• English
  • Čeština
  • Deutsch
  • Español
  • Français
  • Gàidhlig
  • Latviešu
  • Magyar
  • Nederlands
  • Português
  • Português do Brasil
  • Suomi
  • Svenska
  • Türkçe
  • Қазақ
  • বাংলা
  • हिंदी
  • Ελληνικά
  • Log In
  • Communities & Collections
  • Browse OpenUCT
  • English
  • Čeština
  • Deutsch
  • Español
  • Français
  • Gàidhlig
  • Latviešu
  • Magyar
  • Nederlands
  • Português
  • Português do Brasil
  • Suomi
  • Svenska
  • Türkçe
  • Қазақ
  • বাংলা
  • हिंदी
  • Ελληνικά
  • Log In
  1. Home
  2. Browse by Author

Browsing by Author "Simmons, Rob"

Now showing 1 - 2 of 2
Results Per Page
Sort Options
  • Loading...
    Thumbnail Image
    Item
    Open Access
    Mapping the sensitivity of Lesotho's avifauna to wind farm developments
    (2015) Sands, Dara; Simmons, Rob; Ralston, Samantha; Amar, Arjun; McGuinness, Shane
    Anthropogenically induced climate change, coupled with the volatility of world oil markets, has accelerated the global implementation of a variety of renewable energy technologies (RETs). The southern African nation of Lesotho aims to utilise its aeolian resources by harnessing the power of the wind through the development of wind farms. The Lesotho government has approved the development of a 42 turbine wind farm in the Maluti-Drakensberg in north-eastern Lesotho. The development of a wind farm in this area is predicted to result in significant negative impacts on globally important populations of Bearded Vulture Gypaetus barbatus and Cape Vulture Gyps coprotheres, in addition to six other red-listed species, including Black Stork Ciconia nigra and Southern Bald Ibis Geronticus calvus. Concern over the impacts of wind farms on Lesotho's avifauna has resulted in calls for the development of an avian sensitivity map. Sensitivity maps have been developed in many countries, including South Africa, in order to provide locational guidance for the siting of wind farms and indicate areas where the development of wind farms could potentially result in negative impacts on sensitive bird species. This study has developed an avian sensitivity map for Lesotho by creating a species sensitivity index to determine the potential sensitivity of Lesotho's avifauna to wind farms and then mapping the distributions of 14 bird species considered most at risk to identify areas of "medium", "high", "very high", "maximum" and"unknown" senstivity. Individual species maps were converted to 1-km square resolution allowing for a Composite scoring map, selecting the highest sensitivity score for each square, and a Cumulative scoring map, summing all sensitivity score within each square, to be created.
  • Loading...
    Thumbnail Image
    Item
    Open Access
    Using movement modelling to improve the design and analysis of vantage point surveys in bird and wind energy studies
    (University of Cape Town, 2020) Cervantes Peralta, Francisco; Erni, Birgit; Theoni Photopoulou, Theoni; Simmons, Rob
    Wind energy, although mostly a clean and increasingly efficient energy source, is known to affect communities of flying vertebrates. Mortality by collision with turbines is one of the main impacts on birds and bats associated with wind energy. Soaring birds are particularly vulnerable due to their collision prone behaviours, low manoeuvrability, and their slow population recovery rates. The focus of this thesis is on the identification of areas that are intensively used by soaring birds in order to inform wind turbine placement and minimize collision risk. This thesis is particularly concerned with predictions of bird-use intensity that are based on flight trajectories mapped by observers from vantage points. This survey technique is standard practice during the environmental impact assessment of wind energy facilities, although its virtues and limitations are largely untested. Flight trajectories are counted, timed and mapped during these surveys. However, most assessments ignore the spatial information contained in the trajectories, and mappings are often reduced to metrics such as closest distance to a turbine or whether a particular habitat is visited. In this thesis, I use visual mappings of flight trajectories to estimate the long-term distribution of bird activity using: i) a kernel density estimator adapted to calculate the density of flight trajectories, and ii) modelling flights as being driven by a stochastic process under the influence of a potential field. Acknowledging the subjectivity introduced in the mapping of trajectories by field observers, I also study the discrepancy between mapped and true trajectories. Finally, I showcase the application of the various analytical techniques with a case study, in which I compare collision risk predictions with actual observed fatalities at a wind farm in South Africa. Kernel density estimation proved to be a good exploratory technique, and the estimator designed to estimate trajectory density outperformed other methods that ignore the temporal structure in trajectory data. Nevertheless, kernel methods are limited by its inability to predict bird activity outside areas observed from vantage points. Potential-based models allowed predictions in unobserved areas based on landscape characteristics, and showed promising results identifying areas of high collision risk. I found that the difference between true and mapped trajectories can be substantial, and it should be accounted for in any spatial analysis of vantage point observations. Although based on a single study case, the results are promising and show that the spatial distribution of collision risk predicted with the suite of methods presented in this thesis correlates well with the distribution of observed fatalities. The framework proposed to predict collision risk improves existing procedures in that it uses movement and spatial information contained in the observed trajectories. In addition, it accounts for all known sources of uncertainty throughout the modelling process.
UCT Libraries logo

Contact us

Jill Claassen

Manager: Scholarly Communication & Publishing

Email: openuct@uct.ac.za

+27 (0)21 650 1263

  • Open Access @ UCT

    • OpenUCT LibGuide
    • Open Access Policy
    • Open Scholarship at UCT
    • OpenUCT FAQs
  • UCT Publishing Platforms

    • UCT Open Access Journals
    • UCT Open Access Monographs
    • UCT Press Open Access Books
    • Zivahub - Open Data UCT
  • Site Usage

    • Cookie settings
    • Privacy policy
    • End User Agreement
    • Send Feedback

DSpace software copyright © 2002-2026 LYRASIS