EGU2020-11574
https://doi.org/10.5194/egusphere-egu2020-11574
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

The Classification and Quantification of Geodiversity: Addressing Conceptual and Empirical Challenges

Alex G. Neches
Alex G. Neches
  • Independent Researcher, East Grinstead, United Kingdom (alexgabriel.n@yahoo.com)

The 21st century has seen a growing interest for the understanding and quantification of geodiversity – i.e. ‘the natural range (diversity) of geological (rocks, minerals, fossils), geomorphological (landform, physical processes) and soil features’ (Gray, 2004). To date, though, most quantification efforts focus on geosites and geoheritage, which are a mere segment of geodiversity, namely that considered relevant or valuable. Quantification of geodiversity as a whole has only emerged within the last few years and has its own limitations.

This presentation addresses some key challenges in the classification and quantification of geodiversity, while considering conceptual, structural and empirical analogies between geodiversity and biodiversity.

From a spectrum view, material geodiversity is both infinite and finite, with infinite being at the low end of the spectrum and finite being at the high end of it; infinite lithospheric matter merges into finite micro-, meso- and macro-scale landforms, which further combine into ‘even more finite’ landform assemblages, land systems and landscapes.

1. Classifying such an exceptional range is a challenge in itself. Older, very specific classifications, based on physical, chemical, etc. criteria, exist for segments of geodiversity: rocks, soils and minerals. More recent, general classifications, based largely on formation processes, were elaborated for geosites and later for all geodiversity features (Ruban, 2010; Bradbury, 2014). These classifications share similarities with the Linnaean classification of living organisms (e.g. a hierarchical structure with analogous groups). The first are descriptive. The latter are genetic.

For quantification purposes, classifications should be established based on characteristics that are least prone to change. Thus, descriptive classifications based on observed attributes rely less on interpretation and are more stable. Genetic classifications are more problematic and may not be very suitable; unlike living organisms, where each individual is associated with a single Species, geodiversity features can be classified, based on formation processes, under multiple Types, Themes and Classes. This makes double (or multiple) counting imminent.

2. For a more realistic picture, geodiversity should, as much as possible, be quantified at low levels, where division of features/units is either impossible or redundant (e.g. infinite geodiversity, micro-scale landforms). The lower we go within the spectrum, the more diversity we encounter. The higher we go, the more likely we are to move from what is essentially a quantification of elements to a quantification of categories; that is, a concrete measurement is at risk of being replaced with an abstract measurement.

Different aspects of geodiversity can be calculated by mathematical functions, but use of metrics should be consistent with scale. Finite geodiversity, unlike biological communities, has well-defined boundaries and is less mobile; quantification is more straightforward and less affected by unknown variables. Infinite geodiversity, like biological individuals, is composed of identical elements; quantification is more complex and may require use of functions/estimators.

 

References

Bradbury, J., 2014. A keyed classification of natural geodiversity for land management and nature conservation purposes. PGA, 125(3), 329-349

Gray, M., 2004. Geodiversity: Valuing and Conserving Abiotic Nature. John Willey & Sons

Ruban, D. A., 2010. Quantification of geodiversity and its loss. PGA, 121(3), 326-333

How to cite: Neches, A. G.: The Classification and Quantification of Geodiversity: Addressing Conceptual and Empirical Challenges, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11574, https://doi.org/10.5194/egusphere-egu2020-11574, 2020

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