Predicting soil respiration for the Qinghai-Tibet Plateau: An empirical comparison of regression models
Alpine ecosystems like the Qinghai-Tibet Plateau strongly respond to global warming. Their soils, containing large carbon stocks, release more carbon dioxide as a possible consequence. Reciprocally, this may intensify climate warming. The Qinghai-Tibet plateau's large and almost inaccessible te...
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Online Access: | http://210.75.249.4/handle/363003/5770 https://doi.org/10.1016/j.pedobi.2016.01.002 |
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ftchinacascnwipb:oai:210.75.249.4:363003/5770 2023-05-15T17:58:20+02:00 Predicting soil respiration for the Qinghai-Tibet Plateau: An empirical comparison of regression models Bosch, Anna Doerfer, Corina He, Jin-Sheng Schmidt, Karsten Scholten, Thomas 2016 http://210.75.249.4/handle/363003/5770 https://doi.org/10.1016/j.pedobi.2016.01.002 英语 eng PEDOBIOLOGIA http://210.75.249.4/handle/363003/5770 doi:10.1016/j.pedobi.2016.01.002 Soil Respiration Regression Model Qinghai-tibet Plateau Worldclim Science & Technology Life Sciences & Biomedicine CO2 EFFLUX TEMPERATURE SENSITIVITY PERMAFROST DEGRADATION GLOBAL DATABASE ORGANIC-CARBON ALPINE MEADOW WATER-CONTENT FOREST SOIL HIGH ASIA PRECIPITATION Environmental Sciences & Ecology Agriculture Ecology Soil Science Article 期刊论文 2016 ftchinacascnwipb https://doi.org/10.1016/j.pedobi.2016.01.002 2023-03-26T20:23:11Z Alpine ecosystems like the Qinghai-Tibet Plateau strongly respond to global warming. Their soils, containing large carbon stocks, release more carbon dioxide as a possible consequence. Reciprocally, this may intensify climate warming. The Qinghai-Tibet plateau's large and almost inaccessible terrain results in a general data scarcity for this area making the quantification of soil carbon dynamics challenging. The current study provides an area-wide estimation of soil respiration for the Qinghai-Tibet Plateau, which is a key region for climate change studies due to its size and sensitivity. We compared the ability of six regression models to predict soil respiration that were developed within different studies and are based on mean annual air temperature, mean annual precipitation and belowground biomass. We used the WorldClim data sets to approximate annual soil respiration on a regional scale. Compared to field measurements of soil respiration at single spots in different vegetation zones on the Qinghai-Tibet Plateau (max. 1876.63 g Cm-2 year(-1)), our predicted results (max. 1765.13 g Cm-2 year-1) appear to be consistent. The basic difference between grasslands and forests in soil respiration is indicated by all regression models, however, a more precise differentiation between vegetation types is only exhibited by the regression model based on mean annual precipitation. Overall, this model performs best for most and the largest vegetation zones. Nevertheless, the approximations of the model based on mean annual temperature by Raich and Schlesinger (1992) with a lower constant better represent the vegetation zone of the alpine steppe. With this spatial estimation of soil respiration at a regional scale, a basis for assessing an area-specific potential of greenhouse gas emissions on the Qinghai-Tibet Plateau is provided. Moreover, we quantify a complex soil ecological process for this data-scarce area. (C) 2016 Elsevier GmbH. All rights reserved. Article in Journal/Newspaper permafrost Northwest Institute of Plateau Biology: NWIPB OpenIR (Chinese Academy of Sciences) Pedobiologia 59 1-2 41 49 |
institution |
Open Polar |
collection |
Northwest Institute of Plateau Biology: NWIPB OpenIR (Chinese Academy of Sciences) |
op_collection_id |
ftchinacascnwipb |
language |
English |
topic |
Soil Respiration Regression Model Qinghai-tibet Plateau Worldclim Science & Technology Life Sciences & Biomedicine CO2 EFFLUX TEMPERATURE SENSITIVITY PERMAFROST DEGRADATION GLOBAL DATABASE ORGANIC-CARBON ALPINE MEADOW WATER-CONTENT FOREST SOIL HIGH ASIA PRECIPITATION Environmental Sciences & Ecology Agriculture Ecology Soil Science |
spellingShingle |
Soil Respiration Regression Model Qinghai-tibet Plateau Worldclim Science & Technology Life Sciences & Biomedicine CO2 EFFLUX TEMPERATURE SENSITIVITY PERMAFROST DEGRADATION GLOBAL DATABASE ORGANIC-CARBON ALPINE MEADOW WATER-CONTENT FOREST SOIL HIGH ASIA PRECIPITATION Environmental Sciences & Ecology Agriculture Ecology Soil Science Bosch, Anna Doerfer, Corina He, Jin-Sheng Schmidt, Karsten Scholten, Thomas Predicting soil respiration for the Qinghai-Tibet Plateau: An empirical comparison of regression models |
topic_facet |
Soil Respiration Regression Model Qinghai-tibet Plateau Worldclim Science & Technology Life Sciences & Biomedicine CO2 EFFLUX TEMPERATURE SENSITIVITY PERMAFROST DEGRADATION GLOBAL DATABASE ORGANIC-CARBON ALPINE MEADOW WATER-CONTENT FOREST SOIL HIGH ASIA PRECIPITATION Environmental Sciences & Ecology Agriculture Ecology Soil Science |
description |
Alpine ecosystems like the Qinghai-Tibet Plateau strongly respond to global warming. Their soils, containing large carbon stocks, release more carbon dioxide as a possible consequence. Reciprocally, this may intensify climate warming. The Qinghai-Tibet plateau's large and almost inaccessible terrain results in a general data scarcity for this area making the quantification of soil carbon dynamics challenging. The current study provides an area-wide estimation of soil respiration for the Qinghai-Tibet Plateau, which is a key region for climate change studies due to its size and sensitivity. We compared the ability of six regression models to predict soil respiration that were developed within different studies and are based on mean annual air temperature, mean annual precipitation and belowground biomass. We used the WorldClim data sets to approximate annual soil respiration on a regional scale. Compared to field measurements of soil respiration at single spots in different vegetation zones on the Qinghai-Tibet Plateau (max. 1876.63 g Cm-2 year(-1)), our predicted results (max. 1765.13 g Cm-2 year-1) appear to be consistent. The basic difference between grasslands and forests in soil respiration is indicated by all regression models, however, a more precise differentiation between vegetation types is only exhibited by the regression model based on mean annual precipitation. Overall, this model performs best for most and the largest vegetation zones. Nevertheless, the approximations of the model based on mean annual temperature by Raich and Schlesinger (1992) with a lower constant better represent the vegetation zone of the alpine steppe. With this spatial estimation of soil respiration at a regional scale, a basis for assessing an area-specific potential of greenhouse gas emissions on the Qinghai-Tibet Plateau is provided. Moreover, we quantify a complex soil ecological process for this data-scarce area. (C) 2016 Elsevier GmbH. All rights reserved. |
format |
Article in Journal/Newspaper |
author |
Bosch, Anna Doerfer, Corina He, Jin-Sheng Schmidt, Karsten Scholten, Thomas |
author_facet |
Bosch, Anna Doerfer, Corina He, Jin-Sheng Schmidt, Karsten Scholten, Thomas |
author_sort |
Bosch, Anna |
title |
Predicting soil respiration for the Qinghai-Tibet Plateau: An empirical comparison of regression models |
title_short |
Predicting soil respiration for the Qinghai-Tibet Plateau: An empirical comparison of regression models |
title_full |
Predicting soil respiration for the Qinghai-Tibet Plateau: An empirical comparison of regression models |
title_fullStr |
Predicting soil respiration for the Qinghai-Tibet Plateau: An empirical comparison of regression models |
title_full_unstemmed |
Predicting soil respiration for the Qinghai-Tibet Plateau: An empirical comparison of regression models |
title_sort |
predicting soil respiration for the qinghai-tibet plateau: an empirical comparison of regression models |
publishDate |
2016 |
url |
http://210.75.249.4/handle/363003/5770 https://doi.org/10.1016/j.pedobi.2016.01.002 |
genre |
permafrost |
genre_facet |
permafrost |
op_relation |
PEDOBIOLOGIA http://210.75.249.4/handle/363003/5770 doi:10.1016/j.pedobi.2016.01.002 |
op_doi |
https://doi.org/10.1016/j.pedobi.2016.01.002 |
container_title |
Pedobiologia |
container_volume |
59 |
container_issue |
1-2 |
container_start_page |
41 |
op_container_end_page |
49 |
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1766166927081734144 |