Diversity and drivers of oribatid mites (Acari: Oribatida) in boreal peatlands
Bibliographic record
Abstract
Boreal peatlands are important ecosystems for carbon cycling, storing 1/3 of the world’s terrestrial carbon in only ~3% of the globe, making them a key component of potential mitigation strategies in response to global climate warming. Experiments have shown that warming can affect plant and microbial communities in ways that potentially shift peatlands from carbon sinks to sources. Soil food webs, including the microarthropod community, are key in carbon cycling but are relatively understudied both in peatlands and under experimental warming. My research capitalized on a large-scale experimental field manipulation of warming in two contrasting peatland sites in Northern Ontario, and addressed: 1) the diversity of oribatid mites in Canadian peatlands, 2) factors that drive litter decomposition and oribatid mite communities, by examining different microhabitats, 3) how these communities shift under experimental warming, and 4) the carbon flux in the soil food web, using energetic models for natural and warmed conditions. My published synthesis of oribatid mites in peatlands of Canada updates the species records from 71 to 186 species. I also show that peatland oribatid mite communities are driven by soil moisture and temperature, and that responses to warming are species- and site-specific. Oribatid mite community composition is driven by interactions between temperature and moisture, and dependant on peatland type, leading to the conclusion that oribatid communities follow a species sorting metacommunity paradigm driven by environmental filters. Models of carbon flux suggest that compositional changes in the soil food web under warming will significantly alter carbon cycling and potentially the carbon storage potential of peatlands. Using field experiments alongside modelling approaches for soil fauna, my research provides a comprehensive view of the role of peatland microarthropods and their relation to ecosystem processes under environmental changes. My work is also novel because soil systems are often treated as a ‘black box’ in global change carbon models; thus, my work is the first to link changes in peatland soil biodiversity to carbon storage and release.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".