Patterns in stream biofilm communities and organic matter processing in an agricultural stream network: A multi-scale assessment of the influence of groundwater
Bibliographic record
Abstract
Benthic stream biofilm communities support stream ecosystem structure and function by mediating nutrient and carbon cycling. Understanding how environmental factors shape biofilm communities in stream ecosystems is therefore essential. Biofilm communities have been shown to be strongly influenced by nutrient availability and temperature, factors that can be modified by groundwater input at multiple spatial scales. However, in enriched streams, groundwater input as a driver of heterogeneity in surface water environmental conditions has not been well-explored among stream reaches (kilometer scale), habitat types (meter scale), and patches (centimeter scale), nor has the seasonal consistency of these relationships been studied. To investigate the association of groundwater input to biofilm communities, I conducted three interconnected field studies in Kintore Creek, a nutrient-rich agricultural stream network in Ontario, Canada. First, I assessed if variability in groundwater input altered patterns of biofilm communities and cellulose decomposition among reaches over four temperate seasons (Chapter 2). Next, I compared habitats (i.e., riffles and runs) in reaches with high, moderate, and low groundwater inputs to determine if habitat type modified the effects of groundwater input on stream biofilm communities and cellulose decomposition by varying environmental conditions (Chapter 3). Lastly, I assessed the response of stream biofilm communities and cellulose decomposition to a gradient of groundwater upwelling at the patch scale and tested whether small scale variations in environmental conditions are associated with biofilm communities and cellulose decomposition (Chapter 4). The results of Chapter 2 showed no within season association of groundwater input to biofilm communities, with \nvii \nseasonality driving heterogeneity in biofilm communities. Findings in Chapter 3 demonstrated that habitat type modified effects of groundwater input on biofilm communities. Groundwater influence was expressed by greater primary production and decomposition in runs in reaches with groundwater input compared to runs in the reach with no groundwater input. At the patch scale (Chapter 4), groundwater upwelling did not appear to generate substantial variation in surface water conditions, and variability stream velocity was the primary driver of heterogeneity in stream biofilm communities. The findings of this this thesis are in contrast to past work that found effects of groundwater on stream biofilm communities in nutrient-poor streams. These results may be due to cumulative effects of groundwater input throughout the stream network, thereby limiting the ability to detect environmental drivers of groundwater influence at small spatial (i.e., habitat, patch) scales. Therefore, additional studies comparing catchments with differing levels of groundwater are needed to fully understand the influence of groundwater on stream biofilm communities in differing landscape contexts. A major challenge across spatial scales was the ability to represent the impact of groundwater inputs through environmental measures and biofilm communities, suggesting further investigations at the stream water – biofilm interface is required to disentangle the environmental drivers associated to heterogeneity in biofilm communities. The results of this thesis suggest that the influence of groundwater input on stream biofilm communities and processes depends on the context of stream ecosystem, therefore understanding effects of groundwater input requires future research across a diverse range of stream ecosystems.
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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 | 0.001 | 0.001 |
| 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) | 0.000 | 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 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".