Variation in the abundance of mammals on the landscape affects a broad range of ecosystem processes including herbivory, predation, disease spread, and seed dispersal.  However, these patterns, and the effects of human disturbances on them, are poorly understood because of lack of data at the appropriate scales.  The eMammal project recruits citizen scientists to survey mammal communities with motion-sensitive camera traps to tackle the issue of scale, while also involving the general public in authentic scientific research. Over the last two years our volunteers have used camera traps to sample 2300 sites, recording over 2.6 million photographs in ~50,000 trap-nights. We started with a study design addressing hypotheses about the effect of hunting and hiking on wildlife, and are now expanding into developed areas to survey repeated urban-wild gradients.  Statistical analysis of animal diversity, abundance, and activity has given us new insight into the mechanisms that regulate animal abundance. For example, parks in developed areas had higher overall animal activity rates but lower species diversity.  Hunted areas had lower deer but higher coyote activity than nearby unhunted preserves.  Avoidance of hiking trails by animals was minor, and most nocturnal predator species were more commonly detected on-trail. These types of results are only achievable with a large, dispersed database, which would be impossible to collect with traditional methods.  We are currently working to maintain the flow of data by expanding our involvement of citizen scientists and broadening our concept of volunteer data collectors.  For example, we have several programs integrating eMammal into school classrooms and have developed lesson plans aligning with state and national science standards to broaden participation with youth volunteers. This expansion has also begun internationally with projects in five other countries. We look to grow the eMammal project by working with other research groups around the world interested in leading their own camera-trapping project. To this end we are developing customizable web portals and image analysis tools that will not only benefit researchers, but help engage more citizens in the fun activity of running camera traps outdoors, and give them the tools to make scientific discoveries with the data on their own.