Influence of catchment deforestationby logging and natural forest fires on crustacean community size structure in lakes of the Eastern Boreal Canadian forest
Bibliographic record
Abstract
Logging and wildfires are important perturbation factors of the Canadian Boreal forest, but their effects on aquatic communities remain largely unknown. Here, we assess the ecological effects of logging and wildfires on aquatic communities, based on changes in crustacean zooplankton size spectra among logged, burnt and unperturbed lakes of the Canadian Precambrian Boreal Shield. A laboratory version of the Optical Particle Counter (OPC-1L) was used to establish the crustacean size spectra of zooplankton samples collected in 38 lakes characterized by different catchment conditions: logged in 1995 (nine 'logged' lakes); burnt in 1995 (nine 'burnt' lakes); left unperturbed over the past 70 years (20 reference lakes). Size spectra are characterized by crustacean biovolume in 22 size classes, from 200–300 μm equivalent spherical diameter (ESD) to 2300–2400 μm ESD. Size spectra in logged and burnt lakes were on average shifted towards larger size classes relative to reference lakes, although the reference and burnt groups of lakes were the only pair statistically different from one another (at α = 5%). As a result, biovolume of crustacean organisms >1100 μm ESD in burnt lakes was on average higher by 366 and 388%, respectively, 1 and 2 years following catchment perturbations relative to reference lakes. Among a set of 15 water quality variables and 14 fish species density variables, potassium concentration and white sucker density were the most important environmental correlates of crustacean size structure.
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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 | 0.001 | 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 | 0.001 |
| 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".