Stream groundwater inputs generate fine‐scale variation in brook trout phenology and growth across a warming landscape
Bibliographic record
Abstract
Abstract Climate change is increasing global atmospheric temperatures, which can reduce abundance and cause range shifts in species that are sensitive to warming. However, fine‐scale thermal heterogeneity can drive highly variable local responses to climate change, especially in freshwater environments that differ in groundwater inputs and geomorphology. We used temperature data collected during 2012–2021 from 10 small, pristine streams in eastern Canada to characterise thermal variation at a small spatial scale (~25 km 2 ). We then used relationships between daily air and stream temperatures to reconstruct stream temperature since 1980, and assessed how thermal variation influenced the phenology and growth of brook trout ( Salvelinus fontinalis ). Air–stream temperature relationships varied considerably among streams despite their close proximity, with predicted summer temperatures differing up to 9.5°C between warmer rainfall‐dominated streams and cooler groundwater‐dominated streams. Rainfall‐dominated streams warmed more than twice as fast as groundwater‐dominated streams across all seasons since 1980, with nearly four‐fold differences in rates of warming evident during summer months. Fine‐scale thermal heterogeneity also shaped brook trout phenology, as juveniles in rainfall‐dominated streams were estimated to hatch and emerge much later (~70 and 40 days, respectively) and experience faster phenological shifts than in groundwater‐dominated streams. Relationships between juvenile brook trout size and accumulated degree‐days were positive, but slopes differed over two‐fold and did not vary systematically based on stream hydrology, suggesting more idiosyncratic impacts of warming on early growth. Collectively, our study illustrates how species responses to climate change in freshwater environments can be consistent in direction but vary substantially in magnitude owing to the influence of groundwater. Future climate change is likely to increase the thermal stress experienced by brook trout populations in warmer rainfall‐dominated streams, while potentially benefiting those in groundwater‐dominated streams where current temperatures are often suboptimal. Observed differences in the rates and ecological impacts of warming among streams suggest that fine‐scale thermal variation must be considered when forecasting effects of future climate change on stream fish population dynamics.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".