MAMBO partner Daniel Kissling from the University of Amsterdam (UvA) has co-authored a paper for the Basic and Applied Ecology journal that presents the development of an innovative system for automated wildlife monitoring. The study area in focus is the Amsterdam Water Supply Dunes, a coastal Natura 2000 nature reserve in the Netherlands. 

Across this location, the remote monitoring of sensor performance was implemented with 65 wireless 4G wildlife camera traps in conjunction with V/2A solar panels, a more cost-efficient approach, reducing the need for site visits. In that sense, the devices transmit images through a mobile network, allowing scientists and managers to view images and assess results from a distance. Beyond the long-term data storage potential, such monitoring supplies information on the distribution, habitat use, activity and population structure of wildlife species. It is further supported by a deep learning model for identification, which is very promising for easily detecting target species.

Although the set-up costs of the automated system are higher, the annual deployment is much cheaper than that of traditional camera trapping. This is a testament to the fact that continuous monitoring with automated wildlife camera networks is more practical and cost-efficient. Moreover, the system is applicable in open habitats of other nature reserves where mobile networks are available.

Automating wildlife monitoring is very relevant to the MAMBO project as it explores modern approaches to the monitoring of biodiversity. Further details on the paper and the library of MAMBO outputs can be found on this page.