A meta-analysis of the value of ecosystem services of floodplains for the Danube River Basin

Sci Total Environ. 2021 Jul 10:777:146062. doi: 10.1016/j.scitotenv.2021.146062. Epub 2021 Feb 25.

Abstract

Floodplains provide ecosystem services (ES). Their evaluation is complex and integrative assessment remains challenging for sciences and practices. Studies have been published in the last two decades reporting ES monetary values of floodplains. Since ES are site-specific, we focus on those studies regarding the Europe's second largest river basin, namely the Danube River Basin (DRB). By analyzing these studies, we aim to answer the questions: "Do the significant predictor variables differ from previous meta-analyses?" and "Does the spatial database improve the meta-analysis?" In this context, we conducted a systematic review on Scopus and Web of Science combining the four themes "value", "ES", "floodplain", and "location". We conducted a meta-analysis of the Danube floodplains' ES values with different sub-groups based on the ES classes (provisioning, regulating, and cultural) and implemented model selection based on the corrected Akaike Information Criterion. We selected 251 entries from 25 studies to set up with a PostgreSQL spatial database, which provides limitless possibilities to enrich the information on the study areas. We observed that the most important variables to describe ES values of DRB floodplains depend on the ES class, but in general the area proportions of water bodies and riparian landscapes are important, together with the valuation method and the chemical or ecological status of the corresponding river section. Finally, we provided two versions of unconditional benefit-transfer functions to evaluate provisioning, regulating, and cultural ES. This paper complements previously conducted meta-analyses to recognize significant characteristics to value ES and it is a valid basis to help determine the ES value of Danube floodplains.

Keywords: Danube River Basin; Floodplain values; Meta-analytical value transfer; PostgreSQL; Spatial database; Systematic literature review.