4.8 Article

Afforestation driving long-term surface water browning

Journal

GLOBAL CHANGE BIOLOGY
Volume 26, Issue 3, Pages 1390-1399

Publisher

WILEY
DOI: 10.1111/gcb.14891

Keywords

afforestation; atmospheric deposition; browning; climate change; DOC; land use; water color

Funding

  1. Svenska Forskningsradet Formas [2015-01407]
  2. Formas [2015-01407] Funding Source: Formas

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Increase in surface water color (browning), caused by rising dissolved organic carbon (DOC) and iron concentrations, has been widely reported and studied in the last couple of decades. This phenomenon has implications to aquatic ecosystem function and biogeochemical carbon cycling. While recovery from acidification and changes in climate-related variables, such as precipitation and length of growing season, are recognized as drivers behind browning, land-use change has received less attention. In this study, we include all of the above factors and aim to discern their individual and combined contribution to water color variation in an unprecedentedly long (1940-2016) and highly resolved dataset (20 times per month), from a river in southern Sweden. Water color showed high seasonal variability and a marked long-term increase, particularly in the latter half of the dataset (1980). Short-term and seasonal variations were best explained by precipitation, with temperature playing a secondary role. All explanatory variables (precipitation, temperature, S deposition, and land-use change) contributed significantly and together predicted 75% of the long-term variation in water color. Long-term change was best explained by a pronounced increase in Norway spruce (Picea abies Karst) volume-a measure of land-use change and a proxy for buildup of organic soil layers-and by change in atmospheric S deposition. When modeling water color with a combination of explanatory variables, Norway spruce showed the highest contribution to explaining long-term variability. This study highlights the importance of considering land-use change as a factor behind browning and combining multiple factors when making predictions in water color and DOC.

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