Affiliation:
1. Institute of Geography RAS
Abstract
We analyzed four years field observations (2017–2020) of soil CO2 efflux from Chernozems of arable and foreststeppe ecosystems of Kursk region (Russia), which correspond to the period of the maximal current warming. Three wellknown simulation models of different structure and variable sets (DNDC, RothC, T&P) and nonparametric regression analysis were used to estimate annual CO2 emission from soil and contributions of constant and sporadic controls. The applied models satisfactorily predict both the rate of annual soil CO2 emission and its seasonal dynamics on arable Chernozems. However, while RothC is suitable for the whole set of crops considered, DNDC is most suitable for cereals and T&R for bare soils only. A comparison of the contributions of permanent and sporadic factors to soil respiration showed that on an inter-annual scale soil temperature and moisture are less important than yearly crop rotation in Chernozem plowlands, making the latter the most important predictor apart from general land-use type. Although the combination of significant permanent and sporadic factors is able to explain 41% of the soil CO2 emission variance, the leading involvement of spatial controls prevents the construction of quantitative regression models that are able to make forecasts, requiring the use of more sophisticated simulation models (i.e. RothC) in this case. However, the use of the latter does not yet solve the problem of predicting soil CO2 emission and its net balance in forest-covered or steppe areas of Chernozem forest-steppe landscape.
Publisher
Russian Geographical Society
Subject
Environmental Science (miscellaneous),Geography, Planning and Development