Image_1_Relative Importance for Lincoln’s Sparrow (Melospiza lincolnii) Occupancy of Vegetation Type versus Noise Caused by Industrial Development.PNG
Bibliographic record
Abstract
<p>Anthropogenic noise can create an acoustic environment detrimental for animals that communicate using acoustic signals. Currently, most studies of noise and wildlife come from traffic noise in cities. Less is known about the effects of noise created by industry in natural areas. Songbirds far from cities, but influenced by industry, could be affected by noise, but also are likely to be impacted by changes in vegetation conditions related to industrial development. We described the importance of industrial noise (from facilities and transportation) on occupancy of Lincoln’s Sparrow (Melospiza lincolnii) relative to habitat change caused by vegetation alteration and edge effects. Lincoln’s Sparrows naturally breed in varying seral stages and types of boreal forest. To test the influence of industrial noise, we selected three areas in Northern Alberta, Canada with high, medium, and low levels of industrial development and varying road density. At each area, we deployed a systematic arrangement of autonomous recording units (280 units in total, separated by 600 m) for 3 consecutive days. To measure noise, we developed a method that used the relative noise values extracted from the recordings of 8 frequency-octave bands. We obtained three noise measurements: noise with high energy in the low part of the spectrum (mean 0.5–1 kHz), masking level noise (mean 2–8 kHz), and noise in all frequency octave bands (mean 0.5–16 kHz). Proportion of chronic noise sources explained the highest variation of noise in the environment, and less by traffic noise. We found Lincoln’s Sparrow had a higher occupancy in areas with higher proportion of industrial disturbances, shrubs and grass, and decreased in noisy areas. Masking level noise had a negative effect on Lincoln’s Sparrow occupancy in areas with industrial disturbances, relative to areas with similar changes in vegetation structure, but no noise. Masking noise could indicate limitation in communication as noise increases. Our study amplifies the findings of others that future research should consider not only anthropogenic changes to vegetation in human-altered landscapes, but also human-caused changes to acoustic environments.</p>
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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 | 0.001 |
| 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) | 0.042 | 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".