Soil degradation is a critical and growing global problem. As the world population increases, pressure on soil also increases and the natural capital of soil faces continuing decline. International policy makers have recognized this and a range of initiatives to address it have emerged over recent years. However, a gap remains between what the science tells us about soil and its role in underpinning ecological and human sustainable development, and existing policy instruments for sustainable development. Functioning soil is necessary for ecosystem service delivery, climate change abatement, food and fiber production and fresh water storage. Yet key policy instruments and initiatives for sustainable development have under‐recognized the role of soil in addressing major challenges including food and water security, biodiversity loss, climate change and energy sustainability. Soil science has not been sufficiently translated to policy for sustainable development. Two underlying reasons for this are explored and the new concept of soil security is proposed to bridge the science–policy divide. Soil security is explored as a conceptual framework that could be used as the basis for a soil policy framework with soil carbon as an exemplar indicator.
Abstract. Agroforestry is an increasingly popular farming system enabling agricultural diversification and providing several ecosystem services. In agroforestry systems, soil organic carbon (SOC) stocks are generally increased, but it is difficult to disentangle the different factors responsible for this storage. Organic carbon (OC) inputs to the soil may be larger, but SOC decomposition rates may be modified owing to microclimate, physical protection, or priming effect from roots, especially at depth. We used an 18-year-old silvoarable system associating hybrid walnut trees (Juglans regia × nigra) and durum wheat (Triticum turgidum L. subsp. durum) and an adjacent agricultural control plot to quantify all OC inputs to the soil -leaf litter, tree fine root senescence, crop residues, and tree row herbaceous vegetation -and measured SOC stocks down to 2 m of depth at varying distances from the trees. We then proposed a model that simulates SOC dynamics in agroforestry accounting for both the whole soil profile and the lateral spatial heterogeneity. The model was calibrated to the control plot only.Measured OC inputs to soil were increased by about 40 % (+ 1.11 t C ha −1 yr −1 ) down to 2 m of depth in the agroforestry plot compared to the control, resulting in an additional SOC stock of 6.3 t C ha −1 down to 1 m of depth. However, most of the SOC storage occurred in the first 30 cm of soil and in the tree rows. The model was strongly validated, properly describing the measured SOC stocks and distribution with depth in agroforestry tree rows and alleys. It showed that the increased inputs of fresh biomass to soil explained the observed additional SOC storage in the agroforestry plot. Moreover, only a priming effect variant of the model was able to capture the depth distribution of SOC stocks, suggesting the priming effect as a possible mechanism driving deep SOC dynamics. This result questions the potential of soils to store large amounts of carbon, especially at depth. Deep-rooted trees modify OC inputs to soil, a process that deserves further study given its potential effects on SOC dynamics.
Soil is the major terrestrial reservoir of carbon and a substantial part of this carbon is stored in deep layers, typically deeper than 50 cm below the surface. Several studies underlined the quantitative importance of this deep soil organic carbon (SOC) pool and models are needed to better understand this stock and its evolution under climate and land-uses changes. In this study, we tested and compared three simple theoretical models of vertical transport for SOC against SOC profiles measurements from a long-term bare fallow experiment carried out by the Central-Chernozem State Natural Biosphere Reserve in the Kursk Region of Russia. The transport schemes tested are diffusion, advection and both diffusion and advection. They are coupled to three different formulations of soil carbon decomposition kinetics. The first formulation is a first order kinetics widely used in global SOC decomposition models; the second one, so-called "priming" model, links SOC decomposition rate to the amount of fresh organic matter, representing the substrate interactions. The last one is also a first order kinetics, but SOC is split into two pools. Field data are from a set of three bare fallow plots where soil received no input during the past 20, 26 and 58 yr, respectively. Parameters of the models were optimised using a Bayesian method. The best results are obtained when SOC decomposition is assumed to be controlled by fresh organic matter (i.e., the priming model). In comparison to the first-order kinetic model, the priming model reduces the overestimation in the deep layers. We also observed that the transport scheme that improved the fit with the data depended on the soil carbon mineralisation formulation chosen. When soil carbon decomposition was modelled to depend on the fresh organic matter amount, the transport mechanism which improved best the fit to the SOC profile data was the model representing both advection and diffusion. Interestingly, the older the bare fallow is, the lesser the need for diffusion is, suggesting that stabilised carbon may not be transported within the profile by the same mechanisms than more labile carbon
Abstract. This paper deals with the simulation of microbial degradation of organic matter in soil within the pore space at a microscopic scale. Pore space was analysed with microcomputed tomography and described using a sphere network coming from a geometrical modelling algorithm. The biological model was improved regarding previous work in order to include the transformation of dissolved organic compounds and diffusion processes. We tested our model using experimental results of a simple substrate decomposition experiment (fructose) within a simple medium (sand) in the presence of different bacterial strains. Separate incubations were carried out in microcosms using five different bacterial communities at two different water potentials of −10 and −100 cm of water. We calibrated the biological parameters by means of experimental data obtained at high water content, and we tested the model without changing any parameters at low water content. Same as for the experimental data, our simulation results showed that the decrease in water content caused a decrease of mineralization rate. The model was able to simulate the decrease of connectivity between substrate and microorganism due the decrease of water content.
Urban farming, especially on rooftops, is a popular and growing topic in both the media and the scientific literature, providing a genuine opportunity to meet some of the challenges linked to urban development worldwide. However, relatively little attention has been paid to date to the growing medium of green roofs, i.e., Technosols. A better understanding of the influence of Technosols and the link with ecosystem services is required in order to maximize the environmental benefits of urban rooftop farming. Between March 2013 and March 2015, a pilot project called T4P (Parisian Productive rooftoP, Pilot Experiment) was conducted on the rooftop of AgroParisTech University. Urban organic waste was used, and results were compared with those obtained using a commercial potting soil, based on yield and trace metal concentrations, substrate characterization, and the amount of leaching. An assessment of the ecosystem services expected from the Technosols was undertaken in terms of the output of food (food production and quality), regulation of water runoff (quantity and quality), and the recycling of organic waste. Indicators of these ecosystem services (e.g., yield, annual loss of mass of mineral nitrogen) were identified, measured, and compared with reference cases (asphalt roof, green roof, and cropland). Measured yields were almost equivalent to those obtained from horticultural sources in the same area, and the Technosols also retained 74-84% of the incoming rainfall water. This is the first quantitative analysis of ecosystem services delivered by urban garden rooftops developed on organic wastes, and demonstrates their multifunctional character, as well as allowing the identification of trade-offs. An ecosystem services approach is proposed for the design of soilbased green infrastructure of this kind and more generally for the design of sustainable urban agriculture.
Abstract. Changes in global soil carbon stocks have considerable potential to influence the course of future climate change. However, a portion of soil organic carbon (SOC) has a very long residence time (> 100 years) and may not contribute significantly to terrestrial greenhouse gas emissions during the next century. The size of this persistent SOC reservoir is presumed to be large. Consequently, it is a key parameter required for the initialization of SOC dynamics in ecosystem and Earth system models, but there is considerable uncertainty in the methods used to quantify it. Thermal analysis methods provide cost-effective information on SOC thermal stability that has been shown to be qualitatively related to SOC biogeochemical stability. The objective of this work was to build the first quantitative model of the size of the centennially persistent SOC pool based on thermal analysis. We used a unique set of 118 archived soil samples from four agronomic experiments in northwestern Europe with long-term bare fallow and non-bare fallow treatments (e.g., manure amendment, cropland and grassland) as a sample set for which estimating the size of the centennially persistent SOC pool is relatively straightforward. At each experimental site, we estimated the average concentration of centennially persistent SOC and its uncertainty by applying a Bayesian curve-fitting method to the observed declining SOC concentration over the duration of the long-term bare fallow treatment. Overall, the estimated concentrations of centennially persistent SOC ranged from 5 to 11 g C kg −1 of soil (lowest and highest boundaries of four 95 % confidence intervals). Then, by dividing the site-specific concentrations of persistent SOC by the total SOC concentration, we could estimate the proportion of centennially persistent SOC in the 118 archived soil samples and the associated uncertainty. The proportion of centennially persistent SOC ranged from 0.14 (standard deviation of 0.01) to 1 (standard deviation of 0.15). Samples were subjected to thermal analysis by Rock-Eval 6 that generated a series of 30 parameters reflecting their SOC thermal stability and bulk chemistry. We trained a nonparametric machine-learning algorithm (random forests multivariate regression model) to predict the proportion of centennially persistent SOC in new soils using Rock-Eval 6 thermal parameters as predictors. We evaluated the model predictive performance with two different strategies. We first used a calibration set (n = 88) and a validation set (n = 30) with soils from all sites. Second, to test the sensitivity of the model to pedoclimate, we built a calibration set with soil samples from three out of the four sites (n = 84). The multivariate regression model accurately predicted the proportion of centennially persistent SOC in the validation set composed of soils from all sites (R 2 = 0.92, RMSEP = 0.07, n = 30). The uncertainty of the model predictions was quantified by aPublished by Copernicus Publications on behalf of the European Geosciences Union. L. Cécil...
Abstract. An increase in soil organic carbon stock can contribute to mitigate climate change. International negotiation mechanisms and initiatives call for countries to consider land use change and soil management to achieve atmospheric CO2 removal through storage in terrestrial systems (http://4p1000.org/). As a result, policy makers raised a specific operational question to the soil science community: how much and at which annual rate additional carbon can be stored in soils in different 20 locations? It has been suggested that the ability of a soil to store additional organic carbon can be estimated from its carbon saturation deficit (Csat-def), which is defined as the difference between the maximum amount of carbon that can be associated to its fine (<20 µm) fraction and the current amount of carbon associated to its fine fraction. In this opinion paper, we explain why, for conceptual reasons, the soil Csat-def is not appropriate, at least in its present form, for assessing quantitatively the whole-soil (total) organic carbon storage potential for operational purposes. We then propose alternative approaches based on 25 new opportunities offered by the development of national and international soil monitoring programs (possibly coupled with modelling) that can provide quantitatively relevant estimates of soil total carbon storage potential. This pragmatic approach will require a sustained effort to maintain and develop soil monitoring programs worldwide and research allowing proper use of such a large amount of data.
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