Nutrient-cycling microbes in coastal Douglas-fir forests: regional-scale correlation between communities, in situ climate, and other factors
Bibliographic record
Abstract
Microbes such as fungi and bacteria play fundamental roles in litter-decay and nutrient-cycling; however, their communities may respond differently than plants to climate change. The structure (diversity, richness, and evenness) and composition of microbial communities in climate transects of mature Douglas-fir stands of coastal British Columbia rainshadow forests was analyzed, in order to assess in situ variability due to different temperature and moisture regimes. We compared denaturing gradient gel electrophoresis profiles of fungi (18S-FF390/FR1), nitrogen-fixing bacteria (NifH-universal) and ammonia-oxidizing bacteria (AmoA) polymerase chain reaction amplicons in forest floor and mineral soil samples from three transects located at different latitudes, each transect spanning the Coastal Western Hemlock and Douglas-fir biogeoclimatic zones. Composition of microbial communities in both soil layers was related to degree days above 0°C (2725-3489), while pH (3.8-5.5) best explained shifts in community structure. At this spatial scale, climatic conditions were likely to directly or indirectly select for different microbial species while local site heterogeneity influenced community structure. Significant changes in microbial community composition and structure were related to differences as small as 2.47% and 2.55°C in mean annual moisture and temperature variables, respectively. The climatic variables best describing microbial composition changed from one functional group to the next; in general they did not alter community structure. Spatial distance, especially associated with latitude, was also important in accounting for community variability (4-23%); but to a lesser extent than the combined influence of climate and soil characteristics (14-25%). Results suggest that in situ climate can independently account for some patterns of microbial biogeography in coastal Douglas-fir forests. The distribution of up to 43% of nutrient-cycling microorganisms detected in forest soils responded to smaller abiotic gradients than host trees.
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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 | 0.000 |
| 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".