Summary: | Small mammals compose a substantial portion of the seed predators and dispersers, as well as the prey, in many ecosystems. Nevertheless, information on distribution and habitat use is limited, partly because inexpensive, minimally -invasive surveying of small mammals has remained challenging. We created the SiMPL wildlife magnet – a baited camera trap design that allows passive monitoring of wildlife, especially small- to medium-sized mammals. The SiMPL magnet is inexpensive and easy to construct. To evaluate its effectiveness, we conducted a case study using 10 sites operating for two years along an elevation gradient in the White Mountains of the northeastern U.S. We found that the SiMPL wildlife magnet can be used to detect rodents, mesocarnivores, and, to a lesser extent, ungulates. We examined how the detection probability of mammal species changed with the inclusion of a SiMPL wildlife magnet using data from pre- and post-establishment. We found a significant increase in community-level detection probability with the use of SiMPL magnets and for some species, including red squirrels ( Tamiasciurus hudsonicus ), American marten ( Martes americana ), and fisher ( Pekania pennanti ). Moreover, we were able to capture more species with SiMPL magnets than without, including flying squirrels ( Glaucomys spp.), various Cricetidae spp., black bears ( Ursus americanus ), moose ( Alces alces ), owls and other birds. The SiMPL wildlife magnet is an effective, low-cost method for surveying wildlife communities, especially rodents and mesocarnivores. It addresses the limited range view presented by other techniques for capturing small mammals on camera traps and enables efficient collection of phenology data, including vegetation and snowpack. This tool has several applications, including monitoring species' responses to silvicultural practices and global change. Funding provided by: Northeast Climate Adaptation Science Center Crossref Funder Registry ID: http://dx.doi.org/10.13039/100030852 Award Number: This data ...
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