The use of fuzzy plant species density to indicate the effects of land-cover changes on biodiversity. (October 2015) - Ibrahim, Lara; Vogiatzakis, Ioannis N.; Incerti, Guido; Feoli, Enrico
Highlights: New method using floristic data to assess land-cover change effects on biodiversity. Uncertainty is handled by the fuzzy-set theory producing fuzzy species density. Land cover pattern is predicted by Markov chain modelling and cellular automata. Biodiversity maps are produced at any resolution without resource demanding surveys. Example on Butser Hill transect shows plant density dynamics at the landscape scale. Abstract: The assessment of the effects of land-cover changes on biodiversity requires expensive and time-consuming surveys. It is often the case that few data are readily available and time constraints and limited resources do not allow further data collection. In such cases, cost-effective assessment methods are needed. This study puts forward an assessment method which is based on approximate reasoning and is supported by Similarity theory. The suggested method uses Geographic Information Systems and free or low-cost floristic databases and time-series land-cover data. A main assumption is made, that species density, i.e. the number of plant species per unit area, could be used as a good indicator to estimate spatial biodiversity changes due to land-cover changes. The method produces, for a given area, " plausible maps of plant species density " considering land-cover maps. The method, based on approximate reasoning, overcomes the uncertainties inherent to floristic databases, allowing environmental conservation efforts to benefit from these information sources. An example application of the suggested assessment method is presented for the area of Butser Hill in the United Kingdom. The performance of the suggested approach and its limitations are then discussed.