Geodiversity Assessment with Crowdsourced Data and Spatial Multicriteria Analysis

Case studies associated with the 10 major geodiversity-related topics

This paper outlines the 10 major topics related to geodiversity that have emerged since the concept was first introduced in 1993, 30 years ago. After a short introduction, each of the 10 topics is then illustrated by a relevant case study. The 10 topics (italics) and their case studies (bold) are as follows: 1. Celebrating, International Geodiversity Day; 2. Measurement/Assessment, Potential role of remote sensing; 3. Natural Capital and Geosystem Services, Coastal geosystem services; 4. Biodiversity, Mangue de Pedra, Brazil; 5. Geomaterials, The circular economy; 6. Geotourism, World's top geotourism sites?; 7. Geoheritage, Landscape restoration; 8. National Geoconservation, Trump golf course and an SSSI, Scotland; 9. World Heritage Sites and Global Geoparks, Azores Global Geopark, Portugal; 10. Sustainability, Xitle Volcano, Mexico City. It is concluded that, given the way in which geodiversity has developed as a concept, leading to new insights and avenues of research and advancing our understanding of the world since its first use, it clearly now constitutes a significant, geoscientific paradigm. This article is part of the Theo Murphy meeting issue 'Geodiversity for science and society'.

Understanding trait diversity: the role of geodiversity

Geodiversity - the abiotic heterogeneity of Earth's (sub)surface - is gaining recognition for its ecological links to biodiversity. However, theoretical and conceptual knowledge of geodiversity-trait diversity relationships is currently lacking and can improve understanding of abiotic drivers of community assembly. Here we synthesise the state of knowledge of these relationships. We find that some components of geodiversity (e.g., topographic heterogeneity) elicit strong trait responses, whereas other components (e.g., substrate heterogeneity) have marginal effects in driving trait distributions. However, current knowledge is lacking in key aspects, including geodiversity's effect on trait-specific diversity and intraspecific variation. We call for the explicit inclusion of geodiversity when relating environmental drivers to trait diversity, taking advantage of the increasing availability of trait and geodiversity data.

A Framework for Cloud-Based Spatially-Explicit Uncertainty and Sensitivity Analysis in Spatial Multi-Criteria Models

Global sensitivity analysis, like variance-based methods for massive raster datasets, is especially computationally costly and memory-intensive, limiting its applicability for commodity cluster computing. The computational effort depends mainly on the number of model runs, the spatial, spectral, and temporal resolutions, the number of criterion maps, and the model complexity. The current Spatially-Explicit Uncertainty and Sensitivity Analysis (SEUSA) approach employs a cluster-based parallel and distributed Python–Dask solution for large-scale spatial problems, which validates and quantifies the robustness of spatial model solutions. This paper presents the design of a framework to perform SEUSA as a Service in a cloud-based environment scalable to very large raster datasets and applicable to various domains, such as landscape assessment, site selection, risk assessment, and land-use management. It incorporates an automated Kubernetes service for container virtualization, comprising a set of microservices to perform SEUSA as a Service. Implementing the proposed framework will contribute to a more robust assessment of spatial multi-criteria decision-making applications, facilitating a broader access to SEUSA by the research community and, consequently, leading to higher quality decision analysis.