The long-term effects of large-scale changes in forestry, agriculture and other land use on habitats and the large-scale expansion of wind farming  affects bats foraging environments. In order to predict consequences of exploitations on local bat species and populations, good surveys are important. To get good background information for an Environmental Impact Assessment (EIA) it  is crucial to rapidly assess which areas are most important for bats. The aim of this work was to measure the importance of the two types of forest environment for bats foraging : forest areas located close to or far from the lakes. Bat activity and species diversity was measured with automatic ultrasound recorders in 211  nights of fieldwork at 155 locations in 23 areas in different parts of Sweden during June, July and the first two weeks of August 2011 and 2012. A total of 11 species were recorded in forest far from lakes and 8 species in forest close to lakes. Eptesicus nilssonii , Myotis sp. and Pipistrellus pygmaeus were the most common taxa in both habitat types. Activity levels were higher in the vicinity of lakes compared to forests far away from lakes. Species diversity calculated on base on Chao 2 was similar for both types of habitats . The results suggest that the forests close to lakes are the most important habitats to surveys for bats in Sweden and that inventory efforts should be primarily invested in them.

The increase in wind energy production has been relatively rapid and is expected to continue at a global scale. However, numbers of bat carcasses found at wind turbines in North America in the early 21st century raised concern about the plight of this taxon with the growth in wind-energy generation. This led to carcass searches for bats becoming commonplace at wind farms globally. However, few large scale systematic studies have assessed the effects of wind turbines on bats, especially for species considered potentially at higher risk in Europe. In this thesis the number and species of bats killed from wind farms were estimated across Britain, and the important predictors (i.e. activity, turbine characteristics and habitat) of fatality were determined. Insect abundance, biomass and bat activity was also quantified at turbine and control locations, to assess if insects and hence bats were attracted to turbines. In addition, assessments were made of the effects of increasing temporal and spatial replication of acoustic monitoring on estimates of species composition and bat activity. This was assessed for activity monitored at ground and at the centre of the rotor sweep area (the nacelle). Carcass searches were conducted using trained search dogs and concurrently bats were surveyed acoustically at three randomly selected turbines at ground and from the nacelle at 48 wind farms throughout Britain. Bats were also monitored acoustically at paired controls (with a randomly selected turbine) at 20 of the wind farms sites. In addition, nocturnal Diptera were sampled at 18 of the sites using a paired turbine and control design. Across 139 wind turbines, 188,335 bat passes were recorded and 2,973 carcass searches performed. Edge and open aerial foraging species, in particular Pipistrellus pipistrellus and P. pygmaeus were most at risk of fatality 4 at wind farms in Britain. The number of Pipistrellus pipistrellus killed annually in Britain between mid-July and mid-October was estimated at 2,373 95% CI 513 to 4,233 and the number of P. pygmaeus at 3,082 95% CI 1,270 to 4,894. When compared to population estimates, the number of Pipistrellus pygmaeus killed was 57% higher than the number of P. pipistrellus killed (0.19% of the population versus 0.43%, respectively). This may be due to Pipistrellus pygmaeus flying more often within the rotor sweep area compared to P. pipistrellus. Activity measured at the nacelle, which is generally assumed to be a better predictor of fatalities, was not a significant predictor of the probability of a fatality for all species combined, Pipistrellus pipistrellus, or P. pygmaeus. Pipistrellus pipistrellus activity and P. pygmaeus activity, measured at ground level were not good predictors of their respective fatalities. Whilst there was some evidence that Pipistrellus pipistrellus and P. pygmaeus activity monitored at ground level, was a significant predictor of the probability of their respective fatalities occurring, across wide ranging turbine types, fatality estimates were large. This is presumably due to the importance of turbine characterises (the wind speed that turbines become operational (cut-in speeds) turbine and the distance between the ground and blade tip at the bottom of the rotor sweep area) both being important negative predictors of fatalities for Pipistrellus pipistrellus. Predicting from models, if the cut-in speed is increased from 3.5 to 5 m s-1 the number of Pipistrellus pipistrellus fatalities would be reduced by 76% (0.23 fatalities per turbine per month to 0.06). These findings have important implications for guidance, since activity is the ubiquitous measure used to assess fatality risk for all species. Since, Pipistrellus pipistrellus and P. pygmaeus were detected at 98% and 92% of sites respectively; it could be 5 assumed that these species would be detected at the majority of wind farms within their range. Therefore, in a British context, curtailing wind turbines below 5 m s-1 could be an effective mitigation strategy without the costly requirement to monitor activity. Pipistrellus pipistrellus and P. pygmaeus activity was 46% (6.3 ± 1.3 SE mean passes per night c.f. 3.4 ± 1.3 SE) and 34% (4.0 ± 1.4 SE c.f. 2.7 ± 1.4 SE) higher at turbines compared to controls, respectively. Given that habitat and elevation were consistent between paired turbines and controls and monitoring was conducted on the same nights, higher activity at turbines compared to controls provides evidence that these two species are attracted to wind turbines. Furthermore, since the biomass of nocturnal Diptera, the main insect prey for Pipistrellus spp., was higher at controls compared to turbines, and bat foraging at turbines was not predicted by insect abundance or biomass, attraction is unlikely to be due to insects. Evidence presented here shows that bats are attracted to turbines, and therefore measuring activity at pre-construction sites for environmental impact assessments is unlikely to be effective. In conclusion, these results provide further evidence that common species are killed but generally in relatively low numbers, they also support the view that monitoring activity for assessing fatality risk at wind farms is ineffective. It is imperative that wind energy is developed using an evidence based approach. However, it also important that wind energy continues to contribute to an increasing renewable energy sector. In conclusion, results presented here, support that wind turbines are likely to be having a small impact on bat populations in Britain.

No description available.

Artificial brightness of the night sky caused by the backscatter of artificial light in the atmosphere is a consequence of ongoing urbanization. Skyglow covers 88 % of Europe’s surface and poses significant threats to biodiversity. Extensive research on responses of bats to direct light pollution already revealed significant impacts. However, evidence for the influence of skyglow is scarce. Therefore, this study investigates the effects of skyglow on bat activity patterns, namely Pipistrellus pygmaeus and Myotis species, in a rural area outside of Stockholm, Sweden. Additionally, the analysis includes the role of local habitat structures and landscape composition at multiple scales for both activity rate and timing of emergence.The two focal species showed diverging behaviour in their main habitat on the local scale. While Myotis spp. emergence was delayed by about half an hour above the water surface, P. pygmaeus appeared about 20 minutes earlier in forest edges under brighter night skies. Landscape-level skyglow significantly delays the emergence of Myotis spp. above water surfaces by 18 minutes, but P. pygmaeus did not respond to skyglow at the landscape-level. Both, Myotis species and P. pygmaeus, appeared earlier in forest edges than above water surfaces. Evidence on skyglow affecting bat activity rates was weak. Here, local habitat and landscape structure were more important for both species. The total length of all forest edges decreased bat activity at most scales, while activity was lower with the proportion of water and open land at different scales. In conclusion, bat conservation programmes need to consider the effect of skyglow as well as landscape characteristics.

Bat populations across North America are either facing new threats from white-nose syndrome (WNS) and wind energy development or have already experienced precipitous declines. Accordingly, researchers and managers need to know how to best monitor bats to document population and distribution changes, as well as where to look for persisting populations. Landscape-scale WNS impacts to summer bat populations are not well understood, and although acoustic monitoring is commonly used to monitor these populations, there is limited information about differences among acoustic detectors and the implications to managers thereof. My objectives were to model the relationship between WNS impact, influence of available hibernacula, and environmental factors for summer nightly presence of three WNS-affected bats and to compare how multiple models of acoustic detectors perform in terms of detection probability and nightly recorded bat activity. I collected acoustic data from 10 study areas across Virginia, West Virginia, Ohio and Kentucky to describe changes in nightly presence of WNS-affected bat species during summer 2017. During the same period of time, I compared five types of acoustic detectors at Fort Knox, Kentucky. My results show the potential efficacy of using a WNS impact-year metric to predict summer bat presence, and highlight which environmental variables are relevant for large-scale acoustic monitoring. Additionally, my findings suggest that each of the detector types tested would suffice for most research and monitoring activities, but standardization of detector type within the scope of a project or study should be encouraged. / Master of Science / Bat populations across North America are either facing new threats from white-nose syndrome (WNS) and wind energy development or have already experienced devastating declines. Accordingly, wildlife biologists need to know how to best monitor bats to document population and distribution changes, as well as where to look for remaining populations. Landscape-scale WNS impacts to summer bat populations are not well understood, and although acoustic technology is commonly used to monitor these populations, there is limited information about differences among acoustic detectors and the implications to managers thereof. My objectives were to model the relationship between WNS impact, influence of available bat hibernation caves, and environmental factors for summer nightly presence of three WNS-affected bats and to compare how multiple models of acoustic detectors perform in terms of detection probability and nightly recorded bat activity. I collected acoustic data from 10 study areas across Virginia, West Virginia, Ohio and Kentucky to describe changes in nightly presence of WNS-affected bat species during summer 2017. During the same period of time, I compared five types of acoustic detectors at Fort Knox, Kentucky. My results show potential viability of a WNS impact-year metric to predict summer bat presence, and highlight which environmental variables are relevant for large-scale acoustic monitoring. Additionally, my findings suggest that each of the detector types tested would suit most research and monitoring activities, but standardization of detector type within the scope of a project or study should be encouraged.

The large-scale use of artificial light throughout the night has occurred in the last 100 years and continues to increase globally. Artificial light impacts many animal and plant taxa. The effects of artificial light on bats is species specific. The Namib Desert in Namibia is still relatively dark but subject to the same drivers of increasing development and urbanization that have increased the spread of artificial light globally. This study investigated the effects of the introduction of ultraviolet, yellow and white artificial light on the activity of bats in a rural environment with minimal development in the Namib Desert. Four sites, 100 m apart, had one light and one bat detector each. The fourth light was a dark control. Each site was sampled four times by each light type. Bat activity was recorded by the bat detectors. Eight bat species were recorded during the experiment. Activity increased for open air and clutter-edge foraging species analysed. Broadband white light caused the highest increases in activity followed by yellow light when compared with the dark control site. Ultraviolet light caused the lowest increases in activity contrary to expectations. / Mengwaga ye 100 ya go feta go bile le koketšego ye kgolo ya tšhomišo ya seetša sa maitirelo bošego ka moka. Setlwaedi se se ata kudu lefaseng ka moka go feta pele, gomme se ama diphoofolo tše ntši le mehuta ya dimela. Leganata la Namib go la Namibia gabotse le sa ntše le swiswetše, eupša le ka fase ga dikgontšhi tša go oketša tlhabollo le toropofatšo tšeo di hlotšego koketšego tšhomišong ya seetša sa maitirelo lefaseng ka bophara. Dikhuetšo tša seetša sa maitirelo go memankgagane di fapana go ya ka mohuta. Nyakišišo ye e nyakišišitše dikhuetšo tša tsebagatšo ya seetša sa maitirelo sa go phadima, serolwane le se sešweu go modiro wa memankgagane ka tikologong ya nagaselegae ya go ba le tlhabollo ye nyane ka Leganateng la Namib. Seetša se setee le tithekethara e tee ya mankgagane di hlomilwe go le lengwe le le lengwe la mafelo a mane, a go arogantšhwa ka 100 m. Seetša sa bone se be se le taolo ya leswiswi. Lefelo le lengwe le le lengwe le dirilwe mohlala makga a mane ka mohuta wo mongwe le wo mongwe wa seetša. Modiro wa mankgagane e rekotilwe ka ditithekethara tša mankgagane. Mehuta ya mankgagane ye seswai e rekotilwe nakong ya eksperimente. Modiro wa mehuta ya sebakabakeng le ya go sela thobekgeng ye e sekasekilwego e oketšegile. Seetša se sešweu sa porotepente se hlotše dikoketšego tša modiro, sa latelwa ke seetša se se serolwane, ge se bapetšwa le lefelo la taolo ya leswiswi. Go fapana le ditetelo, seetša sa go phadima se hlotše dikoketšego tša fasefase modirong. / School of Environmental Sciences / M. Sc. (Nature Conservation)