Climatic versus geochemical controls on soil organic matter stabilization and greenhouse gas emissions along altitudinal transects in different mountain regions
- Other Conference Item
Rights / licenseCreative Commons Attribution 4.0 International
Terrestrial ecosystems are strongly influenced by climate change and soils are key compartments of the globalcarbon (C) cycle in terms of their potential to store or release significant amounts of C. This study is part ofthe interregional IAEA Technical Cooperation Project INT5153 “Assessing the Impact of Climate Change and itsEffects on Soil and Water Resources in Polar and Mountainous Regions” and aims to elucidate driving factors(climatic versus geochemical) of soil organic carbon (SOC) stabilization and greenhouse gas emissions alongaltitudinal transects in different mountain regions.We present novel data from altitudinal transects of four different mountain regions (Zongo, Cordillera Real, Bo-livia; Mount Kilimanjaro, Tanzania; Gongga, Hengduan Mountains, China; Rauris, Hohe Tauern, Austria). Allaltitudinal transects cover a wide range of natural ecosystems under different climatic (MAT, MAP) and soil geo-chemical parameters. Bulk soil samples (four field replicates per ecosystems) were subjected to a combination ofaggregate and particle-size fractionation followed by organic C, total nitrogen (N), stable isotope (13C,15N) andradiocarbon (14C) analyses of all fractions. Bulk soils were further characterized for their texture, geochemistry(Na, K, Ca, Mg, CECpot, Al, Fe, Mn, Si, pH), nutrient status (NH+4, NO−3, Ptot)and incubated for 63 days to assessgreenhouse gas emissions (CO2, CH4, NO, N2O). Moreover, stable C isotope signatures of CO2were determinedto estimate potential sources of soil respiration (using Keeling plots).Cumulative soil CO2emissions (in gCO2-Ckg−1SOC)were highest for the high altitude grassland and forest sitesof Rauris (25.5-25.8) and lowest for the Kilimanjaro forests (4.8-6.9) as well as Bolivian high altitude grasslands(2.5-4.3). Soil CO2emissions were negatively correlated with SOC content (Pearson correlation coefficient rp=-0.35, p=0.002), showing that soils with low SOC contents release the highest amount of CO2per soil C, possiblydue to large fractions of unprotected SOC and thus low SOC stabilization.Particulate organic matter (POM) and sand content were positively correlated with CO2emissions (rp=0.43,p<0.001 and rp=0.57, p<0.001, respectively) and negatively correlated with SOC content (rp=-0.61, p<0.001for sand content), showing that high amounts of POM and/or a sandy soil texture impede SOC storage and supportCO2emissions. In contrast, microaggregates and clay minerals were negatively correlated with CO2emissions(rp=-0.45, p<0.001 and rp=-0.51, p<0.001, respectively) and positively correlated with SOC content (rp=0.84,p<0.001 for clay content), showing their importance for SOC stabilization.Cation exchange capacity (CEC) was positively correlated with SOC content (rp=0.93, p<0.001) and negativelycorrelated with CO2emissions (rp=-0.41, p<0.001). Oppositely, both Si content and the Si/Al ratio were negatively correlated with SOC content (rp=-0.86, p<0.001 and rp=-0.56, p<0.001, respectively) and positively correlatedwith CO2emissions (rp=0.36, p=0.002 and rp=0.34, p=0.003). These relationships point towards an important roleof soil weathering and geochemistry for the potential of soils to store SOC or release CO2.Further results of soil fractionation, greenhouse gas emissions and geochemistry will be presented in conjunctionwith climatic data of the altitudinal transects to elucidate driving factors of SOC (de)stabilization in high altitudemountain regions. Show more
Journal / seriesGeophysical Research Abstracts
Pages / Article No.
Organisational unit09646 - Dötterl, Sebastian / Dötterl, Sebastian
03868 - Eglinton, Timothy I. / Eglinton, Timothy I.
174300 - Sources and proportions of modern and aged organic carbon eroded from soils under different land-use within catchments in Nepal – Insights from compound-specific 13C & 14C analysis and novel mixing models (SNF)
NotesConference lecture held on april 12, 2018
MoreShow all metadata