Our objective is to develop and apply non-invasive and objective censusing and monitoring techniques as a fundamental resource for wildlife conservation. Our footprint identification technique (FIT) and others based on biometrics, can provide accurate and objective data to monitor endangered species, such as the black rhino (right).

The image on the left    is a left hind footprint     of a white rhino. Landmark    points have been placed,    ready for FIT analysis.     Heel lines, clearly visible in    this image, also characterise    individual rhino and serve as a    useful field identification tool.

• Censusing and monitoring are fundamental tools in wildlife conservation

The conservation of endangered species and the assessment of their associated ecosystems can only be achieved if reliable data are available. Knowledge of numbers and distribution is key to the implementation of strategies for protection and management. 

• The importance of non-invasive monitoring 

We believe that the future of wildlife conservation depends to a large extent on the development of non-invasive, cost-effective and sustainable methods of censusing and monitoring. Many current techniques employed for conservation (radio-collaring, tagging, notching etc) are expensive, sometimes ineffective and often unsustainable. In addition, our research and that of others suggests they may negatively impact on the animals they are trying to protect, by interfering with behaviour and fertility. Developing countries, home to many endangered species, are best able to sustain and manage techniques which are inexpensive.  If these techniques can utilise indigenous tracking skills then they have further benefits in terms of providing local employment. We believe that the footprint identification technique can make a very valuable contribution to wildlife conservation.

Take nothing but photographs; leave nothing but footprints.....

• The Footprint Identification Technique (FIT)

Our Rhinowatch project has developed an award-winning footprint identification technique (FIT) to identify individual black and white rhino from their footprints.  The technique is suitable for identification at the individual and at the species level.

We have recently adapted FIT for the Bengal tiger and have several ongoing projects with other species. It utilises statistical analysis of  geometric profiles derived from digital images of footprints. It produces objective data with a high degree of accuracy, is non-invasive, does not disturb the natural behaviour of the animal and is cost-effective. It is analogous to human fingerprinting, but our challenge is to work with many different species which have different foot structures and live in very different habitats!

• Compiling a footprint database for endangered species

Our first aim is to compile a database of footprints from endangered species, and those existing in areas of high biodiversity where species mapping is required.  We believe this is a unique concept.  Extensive footprint databases exist in the world of human forensic science, but until now no such concept has been utilised for wildlife conservation.  Once we have done this we want to use this database to develop further complementary non-invasive techniques.

To do this, we are encouraging the participation of people working with endangered species or in areas of rich biodiversity.  They might be field scientists, or  work in captive breeding institutions. They might be interested amateur naturalists, conservationists or zoologists.  They might be expert and/or indigenous trackers using tracking skills as part of their daily lives. They might be researchers in other fields eg biometrics or engineering who want to work with WildTrack to analyse data gathered.

Field participants need only a keen eye, a digital camera, GPS and internet access.

A white rhino cow and calf at a waterhole in Namibia. The typically sandy substrate in Namibia is ideally suited for the collection of footprint images, but we are also working with muddy substrates and  undertaking trials with snow prints.

Black rhino photo credit:  Brian Hatson/Rhinowatch