# Effects of two side-by-side camera trap deployments on estimations of richness, abundance, and the detection of medium- and large-sized mammals

## TL;DR

Using two camera traps per site improves detection of medium- and large-sized mammals, leading to better estimates of species richness and faster detection times.

## Contribution

The study empirically demonstrates that dual-camera deployments enhance sampling efficiency and detection reliability in small-scale monitoring.

## Key findings

- Two cameras per site increased detected species richness and number of records per species.
- Detection time was more than twice as fast with dual-camera setups, especially for rarely detected species.
- Single-camera setups risk delayed or missed detections with limited sampling effort.

## Abstract

Medium- and large-sized mammals play key ecological roles but remain difficult to monitor due to low detectability and logistical constraints. Camera traps are widely used to address these challenges; however, survey outcomes are strongly influenced by sampling design. In this study, we evaluated how deploying two side-by-side camera traps per site, compared with a single-camera configuration, affects sampling efficiency and information gain in a small-scale monitoring grid. We quantified differences in detected species richness, number of photographic records, and time to first detection between single- and double-camera deployments. Using two cameras per site significantly increased detected species richness and the number of records per species and reduced time to first detection. Survival analyses showed that detection occurred more than twice as fast under the double-camera design, with particularly strong gains for rarely detected species. Comparisons with a conservative single-camera scenario further highlighted the risk of delayed or missed detections under limited sampling effort. Rather than testing novel ecological hypotheses, our results provide empirically grounded guidance on how site-level camera-trap deployment choices influence detection efficiency, inventory completeness, and the reliability of commonly used biodiversity metrics.