With the increasing need to effectively monitor a growing number of ecosystems of interest due to risks posed to these ecosystems by human activity and climate change, novel approaches to biodiversity monitoring are needed. In this work we demonstrate the application of low cost acoustic recorders based on the Raspberry Pi microprocessor to biodiversity monitoring. The recorders are capable of capturing audio recordings from which we can compute acoustic indices of biodiversity and identify bird species of interest. We compare the acoustic indices of biodiversity and results of point counts aimed at determining bird species presence and find that the acoustic complexity index has a significant positive correlation to point count results. In addition, we show that the presence of the Hartlaub's Turaco, a ubiquitous species in montane forests in Kenya with a distinct call, can be automatically determined using recordings obtained using our setup. Montane species are of interest for long-term automatic monitoring since they are particularly vulnerable to the effects of climate change. Our system is able to deal with the large amounts of data generated by the acoustic recorders. The automatic screening of approximately five hours of recordings for presence of the Hartlaub's Turaco call is achieved in approximately three minutes representing a large time saving that makes use of audio recordings for species identification feasible.