Data and code from: Life under leaves: Substrate-borne vibrations provide a window into the behavior and ecology of two miniaturized geckos

Traditional sampling methods have limited our understanding of the behavioral ecology of leaf litter fauna. Substrate-borne vibrations provide a window that addresses this shortcoming. Under natural conditions, we implemented a passive monitoring system that measures vibrations produced by two miniaturized Puerto Rican geckos: Sphaerodactylus grandisquamis in the mesic karst forest and Sphaerodactylus townsendi in the coastal dry forest. The dichotomy between habitats allowed us to test the hypothesis that microclimate conditions drive divergence in thermoregulatory behavior. For each species in its native habitat, thirty individuals were monitored inside a field enclosure, excluding other vibration sources. We measured vibrations at two strata depths (i.e., surface and bottom) to characterize behavioral responses to diel cycle, microclimate, and predatory bird calls. Vibrational data revealed contrasting activity patterns across strata. Mesic S. grandisquamis showed continuous daytime ..., The vibrational dataset represents field recordings for 1) Sphaerodactylus grandisquamis in the mesic karst forest at Mata de Plátano and 2) Sphaerodactylus townsendi in the coastal dry forest at Cabezas de San Juan, along with concurrent microclimate data from the leaf litter. Processing of vibrational data was conducted in MATLAB, and analyses were performed in R. All data and scripts are provided., , # Data and code from: Life under leaves: Substrate-borne vibrations provide a window into the behavior and ecology of two miniaturized geckos

[https://doi.org/10.5061/dryad.mcvdnck8v](https://doi.org/10.5061/dryad.mcvdnck8v)

## Description of the data and file structure

The vibrational dataset represents field recordings for 1) *Sphaerodactylus grandisquamis* in the mesic karst forest at Mata de Plátano and 2) *Sphaerodactylus townsendi* in the coastal dry forest at Cabezas de San Juan, along with concurrent microclimate data from the leaf litter. Processing of vibrational data was conducted in MATLAB, and analyses were performed in R.

### Files and variables

## **Container: Vibrational_Recordings.zip**

#### Files: **34 segments of acoustic data across 4 sensor types.** File names (“07.XX_YY_YY_Z”) are organised by date (“07.XX_” = 07/XX) followed by time of day (“YY_YY_” = YY:YY), then sensor type (“Z”).

**Description:** Time-synchronised recordings of airborne sound (i.e., air)...,