Abstract
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. We used an empirical subsampling approach involving 2,225 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 and detection rate) for mammals. We found that 25–35 camera sites were needed for precise estimates of species richness, depending on scale of the study. The precision of species-level estimates of occupancy (ψ) was highly sensitive to occupancy level, with <20 camera sites needed for precise estimates of common (ψ > 0.75) species, but more than 150 camera sites likely needed for rare (ψ < 0.25) species. Species detection rates were more difficult to estimate precisely at the grid level due to spatial heterogeneity, presumably driven by unaccounted habitat variability factors 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. 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 could have strong impacts on mammal communities in both tropical and temperate sites.
| Original language | English |
|---|---|
| Pages (from-to) | 700-713 |
| Number of pages | 14 |
| Journal | Methods in Ecology and Evolution |
| Volume | 11 |
| Issue number | 6 |
| DOIs | |
| State | Published - Jun 1 2020 |
Funding
We appreciate support for the original camera trapping field work from National Natural Science Foundation of China (#31572250, #31872210), Riverbanks Zoo and Gardens, Satch Krantz Conservation Fund, Francis Marion University Professional Development Fund and International Collaboration Grants, University of North Carolina‐Wilmington Charles L. Cahill Grant, US National Science Foundation and San Diego Zoo Global. Data from the Tropical Ecology Assessment and Monitoring (TEAM) Network are the result of a collaboration between Conservation International, the Smithsonian Institution and the Wildlife Conservation Society, and partially funded by these institutions, the Gordon and Betty Moore Foundation and other donors. We also acknowledge logistical, permitting and field support from the Ecuador Ministry of the Environment, Sumaco National Park, Jonas Nilsson, Wildsumaco Wildlife Sanctuary, Instituto Nacional de Pesquisas da Amazônia (INPA), Conservation International Suriname, Organization for Tropical Studies, Uganda Wildlife Authority, Museo Tridentino di Scienze Naturali and Institute of Tropical Forest Conservation. Jen Zhou for maintaining and organizing eMammal data for analysis.
| Funders | Funder number |
|---|---|
| Francis Marion University | |
| Smithsonian Institution | |
| Hornocker Wildlife Institute/Wildlife Conservation Society | |
| Conservation International | |
| National Natural Science Foundation of China | 31572250, 31872210 |
| Instituto Nacional de Pesquisas da Amazônia |
Keywords
- camera traps
- community ecology
- detectability
- mammals
- relative abundance
- species richness
- study design
- wildlife surveys
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