Global satellite-driven estimates of heterotrophic respiration
<p>While heterotrophic respiration (<span class="inline-formula"><i>R</i><sub>h</sub></span>) makes up about a quarter of gross global terrestrial carbon fluxes, it remains among the least-observed carbon fluxes, particularly outside the midlatitud...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2019-06-01
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| Series: | Biogeosciences |
| Online Access: | https://www.biogeosciences.net/16/2269/2019/bg-16-2269-2019.pdf |
| Summary: | <p>While heterotrophic respiration (<span class="inline-formula"><i>R</i><sub>h</sub></span>) makes up about
a quarter of gross global terrestrial carbon fluxes, it remains among the
least-observed carbon fluxes, particularly outside the midlatitudes. In situ measurements collected in the Soil Respiration Database (SRDB) number
only a few hundred worldwide. Similarly, only a single data-driven
wall-to-wall estimate of annual average heterotrophic respiration exists,
based on bottom-up upscaling of SRDB measurements using an assumed
functional form to account for climate variability. In this study, we
exploit recent advances in remote sensing of terrestrial carbon fluxes to
estimate global variations in heterotrophic respiration in a top-down
fashion at monthly temporal resolution and <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M2" display="inline" overflow="scroll" dspmath="mathml"><mrow><mn mathvariant="normal">4</mn><msup><mi/><mo>∘</mo></msup><mo>×</mo><mn mathvariant="normal">5</mn><msup><mi/><mo>∘</mo></msup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="34pt" height="11pt" class="svg-formula" dspmath="mathimg" md5hash="4e7aecd62001c6a16011ee459391276a"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="bg-16-2269-2019-ie00001.svg" width="34pt" height="11pt" src="bg-16-2269-2019-ie00001.png"/></svg:svg></span></span> spatial resolution. We
combine net ecosystem productivity estimates from atmospheric inversions of
the NASA Carbon Monitoring System-Flux (CMS-Flux) with an optimally scaled
gross primary productivity dataset based on satellite-observed solar-induced
fluorescence variations to estimate total ecosystem respiration as a
residual of the terrestrial carbon balance. The ecosystem respiration is
then separated into autotrophic and heterotrophic components based on a
spatially varying carbon use efficiency retrieved in a model–data fusion
framework (the CARbon DAta MOdel fraMework, CARDAMOM). The resulting dataset
is independent of any assumptions about how heterotrophic respiration
responds to climate or substrate variations. It estimates an annual average
global average heterotrophic respiration flux of <span class="inline-formula">43.6±19.3</span> Pg C yr<span class="inline-formula"><sup>−1</sup></span>.
Sensitivity and uncertainty analyses showed that the top-down <span class="inline-formula"><i>R</i><sub>h</sub></span> are
more sensitive to the choice of input gross primary productivity (GPP) and net ecosystem productivity (NEP) datasets than to the
assumption of a static carbon use efficiency (CUE) value, with the possible exception of the wet
tropics. These top-down estimates are compared to bottom-up estimates of
annual heterotrophic respiration, using new uncertainty estimates that
partially account for sampling and model errors. Top-down heterotrophic
respiration estimates are higher than those from bottom-up upscaling
everywhere except at high latitudes and are 30 % greater overall (43.6 Pg C yr<span class="inline-formula"><sup>−1</sup></span> vs. 33.4 Pg C yr<span class="inline-formula"><sup>−1</sup></span>). The uncertainty ranges of both methods are
comparable, except poleward of 45<span class="inline-formula"><sup>∘</sup></span> N, where bottom-up
uncertainties are greater. The ratio of top-down heterotrophic to total
ecosystem respiration varies seasonally by as much as 0.6 depending on
season and climate, illustrating the importance of studying the drivers of
autotrophic and heterotrophic respiration separately, and thus the
importance of data-driven estimates of <span class="inline-formula"><i>R</i><sub>h</sub></span> such as those estimated here.</p> |
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| ISSN: | 1726-4170 1726-4189 |