TR32-Database: Database of Transregio 32

[1791] - Soil respiration and its temperature sensitivity (Q10): Rapid acquisition using mid-infrared spectroscopy

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Meyer, N., Meyer, H., Welp, G., Amelung, W., 2018. Soil respiration and its temperature sensitivity (Q10): Rapid acquisition using mid-infrared spectroscopy. Geoderma, 323, 31 - 40. DOI: 10.1016/j.geoderma.2018.02.031.
Title(s):Main Title: Soil respiration and its temperature sensitivity (Q10): Rapid acquisition using mid-infrared spectroscopy
Description(s):Abstract: Spatial patterns of soil respiration (SR) and its sensitivity to temperature (Q10) are one of the key uncertainties in climate change research but since their assessment is very time-consuming, large data sets can still not be provided. Here, we investigated the potential of mid-infrared spectroscopy (MIRS) to predict SR and Q10 values for 124 soil samples of diverse land use types taken from a 2868 km2 catchment (Rur catchment, Germany/Belgium/Netherlands). Soil respiration at standardized temperature (25 °C) and soil moisture (45% of maximum water holding capacity, WHC) was successfully predicted by MIRS coupled with partial least square regression (PLSR, R2= 0.83). Also the Q10 value was predictable by MIRS-PLSR for a grassland submodel (R2= 0.75) and a cropland submodel (R2= 0.72) but not for forested sites (R2= 0.03). In order to provide soil respiration estimates for arbitrary conditions of temperature and soil moisture, more flexible models are required that can handle nonlinear and interacting relations. Therefore, we applied a Random Forest model, which includes the MIRS spectra, temperature, soil moisture, and land use as predictor variables. We could show that SR can be simultaneously predicted for any temperature (5–25 °C) and soil moisture level (30–75% of WHC), indicated by a high R2 of 0.73. We conclude that the combination of MIRS with sophisticated statistical prediction tools allows for a novel, rapid acquisition of SR and Q10 values across landscapes and thus to fill an important data gap in the validation of large scale carbon modeling.
Identifier(s):DOI: 10.1016/j.geoderma.2018.02.031
Responsible Party
Creator(s):Author: Nele Meyer
Author: Hanna Meyer
Author: Gerd Welp
Author: Wulf Amelung
TR32 Topic:Soil
Related Sub-project(s):B3
Subject(s):CRC/TR32 Keywords: Soil, Soil Respiration
File Details
File Name:Meyer_et_al_Geoderma_2018.pdf
Data Type:Text
File Size:1102 kB (1.076 MB)
Date(s):Date Accepted: 2018-02-21
Mime Type:application/pdf
Data Format:PDF
Download Permission:OnlyTR32
General Access and Use Conditions:According to the TR32DB data policy agreement.
Access Limitations:According to the TR32DB data policy agreement.
North:-no map data
Measurement Region:RurCatchment
Measurement Location:--RurCatchment--
Specific Informations - Publication
Article Type:Journal
Page Range:31 - 40
Metadata Details
Metadata Creator:Nele Meyer
Metadata Created:2018-03-28
Metadata Last Updated:2018-04-04
Funding Phase:3
Metadata Language:English
Metadata Version:V42
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