Seasonal synchronicity and multi-decadal stability of headwater biogeochemistry in the northern temperate zone
Bibliographic record
Abstract
Abstract Temporal patterns in chemistry of headwater streams reflect responses of water and elemental cycles to perturbations occurring at local to global scales. We evaluated multi-scale temporal patterns in up to 32 y of monthly observations of stream chemistry (ammonium, calcium, dissolved organic carbon, nitrate, total dissolved phosphorus, and sulfate) in 22 reference catchments within the northern temperate zone of North America. Multivariate autoregressive state-space (MARSS) models were applied to quantify patterns at multi-decadal, seasonal, and shorter intervals during a period that encompassed warming climate, seasonal changes in precipitation, and regional declines in atmospheric deposition. Significant long-term trends in solute concentrations within a subset of the catchments were consistent with recovery from atmospheric deposition (e.g., calcium, nitrate, sulfate) and increased precipitation (e.g., dissolved organic carbon). Lack of evidence for multi-decadal trends in most catchments suggests resilience of northern temperate ecosystems or that subtle net effects of simultaneous changes in climate and disturbance regimes do not result in directional trends. Synchronous seasonal oscillations of solute concentrations occurred across many catchments, reflecting shared climate and biotic drivers of seasonality within the northern temperate zone. Despite shared patterns among catchments at a seasonal scale, multi-scale temporal patterns were statistically distinct among even adjacent headwater catchments, implying that local attributes of headwater catchments modify the signals imparted by atmospheric phenomena and regional disturbances. To effectively characterize hydrologic and biogeochemical responses to changing climate and disturbance regimes, catchment monitoring programs could include multiple streams with contributing areas that encompass regional heterogeneity in vegetation, topography, and elevation. Overall, detection of long-term patterns and trends requires monitoring multiple catchments at a frequency that captures periodic variation (e.g., seasonality) and a duration encompassing the perturbations of interest.
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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 | 0.001 |
| 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".