Towards fully automated remote ecosystem monitoring

Natural ecosystems around the world are being impacted by human activity at an ever-increasing rate. However, we still don’t fully understand the true extent of our actions on these complex systems, limiting our ability to develop sustainable, well informed best practices.

Much of the problem is in collecting sufficient amounts of data from environments which are often difficult for scientists to access and survey thoroughly (e.g. polar regions, tropical rainforests, savannas). Therefore, we have been working on methods of fully-automating ecosystem monitoring in a cost-effective way, that will provide huge amounts of data on the health of a remote ecosystem over long time periods, with minimal effort required by field scientists to maintain the system.

Our first step towards this goal has been to develop a device that continuously records data from a variety of sensors (microphones, cameras, humidity sensors etc.) and uploads the data to the internet directly from the field using a standard mobile phone internet connection. The device is also powered by a solar panel setup, meaning that battery replacements are unnecessary. In theory, once initially set up, this device can sit out in a remote field site indefinitely, with the data sent straight to scientists almost instantaneously. Mobile phone connections are patchy at best in remote locations so a key challenge was to have a low-power system that could opportunistically exploit the available mobile signal.

The kit is cheap and open source so you can make your own and you're welcomed to have an explore: http://www.rpi-eco-monitoring.com and, if you subscribe, you can read more in a recent New Scientist article.  You can read our full paper for free in Methods in Ecology and Evolution for more details - https://besjournals.onlinelibrary.wiley.com/doi/abs/10.1111/2041-210X.13089 

Of particular interest to our group has been using audio to identify calling animals in the tropical forests of Borneo. We work at the SAFE project site in Sabah where ecologists from around the world investigate the effect of logging and the oil palm industry on the biodiversity of these ancient rainforests. A growing network of 12 monitoring devices are currently scattered around the SAFE landscape (see Rob Ewers's work) in areas varying from old-growth forest (with almost no impact from humans) to oil palm plantations. 

A real-time acoustic monitoring unit, deployed in the tropical forests of Sabah, Borneo at the SAFE project site. Data used from these devices helps investigate the effect of the oil palm industry on the biodiversity found in the region.

We are developing algorithms using a wide array of machine learning techniques that will automatically listen to the masses of audio from these monitoring devices in Borneo and give us a real-time measure of the biodiversity in the different forest locations. With a finer scale understanding of the full human impact on these fragile ecosystems we can help inform better sustainable practices for the oil-palm industry to minimise their damage on the threatened species of this region. Sarab, Lorenzo, Rob and Nick