Of walls and floors: how physical structures affect mating song detection in stridulating orthopterans
Bibliographic record
Abstract
Abstract Sensory ecology theory proposes that modalities like vision, audition and olfaction determine habitat selection and behavioural adaptation by organisms. This study explores how physical modifications in the environment influence the probability of detecting mating songs of stridulating orthopterans (suborder Ensifera) in nature. By experimentally introducing floors and walls into vegetated fields, we demonstrated that such structural changes can either enhance or hinder sound propagation and song detection, depending on species‐specific acoustic traits. Song detection probability increased for Nemobiinae species, likely due to improved sound reflection or behavioural attraction to the structures. Conversely, detection of Conocephalinae species decreased in the presence of these structures, suggesting adverse effects on habitat quality and signal transmission. Phaneropterinae species showed no clear response, likely owing to their long‐range song propagation from elevated positions. Song detection was also influenced by air temperature, time of day, vegetation density and microphone position, with warmer temperatures and elevated microphone positions generally enhancing detection. Structural changes to vegetated fields altered not only sound propagation but also potentially species incidence and behaviour. These findings highlight the interplay between the modification of physical structures and species traits. Our results underscore the need for habitat‐specific conservation strategies, particularly in settings where both acoustic and physical environments are continually transformed, such as in urbanised areas.
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 | 0.000 |
| 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".