Monitoring biodiversity on a budget: Optimizing camera trap selection in a biodiversity hotspot

Abstract Ecological monitoring plays a crucial role in conserving biodiversity. However, ensuring that monitoring programs possess adequate statistical power—the capacity to detect changes in populations with a high level of confidence—remains a significant challenge for wildlife managers worldwide. The rise in popularity of camera traps has led to a proliferation of models with varying costs, specifications, and capabilities. This diversity presents both opportunities and challenges for wildlife managers, as selecting the most suitable model requires careful consideration of detection probabilities, deployment durations, and overall cost‐effectiveness. Here, we present a case study comparing the performance of two commercially available camera trap models widely used for monitoring eight species groups within a global biodiversity hotspot. While Reconyx cameras demonstrated superior detectability for most species, the lower‐cost Swift models proved more cost‐effective for increasing statistical power in large‐scale monitoring programs. These results highlight the importance of comparing monitoring technologies using metrics that go beyond nightly detectability, such as statistical power, and evaluating these technologies at the scale at which they are intended to be implemented. These findings provide a framework for wildlife managers to optimize monitoring programs while balancing cost and performance.