eMammal - citizen science camera trapping as a solution for broad-scale, long-term monitoring of wildlife populations

Background/Question/Methods

Nearly 20% of mammals are threatened or endangered, yet we have no long term, broad scale abundance and distribution data for these species.  eMammal is a new initiative that integrates camera trap data from researchers with a growing citizen science effort to increase the spatial and temporal scale of survey data. We launched the citizen science camera trapping effort in 2012 in the mid-Atlantic USA.  Initial research questions evaluate the effects of consumptive and non-consumptive recreation on wildlife communities and assess volunteer learning and experience.  Cameras were deployed in pairs of hunted and un-hunted parks and in each park effects of trail use were measured by cameras deployed on the trail, 50m, and 200m from the trail. Volunteers were trained to set camera traps, deployed cameras in protected areas, and identified and uploaded pictures using custom software.  eMammal uses a cloud computing workflow including a website to coordinate field activities, remote photo upload, expert review of photo ID, and storage of photos and meta-data in a Smithsonian digital repository. We used a survey instrument with validated Likert type questions to assess volunteer attitudes towards wildlife and protected areas, and a questionnaire to measure wildlife identification and natural history knowledge.  

Results/Conclusions

In 2012, 85 volunteers deployed cameras to 687 sites in 12 parks and collected over 25,000 animal detections.  Preliminary results indicate recreation or recreation specific habitat management may influence wildlife community structure. White-tailed deer, black bear, bobcats, red fox and eastern gray squirrel were detected 1.5 to 2 times as often in un-hunted areas.  In hunted areas coyotes and wild turkeys were detected 1.5 to twice as often, and eastern chipmunks and eastern cottontails almost 10 times as often as in un-hunted parks.  White-tailed deer and black bear were detected more frequently off trails, while coyotes, red fox, and bobcats were detected more often on trails. Volunteers were attracted to the project by the desire to contribute to science, but found capturing photos of wildlife the most rewarding experience.  Attitudes toward wildlife and importance of protected areas did not change (n=48, Wilcoxon rank test, p=0.67, 0.71), but knowledge of wildlife significantly increased (n=63, paired t, p=0.01).  The amount of wildlife data collected in a single season shows the potential for camera traps and citizen science.  eMammal combines volunteer and researcher data into a landscape scale dataset to enable conservation and education in today’s rapidly changing world.