Remote sensing of leaf area index: enhanced retrieval from close-range and remotely sensed optical observations

A wide range of models used in agriculture, ecology, carbon cycling, climate and other related studies require information on the amount of leaf material present in a given environment to correctly represent radiation, heat, momentum, water, and various gas exchanges with the overlying atmosphere or the underlying soil. Leaf area index (LAI) thus often features as a critical land surface variable in parameterisations of global and regional climate models, e.g., radiation uptake, precipitation interception, energy conversion, gas exchange and momentum, as all areas are substantially determined by the vegetation surface. Optical wavelengths of remote sensing are the common electromagnetic regions used for LAI estimations and generally for vegetation studies. The main purpose of this dissertation was to enhance the determination of LAI using close-range remote sensing (hemispherical photography), airborne remote sensing (high resolution colour and colour infrared imagery), and satellite remote sensing (high resolution SPOT 5 HRG imagery) optical observations. The commonly used light extinction models are applied at all levels of optical observations. For the sake of comparative analysis, LAI was further determined using statistical relationships between spectral vegetation index (SVI) and ground based LAI. The study areas of this dissertation focus on two regions, one located in Taita Hills, South-East Kenya characterised by tropical cloud forest and exotic plantations, and the other in Gatineau Park, Southern Quebec, Canada dominated by temperate hardwood forest. The sampling procedure of sky map of gap fraction and size from hemispherical photographs was proven to be one of the most crucial steps in the accurate determination of LAI. LAI and clumping index estimates were significantly affected by the variation of the size of sky segments for given zenith angle ranges. On sloping ground, gap fraction and size distributions present strong upslope/downslope asymmetry of foliage elements, and thus the correction and the sensitivity analysis for both LAI and clumping index computations were demonstrated. Several SVIs can be used for LAI mapping using empirical regression analysis provided that the sensitivities of SVIs at varying ranges of LAI are large enough. Large scale LAI inversion algorithms were demonstrated and were proven to be a considerably efficient alternative approach for LAI mapping. LAI can be estimated nonparametrically from the information contained solely in the remotely sensed dataset given that the upper-end (saturated SVI) value is accurately determined. However, further study is still required to devise a methodology as well as instrumentation to retrieve on-ground green leaf area index . Subsequently, the large scale LAI inversion algorithms presented in this work can be precisely validated. Finally, based on literature review and this dissertation, potential future research prospects and directions were recommended.

Oxygen reduction and proton translocation by cytochrome c oxidase

Energy conversion by living organisms is central dogma of bioenergetics. The effectiveness of the energy extraction by aerobic organisms is much greater than by anaerobic ones. In aerobic organisms the final stage of energy conversion occurs in respiratory chain that is located in the inner membrane of mitochondria or cell membrane of some aerobic bacteria. The terminal complex of the respiratory chain is cytochrome c oxidase (CcO) - the subject of this study. The primary function of CcO is to reduce oxygen to water. For this, CcO accepts electrons from a small soluble enzyme cytochrome c from one side of the membrane and protons from another side. Moreover, CcO translocates protons across the membrane. Both oxygen reduction and proton translocation contributes to generation of transmembrane electrochemical gradient that is used for ATP synthesis and different types of work in the cell. Although the structure of CcO is defined with a relatively high atomic resolution (1.8 Å), its function can hardly be elucidated from the structure. The electron transfer route within CcO and its steps are very well defined. Meanwhile, the proton transfer roots were predicted from the site-specific mutagenesis and later proved by X-ray crystallography, however, the more strong proof of the players of the proton translocation machine is still required. In this work we developed new methods to study CcO function based on FTIR (Fourier Transform Infrared) spectroscopy. Mainly with use of these methods we answered several questions that were controversial for many years: [i] the donor of H+ for dioxygen bond splitting was identified and [ii] the protolytic transitions of Glu-278 one of the key amino acid in proton translocation mechanism was shown for the first time.