A systematic review of geospatial techniques for ecological vulnerability modelling across ecological domains

Abstract

Vulnerability modelling in ecology is increasingly studied within the framework of vulnerability assessment, measurement, and modelling, as well as adaptation and security. Geospatial technology plays a very significant role in ecological studies and in assessing the sensitivity and exposure, as well as the adaptive capacity of ecosystems. In this study, within the framework of the PRISMA protocol, 68 empirical case studies were retrieved from the databases of Scopus, SciSpace, Google Scholar, and the Shodhganga repository. These studies include different types of ecosystems, such as forests, aquatic systems, and urban and agricultural ecosystems. The reviewed studies were screened against the inclusion criteria of the present study. The findings of the study reveal positive trends in terms of using methodologies, indicators, models, and software in vulnerability modelling. However, the studies have been found to contain several gaps, especially large-scale vulnerability assessment of forests. Therefore, on the basis of the reviewed studies, the authors recommend the development of models such as machine learning models, incorporation of data from UAVs as well as from LiDAR, and long-term large-scale research for effective management of ecosystems and for policy support in ecology.