Spatial inconsistencies influence global estimates of soil respiration: how can we improve global predictions?
| Author(s) | Stell, Emma | |
| Date Accessioned | 2021-04-20T12:30:51Z | |
| Date Available | 2021-04-20T12:30:51Z | |
| Publication Date | 2020 | |
| SWORD Update | 2021-02-08T17:04:16Z | |
| Abstract | Soil respiration (Rs), the efflux of CO2 from soils to the atmosphere, is a major component of the terrestrial carbon cycle, but is poorly constrained from regional-to-global scales. The global soil respiration database (SRDB) is a compilation of in-situ Rs observations from around the globe that has been consistently updated with new measurements over the past decade. It is unclear whether the addition of data to new versions of the SRDB has produced better-constrained global Rs estimates. We compared two versions of the SRDB (v3.0 n=5173 and v5.0 n=10366) to determine how additional data influenced the global sum and uncertainty of Rs as predicted by a quantile regression forest model. A model parameterized using SRDBv3 yielded a global Rs sum of 88.6 Pg C yr-1, and associated uncertainty of 29.9 (mean absolute error) and 57.9 (standard deviation) Pg C yr-1, whereas parameterization using SRDBv5 yielded 96.5 Pg C yr-1 and associated uncertainty of 30.2 (mean average error) and 73.4 (standard deviation) Pg C yr-1. SRDBv5 included new data from underrepresented regions (e.g., Asia, Africa, South America) which resulted in overall higher model uncertainty. Empirically estimated global heterotrophic respiration (Rh) from v3 and v5 were 49.9-50.2 (mean 50.1) and 53.3-53.5 (mean 53.4) Pg C yr-1, respectively. The SRDBv5 is still biased towards northern latitudes and temperate zones, so we tested that an optimized global distribution of Rs measurements resulted in a global sum of 96.4 ± 21.4 Pg C yr-1 and lower model uncertainty. These results support current global estimates of Rs but highlight spatial inconsistencies that influence model parameterization and interpretation that should be considered to improve predictions across the world. | en_US |
| Advisor | Vargas, Rodrigo | |
| Degree | M.S. | |
| Department | University of Delaware, Department of Geography and Spatial Sciences | |
| Unique Identifier | 1246630645 | |
| URL | https://udspace.udel.edu/handle/19716/28929 | |
| Language | en | |
| Publisher | University of Delaware | en_US |
| URI | https://login.udel.idm.oclc.org/login?url=https://www.proquest.com/dissertations-theses/spatial-inconsistencies-influence-global/docview/2495398131/se-2?accountid=10457 | |
| Keywords | Soil respiration | en_US |
| Keywords | Carbon cycle | en_US |
| Keywords | Soil respiration database | en_US |
| Title | Spatial inconsistencies influence global estimates of soil respiration: how can we improve global predictions? | en_US |
| Type | Thesis | en_US |
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