Complexity Measures Of Ecosystems: The Genome

N Ladegaard1, M Debaljak2 and SE Jørgensen1

1Danish Pharmaceutical University, Institute A, Universitetsparken 2, Building 10, 2100 KBH 0, Denmark
2Faculty of Polytechnics, Nova Gorica, Slovenia

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Abstract


Exergy, because of its holistic nature and because its reliance on the universal laws of thermodynamics, has been proposed as an indicator for ecosystem development (Jørgensen, 2002). Recently-gained knowledge of the thermodynamic properties of ecological systems has enabled us to study structural and processional dynamics of growth and development of ecological systems (Jørgensen & Nielsen, 1998a, 1998b, Jørgensen et al., 2000). Exergy catches firstly the biochemical complexities of the organic structures build-up and secondly the amount of information of the structures in the system. Organisms that are phylogenetically highly developed should contain higher exergy, than less-developed ones, with similar chemical (organic) composition.

The initial approach to catch the information of the organisms in the ecosystem relied on information stored in the number of non-nonsense genes (Jørgensen et al., 1995, Bendoricchio & Jørgensen, 1997). This approach is limited because of the G-value paradox. Another approach (Fonseca et al., 2000) has suggested calculating the maximum number of encoded amino acids in the genome from the measured value of genome size. The maximum coding capacity is estimated from the number of nucleotide triplets. This approach is halted by the C-value paradox. Recent findings (Taft et al., 2003) show that there is a relationship between the ratio of non-coding to coding DNA and biological complexity across the entire phylogenetic spectrum. The findings are consistent, even though data are limited. By sequencing more organisms, genomic information is increasing daily, but the finding of the true content of information stored in the genome and the full understanding of its meaning at the ecosystem level still lie some time ahead. While we are searching for an indicator of genome complexity, we ask the following questions, among others:

How are complex genomes correlated with complex organisms?

How many components are held in biological complexity (Genomic, structure, regulation, life strategy, behaviour, system properties)?

What is the relationship between genome and organism evolution?

Is there a relationship between structure (composition) and organisation (rules, instructions and networks) of the genome?