Functional enrichment of utopian distribution of plant life-forms

Adaptive fuzzy neural inference systems are used to illustrate the primary nodal number of plant life-forms. Categorization of two candidate areas is carried out using the water-energy dynamic (for Ecuador, South America) and Macedonia, Southern Europe), within which the life-form spectra are distributed. Genetic optimization methods are used to expand the primary nodal number to the complete number of life-form categories. The distribution of the elements exhibits a stochastic, binomial distribution and the utopia line and curve are summarized which enhance accuracy of the climatic data and of the consequent numbers of plant species occurrences. Expansion of the distribution of each life-form category is approximated within the Z utopia hyperplane with use of the functional approximation algorithm. This process gives additional structure and informative value to the Z plane, enhancing our ability to make informed policy decisions concerning species and ecosystem conservation

Global plant characterisation and distribution with evolution and climate

Since Arrhenius published seminal work in 1921, research interest in the description of plant traits and grouped characteristics of plant species has grown, underpinning diversity in trophic levels. Geographic exploration and diversity studies prior to and after 1921 culminated in biological, chemical and computer-simulated approaches describing rudiments of growth patterns within dynamic conditions of Earth. This thesis has two parts:- classical theory and multidisciplinary fusion to give mathematical strength to characterising plant species in space and time.Individual plant species occurrences are used to obtain a Species-Area Relationship. The use of both Boolean and logic-based mathematics is then integrated to describe classical methods and propose fuzzy logic control to predict species ordination. Having demonstrated a lack of significance between species and area for data modelled in this thesis a logic based approach is taken. Mamdani and T-S-K fuzzy system stability is verified by application to individual plant occurrences, validated by a multiple interfaced data portal. Quantitative mathematical models are differentiated with a genetic programming approach, enabling visualisation of multi-objective dispersal of plant strategies, plant metabolism and life-forms within the water-energy dynamic of a fixed time-scale scenario. The distributions of plant characteristics are functionally enriched through the use of Gaussian process models. A generic framework of a Geographic Information System is used to visualise distributions and it is noted that such systems can be used to assist in design and implementation of policies. The study has made use of field based data and the application of mathematic methods is shown to be appropriate and generative in the description of characteristics of plant species, with the aim of application of plant strategies, life-forms and photosynthetic types to a global framework. Novel application of fuzzy logic and related mathematic method to plant distribution and characteristics has been shown on a global scale. Quantification of the uncertainty gives novel insight through consequent trophic levels of biological systems, with great relevance to mathematic and geographic subject development. Informative value of Z matrices of plant distribution is increased substantiating sustainability and conservation policy value to ecosystems and human populations dependent upon them for their needs.Key words: sustainability, conservation policy, Boolean and logic-based, fuzzy logic, genetic programming, multi-objective dispersal, strategies, metabolism, life-forms