Biological modelling for sustainable ecosystems

Furze, James, Zhu, Quanmin, Hill, Jennifer ORCID: 0000-0002-0682-783X and Qiao, F. (2017) Biological modelling for sustainable ecosystems. In: Mathematical Advances Towards Sustainable Environmental Systems. Springer International Publishing, Cham,Switzerland, pp. 9-42. ISBN 9783319439006

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Abstract

Modelling of biological systems is discussed in terms of the primary producers of trophic levels of organisation of life. Richness of plant communities enables sustainability to be reached within subsequent trophic levels. Plant dimensions of life history strategy, primary metabolic type and life form are defined and discussed with respect to the water–energy topography dynamic of climatic variables. The role of biogeography is given and classical approaches to species distributions and both antecedent and consequent variables within plants differentiated modelling frameworks are discussed. The algorithmic modelling frameworks applied in plant systems are justified statistically and with reference to established models. Mechanisms of dispersing discrete distributes are covered in consideration of genetic programming techniques. Further analysis expanding discrete approaches through functional transformations is considered and detail of a Gaussian Process Model is shown. Case study data of global locations is considered by means of discrete approaches of strategy and photosynthetic type and a continual approach of life form distribution. Algorithms for all processes and techniques are shown and graphical distributions made in illustration of the techniques. Synergy which may take place between the techniques is elaborated and flow diagrams of multiple benefits in pattern identification and further analysis are given. Recommendations of planting policies and policy implementation methods are covered in the final section, which also gives further direction on which we can base investigations which allow rational truth of distributes to be maximised and hence modulation of future modelling frameworks. Value is provided in terms of empirical, cause–effect and combinatorial approaches allowing us to process information effectively, structuring trophic levels and our own communities’ expansive needs.

Item Type: Book Section
Uncontrolled Keywords: Modelling; Life; Sustainability; Dimensions; Synergy; 30 combinatorial; Information; Trophic levels
Subjects: G Geography. Anthropology. Recreation > GE Environmental Sciences
Q Science > QH Natural history > QH301 Biology
Divisions: Professional Services > Academic Development Unit
Research Priority Areas: Learning and Professional Contexts
Depositing User: Marta Kemp
Date Deposited: 16 Jan 2020 16:34
Last Modified: 16 Jan 2020 16:34
URI: http://eprints.glos.ac.uk/id/eprint/7979

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