What is MammalWeb? MammalWeb is a "citizen science" platform intended to collate, validate and curate camera trap data that can inform us about the distribution and ecology of mammals.
Why monitor mammals? Mammals are often elusive. Often coming out at night, and not in great numbers, it is hard to monitor their populations, where they are distributed, and how they behave. Knowing these things is important for a wide range of applications, including conservation and the sustainable development our natural landscape.
What is the aim of MammalWeb? MammalWeb's aims include:
- To engage more members of the public in monitoring wild mammals, increasing awareness of this relatively secretive component of the wildlife around us.
- To gain a better understanding of the distributions and behaviours of wild mammals and the factors that affect them.
- To ensure consistent recording and curation of camera trap data, regardless of the purposes of its collection.
- To provide a conduit for deposition of data in national archives.
- To conduct research into the interpretation and analysis of the collated data, in order to provide a better understanding of the ecology and behaviour of target species.
Read more about MammalWeb and the ten principles of citizen science.
Read more about MammalWeb's findings.
What are camera traps? Camera traps are devices that do not actually catch the animals, but detect and photograph any animal that moves in front of them. They are relatively easy to set up, and cause less stress to animals than traditional monitoring methods, like capturing and tagging. Camera trapping can help us to learn what animals occur in an area, when they are active, and how they time important seasonal events, such as reproduction. With careful development and analysis, camera traps can also tell us about the abundance of species in different areas and at different times. Battery-powered camera traps can be left in the wild taking pictures for months, so do not need constant checks.
Who can get involved? Anyone can get involved with MammalWeb, in one (or more) of three ways. First, any individual can also register for an account to start identifying what's pictured in the uploaded images (find out about Spotting to participate). Second, anyone who owns or can borrow a camera trap can upload image data to the site, along with information about where the images were obtained and over what period (find out about Trapping to participate). Third, organisations that already deploy camera traps (or those that are considering doing so) can contact us about setting up a 'project'; this will allow them to submit image data to the platform and to involve others in the job of classifying those data (find out about Projects to participate). Click the links in this paragraph for more information on any of these possibilities.
Read about MammalWeb's Terms and Conditions.
Who runs MammalWeb? MammalWeb was set up in collaboration between Durham University and Durham Wildlife Trust. It is run by MammalWeb Limited. MammalWeb Limited is a not-for-profit company limited by guarantee. Directors include representatives from Durham University's departments of Anthropology, Bioscience and Computer Science, Durham Wildlife Trust, the National Wildlife Management Centre and Manifesto Digital. Much of the hard work involved in setting up and running the platform, and in understanding the data is conducted by other scientists at Durham University, including the following:
Emily is conducting a PhD with a focus on improving the efficiency with which citizen science data - not just those generated by the MammalWeb project - can be verified. Emily will also be considering the impacts of confidence in the data on the downstream use of citizen science data.
Sian's PhD is focused on improving engagement, to get as many people as possible taking part in, and enjoying MammalWeb. Later on, Sian will use the data to answer questions about camera trapping methods, and their impacts on both engagement and ecological inferences.
Sammy is conducting a PhD with two major components. First, she has been conducting a rigorous, standardised survey of County Durham, to provide a comparison with the data submitted by participants. Second, she is also assessing ways to get schools and school children involved in monitoring.
Jonathan, who has a background in physics, is conducting a PhD on the use of image analysis and deep learning to help us extract more information more quickly from submitted photographs, thereby ensuring that the data can be put to use more quickly.
Alumni and other acknowledgements
Pen-Yuan Hsing completed his PhD in 2019. Pen's PhD was focused on the early design of MammalWeb and the recruitment and training of participants. Pen also showed how the data could be analysed to yield insights into spatial and temporal aspects of species' ecology.
A number of MBiol (degree with integrated masters) students have conducted research projects on MammalWeb, helping to inform the design and interpretation of the project. They include: Courtney Neal (2016), Bryony Jones (2018), Toby Atkinson-Coyle (2018) and Balint Ternyik (2020).
Undergraduates, interns and other contributors
We are also grateful to the wide variety of additional students, interns and others who have helped with the project from 2014 to the present. They include: Magnus Bower, Emma Brown, Florian Graber, David Jarrett, Alice Miller, Emily Perrin, Emily Townley and Lucy Zhang.
Since its early creation by Steven Bradley, almost all of the work to add features and troubleshoot the platform has been conducted by Helen Chappell of Rhombus Technology. We are enormously grateful to Helen for her tireless work on the site and for her huge achievements in spite of the incompetence of the rest of the team!
Former Board Member
We are grateful to Simon Hodgkinson of the Smart Earth Network, one of the founding directors of MammalWeb CLG. Simon's faith in what we were trying to achieve, and his insistence on a more corporate structure to take that forward, were important drivers in creating the structure that now underpins MammalWeb.