Influence of precipitation on CO2 soil emission in pine forests of the Central Siberia boreal zone

A V Makhnykina,A S Prokushkin,D A Polosukhina,S V Verkhovets,N N Koshurnikova

doi:10.1088/1755-1315/211/1/012043

Abstract

Boreal forests in Siberia cover more than 70% of the area of this region. Due to climate change these ecosystems represent a very sensitive and significant source of carbon. In the forests, the total ecosystem respiration tends to be dominated by the soil respiration, which accounts for approximately 70% of this large flux. Global models predict that the soil respiration will increase more than the total net primary productivity in response to climate warming and increasing precipitation. In consequence, the terrestrial carbon sink is expected to decline. However, for the Siberian boreal forest there is still a gap in understanding of the future response of soil emission to drought or overprecipitation conditions. In our study we estimate how various moisture conditions could change soil emission in the boreal zone. From field observation data we find optimal soil moisture conditions. The highest dependence between the soil temperature and soil emission rates has been obtained under the optimal soil moisture conditions.

Highlights

Boreal forests cover about 11% of the earth's land surface, being the largest terrestrial biome
From field observation data we find optimal soil moisture conditions
The highest dependence between the soil temperature and soil emission rates has been obtained under the optimal soil moisture conditions

Summary

Introduction

Boreal forests cover about 11% of the earth's land surface, being the largest terrestrial biome. These forests play a significant role in the global carbon cycle and are sensitive to future climate warming [1]. CO2 fluxes from the soil strongly correlate with changes in the soil temperature when water is not a limiting factor [3]. The seasonal dependence of soil CO2 emissions on the water content in soil is still poorly understood, since changes in the soil temperature and water content often correlate with each other, and the independent influence of each variable is difficult to detect or interpret [6]

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