underground in the organic soil profile and collected at 2- and 14-month incubation. The litter samples were analyzed for community structure of bacteria and fungi and mass weight loss. After 2-month incubation, bacterial and fungal community compositions were already structured interactively by the spider density and warming treatments. Such interaction effect was also found in litter microbial community structure as well as litter mass loss rates after 14-month incubation. Our results show that wolf spiders have indirect, cascading effects on microbial community structure but that warming can alter these effects. The non-linear responses of microbial communities and litter decomposition to warming and increased spider density cast uncertainty in predicting structure and function of Arctic terrestrial ecosystem under warmer conditions in the future. IMPORTANCE This is one of the first studies demonstrating that predator abundances and increased temperature interactively structure litter microbial communities in the Arctic. The Arctic is one of the fastest warming regions due to climate change and contains disproportionately large amounts of soil organic matter, including thick litter which accumulated over the long time because of slow decomposition. The accelerated soil organic matter decomposition due to the rapid warming can cause positive feedback where resulting greenhouse gas emission contribute to further global warming. Since microbial structure can affect decomposition rates of litter, the observed non-linear responses of soil microbial community compositions and litter decomposition rates indicate challenges in predicting Arctic ecosystem responses in the future.
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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 | 0.000 | 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".