Emerging Technology: Computational Sustainability - Essay Example

? Computation Sustainability and Biodiversity Biodiversity is composed of all the ecosystems, genes and species in a particular area with its scale being dependent on variation of the various life forms in an ecosystem or the entire earth as well as the genes in a particular species in the ecosystem. The health of the various ecosystems can be measured by biodiversity largely due to the climate and interactions between the different species that affect biodiversity. Species in an ecosystem are biologically arranged, and this arrangement is dependent on various factors such as climate as well as dependency between species on the ecosystem. The distribution of species is subject to change in the ecosystems, depending on environmental factors as well as seasonal changes and the availability of resources on the ecosystem. This paper illustrates how computational sustainability, using computational methods such as species distribution modeling are used to predict future distribution patterns of a given species or group of species by use of a combination of various factors such as water depth, climate as well as distribution of other species Introduction Species range is the distribution of a particular species in a given ecosystem. Of importance is the difference between dispersion and distribution of species (Goldstein, 2011). The latter involves individuals moving from their original homes, especially during seasons such as mating or as a result of dispersion by air, land or water (Greco, 2012). Globalization and the transport industry have been huge facilitators of movement of species, largely contributing to dispersion of species from one geographical location to another (Jakab, 2008), whether it is between countries or continents. Geographical movement of species can be predicted before the actual movement takes place (Meyers, 2012). Thanks to computational sustainability, computational methods such as species distribution modeling are used to predict future distribution patterns of a given species or group of species by use of a combination of various factors such as water depth, climate as well as distribution of other species (Miller, 2008). The distribution modeling is developed to have the capacity to also include factors such as dispersal, migration as well as changes in the environment to make the predictions (Murgante, 2011). The distribution of species in an ecosystem is also depended on the scale it is being viewed from, whether it is a sample or the entire population (Murgante, 2012). . Computational sustainability is aimed at application of techniques in operation research, computer science, and information technology to ensure a balance between nature, environment as well as society’s needs for achievement of sustainable development (Taniar, 2010). Models on species distribution can be used in measuring climatic changes, especially in the advent of global warming and climate change as well as evaluation of the various policies modeled on the efforts aimed at conservation of the environment (Sharma & Mudhoo, 2011). The models can also be used to measure the extent and level of human activities affecting the environment such as deforestation as well as prioritizing the various areas that need policy intervention in an effort of minimizing damage on the ecosystem such as large scale fishing (Starrett, 2009). Discussion on Computation Sustainability, Biodiversity, Solutions and Threats Computational sustainability models focus on the development of frameworks for decision making on managerial level, focusing more on resource allocation and generation of solutions on problems affecting the society (Thrift & Kitchin, 2009). The models focus on problems that are large in scale and complex to solve. These problems are often difficult to solve by use of existent mechanisms for problem solving. The levels of complexity of the said problems affecting biodiversity are dynamic while the environment itself is uncertain. Computational models aim at applying research to problems by bringing together expertise from various disciplines such as biology, computer science, mathematics and statistics to come up with solutions (Vallero & Brasier, 2008). Continued depletion of natural resources threatens the existence of life on planet earth for both current and future generations. Needs for the present should not compromise on the ability of the future generations realize their needs (Sharma & Mudhoo, 2011). Issues on the development of structures for sustained development are complex in nature and require high levels of knowledge and skill in coming up with sustainable solutions. Making decisions concerning environmental society as well as economic needs require optimal levels of thinking as well as computational expertise on science, economics, environmental and other related disciplines (Vallero & Brasier, 2008). Conclusion It becomes important for scientists especially those specializing in computer, information technology, mathematics, economics, operations research to come together and pool their talent into a common objective that involves helping finding effective solutions to societal tribulations (Sharma & Mudhoo, 2011). These solutions mainly range from optimal allocation of resources to optimal management of the said resources. According to Sharma & Mudhoo (2011), for computational sustainability to work, there is the need to develop tools, methods and proper guide lines in the new field of computational sustainability to ensure the much needed balance between societal needs, economics and the environment is achieved. Agriculture, deforestation, urbanization as well as land development among others factors have contributed greatly to decline of some species, at times to extinction. This has been as a result of activities such as urbanization on natural habitats (Vallero & Brasier, 2008). One way of protecting species in an ecosystem involves creation of conservation reserves for the species such as national parks and reserves. From the perspective of computational sustainability, mathematical models can be used to optimize certain aspects of conservation efforts (Vallero & Brasier, 2008). These include optimization of the suitability of the habitats while at the same time considering the constraints involved such as insufficient budgets. Projects like conservation efforts often require huge capital input. Computational sustainability involves the coming together of various professionals such as scientists, mathematicians, biologists and so on. On biodiversity, biologist can form part of computational sustainability by coming up with ways of reduction of the fragmentation of natural habitats through creation and promoting, for example, conservation corridors that are essentially a continuous area of land that is protected that links biological zones/ecosystems (Thrift & Kitchin, 2009). Designing of the corridors as a specialty of the biologist and biodiversity is among the many forms of problems computational sustainability can be used to solve some of society’s problems (Thrift & Kitchin, 2009). References Carayannis, E. G. (2012). 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Proceedings of the 2007 Third International Conference on Information and Automation for Sustainability 4-6 December 2007, Melbourne, Australia. Piscataway, N.J.: IEEE. Read More