State-space prediction of soil respiration time series in temperate, semi-arid grassland in northern China

Article

<< Previous

Next >>

Contents Vol 50(4)

doi:10.1071/SR12068

Soil, Land Care & Environmental Research

	Search




	Advanced Search



	Journal Home

	About the Journal

	Editorial Board

	Contacts

	For Advertisers



	Content

	Online Early

	Current Issue

	Just Accepted

	All Issues

	Special Issues

	Sample Issue



	For Authors

	General Information

	Notice to Authors

	Submit Article

	Open Access



	For Referees

	Referee Guidelines

	Review Article

	Annual Referee Index



	For Subscribers

	Subscription Prices

	Customer Service

	Print Publication Dates

e-Alerts

Subscribe to our Email Alert or

feeds for the latest journal papers.

Connect with us

Now Online

State-space prediction of soil respiration time series in temperate, semi-arid grassland in northern China

Xiaoxu Jia ^A, Ming’an Shao ^B ^C and Xiaorong Wei ^A

^A State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Northwest A & F University, Yangling 712100, China.
^B Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
^C Corresponding author. Email: mashao@ms.iswc.ac.cn

Australian Journal of Soil Research 50(4) 293-303 http://dx.doi.org/10.1071/SR12068
Submitted: 15 March 2012 Accepted: 24 May 2012 Published: 3 July 2012





	PDF (430 KB) $25



	Export Citation

Print

Abstract

The prediction of soil respiration (Rs) has traditionally been studied using classical statistical methods. These methods do not consider temporal/spatial coordinates and assume independence between samples. The aim was to determine the primary factors influencing Rs and to develop a state-space model able to predict soil respiration. This study was conducted during one growing season, from July to October 2010, in temperate, semi-arid grassland. Data were collected for Rs, air temperature, soil surface temperature, soil temperature at a depth of 5 cm, soil moisture, air pressure, and relative humidity. Additionally, a novel autoregressive state-space method was used to simulate and predict Rs based on primary factors, and the quality of prediction was compared with the quality of prediction using classical statistics. Soil surface temperature and soil moisture were identified as primary factors affecting Rs. The state-space model that included soil surface temperature was a simple but effective model, accounting for 95% of the variation in Rs. The classical statistical models, however, represented only 39–69% of the variation in Rs. Furthermore, the quality of prediction of the state-space models was consistently much better than the quality from the classical statistical methods. State-space analysis is an effective tool for studying the temporal relationships between soil respiration and influencing factors. Additionally, the state-space method is recommended for predicting soil respiration using soil surface temperature in semi-arid grassland in northern China.

Additional keywords: autoregressive soil respiration prediction, classical regression models, semiarid grassland, soil respiration, state-space models.

References

Chen QS, Li LH, Han XG, Yan ZD, Wang YF, Yuan ZY (2003) Influence of temperature and soil moisture on soil respiration of a degraded steppe community in the Xilin river basin of Inner Mongolia. Acta Phytoecologica Sinica [In Chinese with English abstract] 27, 202–209.

Chimner RA (2004) Soil respiration rates of tropical peat lands in Micronesia and Hawaii. Wetlands 24, 51–56.
| CrossRef |

Cook FJ, Thomas SM, Kelliher FM, Whitehead D (1998) A model of one-dimensional steady-state carbon dioxide diffusion from soil. Ecological Modelling 109, 155–164.
| CrossRef | CAS |

Davidson EA, Belk E, Boone RD (1998) Soil water content and temperature as independent or confounded factors controlling soil respiration in a temperature mixed hardwood forest. Global Change Biology 4, 217–227.
| CrossRef |

Davidson EA, Verchot LV, Cattanio JH, Ackerman IL, Carvalho JEM (2000) Effects of soil water content on soil respiration in forests and cattle pastures of eastern Amazonia. Biogeochemistry 48, 53–69.
| CrossRef | CAS |

Grace J, Rayment M (2000) Respiration in the balance. Nature 404, 819–820.
| CrossRef | CAS |

Granier A, Ceschia E, Damesin C, Dufrene E, Epron D, Gross P, Lebaube S, Le Dantee V, Le Goff N, Lemoine D (2000) The carbon balance of a young Beech forest. Functional Ecology 14, 312–325.
| CrossRef |

Högberg P, Nordgren A, Buchmann N, Taylor AFS, Ekblad A, Högberg MN, Nyberg G, Löfvenius MO, Read DJ (2001) Large-scale forest girdling shows that current photosynthesis drives soil respiration. Nature 411, 789–792.
| CrossRef |

Howard DM, Howard PJA (1993) Relationships between CO₂ evolution, moisture content and temperature for a range of soil types. Soil Biology & Biochemistry 25, 1537–1546.
| CrossRef |

Hui S, Wendroth O, Parlange MB, Nielsen DR (1998) Soil variability–infiltration relationships of agroecosystems. Journal of Balkan Ecology 1, 21–40.

Jia BR, Zhou GS, Wang YH, Wang F, Wang X (2006) Effects of temperature and soil water-content on soil respiration of grazed and ungrazed Leymus chinensis steppes, Inner Mongolia. Journal of Arid Environments 67, 60–76.
| CrossRef |

Jia BR, Zhou GS, Yuan WP (2007) Modeling and coupling of soil respiration and soil water content in fenced Leymus chinensis steppe, Inner Mongolia. Ecological Modelling 201, 157–162.
| CrossRef |

Jia XX, Shao MA, Wei XR, Horton R, Li XZ (2011) Estimating total net primary productivity of managed grasslands by a state-space modeling approach in a small catchment on the Loess Plateau, China. Geoderma 160, 281–291.
| CrossRef | CAS |

Journel AG, Huijbregts CJ (1991) ‘Mining geostatistics.’ (Academic Press: London)

Kang S, Doh S, Lee DS, Lee D, Jin VL, Kimball JS (2003) Topographic and climatic controls on soil respiration in six temperate mixed-hardwood forest slopes, Korea. Global Change Biology 9, 1427–1437.
| CrossRef |

Kucera CL, Kirkham DR (1971) Soil respiration studies in tallgrass prairie in Missouri. Ecology 52, 912–915.
| CrossRef | CAS |

Li LH, Wang QB, Bai YF, Zhou GS, Xing XR (2000) Soil respiration of a Leymus chinensis grassland stand in the XiLin river basin as affected by over-grazing and climate. Acta Phytoecologica Sinica [In Chinese with English abstract] 24, 680–686.

Liu SH, Fang JY (1997) Effect factors of soil respiration and the temperature’s effects on soil respiration in the global scale. Acta Ecologica Sinica [In Chinese with English abstract] 17, 469–476.

Nielsen DR, Alemi MH (1989) Statistical opportunities for analyzing spatial and temporal heterogeneity of field soils. Plant and Soil 115, 285–296.
| CrossRef |

Nielsen DR, Wendroth O (2003) Spatial and temporal statistics—sampling field soils and their vegetation. In ‘Geoecology textbook’. (Catena-Verlag: Reiskirchen)

Nielsen DR, Katul GG, Wendroth O, Folegatti MV, Parlange MB (1994) State-space approaches to estimate soil physical properties from field measurements. In ‘Proceedings of 15th Conference of ISSS. Comm. I, Symposium on Soil Physics and Environmental Protection, vol. 2a’. Acapulco, Mexico, pp. 61–85.

Peterson KM, Billings WD (1975) Carbon dioxide flux from tundra soils and vegetation as related to temperature at Barrow, Alaska. American Midland Naturalist 94, 88–98.
| CrossRef |

Qi LB, Fan J, Shao MA, Wang WZ (2008) Seasonal changes in soil respiration under different land use patterns in the water-wind erosion crisscross region of the Loess Plateau. Acta Ecologica Sinica [In Chinese with English abstract] 28, 5428–5436.

Raich JW, Potter CS (1995) Global patterns of carbon dioxide emissions from soils. Global Biogeochemical Cycles 9, 23–36.
| CrossRef | CAS |

Raich JW, Schlesinger WH (1992) The global carbon dioxide flux in soil respiration and its relationship to vegetation and climate. Tellus 44B, 81–99.

Rodeghiero M, Cescatti A (2005) Main determinants of forest soil respiration along an elevation/temperature gradient in the Italian Alps. Global Change Biology 11, 1024–1041.
| CrossRef |

Schlentner RE, Van Cleve K (1985) Relationships between CO₂ evolution from soil, substrate temperature, and substrate moisture in four mature forest types in interior Alaska. Canadian Journal of Forest Research 15, 97–106.
| CrossRef | CAS |

Schlesinger WH, Andraws JA (2000) Soil respiration and the global carbon cycle. Biogeochemistry 48, 7–20.
| CrossRef | CAS |

Shumway RH (1988) ‘Applied statistical time series analyses.’ (Prentice Hall: Englewood Cliffs, NJ)

Tang J, Baldocchi DD, Xu L (2005) Tree photosynthesis modulates soil respiration on a diurnal time scale. Global Change Biology 11, 1298–1304.
| CrossRef |

Timm LC, Reichardt K, Oliveira JCM, Cassaro FAM, Tominaga TT, Bacchi OOS, Dourado-Neto D (2003a) Sugarcane production evaluated by the state-space approach. Journal of Hydrology 272, 226–237.
| CrossRef | CAS |

Timm LC, Reichardt K, Oliveira JCM, Cassaro FAM, Tominaga TT, Bacchi OOS, Dourado-Neto D (2003b) State-space approach for evaluating the soil–plant–atmosphere system. In ‘Lectures notes at the College on Soil Physics’. International Centre for Theoretical Physics, Trieste, Italy, pp. 387–427.

Tufekcioglu A, Raich JW, Isenhart TM, Schultz RC (2001) Soil respiration within riparian buffers and adjacent crop fields. Plant and Soil 229, 117–124.
| CrossRef | CAS |

Wang FY, Zhou GS, Jia BR, Wang YH (2003) Effects of heat and water factors on soil respiration of restoring Leymus Chinensis Steppe in degraded land. Acta Phytoecologica Sinica [In Chinese with English abstract] 27, 644–649.

Wendroth O, Reynolds WD, Vieira SR, Reichardt K, Wirth S (1997) Statistical approaches to the analysis of soil quality data. In ‘Soil quality for crop production and ecosystem health’. Development in Soil Science, Vol. 25. (Eds EG Gregorich, MR Carter) pp. 247–276. (Elsevier: New York)

Wendroth O, Jürschik P, Giebel A, Nielsen DR (1999) Spatial statistical analysis of on-site-crop yield and soil observation for site-specific management. In ‘Proceedings of the Fourth International Conference on Precision Agriculture’. (Eds PC Robert, RH Rust, WE Larson) pp. 159–170. (ASA-SSSA-CSSA: Madison, WI)

Wendroth O, Reuter HI, Christian Kersebaum K (2003) Predicting yield of barley across a landscape: a state-space modeling approach. Journal of Hydrology 272, 250–263.
| CrossRef |

Subscriber Login

	Username: Password:

Legal & Privacy | Contact Us | Help