RESUMO
Wetlands play a disproportionate role in the global climate as major sources and sinks of greenhouse gases. Herbicides are the most heavily used agrochemicals and are frequently detected in aquatic ecosystems, with glyphosate and 2,4-Dichlorophenoxyacetic acid (2,4-D), representing the two most commonly used worldwide. In recent years, these herbicides are being used in mixtures to combat herbicide-tolerant noxious weeds. While it is well documented that herbicide use for agriculture is expected to increase, their indirect effects on wetland greenhouse gas dynamics are virtually unknown. To fill this knowledge gap, we conducted a factorial microcosm experiment using low, medium, and high concentrations of glyphosate or 2,4-D, individually and in combination to investigate their effects on wetland methane, carbon dioxide, and nitrous oxide fluxes. We predicted that mixed herbicide treatments would have a synergistic effect on greenhouse gases compared to individual herbicides. Our results showed that carbon dioxide flux rates and cumulative emissions significantly increased from both individual and mixed herbicide treatments, whereas methane and nitrous oxide dynamics were less affected. This study suggests that extensive use of glyphosate and 2,4-D may increase carbon dioxide emissions from wetlands, which could have implications for climate change.
RESUMO
Climate warming is expected to increase global methane (CH4 ) emissions from wetland ecosystems. Although in situ eddy covariance (EC) measurements at ecosystem scales can potentially detect CH4 flux changes, most EC systems have only a few years of data collected, so temporal trends in CH4 remain uncertain. Here, we use established drivers to hindcast changes in CH4 fluxes (FCH4 ) since the early 1980s. We trained a machine learning (ML) model on CH4 flux measurements from 22 [methane-producing sites] in wetland, upland, and lake sites of the FLUXNET-CH4 database with at least two full years of measurements across temperate and boreal biomes. The gradient boosting decision tree ML model then hindcasted daily FCH4 over 1981-2018 using meteorological reanalysis data. We found that, mainly driven by rising temperature, half of the sites (n = 11) showed significant increases in annual, seasonal, and extreme FCH4 , with increases in FCH4 of ca. 10% or higher found in the fall from 1981-1989 to 2010-2018. The annual trends were driven by increases during summer and fall, particularly at high-CH4 -emitting fen sites dominated by aerenchymatous plants. We also found that the distribution of days of extremely high FCH4 (defined according to the 95th percentile of the daily FCH4 values over a reference period) have become more frequent during the last four decades and currently account for 10-40% of the total seasonal fluxes. The share of extreme FCH4 days in the total seasonal fluxes was greatest in winter for boreal/taiga sites and in spring for temperate sites, which highlights the increasing importance of the non-growing seasons in annual budgets. Our results shed light on the effects of climate warming on wetlands, which appears to be extending the CH4 emission seasons and boosting extreme emissions.