Dynamics of soil organic carbon stock in a typical catchment of the Loess Plateau: comparison of model simulations with measurements

Wu, Xing; Akujärvi, Anu; Lü, Nan; Liski, Jari; Li, Guohua; Wang, Yafeng; Holmberg, Maria; Li, Fēi; Zeng, Yuan; Fu, Bojie

doi:10.1007/s10980-014-0110-3

Cited by 17 publications

(11 citation statements)

References 46 publications

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“…At the global scale, the distribution of organic soil C to different biomes calculated using Yasso07 was "in good agreement" with a Harmonized World Soil Data Base, although for tree-dominated biomes and biomes affected by anaerobic decomposition and permafrost, the model showed a consistent underestimation (Goll et al 2015). Simulated soil C stock in next-to-cropland forests and croplands was similar to Finnish measurements (Akujärvi et al 2014), and C stock and stock changes were estimated "reasonably well" in a region of Loess Plateau in China (Wu et al 2015). A number of studies have made comparisons on the site scale; simulated soil C stocks were about 20% smaller than measured at two sites in Switzerland (11.2 vs. 13.9 kg·m −2 at one site, 11.1 vs. 14.2 kg·m −2 at another) (Rühr and Eugster 2009).…”

Section: Spatial Scale Of Yasso07 Applicationsupporting

confidence: 53%

Underestimation of boreal forest soil carbon stocks related to soil classification and drainage

et al. 2016

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Soil organic carbon (C), accumulated over millennia, comprise more than half of the C stored in boreal and temperate forest landscapes. We used the Norwegian national forest inventory and soil survey network (n = 719, no deep organic soils) to explore the validity of a deterministic model representation of this pool (Yasso07). We statistically compared simulated and measured soil C stocks and related differences (measured -simulated) to site factors (drainage, topography, climate, vegetation, C-to-N ratio, and soil classification). Median C stocks were 5.0 kg C·m −2 (model) and 14.5 kg C·m −2 (measurements). Soil C differences related to site factors (r 2 of 0.16 to 0.37). For Brunisols, Gleysols, and wet Organic soils, differences related primarily to topographic wetness. For Regosols, Podzols, and Dystric Eluviated Brunisols, they related to climate, profile depth, and, in some cases, drainage class and site index. We argue that soil moisture regimes in our study area overrule tree productivity effects in the determination of soil C stocks and present conditions for soil formation that the model cannot (and does not explicitly) account for. These are processes such as humification and podsolization that involve eluviation and illuviation of dissolved organic C (DOC) with sesquioxides to form spodic B horizons and carbon enrichment due to hampered decomposition in frequently anoxic conditions.Key words: drainage, national forest inventory (NFI), SOC simulation, soil classification, soil-forming factors, soil moisture regime, soil survey, podsolization, Yasso07. Résumé :Le carbone (C) organique du sol accumulé au fil des millénaires correspond à plus de la moitié du C stocké dans les paysages forestiers boréaux et tempérés. Nous avons utilisé l'inventaire forestier national norvégien et le réseau d'inventaire des sols (n = 719, aucun sol organique épais) pour étudier la validité d'une représentation de ce réservoir (Yasso07) à l'aide d'un modèle déterministe. Nous avons statistiquement comparé les stocks de C du sol simulés et mesurés, et relié leurs différences (mesurés -simulés) à des caractéristiques de la station (drainage, topographie, climat, végétation, rapport de C à N et classification du sol). Les stocks médians de C atteignaient 5,0 (simulé) et 14,5 (mesuré) kg C·m -2 . Les différences de C du sol étaient reliées aux caractéristiques des stations (r 2 de 0,16 à 0,37). Pour les brunisols, les gleysols et les sols organiques humides, les différences étaient surtout reliées à l'humidité topographique. Pour les régosols, les podzols et les brunisols dystriques éluviés, les différences étaient reliées au climat, à la profondeur du profil et, dans certains cas, à la classe de drainage et à l'indice de qualité de station. Nous avançons que le régime d'humidité du sol de notre aire d'étude est un facteur plus important que les effets de la productivité ligneuse pour déterminer les stocks de C, et qu'il engendre des conditions de formation des sols dont le modèle ne peut tenir compte et ne tient pas ...

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Section: Spatial Scale Of Yasso07 Applicationsupporting

confidence: 53%

Underestimation of boreal forest soil carbon stocks related to soil classification and drainage

et al. 2016

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“…Soil carbon pools (especially those at sites that have undergone disturbances in recent centuries) may not have achieved a complete steady state but may still be in a transient or partial steady state. In such states, the slow-cycling pools can still be accumulating carbon, while the relatively rapid-cycling pools have already recovered a dynamic equilibrium (Wutzler and Reichstein, 2007). In this study, we equally adopted the partial steady-state assumption to mimic such a circumstance.…”

Section: Datamentioning

confidence: 99%

Modeling soil organic carbon dynamics in temperate forests with Yasso07

Mao¹,

Derrien²,

Didion³

et al. 2019

Biogeosciences

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Abstract. In a context of global changes, modeling and predicting the dynamics of soil carbon stocks (CSs) in forest ecosystems are vital but challenging. Yasso07 is considered to be one of the most promising models for such a purpose. We examine the accuracy of its prediction of soil carbon dynamics over the whole French metropolitan territory at a decennial timescale. We used data from 101 sites in the RENECOFOR network, which encompasses most of the French temperate forests. These data include (i) the quantity of above-ground litterfall from 1994 to 2008, measured yearly, and (ii) the soil CSs measured twice at an interval of approximately 15 years (once in the early 1990s and around 2010). We used Yasso07 to simulate the annual changes in carbon stocks (ACCs; in tC ha−1 yr−1) for each site and then compared the estimates with actual recorded data. We carried out meta-analyses to reveal the variability in litter biochemistry in different tree organs for conifers and broadleaves. We also performed sensitivity analyses to explore Yasso07's sensitivity to annual litter inputs and model initialization settings. At the national level, the simulated ACCs (+0.00±0.07 tC ha−1 yr−1, mean ± SE) were of the same order of magnitude as the observed ones (+0.34±0.06 tC ha−1 yr−1). However, the correlation between predicted and measured ACCs remained weak (R2<0.1). There was significant overestimation for broadleaved stands and underestimation for coniferous sites. Sensitivity analyses showed that the final estimated CS was strongly affected by settings in the model initialization, including litter and soil carbon quantity and quality and also by simulation length. Carbon quality set with the partial steady-state assumption gave a better fit than the model with the complete steady-state assumption. With Yasso07 as the support model, we showed that there is currently a bottleneck in soil carbon modeling and prediction due to a lack of knowledge or data on soil carbon quality and fine-root quantity in the litter.

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“…Modelling and evaluation of carbon and water services of ecosystems Wu et al (2015) simulated the dynamics of soil organic carbon (SOC) stocks in the Yangjuangou catchment of the Loess Plateau (China) using remote sensing techniques and the Yasso07 model. Forest and grassland showed a more effective accumulation of SOC than the other land use types in the study area.…”

Section: About This Special Issuementioning

confidence: 99%

Ecosystem services modeling in contrasting landscapes

Forsius

2015

Landscape Ecol

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Landscape ecology can make a large contribution to ecosystem service (ES) studies since most ESs are place-based, and thus best evaluated, maintained, enhanced, and restored using integrative techniques at the landscape scale. Integration of field observation, modeling, and remote sensing are increasingly used to quantify and assess ES at different scales. In this special issue, several comprehensive methodologies and tools are described in the thirteen papers included. The papers are grouped into four categories: modelling and evaluation of carbon and water services of ecosystems, comprehensive analysis and assessment of multiple ESs, integrated ES methodologies for conservation, and development of integrated modeling environments for ESs. We believe that these papers provide both useful methods and tools to simulate and evaluate ESs at different spatial and temporal scales, as well as interesting results from case studies. We also hope that they can provide information for policy makers and managers regarding wiser landscape management and conservation.Keywords Landscape ecology Á Ecosystem service assessment Á Conservation Á Trade-off Á Adaptation Á Climes Á LTER The significance and advancement in ecosystem services modeling Ecosystems generate a range of goods and services important for human well-being, collectively called ecosystem services (ESs). It has proven difficult to quantitatively estimate these benefits that nature provides to people (Mace et al. 2012). Spatially explicit values of services across landscapes-of central importance also to inform land use and management decisions-are often lacking. Furthermore, climate and land use changes provide the major challenges for the sustainable management of the key ESs and hence sector-specific adaptation measures are needed Fu et al. 2013). These adaptation measures have to be based on the understanding of (i) the likelihood of change, (ii) vulnerability of the specific sectors to the predicted change, (iii) information about trade-off relationships, and (iv)

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Dynamics of soil organic carbon stock in a typical catchment of the Loess Plateau: comparison of model simulations with measurements

Cited by 17 publications

References 46 publications

Underestimation of boreal forest soil carbon stocks related to soil classification and drainage

Underestimation of boreal forest soil carbon stocks related to soil classification and drainage

Modeling soil organic carbon dynamics in temperate forests with Yasso07

Ecosystem services modeling in contrasting landscapes

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