Small- and large-scale patches shape benthic microbial community structure and function in streams at the subcontinental scale
Bibliographic record
Abstract
ABSTRACT Streams and rivers process dissolved and particulate matter as water moves along the land-to-ocean continuum, making important contributions to global biogeochemical cycles. Yet, predicting stream and river microbial metabolism associated with biogeochemical transformations at broad spatial scales remains challenging. Here, we used data from the National Ecological Observatory Network program to investigate whether ecological relationships among microbial community structure and function and environmental conditions observed at small scales hold at the subcontinental scale. We found that microbial communities were best explained by site-specific conditions. However, when field replicates were averaged, stream physico-chemical characteristics such as pH and temperature emerged as driving factors. This indicates that water quality acted as an environmental filter on microbial communities at the subcontinental scale, but was masked by small-scale patches that created high spatial heterogeneity. Our findings underscore the importance of considering multiple spatial scales to fully understand benthic microbial communities’ role in stream biogeochemistry. SCIENTIFIC SIGNIFICANCE STATEMENT Microbial communities in streams process materials as water flows toward the ocean. As microbial communities are influenced by environmental conditions, it remains challenging to predict stream microbial metabolism at large spatial scales. In this study, we used the National Ecological Observatory Network (NEON) public database to investigate the drivers of microbial community structure and functions in stream sediments across the USA. This unique dataset revealed high variability in microbial communities among streams that were best explained by local conditions, then by water quality and streambed habitat type. However, stream physico-chemical characteristics emerged as strong predictors of microbial communities when field replicates were averaged and considered as single, large microbial communities. These findings indicate multiple spatial scales must be considered to fully understand benthic microbial communities.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".