Anthropogenic activities significantly increase annual greenhouse gas (GHG) fluxes from temperate headwater streams in Germany

溪流 环境科学 温带气候 温室气体 温带森林 水文学(农业) 大气科学 生态学 海洋学 地质学 计算机网络 岩土工程 计算机科学 生物
作者
Ricky Mwangada Mwanake,Gretchen M. Gettel,Elizabeth Gachibu Wangari,Clarissa Glaser,Tobias Houska,Lutz Breuer,Klaus Butterbach‐Bahl,Ralf Kiese
出处
期刊:Biogeosciences [Copernicus Publications]
卷期号:20 (16): 3395-3422 被引量:26
标识
DOI:10.5194/bg-20-3395-2023
摘要

Abstract. Anthropogenic activities increase the contributions of inland waters to global greenhouse gas (GHG; CO2, CH4, and N2O) budgets, yet the mechanisms driving these increases are still not well constrained. In this study, we quantified year-long GHG concentrations, fluxes, and water physico-chemical variables from 28 sites contrasted by land use across five headwater catchments in Germany. Based on linear mixed-effects models, we showed that land use was more significant than seasonality in controlling the intra-annual variability of the GHGs. Streams in agriculture-dominated catchments or with wastewater inflows had up to 10 times higher daily CO2, CH4, and N2O emissions and were also more temporally variable (CV > 55 %) than forested streams. Our findings also suggested that nutrient, labile carbon, and dissolved GHG inputs from the agricultural and settlement areas may have supported these hotspots and hot-moments of fluvial GHG emissions. Overall, the annual emission from anthropogenic-influenced streams in CO2 equivalents was up to 20 times higher (∼ 71 kg CO2 m−2 yr−1) than from natural streams (∼ 3 kg CO2 m−2 yr−1), with CO2 accounting for up to 81 % of these annual emissions, while N2O and CH4 accounted for up to 18 % and 7 %, respectively. The positive influence of anthropogenic activities on fluvial GHG emissions also resulted in a breakdown of the expected declining trends of fluvial GHG emissions with stream size. Therefore, future studies should focus on anthropogenically perturbed streams, as their GHG emissions are much more variable in space and time and can potentially introduce the largest uncertainties to fluvial GHG estimates.
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