Multivariate conditional stochastic simulation of soil heterotrophic respiration at plot scale
This page lists all metadata that was entered for this dataset. Only registered users of the TR32DB may download this file.
Feature
Request download
Citation
Citation Options
Identification
| Title: | Main Title: Multivariate conditional stochastic simulation of soil heterotrophic respiration at plot scale |
| Description: | Abstract: Soil heterotrophic respiration fluxes at plot scale exhibit substantial spatial and temporal variability. Within this study secondary information was used to spatially predict heterotrophic respiration. Chamber-based measurements of heterotrophic respiration fluxes were repeated for 15 measurement campaigns within a bare 13× ^ 14 m2 soil plot. Soil water contents and temperatures were measured simultaneously with the same spatial and temporal resolution. Further, we used measurements of soil organic carbon content and apparent electrical conductivity as well as the prior measurement of the target variable. The previous variables were used as co-variates in a stepwise multiple linear regression analysis to spatially predict bare soil respiration. In particular the prior measurement of the target variable, the soil water content and the apparent electrical conductivity, showed a certain, even though limited, predictive power. In the first step we applied external drift kriging and regression kriging to determine the improvement of using co-variates in an estimation procedure in comparison to ordinary kriging. The improvement using co-variates ranged between 40 and 1% for a single measurement campaign. The difference in improving the prediction of respiration fluxes between external drift kriging and regression kriging was marginal. In a second step we applied sequential Gaussian simulations conditioned with external drift kriging to generate more realistic spatial patterns of heterotrophic respiration at plot scale. Compared to the estimation approaches the conditional stochastic simulations revealed a significantly improved reproduction of the probability density function and the semi-variogram of the original point data. |
| Identifier: | 10.1016/j.geoderma.2009.11.018 (DOI) |
Responsible Party
| Creators: | Michael Herbst (Author), Nils Prolingheuer (Author), Alexander Graf (Author), Johan A. Huisman (Author), Lutz Weihermüller (Author), Jan Vanderborght (Author), Harry Vereecken (Author) |
| Publisher: | Elsevier |
| Publication Year: | 2013 |
Topic
| TR32 Topic: | Soil |
| Related Subproject: | B1 |
| Subjects: | Keywords: CO2, Carbon, Field Scale, Spatial Variability, External Drift Kriging, Heterotrophic Respiration |
File Details
| Filename: | 2010_Herbst_Geoderma.pdf |
| Data Type: | Text - Article |
| Size: | 9 Pages |
| File Size: | 1.4 MB |
| Dates: | Accepted: 21.11.2009 Available: 16.10.2009 |
| Mime Type: | application/pdf |
| Data Format: | |
| Language: | English |
| Status: | Completed |
Constraints
| Download Permission: | Only Project Members |
| General Access and Use Conditions: | For internal use only |
| Access Limitations: | For internal use only |
| Licence: | [TR32DB] Data policy agreement |
Geographic
Specific Information - Publication
| Publication Status: | Published |
| Review Status: | Peer reviewed |
| Publication Type: | Article |
| Article Type: | Journal |
| Source: | Geoderma |
| Source Website: | www.elsevier.com/locate/geoderma |
| Volume: | 160 |
| Number of Pages: | 9 (74 - 82) |
Metadata Details
| Metadata Creator: | Nils Prolingheuer |
| Metadata Created: | 02.12.2013 |
| Metadata Last Updated: | 02.12.2013 |
| Subproject: | B1 |
| Funding Phase: | 1 |
| Metadata Language: | English |
| Metadata Version: | V50 |
Metadata Export
| Metadata Schema: |
Dataset Statistics
| Page Visits: | 1095 |
| Metadata Downloads: | 0 |
| Dataset Downloads: | 0 |
Dataset Activity
Feature
DownloadBy downloading this dataset you accept the license terms of [TR32DB] Data policy agreement and TR32DB Data Protection Statement
Adequate reference when this dataset will be discussed or used in any publication or presentation is mandatory. In this case please contact the dataset creator.
Adequate reference when this dataset will be discussed or used in any publication or presentation is mandatory. In this case please contact the dataset creator.
