Supporting the planning and management of biodiversity through the development of a geospatial decision support system

Abstract

AbstractToday, the issue of biodiversity conservation is, more than ever before, one of primary importance since it has become common knowledge that biodiversity provides many services that are relevant to the sustaining of ecological integrity and, so, for the benefit of humanity. Within this framework, rural areas are particularly exposed to degradation threats and, therefore, biodiversity loss due to their lying between and interlinking with urban and natural areas. The European Commission underlines the relevance of this conservation in its Biodiversity Strategy for 2030, which identifies a series of needs for conserving biodiversity in Europe, among which is the need for more operational tools to support biodiversity management. This paper aims to demonstrate that a geoSpatial decision support system (S‐DSS), developed through focused interdisciplinary research and implemented over a Geospatial Cyberinfrastructure, might provide a powerful web‐based operational tool to encourage both the engagement of a large range of end‐users and stakeholders and the better implementation of the Habitats Directive as indicated by the Biodiversity Strategy for 2030. The platform supports data visualization and on‐the‐fly computer applications for modeling, all via a web browser. The S‐DSS tool brings together knowledge of soil and environmental sciences, biodiversity and information technology. The S‐DSS tool is demonstrated through three use cases in the Campania region (Southern Italy) from different users' perspectives. The connection of data and model aims to provide information that will improve knowledge and awareness of biodiversity. In just a few clicks, the production of maps, results and statistics provides an overview of the biodiversity over a personalized area drawn by the user. The approach is highly transferable to other areas, from other administrative regions to the whole European territory, because it is based on general algorithms that are easily applied elsewhere, providing there is the necessary data availability.