Evaluation of Top‐Down and Bottom‐Up Global Terrestrial Respiration Estimates and Their Mismatch With Model Simulations
Overview & Synopsis
Terrestrial respiration is one of the poorly understood processes in the global carbon cycle. However, expanding observations and machine learning approaches have led to a proliferation of estimates. We compiled total ecosystem and heterotrophic respiration estimates derived from top‐down atmospheric inversions and bottom‐up upscaling of ecosystem observations and compared them with dynamic vegetation model (DGVM) simulations over the 1980–2020 period. Our analysis revealed a convergence in mean annual global total ecosystem respiration estimates between top‐down 97.1 (± SD 6.8) PgC yr −1 and bottom‐up 98.5 (±13.4) PgC yr −1, which were both significantly lower than the ensemble mean from DGVM estimates 133.7 (±4.7) PgC yr −1. We also found similar temporal trends between top‐down total ecosystem respiration 0.075 (±0.05) PgC yr −2 and bottom‐up total soil respiration estimates of 0.05 (±0.05) PgC yr −2 ; however, the ensemble mean of total ecosystem respiration trends was 5–7 times larger (0.34 PgC yr −2 ). Global heterotrophic respiration showed much less agreement, ranging from top‐down estimates of 42.7 (±4.0) PgC yr −1 to bottom‐up estimates of 51.5 (±4.0) PgC yr −1 and a significantly larger ensemble model mean estimate of 60.8 PgC yr −1 (±1.9). The temporal trends in observation‐based bottom‐up estimates of heterotrophic respiration (0.03 ± 0.007 PgC yr −2 ) were only one fifth of the model ensemble mean trend (0.15 ± 0.04 PgC yr −2 ). Thus, total global ecosystem respiration is dominated by belowground respiration (87%), and belowground respiration is dominated by heterotrophic respiration (60%). Therefore, improved regional and heterotrophic respiration estimates are necessary to reduce uncertainties regarding future global respiration.
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Document Information
| Document Title | Evaluation of Top‐Down and Bottom‐Up Global Terrestrial Respiration Estimates and Their Mismatch With Model Simulations |
|---|---|
| Author / Organization | Ashley Ballantyne, Ben Bond‐lamberty, Arthur Endsley, Etienne Fluet‐chouinard, Zhihua Liu, Kaizad Patel, Elizabeth Smith, Rodrigo Vargas, Bo Zhao |
| Subject & Discipline | Multidisciplinary Academic Open Research |
| Categories | Science & Mathematics |
| Publication Year | 2026 |
| License / Rights | Open Access / Creative Commons |
| Resource Verification | Listed PDF (Verification Pending) |
| Original Host Website |
HAL Open Science
(hal.science)
|
| File Format | application/pdf (Portable Document Format) |
| Language | EN |
| Catalog ID | DOC-123849 |
| Original Source Link | Visit Source Page on hal.science » |