Drop-camera surveys are widely used for rapid assessment of benthic habitats, particularly in remote and logistically challenging coastal environments. However, determining how many replicate deployments are required to adequately characterise site-level benthic communities remains a key uncertainty in benthic survey design. This is especially relevant in low-relief seagrass, soft sediment, and mixed-substrate habitats, where fine-scale spatial variability can influence estimates of benthic cover, community composition, and species detection, ultimately influencing the quality and consistency of benthic data used to assess condition and change within marine protected areas.
Here, we use a large, multi-regional dataset from northern Australia to evaluate how within-site replication influences the reliability of benthic data underpinning mapping and monitoring outputs. Subsampling analyses were used to quantify how replication (k = 1–10) influences (1) the precision of benthic cover estimates, (2) the detection reliability of benthic groups, and (3) the recovery of community composition across a gradient of habitat types. This work provides practical, evidence-based guidance for selecting replication levels in drop-camera surveys. By identifying trade-offs between sampling effort and information gain, these findings support the design of efficient, defensible monitoring programs, improving consistency, comparability, and confidence in assessments used to evaluate management effectiveness and guide conservation outcomes.