Aeroscapes and the Sensory Ecology of Olfaction in a Tropical Dry Forest
Bibliographic record
Abstract
Aeroscapes—dynamic patterns of air speed and direction—form a critical component of landscape ecology by shaping numerous animal behaviors, including movement, foraging, and social and/or reproductive interactions. Aeroecology is particularly critical for sensory ecology: air is the medium through which many sensory signals and cues propagate, inherently linking sensory perception to variables such as air speed and turbulence. Yet, aeroscapes are seldom explicitly considered in studies of sensory ecology and evolution. A key first step towards this goal is to describe the aeroscapes of habitats. Here, we quantify the variation in air movement in two successional stages (early and late) of a tropical dry forest in Costa Rica. We recorded air speeds every 10 seconds at five different heights simultaneously. Average air speeds and turbulence increased with height above the ground, generally peaked midday, and were higher overall at the early successional forest site. These patterns of lower air speed and turbulence at ground level and overnight have important implications for olfactory foraging niches, as chemotaxis is most reliable when air movement is low and steady. We discuss our results in the context of possible selective pressures and observed variation in the foraging ecology, behaviors, and associated morphologies of resident vertebrates, with a focus on mammals. However, these data also have relevance to researchers studying socioecology, invertebrate biology, plant evolution, community ecology and more. Further investigation into how animals use different forest types, canopy heights and partition activities across different times of day will further inform our understanding of how landscape and sensory ecology are interrelated. Finally, we emphasize the timeliness of monitoring aeroecology as global wind patterns shift with climate change and human disturbance alters forest structure, which may have important downstream consequences for biological conservation.
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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".