Effects of forest harvesting on summer stream temperatures in New Brunswick, Canada: an inter-catchment, multiple-year comparison
Bibliographic record
Abstract
Abstract. This paper presents a pre- and post-harvest comparison of stream temperatures collected in five neighbouring streams (sub-catchments) over a period of five years (1994-1998). The aim of the study was to determine whether land cover changes from clear cutting in areas outside forest buffer zones (applied to streams >0.5 m wide) might contribute to an increase in summer mean stream temperatures in buffered streams downslope by infusion of warmed surface and sub-surface water into the streams. Specific relationships were observed in all five forest streams investigated. To assist in the analysis, several spatially-relevant variables, such as land cover change, mid-summer potential solar radiation, flow accumulation, stream location and slope of the land were determined, in part, from existing aerial photographs, GIS-archived forest inventory data and a digital terrain model of the study area. Spatial calculations of insolation levels for July 15th were used as an index of mid-summer solar heating across sub-catchments. Analysis indicated that prior to the 1995 harvest, differences in stream temperature could be attributed to (i) topographic position and catchment-to-sun orientation, (ii) the level of cutting that occurred in the upper catchment prior to the start of the study, and (iii) the average slope within harvested areas. Compared to the pre-harvest mean stream temperatures in 1994, mean temperatures in the three streams downslope from the 1995 harvest areas increased by 0.3 to 0.7°C (representing a 4-8% increase; p-value of normalised temperatures <<0.05). The greatest temperature change occurred in the stream that had the greatest proportion of its upper catchment harvested (16.8%), which also had the highest calculated potential solar loading ( ~2749 MJ per stream cell). From the analysis it was determined that the thinning applied to the forest buffer of that stream, with a basal area removal of ~28%, was insufficient to cause significant change in the observed stream temperature. Similar effects were observed following a second harvest in 1997. In general, increases in mean stream temperature coincided with forest harvesting activities outside forest buffers, where conditions promoting stream warming were greatest. In this study, no clear relationship existed between forest buffer strip width (ranging from 30-60 m) and the level of stream warming observed at the monitoring stations. Keywords: terrain attributes, solar radiation, land cover, forest buffers, New Brunswick regulations, spatial modelling, DEM, forest covertypes
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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".