2014
DOI: 10.4028/www.scientific.net/amm.692.70
|View full text |Cite
|
Sign up to set email alerts
|

Seasonal and Interannual Variation of Soil Respiration on the Sanjiang Plain Wentlands in Northeast China

Abstract: Response of soil respiration in temperate wetlands in northeast China was studied from June 2009 to September 2011. Li-Cor 6400 infrared gas analyzer connected with a chamber was used to quantify the soil respiration. Results showed that soil respiration displayed a distinct seasonal pattern, with higher values observed in midsummer and lower values in spring and autumn. Furthermore, soil respiration exhibited a significant inter-annual variation. In addition, soil respiration presented significant positive ex… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2018
2018
2018
2018

Publication Types

Select...
1

Relationship

0
1

Authors

Journals

citations
Cited by 1 publication
(1 citation statement)
references
References 4 publications
0
1
0
Order By: Relevance
“…In spatial terms, by applying process-based or geostatistical models, these studies use gridded data to simulate the spatial distribution of Rs within China as a whole or particular regions in China [32,35]. Temporally, by calculating the interannual mean Rs values for entire regions, they analyse the trends in Rs revealed by time series [34,36]. However, few studies combine spatially gridded data and time series data to perform deep analyses of variations in Rs.…”
Section: Introductionmentioning
confidence: 99%
“…In spatial terms, by applying process-based or geostatistical models, these studies use gridded data to simulate the spatial distribution of Rs within China as a whole or particular regions in China [32,35]. Temporally, by calculating the interannual mean Rs values for entire regions, they analyse the trends in Rs revealed by time series [34,36]. However, few studies combine spatially gridded data and time series data to perform deep analyses of variations in Rs.…”
Section: Introductionmentioning
confidence: 99%