An empirical evaluation of camera trap study design: how many, how long, and when?

1. Camera traps deployed in grids or stratified random designs are a well-established survey tool for wildlife but there has been little evaluation of study design parameters. 2. We used an empirical subsampling approach involving 2225 camera deployments run at 41 study areas around the world to evaluate three aspects of camera trap study design (number of sites, duration and season of sampling) and their influence on the estimation of three ecological metrics (species richness, occupancy, detection rate) for mammals. 3. We found that 25-35 camera locations were needed for precise estimates of species richness, depending on scale of the study. The precision of species-level estimates of occupancy was highly sensitive to occupancy level, with <20 camera sites needed for precise estimates of common (>0.75) species, but more than 150 sites likely needed for rare (<0.25) species. Species detection rates were more difficult to estimate precisely at the grid level due to spatial heterogeneity, presumably driven by unaccounted for habitat variability within the study area. Running a camera at a site for 2 weeks was most efficient for detecting new species, but 3-4 weeks were needed for precise estimates of local detection rate, with no gains in precision observed after 1 month. Metrics for all mammal communities were sensitive to seasonality, with 37-50% of the species at the sites we examined fluctuating significantly in their occupancy or detection rates over the year. This effect was more pronounced in temperate sites, where seasonally sensitive species varied in relative abundance by an average factor of 4-5, and some species were completely absent in one season due to hibernation or migration. 4. We recommend the following guidelines to efficiently obtain precise estimates of species richness, occupancy and detection rates with camera trap arrays: run each camera for 3-5 weeks across 40-60 sites per array. We recommend comparisons of detection rates be model-based and include local covariates to help account for small-scale variation. Furthermore, comparisons across study areas or times must account for seasonality, which had strong impacts on mammal communities in both tropical and temperate sites.,We used camera trap data already available through repositories or collaborators. Most data came from the eMammal or TEAM repositories. We also used one data set (China) from collaborators that was not already archived. All camera traps were set similarly, in being placed on a tree at 0.5m facing parallel to the ground, with no bait. A variety of camera models were used, but all had infrared flashes and fast (<0.5s) trigger times. Camera trap designs were either regular (grid) or stratified random.,For this paper we wanted to asess the importance of three things to camera trap study design: amount of locations surveyed (spatial), amount of time each survey ran (temporal), and rather season mattered (seasonal). We broke into three teams to analyze these data, and used three slightly different collections of data for each team. Thus, you will find three datasets labeled as to which analyses they were part of: spatial, temporal, or seasonal. All data is presented as raw detection data, giving the date, time, and species for each time photograph was recorded. These are organized as 'deployments' representing a time period a camera was placed in a given location. We are including a TXT file with the Data Dictionary from eMammal that describes all the standard fields. A few files have additional fields we added that should be self explanatory.