International Journal of Bioinformatics and Computational Biology  
Manuscript Information
 
 
Estimating Biodiversity and the Fractal Nature of Ecosystems
International Journal of Bioinformatics and Computational Biology
Vol.5 , No. 1, Publication Date: Sep. 4, 2020, Page: 15-24
824 Views Since September 4, 2020, 152 Downloads Since Sep. 4, 2020
 
 
Authors
 
[1]    

Wilfried Allaerts, Biological Publishing A&O and Immunology Department, Erasmus MC, Rotterdam, The Netherlands.

 
Abstract
 

The problem of biodiversity impairment not only poses a global threat to the planet’s biosphere and causes global health issues, it is also a cumbersome pièce de résistance for mathematical modeling. Already the definition of biodiversity requires knowledge of the hierarchical structure of an ecological environment and taxonomic complexity of life forms in all of their manifestations. Not only the enumeration of easily recognized, large vertebrate species, but an estimation of all living species present in a given area, forms the ultimate challenge for biodiversity estimation. This is an important goal for enabling a scientifically sound approximation of biodiversity impairment. In this paper, the analogy of the fractal geometry of nature and the fractal appearance of ecosystems is followed, in order to define a constitutive approach for estimating the local and global biodiversity of an ecosystem. Moreover, following the rationale of percolation theory and Mandelbrot’s (1983) definition of the bounds of a critical fractal dimension in a hierarchically stratified system, the notions of critical biodiversity and biodiversity resilience strength (BRS) are proposed. It is concluded that in order to understand the dynamics of biodiversity change in a stressed, stratified environment such as the global biosphere, not only the stratification into trophic levels, but also short and long distance migration effects have to be considered.


Keywords
 

Biodiversity, Biodiversity Resilience Strength, Fractal Dimension, Similarity and Mass Dimension, Uniformity Index, Percolation Probability


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