Monitoring Seasonal and Secondary Succession Processes in Deciduous Forests using Near-Surface Optical Remote Sensing and Wireless Sensor Networks

  • Author / Creator
    Rankine, Cassidy J
  • The goal of this thesis is to address the need for improved monitoring of forest ecosystem dynamics in the context of anthropogenic global change by proposing the use of near-surface optical remote sensing approaches paired with emerging wireless sensor network (WSN) technologies in order to evaluate changing forest seasonality and succession patterns, specifically in the semi-arid tropics and sub-tropics. Climate change is expected to affect terrestrial ecosystems through bottom-up control of primary productivity by extending or decreasing growing season length in seasonally photosynthetic vegetation. Human land use imposes top-down control over ecosystems by modifying disturbance regimes, with subsequent ecosystem regeneration depending on land use policy and management. The interplay between bottom-up climate forces and top-down anthropogenic forces on tropical dry forest (TDF) ecosystem recovery and productivity is poorly understood and is an underlying theme in this thesis. As such, this thesis introduces and assesses the novel application of WSN technology for spatio-temporal micrometeorological characterization and near-surface optical remote sensing of deciduous broadleaf forest canopy photosynthetic dynamics. The results reveal major benefits as well as challenges in the synergistic use of optical in-situ and satellite observation platforms for monitoring leaf phenology and secondary succession processes in deciduous forests, with case studies from the boreal and tropical dry broadleaf forests. Chapter one reviews the motivations behind the methods and experiments presented in this thesis. Chapter two reveals how low-power wireless data transmission is influenced by seasonal changes in boreal forest leaf phenology and weather conditions to help improve WSN designs for forestry applications. Chapter three describes local meteorological drivers of leaf phenology in detail for a Brazilian TDF in the state of Minas Gerais, and further explores how sub-canopy climate moderation effects are influenced by secondary forest stand age and extreme drought seasonality in order to characterize TDF microclimatic ecosystem services and better understand drought risk factors for seedling establishment and tree recruitment in future TDFs. Chapter four investigates the correlations between remotely sensed and near-surface hyper-temporal observations of TDF phenology in the context of future change detection for climate driven shifts in TDF productivity, revealing significant limitations in MODIS vegetation greenness time series for phenology monitoring in TDFs. Finally, chapter five reviews the significance and main contributions of these experiments. The experimental results presented here may be specific to tropical dry and boreal forest ecosystems, but the methods and ideas apply to all forest ecosystems in order to improve environmental monitoring technologies and our understanding of vegetation seasonality and secondary forest succession in our rapidly changing global environment.

  • Subjects / Keywords
  • Graduation date
  • Type of Item
  • Degree
    Doctor of Philosophy
  • DOI
  • License
    This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.
  • Language
  • Institution
    University of Alberta
  • Degree level
  • Department
    • Department of Earth and Atmospheric Sciences
  • Supervisor / co-supervisor and their department(s)
    • Dr. Arturo Sanchez-Azofeifa (Earth and Atmospheric Sciences)
  • Examining committee members and their departments
    • Dr. Arturo Sanchez-Azofeifa (Earth and Atmospheric Sciences)
    • Dr. Petr Musilek (Electrical Engineering)
    • Dr. Mark Johnson (Earth, Ocean and Atmospheric Sciences)
    • Dr. Benoit Rivard (Earth and Atmospheric Sciences)
    • Dr. Mike MacGregor (Computing Sciences)