This project is available for public Spotting but Trapping is restricted. If you would like to join this project as a Trapper please contact us at email@example.com.
A large-scale camera trapping project to study mammal distribution, abundance and behaviour across County Durham. For this project, camera traps were placed in a systematic grid of 109 sites over summer 2018.
Between June and October 2018, we carried out the largest ever camera trapping survey of County Durham! Cameras were set up in a systematic grid of 109 points across the whole county and each camera was left in place for at least two weeks. The mass of data we collected will allow us to study mammal behaviour, species distributions and abundances, and community composition. The information we gain will form an important resource for those tasked with managing and conserving wildlife in the north east.
Our new dataset will also cast light on the data collected in the longer-term MammalWeb UK project. In particular, it will help us to interpret the more ad-hoc data being collected within MammalWeb, identifying which questions we can answer with confidence using the more ad-hoc approach, and which questions should be approached with greater caution. This will allow MammalWeb to use the data it generates to its full potential.
To do any of this, though, we need your help! Having 40 cameras, rotated around 109 sites, means we’ve collected a lot of images (523,734 to be exact!), and now we need to know what species are in them. By helping us to classify the images in this project, you’ll help us gain insight into the distribution, abundance, and behaviour of mammals in County Durham, as well as maximising the potential benefit of the MammalWeb project as a whole. A camera trapping project of this scale has not previously been done in the North East; we would be really grateful if you could sit back, put your feet up, and do a bit of spotting!
Note: this project includes some long image sequences, which might take a long time to load if you have a relatively slow internet connection.