| 1. |
- Harden, Jennifer W., et al.
(author)
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Networking our science to characterize the state, vulnerabilities, and management opportunities of soil organic matter
- 2018
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In: Global Change Biology. - : Wiley. - 1354-1013 .- 1365-2486. ; 24:2, s. e705-e718
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Journal article (peer-reviewed)abstract
- Soil organic matter (SOM) supports the Earth's ability to sustain terrestrial ecosystems, provide food and fiber, and retains the largest pool of actively cycling carbon. Over 75% of the soil organic carbon (SOC) in the top meter of soil is directly affected by human land use. Large land areas have lost SOC as a result of land use practices, yet there are compensatory opportunities to enhance productivity and SOC storage in degraded lands through improved management practices. Large areas with and without intentional management are also being subjected to rapid changes in climate, making many SOC stocks vulnerable to losses by decomposition or disturbance. In order to quantify potential SOC losses or sequestration at field, regional, and global scales, measurements for detecting changes in SOC are needed. Such measurements and soil-management best practices should be based on well established and emerging scientific understanding of processes of C stabilization and destabilization over various timescales, soil types, and spatial scales. As newly engaged members of the International Soil Carbon Network, we have identified gaps in data, modeling, and communication that underscore the need for an open, shared network to frame and guide the study of SOM and SOC and their management for sustained production and climate regulation.
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| 2. |
- Haverd, Vanessa, et al.
(author)
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Carbon cycle responses of semi-arid ecosystems to positive asymmetry in rainfall
- 2017
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In: Global Change Biology. - : Wiley. - 1365-2486 .- 1354-1013. ; 23:2, s. 793-800
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Journal article (peer-reviewed)abstract
- Recent evidence shows that warm semi-arid ecosystems are playing a disproportionate role in the interannual variability and greening trend of the global carbon cycle given their mean lower productivity when compared with other biomes (Ahlström et al. 2015 Science, 348, 895). Using multiple observations (land-atmosphere fluxes, biomass, streamflow and remotely sensed vegetation cover) and two state-of-the-art biospheric models, we show that climate variability and extremes lead to positive or negative responses in the biosphere, depending on vegetation type. We find Australia to be a global hot spot for variability, with semi-arid ecosystems in that country exhibiting increased carbon uptake due to both asymmetry in the interannual distribution of rainfall (extrinsic forcing), and asymmetry in the response of gross primary production (GPP) to rainfall change (intrinsic response). The latter is attributable to the pulse-response behaviour of the drought-adapted biota of these systems, a response that is estimated to be as much as half of that from the CO2 fertilization effect during 1990–2013. Mesic ecosystems, lacking drought-adapted species, did not show an intrinsic asymmetric response. Our findings suggest that a future more variable climate will induce large but contrasting ecosystem responses, differing among biomes globally, independent of changes in mean precipitation alone. The most significant changes are occurring in the extensive arid and semi-arid regions, and we suggest that the reported increased carbon uptake in response to asymmetric responses might be contributing to the observed greening trends there.
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| 3. |
- Tagesson, Torbern, et al.
(author)
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A physiology-based Earth observation model indicates stagnation in the global gross primary production during recent decades
- 2021
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In: Global Change Biology. - : Wiley. - 1354-1013 .- 1365-2486. ; 27:4, s. 836-854
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Journal article (peer-reviewed)abstract
- Earth observation-based estimates of global gross primary production (GPP) are essential for understanding the response of the terrestrial biosphere to climatic change and other anthropogenic forcing. In this study, we attempt an ecosystem-level physiological approach of estimating GPP using an asymptotic light response function (LRF) between GPP and incoming photosynthetically active radiation (PAR) that better represents the response observed at high spatiotemporal resolutions than the conventional light use efficiency approach. Modelled GPP is thereafter constrained with meteorological and hydrological variables. The variability in field-observed GPP, net primary productivity and solar-induced fluorescence was better or equally well captured by our LRF-based GPP when compared with six state-of-the-art Earth observation-based GPP products. Over the period 1982–2015, the LRF-based average annual global terrestrial GPP budget was 121.8 ± 3.5 Pg C, with a detrended inter-annual variability of 0.74 ± 0.13 Pg C. The strongest inter-annual variability was observed in semi-arid regions, but croplands in China and India also showed strong inter-annual variations. The trend in global terrestrial GPP during 1982–2015 was 0.27 ± 0.02 Pg C year−1, and was generally larger in the northern than the southern hemisphere. Most positive GPP trends were seen in areas with croplands whereas negative trends were observed for large non-cropped parts of the tropics. Trends were strong during the eighties and nineties but levelled off around year 2000. Other GPP products either showed no trends or continuous increase throughout the study period. This study benchmarks a first global Earth observation-based model using an asymptotic light response function, improving simulations of GPP, and reveals a stagnation in the global GPP after the year 2000.
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| 4. |
- Piao, Shilong, et al.
(author)
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Evaluation of terrestrial carbon cycle models for their response to climate variability and to CO2 trends
- 2013
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In: Global Change Biology. - : Wiley. - 1354-1013. ; 19:7, s. 2117-2132
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Journal article (peer-reviewed)abstract
- The purpose of this study was to evaluate 10 process-based terrestrial biosphere models that were used for the IPCC fifth Assessment Report. The simulated gross primary productivity (GPP) is compared with flux-tower-based estimates by Jung etal. [Journal of Geophysical Research 116 (2011) G00J07] (JU11). The net primary productivity (NPP) apparent sensitivity to climate variability and atmospheric CO2 trends is diagnosed from each model output, using statistical functions. The temperature sensitivity is compared against ecosystem field warming experiments results. The CO2 sensitivity of NPP is compared to the results from four Free-Air CO2 Enrichment (FACE) experiments. The simulated global net biome productivity (NBP) is compared with the residual land sink (RLS) of the global carbon budget from Friedlingstein etal. [Nature Geoscience 3 (2010) 811] (FR10). We found that models produce a higher GPP (133 +/- 15Pg Cyr-1) than JU11 (118 +/- 6Pg Cyr-1). In response to rising atmospheric CO2 concentration, modeled NPP increases on average by 16% (5-20%) per 100ppm, a slightly larger apparent sensitivity of NPP to CO2 than that measured at the FACE experiment locations (13% per 100ppm). Global NBP differs markedly among individual models, although the mean value of 2.0 +/- 0.8Pg Cyr-1 is remarkably close to the mean value of RLS (2.1 +/- 1.2 Pg Cyr-1). The interannual variability in modeled NBP is significantly correlated with that of RLS for the period 1980-2009. Both model-to-model and interannual variation in model GPP is larger than that in model NBP due to the strong coupling causing a positive correlation between ecosystem respiration and GPP in the model. The average linear regression slope of global NBP vs. temperature across the 10 models is -3.0 +/- 1.5Pg Cyr-1 degrees C-1, within the uncertainty of what derived from RLS (-3.9 +/- 1.1Pg Cyr-1 degrees C-1). However, 9 of 10 models overestimate the regression slope of NBP vs. precipitation, compared with the slope of the observed RLS vs. precipitation. With most models lacking processes that control GPP and NBP in addition to CO2 and climate, the agreement between modeled and observation-based GPP and NBP can be fortuitous. Carbon-nitrogen interactions (only separable in one model) significantly influence the simulated response of carbon cycle to temperature and atmospheric CO2 concentration, suggesting that nutrients limitations should be included in the next generation of terrestrial biosphere models.
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