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      Contribution of land use to the interannual variability of the land carbon cycle

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          Abstract

          Understanding the driving mechanisms of the interannual variability (IAV) of the net land carbon balance (S net) is important to predict future climate–carbon cycle feedbacks. Past studies showed that the IAV of S net was correlated with tropical climate variation and controlled by semiarid vegetation. But today’s land ecosystems are also under extensive human land use and management. Here, we report a previously hidden role of land use in driving the IAV of S net by using an improved biosphere model. We found that managed land accounted for 30–45% of the IAV of S net over 1959–2015, while the contribution of intact land is reduced by more than half compared with previous assessments of the global carbon budget. Given the importance of land use in modulating future land climate–carbon cycle feedbacks, climate mitigation efforts should strive to reduce land-use emissions and enhance the climate resilience of carbon sinks over managed land.

          Abstract

          Terrestrial carbon uptake as high inter-annual variability which can be used to help understand future responses to climate change. Here the authors’ modeling reveals a large portion of this variability is driven by human land use changes and management, and not captured by other models.

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          Sensitivity of tropical carbon to climate change constrained by carbon dioxide variability.

          The release of carbon from tropical forests may exacerbate future climate change, but the magnitude of the effect in climate models remains uncertain. Coupled climate-carbon-cycle models generally agree that carbon storage on land will increase as a result of the simultaneous enhancement of plant photosynthesis and water use efficiency under higher atmospheric CO(2) concentrations, but will decrease owing to higher soil and plant respiration rates associated with warming temperatures. At present, the balance between these effects varies markedly among coupled climate-carbon-cycle models, leading to a range of 330 gigatonnes in the projected change in the amount of carbon stored on tropical land by 2100. Explanations for this large uncertainty include differences in the predicted change in rainfall in Amazonia and variations in the responses of alternative vegetation models to warming. Here we identify an emergent linear relationship, across an ensemble of models, between the sensitivity of tropical land carbon storage to warming and the sensitivity of the annual growth rate of atmospheric CO(2) to tropical temperature anomalies. Combined with contemporary observations of atmospheric CO(2) concentration and tropical temperature, this relationship provides a tight constraint on the sensitivity of tropical land carbon to climate change. We estimate that over tropical land from latitude 30° north to 30° south, warming alone will release 53 ± 17 gigatonnes of carbon per kelvin. Compared with the unconstrained ensemble of climate-carbon-cycle projections, this indicates a much lower risk of Amazon forest dieback under CO(2)-induced climate change if CO(2) fertilization effects are as large as suggested by current models. Our study, however, also implies greater certainty that carbon will be lost from tropical land if warming arises from reductions in aerosols or increases in other greenhouse gases.
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            Carbon emissions from land use and land-cover change

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              Anthropogenic land use estimates for the Holocene – HYDE 3.2

              This paper presents an update and extension of HYDE, the History Database of the Global Environment (HYDE version 3.2). HYDE is an internally consistent combination of historical population estimates and allocation algorithms with time-dependent weighting maps for land use. Categories include cropland, with new distinctions for irrigated and rain-fed crops (other than rice) and irrigated and rain-fed rice. Grazing lands are also provided, divided into more intensively used pasture and less intensively used rangeland, and further specified with respect to conversion of natural vegetation to facilitate global change modellers. Population is represented by maps of total, urban, rural population, population density and built-up area. The period covered is 10 000 before Common Era (BCE) to 2015 Common Era (CE). All data can be downloaded from https://doi.org/10.17026/dans-25g-gez3 . We estimate that global population increased from 4.4 million people (we also estimate a lower range <  0.01 and an upper range of 8.9 million) in 10 000 BCE to 7.257 billion in 2015 CE, resulting in a global population density increase from 0.03 persons (or capita, in short cap) km −2 (range 0–0.07) to almost 56 cap km −2 respectively. The urban built-up area evolved from almost zero to roughly 58 Mha in 2015 CE, still only less than 0.5 % of the total land surface of the globe. Cropland occupied approximately less than 1 % of the global land area (13 037 Mha, excluding Antarctica) for a long time period until 1 CE, quite similar to the grazing land area. In the following centuries the share of global cropland slowly grew to 2.2 % in 1700 CE (ca. 293 Mha, uncertainty range 220–367 Mha), 4.4 % in 1850 CE (578 Mha, range 522–637 Mha) and 12.2 % in 2015 CE (ca. 1591 Mha, range 1572–1604 Mha). Cropland can be further divided into rain-fed and irrigated land, and these categories can be further separated into rice and non-rice. Rain-fed croplands were much more common, with 2.2 % in 1700 CE (289 Mha, range 217–361 Mha), 4.2 % (549 Mha, range 496–606 Mha) in 1850 CE and 10.1 % (1316 Mha, range 1298–1325 Mha) in 2015 CE, while irrigated croplands used less than 0.05 % (4.3 Mha, range 3.1–5.5 Mha), 0.2 % (28 Mha, range 25–31 Mha) and 2.1 % (277 Mha, range 273–278 Mha) in 1700, 1850 and 2015 CE, respectively. We estimate the irrigated rice area (paddy) to be 0.1 % (13 Mha, range 9–16 Mha) in 1700 CE, 0.2 % (28 Mha, range 26–31 Mha) in 1850 CE and 0.9 % (118 Mha, range 117–120 Mha) in 2015 CE. The estimates for land used for grazing are much more uncertain. We estimate that the share of grazing land grew from 5.1 % in 1700 CE (667 Mha, range 507–820 Mha) to 9.6 % in 1850 CE (1192 Mha, range 1068–1304 Mha) and 24.9 % in 2015 CE (3241 Mha, range 3211–3270 Mha). To aid the modelling community we have divided land used for grazing into more intensively used pasture, less intensively used converted rangeland and less or unmanaged natural unconverted rangeland. Pasture occupied 1.1 % in 1700 CE (145 Mha, range 79–175 Mha), 1.9 % in 1850 CE (253 Mha, range 218–287 Mha) and 6.0 % (787 Mha, range 779–795 Mha) in 2015 CE, while rangelands usually occupied more space due to their occurrence in more arid regions and thus lower yields to sustain livestock. We estimate converted rangeland at 0.6 % in 1700 CE (82 Mha range 66–93 Mha), 1 % in 1850 CE (129 Mha range 118–136 Mha) and 2.4 % in 2015 CE (310 Mha range 306–312 Mha), while the unconverted natural rangelands occupied approximately 3.4 % in 1700 CE (437 Mha, range 334–533 Mha), 6.2 % in 1850 CE (810 Mha, range 733–881 Mha) and 16.5 % in 2015 CE (2145 Mha, range 2126–2164 Mha).
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                Author and article information

                Contributors
                chaoyuejoy@gmail.com
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                23 June 2020
                23 June 2020
                2020
                : 11
                : 3170
                Affiliations
                [1 ]ISNI 0000 0004 1760 4150, GRID grid.144022.1, State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, , Northwest A&F University, ; Yangling, Shaanxi 712100 People’s Republic of China
                [2 ]ISNI 0000 0004 4910 6535, GRID grid.460789.4, Laboratoire des Sciences du Climat et de l’Environnement, LSCE/IPSL, CEA-CNRS- UVSQ, , Université Paris-Saclay, ; 91191 Gif-sur-Yvette, France
                [3 ]ISNI 0000 0001 2185 0926, GRID grid.251079.8, Woods Hole Research Center, ; Falmouth, MA 02540 USA
                Author information
                http://orcid.org/0000-0003-0026-237X
                http://orcid.org/0000-0001-8560-4943
                http://orcid.org/0000-0002-3298-7028
                Article
                16953
                10.1038/s41467-020-16953-8
                7311403
                32576826
                727538ec-3a16-48f3-9b97-d1479f29c0ef
                © The Author(s) 2020

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 29 November 2019
                : 2 June 2020
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100000780, European Commission (EC);
                Award ID: 603542
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100001809, National Natural Science Foundation of China (National Science Foundation of China);
                Award ID: 41971132
                Award Recipient :
                Funded by: European Research Council through Synergy grant ERC-2013-SyG-610028; Strategic Priority Research Program of Chinese Academy of Sciences (Grant No. XDB40020300)
                Categories
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                © The Author(s) 2020

                Uncategorized
                biogeochemistry,carbon cycle,climate sciences
                Uncategorized
                biogeochemistry, carbon cycle, climate sciences

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