Brownification on hold: What traditional analyses miss in extended surface water records. (15th September 2021)

• Record Type: Journal Article
• Authors: Eklöf, Karin; von Brömssen, Claudia; Amvrosiadi, Nino; Fölster, Jens; Wallin, Marcus B.; Bishop, Kevin
• Is Part Of: Water research. Volume 203(2021)
• Publication Date: 2021-09-15
• Subjects: Brownification -- Organic matter -- Absorbance -- Watercourses -- Long-term trends -- Generalized additive mixed model; Water -- Pollution -- Research -- Periodicals; 363.7394
• DOI: 10.1016/j.watres.2021.117544
• Languages: English
• ISSNs: 0043-1354

Abstract

Highlights: Three decades of brownification in 164 Swedish watercourses were evaluated. Widespread organic carbon increases ceased in 2010, color increases ceased in 2000. Organic carbon in many watercourses became less colored after 2000. Long-term trends must be evaluated with appropriate statistical methods. Abstract art caption: The mean estimated trend of TOC concentration based on 164 watercourses 1990–2020. Abstract: Widespread increases in organic matter (OM) content of surface waters, as measured by color and organic carbon (OC), are a major issue for aquatic ecosystems. Long-term monitoring programs revealed the issue of "brownification", with climate change, land cover changes and recovery from acidification all suspected to be major drivers or contributing factors. While many studies have focused on the impact and drivers, fewer have followed up on whether brownification is continuing. As time-series of OM data lengthen, conventional data-analysis approaches miss important information on when changes occur. To better identify temporal OM patterns during three decades (1990–2020) of systematic monitoring, we used generalized additive models to analyze 164 time-series from watercourses located across Sweden. Increases in OC that were widespread during 1990–2010 ceased a decade ago, and most color increases ceased 20 years ago. These findings highlight the need to reassess the understanding of brownification's spatial and temporal extent, as well as the tools used to analyze lengthening time series. Graphical abstract: Image, graphical abstract