The increasing number of proposed wind farm developments in South Africa provides an immediate reason to assess bat activity and diversity, with the expectation of developing measures to mitigate for negative impacts. The overall aim of this thesis was contribute to an understanding of the drivers of bat activity, relevant to wind turbines, and to determine what factors (exogenous – environmental, or endogenous – intrinsic physiological processes) contributed to observed bat activity patterns, at the Metrowind Van Stadens Wind Farm in the Eastern Cape of South Africa.
A combination of active (mist netting) and passive (acoustic) bat monitoring techniques were used to determine free-ranging bat activity patterns (Chapter 3). A total of 889 bat passes were recorded over 323 detector nights from the beginning of May 2012 to the end of December 2012. The Cape serotine bat (82%) and the Egyptian free-tailed bat (97%) made up the majority of all bat passes recorded on site. Large variations in bat activity per month and per hour were apparent, with bat activity peaking in May 2012 and during the first few hours after sunset (18:00-23:00). Patterns in nightly, free-ranging bat activity at the site were modelled against various environmental conditions. Month, temperature, wind speed and an interaction between month and rainfall were the most significant predictors of bat activity, explaining 80% of the variation observed on free-ranging bat activity patterns.
A total of eight Cape serotine bats (Table 4.1.) were caught in mist nets on site and changes in the resting metabolic rate (RMR) of torpid (n = 6), and normothermic (n = 2) bats, over a 24 hr period, were measured and used to predict free-ranging Cape serotine bat activity (Chapter 4). Cape serotine bats showed a high proclivity for torpor in the laboratory and peaks in RMR were observed at 18:00 (0.89 ± 0.95 VO2 mℓ.g-1 .hr-1 ) and again from 20:00- 21:00 (0.89 ± 0.91 VO2 mℓ.g-1 .hr-1 ). Peaks in RMR of torpid individuals coincided with peaks in the average hourly free-ranging activity of the Cape serotine bat, and RMR explained 33% of the variation and was a good predictor of free-ranging bat activity (R2 = 0.2914).
This study showed that both exogenous (Chapter 3) and endogenous (Chapter 4) factors drive bat activity in the wild. Although this dissertation was not intended for wind turbine management, the information presented on the biology and activity of bats is important for managing interactions between bats and wind turbines. By determining what factors influence bat activity, we are able to predict when bats will be most active and thus can develop mitigation measures to reduce the potential impacts that wind turbines will have on the bat community. In order to conserve bats and reduce potential bat fatalities from occurring at the site, mitigation measures should be concentrated to those times when bats are most active (May and during the first few hours after sunset – 18:00 to 22:00).