Mapping uncertainty of ICP-Forest biodiversity data: From standard treatment of diffusion to density-equalizing cartograms

Data uncertainty due to spatial gaps and heterogeneity is a fundamental problem in conservation and environmental planning. Thus, investigation of issues related to data uncertainty contributes to more efficient conservation plans. We evaluated the uncertainty of data related to forest diversity descriptors using a diffusion-based cartogram approach that visually displays how data information change in function with respect to degree of uncertainty. We used ground vegetation data for 3093 plots collected as part of the BioSoil project through the ICP Forests Level I network and stored in the LI-BioDiv database. For each plot, we assigned an uncertainty value based on the survey season and the mean monthly temperature for the survey period. The density-equalizing map or cartogram highlights that data collected in Spain, the United Kingdom and the German federal states of Berlin and Brandenburg have smaller values of species richness corresponding to larger values of uncertainty. We found that an awareness of the negative relationship between the survey period and species richness can lead to improved data handling and analysis. We demonstrated that cartograms are efficient tools for evaluating and managing uncertainty and can strengthen the results of data analysis by providing alternative perspectives and interpretations of spatial phenomena