| Autor: |
Davis AJ; United States Department of Agriculture, Animal and Plant Health Inspection Service, Wildlife Services, National Wildlife Research Center, 4101 Laporte Avenue, Fort Collins, CO, 80521, USA. Amy.J.Davis@usda.gov., Keiter DA; University of Georgia, Savannah River Ecology Laboratory, D. B. Warnell School of Forestry and Natural Resources, PO Drawer E, Aiken, SC, 29802, USA.; University of Nebraska, School of Natural Resources, Hardin Hall, 3310 Holdrege St., Lincoln, NE, 68583-0961, USA., Kierepka EM; University of Georgia, Savannah River Ecology Laboratory, D. B. Warnell School of Forestry and Natural Resources, PO Drawer E, Aiken, SC, 29802, USA.; Trent University, Peterborough, Ontario, K9L 0G2, Canada., Slootmaker C; United States Department of Agriculture, Animal and Plant Health Inspection Service, Wildlife Services, National Wildlife Research Center, 4101 Laporte Avenue, Fort Collins, CO, 80521, USA.; Mountain Data Group, 115 N. College Ave. Suite 220, Fort Collins, CO, 80524, USA., Piaggio AJ; United States Department of Agriculture, Animal and Plant Health Inspection Service, Wildlife Services, National Wildlife Research Center, 4101 Laporte Avenue, Fort Collins, CO, 80521, USA., Beasley JC; University of Georgia, Savannah River Ecology Laboratory, D. B. Warnell School of Forestry and Natural Resources, PO Drawer E, Aiken, SC, 29802, USA., Pepin KM; United States Department of Agriculture, Animal and Plant Health Inspection Service, Wildlife Services, National Wildlife Research Center, 4101 Laporte Avenue, Fort Collins, CO, 80521, USA. |
| Abstrakt: |
A critical element in effective wildlife management is monitoring the status of wildlife populations; however, resources to monitor wildlife populations are typically limited. We compared cost effectiveness of three common population estimation methods (i.e. non-invasive DNA sampling, camera sampling, and sampling from trapping) by applying them to wild pigs (Sus scrofa) across three habitats in South Carolina, U.S.A where they are invasive. We used mark-recapture analyses for fecal DNA sampling data, spatially-explicit capture-recapture analyses for camera sampling data, and a removal analysis for removal sampling from trap data. Density estimates were similar across methods. Camera sampling was the least expensive, but had large variances. Fecal DNA sampling was the most expensive, although this technique generally performed well. We examined how reductions in effort by method related to increases in relative bias or imprecision. For removal sampling, the largest cost savings while maintaining unbiased density estimates was from reducing the number of traps. For fecal DNA sampling, a reduction in effort only minimally reduced costs due to the need for increased lab replicates while maintaining high quality estimates. For camera sampling, effort could only be marginally reduced before inducing bias. We provide a decision tree for researchers to help make monitoring decisions. |
