Lucie Merlier

Frederic Kuznik

Gilles Rusaouen

Julien Hans

Frédéric Kuznik

Numerical study of the wind

come

Introduction

A wide diversity of urban fabrics exists around the world, especially in traditional neighborhoods. They are generally linked with typical spatial configurations of buildings. In particular, open, compact and attached forms were developed depending on the local geography, climate and culture. The different levels of porosity that characterize these urban forms involve different very-local micro-climates and internal wind patterns. Indeed, the very-local interactions between mean winds and the shape and layout of urban structures determine to a large extent the flow structures that develop in the urban canopy layer. These aerodynamic phenomena affect in turn, among other things, urban ventilation processes, wind and thermal comfort as well as the climate at the upper scale of the city.

At the spatial scales of the building and street canyon, specific air flow structures develop within courtyards and other urban outdoor spaces linked with constructions. They depend on the orientation of these outdoor spaces in relation to the mean wind incidence, as well as openness, i.e. whether these outdoor spaces are external, partially or totally surrounded by a building or contained inside a building group. This paper presents a numerical study performed to analyze and better understand the aerodynamic processes leading to these flow structures developing around buildings and inside urban blocks depending on their topological features. Only forced convection processes are considered. The effects of the horizontal openness of courtyards and internal open spaces of urban blocks are more specifically examined. Providing information on the wind conditions next to buildings and on ventilation processes, such observations linking urban morphological properties to physical phenomena would support a better understanding of the urban heat island phenomenon on larger urban scales, as well as a more integrated and bio-climatic design of buildings and urban areas on smaller scales.

Computational model

Validation study

The study is based on numerical experiments, which are performed using computational fluid dynamic (CFD) models and the commercial software Ansys Fluent, versions 14.5 and 15 (Fluent inc. 2013). A Reynolds averaged Navier-Stokes (RANS) method is used. The model was preliminarily validated by comparison with high quality reduced-scale experimental data from wind-tunnel tests (CEDVAL, Meteorological Institute of Hamburg 2013) as well as detailed numerical predictions obtained using the lattice Boltzmann Method and a large eddy simulation approach (LBM LES, [START_REF] Obrecht | Towards Aeraulic Simulations at Urban Scale Using the Lattice Boltzmann Method[END_REF]. The accuracy of steady RANS predictions was evaluated in cases of an isolated and a regular array of rectangular obstacles. More specifically, the performance of two turbulence models, namely the realizable k-ε model (Rk-ε) and the Reynolds stress model (RSM), was evaluated. In comparison with k-ε turbulence models, the RSM accounts for anisotropic effects of turbulence on the mean flow.

For more details about the validation study, please refer to [START_REF] Merlier | On the Interactions between Urban Structures and Air Flows: A Numerical Study of the Effects of Urban Morphology on the Building Wind Environment and the Related Building Energy Loads[END_REF].

On the one hand, the Rk-ε model was found to predict flow structures that better match experimental data very close to the isolated obstacle. On the other hand, the RSM better predicts the recirculation in the cavity zone downstream the rectangular block. In addition, this later model better reproduces the vortical structure developing between obstacles in the multi obstacle case, whereas no recirculation is predicted by the Rk-ε. RSM predictions are also generally in better agreement with the LBM LES results than the Rk-ε results are. Nonetheless, note that the flow intermittence probably affects RSM results. No clear stabilization of the mean flow profiles could be achieved where the flow is reported very unsteady by the experimental documentation. Hence, according to the validation study, the steady RANS RSM is able to reproduce the main physical phenomena, although imperfectly being a steady RANS model. As a consequence, actual simulations were performed using the steady RANS RSM.

Settings of the computational model

CFD simulations were performed for different building and urban block generic types, which were specifically designed for that purpose. These morphological types are based on an analysis and abstraction of urban textures that exist in different regions of the world, as well as an identification of the urban morphological factors that affect aerodynamic processes that develop in the urban canopy layer. Examples of the analyzed urban patterns can be found in [START_REF] Firley | Fluent release 14.5 user guide[END_REF] and [START_REF] Salat | Cities and Forms: on sustainable urbanism[END_REF]. To examine the effects of the topological properties of built structures, a cubic, a U, and a patio buildings as well as a cube and a continuous patio arrays are focused on. The height of each construction is H = 10 m. Figure 1 illustrates the different case studies currently considered.

The approach flow was designed using a preliminary simulation of a virtual 10 km long empty tunnel. According to the Davenport's classification, the resulting mean wind profile corresponds to an intermediate roughness class between an open and a roughly open landscape [START_REF] Wieringa | New revision of Davenport roughness classification[END_REF]). The mean velocity speed at 10 m high equals 4.3 m.s -1

. The computational domain respects the recommendations of [START_REF] Tominaga | AIJ Guidelines for Practical Applications of CFD to Pedestrian Wind Environment around Buildings[END_REF] in terms of size and spatial discretization. Cell dimensioning down to 15 cm was used for complex cases. Mesh sensitivity was verified for the isolated building types but not for the arrays because of the mesh size already involved (> 15-25.10 6 cells). The numerical schemes used are second order at least. Convergence was verified by monitoring mean velocity and turbulent properties profiles for several lines along the domain and by checking the overall evolution of the simulation residuals. Note that no stabilization of the profiles could be achieved for the continuous patio array case. Numerical instabilities periodically occurred. This might be explained by the physical complexity of the flow field, which might not show clear and stable recirculation zones. For this case, results were taken after 2.10 3 iterations during which no numerical instability occurred.

Results and analysis

Figure 2 -Figure 15 show the 3D mean velocity streamlines as well as the 3D mean vorticity contours1 around the generic constructions and within courtyards. Simulation results were post processed using the free and open source software ParaView. Typical flow structures around sharp edged obstacles basically develop:

 the horseshoe vortex which begins upwind and extends downstream on the sides of obstacles  the separated bubbles after the leading edges of obstacles  and the arch vortex downstream obstacles.

Recirculation phenomena located in under-pressure zones generally correspond to low velocity zones. On the contrary, corner streams show high velocities. Within courtyards and canyons, vortical recirculation phenomena develop. Their features depend on the openness of the court or canyon involved, its orientation with respect to the wind incidence and its location with respect to the upstream leading edge of the built structure in case of arrays. In cases of isolated buildings, results show quite different flow patterns and recirculation phenomena in courts depending on their horizontal openness and orientation in relation to the approach flow. Regarding semi-open courts, the internal flow recirculation is often merged with the surrounding flows. Typically, the court of the U building 1 modifies the basic standing vortex as part of it is entrapped inside. A recirculation shaped as a semi arch vortex develops in the court of the U building 2 driven by the above and lateral flows. Note that such flow structures are observed because of the small depth of courts. When deeper, a self-contained vertical structure, which resembles to that developing within the patio, may develop [START_REF] Merlier | On the Interactions between Urban Structures and Air Flows: A Numerical Study of the Effects of Urban Morphology on the Building Wind Environment and the Related Building Energy Loads[END_REF].

The flow patterns developing within the open spaces of urban blocks show flow paths or recirculation phenomena, which more or less interfere with the surrounding flows. These different flow patterns are characterized by different levels of vorticity and mean velocities, creating higher wind speeds or rather sheltered zones in flow recirculation regions. Such vortical recirculation regions develop in courts, canyons and downstream obstacles. In comparison with the flow structures developing around corresponding isolated building types, the flow structures developing in arrays are altered because of the presence of the additional constructions. These constructions directly affect the basic recirculation phenomena or create a general group effect which modifies the driving aerodynamic forces. Essentially, corner streams are altered in the first line of cubes and the general recirculation that develops above the upstream part of the continuous patio array affects the vortical structures within the underlying patios. Two structures occur inside: one related to the top separated bubble and the second below. The different flow structures then evolve streamwise showing less defined shapes in the cube array because of the sheltering provided by the upstream obstacles and the convergence of lateral flows, and showing more usual shapes in patios.

Conclusion

This study uses CFD to analyze the flow structures that develop around built structures depending on their topological properties. A steady RANS approach is implemented. Generic case studies and forced convection processes are considered.

The presence of courts or surrounding constructions modifies flow structures with respect to the basic structures usually observed around isolated sharp-edged obstacles. The different basic flow structures are intensified; reduced or may even be prevented depending on the topology of the built structure. Hence, the built design appears to be critical in defining urban air flows and therefore urban microclimates. The different flow patterns created may affect the pedestrian wind comfort, the convective cooling of surfaces, the turbulent heat removal as well as the building energy loads due to air infiltration and heat transmission through the building envelope. Nevertheless, to evaluate these effects in details, a more detailed computational approach is required.

Figure 1 :

 1 Figure 1: Case studies

Figure 2 :Figure 9 :

 29 Figure 2: Flow structures around the cube Figure 3: Flow structures within and around the patio

Blue : 0.5 rad. s -1 ; green : 1.5 rad ;s -1 , red : 5.5 rad.s -1 .


Seddik Yassine Abdelouadoud
email: seddik.abdelouadoud@mines-paristech.frrobin.girard@mines-paristech.fr

Robin Girard

Thierry Guiot
email: thierry.guiot@cstb.fr

PLANNING-ORIENTED YEARLY SIMULATION OF ENERGY STORAGE OPERATION IN DISTRIBUTION SYSTEM FOR PROFIT MAXIMIZATION, VOLTAGE REGULATION AND RESERVE PROVISIONNING

The connection of generation units at the distribution level is expected to increase significantly in the future. This phenomenon will have impacts on the planning and operation of the electric system, both at the local (e.g. appearance of reverse power flows) and global (e.g. modification of the supply-demand equilibrium and of the reserve provisioning capabilities) level. In this context, storage devices are increasingly seen as a possible way to mitigate these impacts, with the caveat -compared to alternative solutions-that their versatility comes with high investment costs. Consequently, it is of the utmost importance to make sure that the full capabilities of these storage devices are put to use. Following this line of thought, this paper presents an algorithm suitable for planning purposes that simulates the yearly operation of distributed energy storage units connected at the medium voltage level to maximize the profit drawn from market operation while respecting voltage and reserve requirement constraints.

INTRODUCTION

In order to ensure the sustainability of electric power system, the share of renewable energies in the production mix will increase in the future. For example, the European Union has set goals for its member states in order to attain a 20% share of renewable energy in its final energy consumption by 2020. This target will be partially met by integrating significant amounts of dispersed renewable energy generators (mainly photovoltaic (PV) and wind power) to the distribution grid. These developments will have considerable impact on the design and operation of the electric system, both at the national and local level, some of which are detailed in the remainder of this introduction. The rest of this paper is organized as follows: first, we will outline the potential applications for storage in this context and how they are modelled, then we will present the methodology applied to solve the resulting optimization problem and end by applying it to a case study and discussing the influence of relevant parameters.

Impacts at the global level

The production side of current electric systems consists in a set of base, intermediate and peak load power plants that is optimal considering the load pattern -and its expected evolution-of the area served. Due to their inherent non-dispatchable nature, wind and PV power can be essentially considered, for this purpose, as negative loads. Consequently, a massive development of such production means will entail a change in the optimal distribution between base, intermediate and peak load power plants, as the resulting net load pattern will be different, and probably more variable, than the existing one. In a liberalized electricity market, this translates into a modification of prices patterns, consisting mainly in lowering prices when non-dispatchable generation levels are high and load levels are low. Taken even further, it can lead to the appearance of negative prices on the spot market.

Spinning reserves are used by system operators to compensate for unpredictable imbalances between supply and demand that can be caused by errors in load forecasting or unplanned outages of generation units. Thus, the massive introduction of non-dispatchable renewable generation units will have an impact on reserve requirement calculation, as the uncertainty on their forecasting is likely to have different characteristics from that of the load. However, it is not yet clear if this will translate into an increase in reserve requirements compared to the traditional rule of using the power generated by the largest unit connected to the grid (see [START_REF] Doherty | A new approach to quantify reserve demand in systems with significant installed wind capacity[END_REF] and [START_REF] Ortega-Vazquez | Estimating the spinning reserve requirements in systems with significant wind power generation penetration[END_REF] for contrasting results). What is clear nonetheless is that the replacement of conventional generators by non-dispatchable ones -who are unable to provide spinning reserves in their current operation mode-will induce a change in how reserves are provisioned, either by forcing conventional generators to operate further from their optimal set-points or by resorting to alternatives solutions.

Impacts at the local level

Traditionally, the distribution system has been designed to deliver low-voltage electricity to end-users from centralized power plants connected to the transmission system. It is thus operated under the assumption of unidirectional power flows. The integration of distributed energy sources challenges this assumption since, at high penetration level, it is possible that local generation will surpass local load. The first issue created by these new operating conditions concerns voltage levels. Indeed, current distribution systems have been designed to take full advantage of the permissible voltage range by setting the voltage near the upper limit at the substation and selecting line characteristics that ensure the voltage at the end of the feeder in peak load conditions is still above the lower threshold, while minimizing their cost. The consequence is that, in case of a reverse power flow, it is possible to encounter upper-limit voltage violation even if the magnitude of the reverse power flow is significantly lower than that of the expected peak load [START_REF] Liu | Distribution System Voltage Performance Analysis for High-Penetration Photovoltaics[END_REF].

THE POTENTIAL ROLE OF STORAGE IN THIS CONTEXT

Storage is often considered, among other alternatives, as a natural candidate to accompany a significant development of intermittent energy sources (see, for example, [START_REF] Schaber | Utility scale storage of renewable energy[END_REF]). But let's not forget that storage means are already today an integral part of some electric systems. For example, in France, 5 GW of pumped hydro are in operation, mainly to accommodate for a large inflexible nuclear generation fleet and provide ancillary services. For an exhaustive account of the roles that storage devices can play in an electric system, please refer to [START_REF] Eyer | Energy Storage for the Electricity Grid: Benefits and Market Potential Assessment Guide[END_REF].

In the introduction, we have outlined some of the excepted impacts on the electric system of a shift to intermittent renewable energy sources. The objective of this section is to present how storage devices could help mitigate these and how to model such applications. Henceforth, we will operate under the assumption of the existence of a deregulated electricity market and an Active Distribution Network, as outlined in [START_REF] Kramer | Advanced Power Electronic Interfaces for Distributed Energy Systems[END_REF]. In particular, we suppose that the DSO has the possibility to control active and reactive power from distributed storage and generation means and has access to the relevant network physical quantities through a suitable ICT infrastructure. Furthermore, the DSO is responsible for the local supply-demand equilibrium downstream of the substation considered and is able to participate in electricity market where it is a price taker.

Energy Time-Shift

The first impact outlined in the introduction is the modification of the supply-demand equilibrium. If we assume that market prices are a relevant indicator of the state of the supply-demand equilibrium, an operator using a storage device to maximize its profit on the market by buying at low prices and selling at high ones (an application sometimes referred to as "price arbitrage" or "energy arbitrage", as in [START_REF] Graves | Opportunities for electricity storage in deregulating markets[END_REF]) will take part in the mitigation of such an impact.

As in [START_REF] Graves | Opportunities for electricity storage in deregulating markets[END_REF], we adopt a simplified model for energy storage devices, taking in account maximum power for charge and discharge, energy capacity and efficiency. In this light, the energy time-shift application can be modelled by the following set of equations : is the maximal power transacted on the market.

   T t t Market t Market P C min (1)         K k t k st t k RE t k
init k t p k dis p k dis p k ch k ch t k SOC P P SOC K k T t                 1 , , , , , ,   (3) max , , max , , 0 , 0 , , k dis t k dis k ch t k ch P P P P K k T t        (4) max 0 , , k t k SOC SOC K k T t      (5) (2)
(1) represents the minimization of the cost incurred to the DSO, (2) expresses the local supply-demand equilibrium for which the DSO is responsible, (3) models the evolution of the storage device state-of-charge while (4), ( 5) and ( 6) deal with technical limitations.

Spinning Reserve Provisioning

A potential fair solution -in terms of reducing negative externalities-to the second impact mentioned in the introduction would be to devise a mechanism requiring non-dispatchable energy producers to provide spinning reserves as a function of the power produced, so that the diminished reserve provisioning capabilities of conventional generating units are compensated for at the system level. Hereafter, we assume that such a mechanism exists, that the reserve requirement is proportional to the power produced and that it is fulfilled by the storage devices deployed in the system considered. From a modeling perspective, this translates into the following set of equations :

            K k t k RE UpReserve K k t k ch t k dis k dis P P P P T t , , , max ,  (7)
            K k t k RE e DownReserv K k t k dis t k ch k ch P P P P T t , , , max ,  (8)
where

Voltage Control

Henceforth, we assume that the storage devices and renewable energy units are connected to the grid through an Advanced Power Electronic Interface (APEI), as defined in [START_REF] Kramer | Advanced Power Electronic Interfaces for Distributed Energy Systems[END_REF], and that the substation transformer is equipped with an On-Load Tap Changer (OLTC), for which we use a simplified continuous model. We also assume that the grid downstream of the substation has a radial structure, which allows us to use the set of network equations defined in [START_REF] Venkatesh | An accurate voltage solution method for radial distribution systems[END_REF]

Q Q U Q P X Q j j j , , 2 2           (10) 0 2 2 2 2 2                  t j j t j t i j t j j t j t j S Z U U X Q R P U (11) 2 2 2 2 2 2 2
, ,

t t t l l l t t j j j j j Q P S X R Z V U      (
Q Q Q Q , , , ,    (14) max min max min , OLTC t OLTC OLTC t j V V V V V V     ( 15

METHODOLOGY

The optimization problem defined by equations ( 1) to ( 16) is non-linear, due to the presence of quadratic terms, and non-convex because of the terms

t kk t kk t kk U Q P 2 2
 in equations ( 9) and (10). The control variables are the vectors of active and reactive power injected by the storage devices, the vectors of reactive power injected by the renewable energy APEI and the vector of voltage downstream of the OLTC-equipped transformer. (3) introduces a time-coupling constraints that prevents us from solving the problem time step by time step. Consequently, if we want to solve it for a year with onehour time steps, the dimensionality of the problem becomes very high. These combined characteristics make the problem difficult to solve, especially in a context of distribution system planning, for which a high number of varying instances have to be solved (see, for example, [START_REF] Martins | Active distribution network integrated planning incorporating distributed generation and load response uncertainties[END_REF]) in order to attain an optimal planning. Hereafter, we present the simplification adopted to find a satisfactory compromise between optimality and computational time.

Partial time-decoupling

As explained before, the coupling between the time steps is induced by the evolution of the state-of-charge of the storage units. Moreover, these state-of-charges are dependent only from the active powers produced by the storage devices, which are mainly driven by the evolution of market prices. As these market prices often present strong daily and weekly pattern, we can guess that there may be a time horizon above which no significant additional benefits can be captured. We verify this by solving (1) to [START_REF] Venkatesh | An accurate voltage solution method for radial distribution systems[END_REF]

Scheduling and voltage control decoupling

The observation of (1) shows that only active powers have an influence on the objective function, while reactive powers only play a role when voltage magnitudes are inadequate. For the remainder, we define three types of time steps: a time step is deemed noncritical if the network equations and constraints are not active, semi-critical if they are active but not binding and critical if they are. From [START_REF] Liu | Distribution System Voltage Performance Analysis for High-Penetration Photovoltaics[END_REF], we know that, even at high levels of penetration of photovoltaic generators, voltage limit violations are infrequent events. To further this claim in the presence of storage devices, we execute simulations on the 69-bus medium-voltage network used in [START_REF] Venkatesh | An accurate voltage solution method for radial distribution systems[END_REF] for various levels of photovoltaic and storage penetration (defined as the ratio between the maximal apparent power of PV and storage connected at a given node and its annual maximal load) and compute the numbers of semi-critical and critical time steps.

Figure 1 : number of critical and semi-critical time steps

We thus observe that, even at unconventionally high levels of penetration, the number of critical time steps remains relatively low. This allows us to separate the complete problem in a linear multi-stage master problem of scheduling active powers defined by ( 1) to ( 8), for which we further reduce the number of variables by aggregating the storage units with the same efficiency and discharge duration, and a single-stage non-linear nonconvex problem defined by ( 9) to ( 16) to which we add the objective of minimizing the quadratic deviation from the master problem results. We then recombine both results to find a solution respecting the constraints while being close enough to the objective function optimal value (an upper bound on the loss of optimality induced can be evaluated, as the results of the master problem give us a lower bound on the cost function).

CASE STUDY

We apply this methodology to a case study consisting in the 69-bus network mentioned above, with residentialtype loads connected at each node and scaled so that the annual maximal load is equal to the loads used in [START_REF] Venkatesh | An accurate voltage solution method for radial distribution systems[END_REF]. Reactive loads are defined, so that the power factor remains constant and equal to the one used in [START_REF] Venkatesh | An accurate voltage solution method for radial distribution systems[END_REF]. We study the impact of the deployment of PV generators and storage units by making the number of nodes equipped (N) and the level of penetration, as defined above, (L) vary. For each number of nodes equipped, the nodes are chosen in increasing order of driving-point resistance. Below, we present some of the results obtained.

CONCLUSION

First, we have outlined some of the opportunities for storage units presented by the expected deployment of renewable energy generators in the distribution system. Then, we have modelled these applications in the form of a non-convex non-linear optimization problem that we separate in a master and a slave problem in order to make it tractable. We end by applying in to case study, and verify that the results are coherent with what was expected. Future research will be conducted along three axis : improving the computational efficiency of the algorithm, adding other applications of storage to the model and integrating it in an exhaustive distribution system planning process.

Figure 2 :Figure 3 :

 23 Figure 2 : Influence of voltage limit violations on active powers for a critical time step

Figure 4 :

 4 Figure 4 : (a) Voltage magnitude by node and by time step, sorted in increasing order of voltage magnitude

  load, the renewable energy power injected, the charge, discharge, algebraic power injected in the grid and state-of-charge of the storage device, at bus k during time step t .

	max Market P where T is the set of time steps considered, K is the set max , t Market Market P P T t      (6) of buses considered, t Market C is the market price forecast, t Market P is the algebraic power transacted on the market (equivalent here to the power transiting through the substation and positive when buying) during time step t , t Loss P are the aggregate network losses downstream of the substation, t k t k s t k dis t k ch t k RE t k Load SOC P P P P P , , , , , , , , , , are, respectively, the max , max , max , , k dis k ch k P P SOC are the energy capacity, maximal discharge power and maximal charge power of the storage device connected at bus k , while max Market P

Table 1 : Evolution of optimality and computation time as a function of the time horizon

 1 for a year and one-hour time steps and for various time horizons, while measuring the computation time. Results are presented in the table below and lead us to choose a 7-day time horizon.

	Time Horizon	Cost variation	Computation
	(in days)	(in %)	time (in seconds)
	1	0	26
	7	-2.02	70
	70	-2.11	709
	140	-2.11	2614

CIRED

2013, 22nd International conference & exhibition on electricity distribution, Electricity distribution systems for a sustainable future June 10-13, 2013, Stockholm, Sweden [Paper 1243]

CIRED 2013, 22nd International conference & exhibition on electricity distribution, Electricity distribution systems for a sustainable future June 10-13, 2013, Stockholm, Sweden [Paper 1243]

CIRED 2013, 22nd International conference & exhibition on electricity distribution, Electricity distribution systems for a sustainable future June 10-13, 2013, Stockholm, Sweden [Paper 1243]


Bernard G Barthès
email: <barthes@mpl.ird.fr>

Ernest Kouakoua

Marie-Christine Larré-Larrouy

Tantely M Razafimbelo

Edgar F De Luca

Anastase Azontonde

Carmen S V J Neves

Pedro L De Freitas

Christian L Feller

Texture and sesquioxide effects on water-stable aggregates and organic matter in some tropical soils

Keywords: Kaolinitic soils, Aggregation, Organic matter, Texture, Sesquioxides, Aluminium

ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Soil organic matter (OM) and aggregation are important determinants of soil fertility and productivity, and are key factors in the global carbon (C) cycle. Indeed, soil OM is a source of nutrients, promotes structure and water retention, and is a substrate for soil heterotrophs [START_REF] Baldock | Role of the soil matrix and minerals in protecting natural organic materials against biological attack[END_REF]. Soil aggregation has a major influence on root development, on water and C cycling, and on soil resistance to erosion [START_REF] Kay | Soil structure and organic carbon: a review[END_REF].

Moreover, soil OM and aggregation are closely linked one to another: OM is considered an important aggregate binding agent, on the one hand, and may be physically protected against decomposition within stable aggregates, on the other hand [START_REF] Feller | Physical control of soil organic matter dynamics in the tropics[END_REF][START_REF] Angers | Dynamics of soil aggregation and C sequestration[END_REF].

However, the stability of soil OM and aggregation as well as relationships between OM and aggregation are affected by the presence of sesquioxides. Indeed, the aggregating role of OM could be less effective in soils that include large amounts of such inorganic constituents (Tisdall and Oades, 1982;[START_REF] Six | Soil organic matter, biota and aggregation in temperate and tropical soils -Effect of no-tillage[END_REF]. Due to the role of sesquioxides in the stabilization of OM [START_REF] Dalal | Aggregation and organic matter storage in sub-humid and semi-arid soils[END_REF][START_REF] Guggenberger | Effect of mineral colloids on biogeochemical cycling of C, N, P, and S in soil[END_REF], the importance of aggregation in the stability of OM should also be re-examined for soils that are rich in sesquioxides. This is the case for low-activity clay (LAC) soils, which include clay minerals dominated by 1:1 phyllosilicates, as kaolinite, associated with crystallized and poorly or non-crystallized iron (Fe) and aluminium (Al) oxides and hydroxides. They cover about 60-70% of tropical areas [START_REF] Segalen | Les Sols Ferrallitiques et leur Répartition Géographique. Tome 1. Introduction Générale. Les Sols Ferrallitiques : leur Identification et Environnement Immédiat[END_REF], where they are mainly represented by Alfisols, Oxisols and Ultisols according to the US Soil Taxonomy (Soil Survey Staff, 1999) or by Acrisols, Ferralsols and Nitisols according to the FAO soil classification (FAO-ISRIC-ISSS, 1998). Though they are widely distributed, LAC tropical soils have received much less attention than soils from temperate areas, and knowledge on OM and aggregation in LAC tropical soils still remains fragmentary.

As far as LAC tropical soils are concerned, more information is thus useful to verify the importance of sesquioxides in soil OM and aggregate stability, and complementarily, to characterize the interrelations between OM and aggregation. The influence of texture on soil OM is more clearly established. Several studies, some of them regarding LAC tropical soils, showed that soil C content increases with clay content [START_REF] Feller | Physical control of soil organic matter dynamics in the tropics[END_REF]. However, the role of texture in stable aggregation remains questionable (Le [START_REF] Bissonnais | Soil characteristics and aggregate stability[END_REF][START_REF] Amézketa | Soil aggregate stability: a review[END_REF], and requires additional investigations.

Soil OM may first be considered through the determination of total soil C content (Ct), as far as soils do not include carbonates. It can also be characterized by chemical fractionations, but the importance of the obtained fractions (e.g. fulvic and humic acids) towards major soil processes such as aggregation and OM mineralization is not yet well established [START_REF] Feller | Physical control of soil organic matter dynamics in the tropics[END_REF][START_REF] Baldock | Interactions of organic materials and microorganisms with minerals in the stabilization of soil structure[END_REF]. Therefore, increasing attention has progressively been paid to procedures that involve physical fractionations of soil OM, e.g. particle size fractionations. Indeed, the characterization of OM associated with soil primary particles (sands, silts, clay) has proved to be a relevant approach to separate fractions that have different morphologies, composition, and dynamics [START_REF] Christensen | Physical fractionation of soil and organic matter in primary particle size and density separates[END_REF][START_REF] Feller | Physical control of soil organic matter dynamics in the tropics[END_REF]. The characterization of water-stable aggregate distribution, which may be achieved using simple laboratory procedures, also provides useful information on soil quality and behaviour (Tisdall and Oades, 1982;[START_REF] Amézketa | Soil aggregate stability: a review[END_REF][START_REF] Barthès | Field-scale run-off and erosion in relation to topsoil aggregate stability in three tropical regions (Benin, Cameroon, Mexico)[END_REF].

The objectives of the present work were (i) to characterize the size distributions of stable aggregates and organic constituents associated with primary particles, (ii) to study how these distributions were affected by soil texture and Al-and Fe-sesquioxides, and (iii) how these distributions were interrelated, for a range of topsoil layers (0-10 cm) from LAC soils from sub-Saharan Africa and Brazil.

Material and methods

Sites and sampling

Composite soil samples were collected at 0-10 cm depth in 18 plots: five in southern Congo-Brazzaville (two sites in the same region), four in southern Benin (one site), and nine in Brazil, including three in Goiás (one site), three in São Paulo (three sites), and three in Paraná (one site). Table 1 provides information on location, climate, soil type, parent material, texture, clay mineralogy, and land use. The climate is tropical (Congo, Benin, Goiás) or subtropical (Paraná, São Paulo), ranges in mean annual rainfall and temperature being 1100-1600 mm and 23-27°C, respectively. Soils are mainly Oxisols and Ultisols, with sandy to clayey texture, and clay mineralogy is dominated by kaolinite. Further information on sites and soils was given by [START_REF] Kouakoua | Relations entre stabilité de l'agrégation et matière organique totale et soluble à l'eau chaude dans des sols ferrallitiques argileux (Congo, Brésil)[END_REF] for Congo, Goiás and Paraná, [START_REF] Barthès | Field-scale run-off and erosion in relation to topsoil aggregate stability in three tropical regions (Benin, Cameroon, Mexico)[END_REF] for Benin, and De Luca (2002) for São Paulo. Samples were generally collected using 0.25-to 0.5-L cylinders, air-dried at room temperature, then gently crushed using a mortar and pestle and sieved through a 2-mm mesh. Aliquots were finely ground to pass a 0.2-mm mesh, also using a mortar and pestle.

Aggregate fractionation

The distribution of water-stable aggregates was determined on 2-mm sieved air-dried soil samples using a test adapted from [START_REF] Kemper | Aggregate stability and size distribution[END_REF]. Four grams of soil were rapidly immersed into deionised water for 30 min then wet-sieved during 6 min, using a motor-driven holder lowering and raising 200-µm sieves into containers of water. On the one hand, the fraction > 200 µm was dried at 105°C then weighed. It was successively sieved into dispersive NaOH solution (0.05 M), dried at 105°C, and weighed to determine coarse sand content. Stable macroaggregate (> 200 µm) content was calculated as the difference between fraction > 200 µm and coarse sands. On the other hand, the fraction < 200 µm was transferred to a glass cylinder, which was shaken by hand (30 end-over-end tumblings) and left to stand during the correct settling time for the 0-20 µm fraction (pipette method). An aliquot of the fraction < 20 µm was then siphoned from the upper 10 cm of the suspension, dried at 105°C, weighed, and referred to the cylinder volume to determine microaggregate (< 20 µm) content.

Mesoaggregate (20-200 µm) content was calculated by difference between total soil and other fractions. Compared to the macroaggregate fraction (> 200 µm), which included genuine aggregates only due to coarse sand-correction, the meso-and microaggregate fractions included aggregates as well as primary particles of the same size. Measurements were made on four replicates per sample. It should be noticed that the aggregate fractions were not extracted thus were not available for further analyses.

Particle size fractionation of organic matter

The particle size fractionation of OM requires maximum soil dispersion with minimum particle alteration. It was carried out on 2-mm sieved air-dried soil samples of 40 g (sandy soils) or 20 g (other soils), in duplicate, following [START_REF] Gavinelli | A routine method to study soil organic matter by particle-size fractionation: examples for tropical soils[END_REF]. Each sample was pre-soaked overnight at 4°C in deionised water with 2.5 g L -1 sodium metaphosphate. It was then shaken with agate balls in a rotary shaker for 2 h (sandy soils) or 6 h (others).

Indeed, a long shaking duration is necessary to achieve maximum dispersion in clayey samples, but in coarse textured samples it may lead to an alteration of coarse organic particles by sands [START_REF] Feller | Utilisation des résines sodiques et des ultrasons dans le fractionnement granulométrique de la matière organique des sols. Intérêt et limites[END_REF]. Next the soil suspension was wet-sieved through 200-and 50µm sieves, successively. The fractions remaining in the sieves were washed with water and the washings added to the 0-50 µm suspension. The suspension < 50 µm was ultrasonicated for 10 min with a probe-type ultrasound generating unit, then it was sieved on a 20-µm screen, and the residual material obtained from the sieve was washed. The three fractions > 20 µm were dried at 60°C and weighed. The suspension < 20 µm was transferred to a 1-L glass cylinder, where water was added to bring the volume to 1 L. Then the cylinder was shaken by hand (30 end-over-end tumblings) and left to stand during the correct settling time for the 0-2 µm fraction (pipette method). The upper 30 cm of the suspension, which included particles < 2 µm only, was siphoned off. The process (i.e. water addition, shaking, settling, and siphoning) was repeated until the supernatant was clear thus the fraction 0-2 µm extracted completely (five cycles at least). The 0-2 µm suspension was then flocculated with strontium chloride, centrifuged, filtered, and the pellets were washed with water, dried at 60°C and weighed. For some samples (Benin, Saõ Paulo), the supernatant from centrifugation and the washing waters from previous sieving operations were grouped, then an aliquot was collected and filtrated at 0.2 µm for the analysis of soluble organic C. The 2-20 µm fraction, which remained at the bottom of the sedimentation cylinder, was also dried at 60°C and weighed.

All these fractions, separated from completely dispersed soil samples, were called dispersed fractions, as opposed to aggregate fractions. In the present paper, data regarding the dispersed fractions 50-200 and 20-50 µm have been combined (20-200 µm), as well as those regarding the fractions 2-20 and 0-2 µm (< 20 µm).

Analyses of carbon, pH, and iron and aluminium sesquioxides

Carbon contents of finely ground (< 0.2 mm) soil aliquots and dispersed fractions were determined by dry combustion using a Leco CHN 600 elemental analyzer (St Joseph, MI). In the absence of carbonates, all C was assumed to be organic. Soluble organic C was analyzed using a Shimadzu TOC 5000 analyzer (Kyoto, Japan). The pH in water was determined with a soil:solution ratio of 1:2.5. On whole soil aliquots, "free" Fe (Fe CBD ) and Al (Al CBD ) were extracted with citrate-bicarbonate-dithionite (CBD), "amorphous" Fe (Fe OX ) and Al (Al OX ) with ammonium oxalate, and all were analyzed using an Unicam P 900 (Cambridge, UK) atomic absorption spectrometer [START_REF] Rouiller | Méthodes d'analyses des sols[END_REF].

Statistical analyses

Simple and multiple linear correlation coefficients were calculated between variables, and their significance was denoted NS for p  0.05, * for p < 0.05, ** for p < 0.01, and *** for p < 0.001. Principal component analyses (PCAs) were also carried out on the dataset. The objective of PCA is to reduce the number of original variables in a smaller number of representative and uncorrelated factors, and to detect structure in the relationships between original variables [START_REF] Lebart | Statistique Exploratoire Multidimensionnelle[END_REF].

Results

Studied variables are presented in Table 2, and main correlations between them in Table 3.

Soil texture and contents in Fe-and Al-sesquioxides

The cumulative yield of dispersed fractions ranged from 95 to 101%, and averaged 99%. Clay plus fine silts (< 20 µm) ranged from 8 to 87%; they correlated negatively with coarse sands (> 200 µm), and to a lesser extent, with coarse silts plus fine sands (20-200 µm).

Soil content in Fe CBD ranged from 8 to 99 g kg -1 , and Al CBD , Fe OX and Al OX from 0.4 to 7.6 g kg -1 . All correlated positively one with another in general, particularly Fe CBD and Fe OX , and Al CBD and Al OX . Moreover, all correlated positively with clay plus fine silts, Al CBD especially. Clay plus fine silts tended to increase and coarse sands to decrease with land use intensification (i.e. cultivation, tillage, reduced surface cover) 1 . In contrast, the effect of land use on Fe-and Al-sesquioxides was not clear.

Soil aggregate distribution; relations with texture and Fe-and Al-sesquioxides

The cumulative yield of aggregate fractions plus coarse sands was 100% by definition, the mesoaggregate fraction being calculated by difference. Aggregate distributions were generally dominated by macroaggregates (> 200 µm): they included 42 to 82% of the mass of aggregate fractions (coarse sands being excluded), and represented a higher soil proportion than mesoaggregates (20-200 µm) in 16 out of the 18 samples. The proportion of microaggregates (< 20 µm) was very low. Macro-and mesoaggregate fractions did not correlate significantly (except on a coarse sand-free basis, due to the low proportion of microaggregates). The proportion of microaggregates did not relate clearly with other aggregate fractions.

Considering all 18 plots, the macroaggregate fraction correlated negatively with coarse sands and positively with clay plus fine silts, Al CBD , Al OX (Figure 1a), and to a lesser extent, with Fe CBD and Fe OX . It seemed that macroaggregates correlated with clay plus fine silts "indirectly" (relation A), as a consequence of their close negative correlations with coarse sands (relation B), which related negatively with clay plus fine silts (relation C). Indeed, the product of coefficient correlations assigned to relations B and C was similar to the coefficient correlation assigned to relation A. Meso-and microaggregate fractions related less closely with texture and sesquioxides.

Soil carbon; relations with texture and Fe-and Al-sesquioxides

For the studied samples, Ct ranged from 5 to 43 g C kg -1 . The cumulative C yield in dispersed fractions ranged from 78 to 101%, and averaged 90%. Rather low recoveries could be attributed, at least partly, to soluble C. Indeed, when it was determined, soluble C accounted for 6 to 9% of Ct (data not shown), which agreed with data reported by [START_REF] Christensen | Physical fractionation of soil and organic matter in primary particle size and density separates[END_REF]. On average, the dispersed fractions > 200, 20-200 and < 20 µm included respectively 37, 15 and 27 g C kg -1 fraction (C concentrations). This corresponded to 1.5, 0.8 and 1.9 times 1 The effects of land use on many soil properties are fairly well established (cf. end of section 4.7) and the present paper did not aim at discussing them extensively. However, increasing topsoil clay content upon land use intensification has not been often reported. It might be due to erosion, which generally increases with land use intensification and leads to the outcropping of sub-superficial layers that are more clayey than superficial ones in many LAC tropical soils.

Ct (C enrichments), represented 1.6, 3.1 and 13.2 g C kg -1 soil (C amounts), and accounted for 8, 17 and 65% of Ct, respectively. Size distributions of organic constituents were thus dominated by fine OM (46 to 80% of Ct). Considering all 18 soil samples, Ct correlated positively with C amount in every dispersed fraction, especially with that of fraction < 20 µm.

Carbon amounts in the dispersed fractions 20-200 and > 200 µm correlated closely one with another, but correlated less closely with that of fraction < 20 µm.

Considering all 18 soil samples, texture related clearly with the characteristics of several C pools (Figure 2). Clay plus fine silts correlated positively with Ct and C amount in the dispersed fraction < 20 µm (Figures 1b and1c), with C concentration and enrichment in the dispersed fraction > 200 µm, and negatively with C enrichment in the dispersed fraction < 20 µm. Soil content in Al CBD , and in Al OX to a lesser extent, correlated closely with Ct and C amount in the dispersed fraction < 20 µm (Figures 1b and1c), and less closely, with C amounts in the coarser fractions. By contrast, Fe CBD and Fe OX did not relate clearly with Ct and fraction C amounts. Multiple linear correlations between C amount in a given fraction, on the one hand, and two or more variables regarding texture and/or sesquioxides, on the other hand, were not closer than corresponding simple linear correlations or were not significant..

Possible determinants of soil aggregation and organic matter

Considering all 18 soil samples, soil content in stable macroaggregates correlated positively with Ct and with C amount in the dispersed fraction < 20 µm (Figure 3), but each of them correlated more closely with Al CBD (Figure 1). To a lesser extent, macroaggregate content correlated with C amount in the dispersed fractions > 200 and 20-200 µm, but each of them correlated more closely with Al OX . Multiple linear correlations between macroaggregate content, on the one hand, and Al-extracts and fraction C amounts, on the other hand, were not closer than corresponding simple correlations. Relationships between meso-or microaggregate fractions and Ct or fraction C amounts were not significant.

Data thus suggested that Al CBD , and Al OX to a lesser extent, were major determinants of soil aggregation and OM content in the studied soils. However, when considering each location separately, Al CBD and Al OX varied generally within narrow ranges, and the abovementioned correlations were not significant in general. By contrast, the effect of land use became important: land use intensification (i.e. cultivation, tillage, reduced surface cover) generally caused a decrease in the proportion of macroaggregates, in C concentration and amount in every dispersed fraction, thus in Ct. These effects have already been described for several of the studied sites [START_REF] Kouakoua | Relations entre stabilité de l'agrégation et matière organique totale et soluble à l'eau chaude dans des sols ferrallitiques argileux (Congo, Brésil)[END_REF][START_REF] Barthès | Field-scale run-off and erosion in relation to topsoil aggregate stability in three tropical regions (Benin, Cameroon, Mexico)[END_REF], and will not be detailed here.

Principal component analysis (PCA)

Three main PCAs were carried out, with active variables that contributed to factor definition, and supplementary variables that did not. Considering supplementary variables helped limiting the over-influence of linked variables (e.g. C amounts of fractions and their sum Ct). Clay plus fine silts, coarse silts plus fine sands, Al CBD and Fe CBD were always considered active variables. For the first PCA, C amounts in dispersed fractions were also considered active, while Ct, aggregate fractions, Al OX and Fe OX were considered supplementary. For the second PCA, fraction C concentrations were considered active, and Ct, fraction C amounts and aggregate fractions supplementary. Finally, for the third PCA, macro-and mesoaggregate fractions were considered active, and Ct and fraction C amounts supplementary.

On the whole, the three PCAs showed similar structure in the relationships between variables (the first PCA is presented in Figure 4). The first factor included 58-62% of the total variability, the second factor 20-22%, and the three first factors together 90-92%.

Macroaggregate content and Al CBD were always very closely associated, and were associated with C amount < 20 µm and Ct, confirming their strong interrelations. The coordinates of these four variables on the first factor ranged from -0.77 to -0.96. Clay plus fine silts were associated with this group of variables, but to a lesser extent. Amounts of C in the dispersed fractions > 200 and 20-200 µm were associated one with another, as well as the corresponding C concentrations. When Fe OX and Al OX were included in the analysis, they were associated with Fe CBD and Al CBD , respectively.

Discussion

Size distribution of stable aggregates

Stable macroaggregates (> 200 µm) dominated aggregate distributions in general. A high content in stable macroaggregates has often been reported for clayey LAC tropical soils [START_REF] Oades | Aggregate hierarchy in soils[END_REF][START_REF] Albrecht | Déterminants organiques et biologiques de l'agrégation : implications pour la recapitalisation de la fertilité physique des sols tropicaux[END_REF][START_REF] Six | Soil organic matter, biota and aggregation in temperate and tropical soils -Effect of no-tillage[END_REF] but less frequently for coarse-textured ones [START_REF] Dalal | Aggregation and organic matter storage in sub-humid and semi-arid soils[END_REF]Spaccini et al., 2001), where it has been considered that macroaggregation could be less stable [START_REF] Albrecht | Déterminants organiques et biologiques de l'agrégation : implications pour la recapitalisation de la fertilité physique des sols tropicaux[END_REF]. Thus stable aggregation was well developed in the studied soils, and this probably stands for most LAC tropical soils. Within aggregate fractions (i.e. on a coarse sand-free basis), the very close correlation between macro-and mesoaggregates suggested an aggregate hierarchy: macroaggregate disruption released mesoaggregates mainly, and conversely, macroaggregates resulted mainly from bounding of mesoaggregates. Aggregate hierarchy has not often been reported in LAC soils. [START_REF] Oades | Aggregate hierarchy in soils[END_REF] reported such a hierarchy for an Alfisol and a Mollisol (dominated by 2:1 clay mineralogy), but not for a clayey Oxisol. Six et al. (2000a) also found a higher degree of aggregate hierarchy in 2:1 than in 1:1 clay-dominated soils.

However, [START_REF] Feller | Aggregation and organic matter storage in kaolinitic and smectitic tropical soils[END_REF] reported a tendency to an aggregate hierarchy for an Ultisol, an Inceptisol and an Oxisol.

Size distribution of organic constituents

In the present study, the dispersed fractions > 200, 20-200 and < 20 µm included 8, 17, and 65% of Ct in average, respectively. This was consistent with data from tropical soils reviewed by [START_REF] Feller | Physical control of soil organic matter dynamics in the tropics[END_REF], which indicated that proportions of Ct in the dispersed fractions > 50, 2-50 and < 2 µm generally ranged from 10 to 30%, 20 to 40%, and 35 to 70%, respectively. The present study also showed that Ct correlated positively with C amount in every dispersed fraction (in g C kg -1 soil), with fine fraction C especially. Thus changes in Ct resulted from changes in every size class, but depended more closely on those in the fine fraction. Studying 21 grassland topsoils from Saskatchewan to Texas, [START_REF] Amelung | Carbon, nitrogen, and sulfur pools in particle-size fractions as influenced by climate[END_REF] similarly reported positive correlations between Ct and C amount in every dispersed fraction, in the fine one especially, and found that the dispersed fraction < 20 µm included 58 to 99% of Ct. For a clayey Oxisol under bush savanna and pasture in Brazil, [START_REF] Roscoe | Soil organic matter dynamics in density and particle size fractions as revealed by the 13 C/ 12 C isotopic ratio in a Cerrado's oxisol[END_REF] also found positive correlations between Ct and fraction C amounts. Moreover, the present study showed that C amounts in the dispersed fractions 20-200 and > 200 µm correlated closely one with another but correlated poorly with C amount in the fine fraction. Similar relationships were found between fraction C concentrations (in g C kg -1 fraction). This suggested that organic compartments > 200 and 20-200 µm had similar dynamics, which differed from those of organic fraction < 20 µm. Indeed, several works supported the evidence that organic constituents > 20 µm are plant debris mainly, the coarser ones being less decomposed and having a more recognizable morphology than the finer ones, whereas organic constituents < 20 µm are more humified and have a slower turnover [START_REF] Feller | Physical control of soil organic matter dynamics in the tropics[END_REF][START_REF] Baldock | Role of the soil matrix and minerals in protecting natural organic materials against biological attack[END_REF][START_REF] Guggenberger | Effect of mineral colloids on biogeochemical cycling of C, N, P, and S in soil[END_REF].

Influence of texture on soil aggregation

Macro-and mesoaggregate fractions correlated positively with clay plus fine silts.

However, this seemed to result largely from negative correlations between all three variables and coarse sands: an increase in coarse sands caused simultaneous decreases in clay plus fine silts and aggregate fractions, and there was no evidence of direct influence of clay plus fine silts on aggregate fractions, macroaggregates especially. This contrasted with the rather general agreement that clay content positively affects aggregate stability, as reported in reviews by Le [START_REF] Bissonnais | Soil characteristics and aggregate stability[END_REF] and [START_REF] Amézketa | Soil aggregate stability: a review[END_REF]. However, these authors mentioned contradictory results, especially when considering wide ranges of soils, because significant correlations between clay and aggregation have often been established within narrow ranges of soils. [START_REF] Dalal | Aggregation and organic matter storage in sub-humid and semi-arid soils[END_REF] did not consider that clays were important agents of aggregate stabilization in Oxisols and Ultisols, and [START_REF] Six | Soil organic matter, biota and aggregation in temperate and tropical soils -Effect of no-tillage[END_REF] did not find any correlation between clay content and aggregate stability over a wide range of soils from tropical and temperate areas.

Influence of texture on soil organic matter

The present study confirmed the positive relation between Ct and clay plus fine silts, which was reported for LAC tropical soils by [START_REF] Feller | Physical control of soil organic matter dynamics in the tropics[END_REF]. When plotting Ct against clay plus fine silts (in %), slope coefficient was very close to that calculated by these authors (0.036 vs. 0.037). Indeed, soil texture is considered a key variable affecting Ct, as a result of electrostatic binding between negatively charged clay surfaces and organic colloids via cation bridges [START_REF] Ingram | Managing carbon sequestration in soils: concepts and terminology[END_REF][START_REF] Paustian | Environmental and management drivers of soil organic carbon stock changes[END_REF]. Due to sorption of fine organic constituents to fine mineral particles, C amount in the fine fraction increases with the proportion of fine primary particles, as confirmed by [START_REF] Feller | Aggregation and organic matter storage in kaolinitic and smectitic tropical soils[END_REF] over a range of tropical soils. As fine fraction C includes the highest proportion of Ct, Ct also increases with clay plus fine silts. Thus clayey soils contain more C, but the present study showed that C enrichment affected their coarse fraction mainly, whereas in coarse-textured soils C enrichment rather affected the fine fraction. [START_REF] Christensen | Physical fractionation of soil and organic matter in primary particle size and density separates[END_REF] also reported in his review that C enrichment in the fine fraction was inversely related to its proportion in the whole soil. [START_REF] Dalal | Aggregation and organic matter storage in sub-humid and semi-arid soils[END_REF] similarly noticed preferential C enrichment of the clay fraction in coarse-textured soils. Studying grassland topsoils from Canada to Texas, Amelung et al.

(1998) observed that C concentrations in the dispersed fractions 250-2000 and 20-250 µm were inversely related to their respective proportions in the whole soil, and suggested that it was largely explained by a dilution effect. The influence of texture on C concentration in coarse fractions could also be attributed to encrustation of plant debris by fine mineral particles, which are attached to mucilages produced by microorganisms that feed on debris (Tisdall and Oades, 1982;[START_REF] Angers | Dynamics of soil aggregation and C sequestration[END_REF]. This helped explain the positive correlation between clay plus fine silts and C concentration and enrichment in the dispersed fraction > 200 µm. Additionally, the present study showed that the relationship between the mass of the fraction and the C amount it contains was less clear for the dispersed fractions 20-200 and > 200 µm than for that < 20 µm. This suggested that soil OM dynamics were more affected by fine than by coarse primary particles. This was confirmed by [START_REF] Amelung | Carbon, nitrogen, and sulfur pools in particle-size fractions as influenced by climate[END_REF] for a range of North American grasslands, where C amount in the dispersed fraction < 20 µm correlated positively with clay plus fine silts, whereas C amounts in coarser fractions did not relate to texture.

Influence of sesquioxides on soil aggregation

Soil content in stable macroaggregates correlated closely with Al CBD, Al OX , and to a lesser extent, with Fe CBD and Fe OX . Many authors mentioned the importance of sesquioxides in aggregate stability, in LAC soils especially [START_REF] Kemper | Aggregate stability of soils from western United States and Canada[END_REF][START_REF] Oades | Aggregate hierarchy in soils[END_REF][START_REF] Bissonnais | Soil characteristics and aggregate stability[END_REF]Six et al., 2000b). The role of these compounds has been attributed to their flocculation capacity, to their binding effect of clay particles to organic molecules, and to their possible precipitation as gels on clay surfaces, but this was reported to affect mesoaggregation mainly [START_REF] Amézketa | Soil aggregate stability: a review[END_REF]. Electrostatic bindings between clays and oxides has also been mentioned, but due to their limited range of action, it has been hypothesized that these interactions result in macroaggregates that are not stable enough to resist fast wetting [START_REF] Six | Soil organic matter, biota and aggregation in temperate and tropical soils -Effect of no-tillage[END_REF].

While the predominant role of free Fe oxides in macroaggregate stability has been reported by several authors, for Oxisols especially [START_REF] Kemper | Aggregate stability of soils from western United States and Canada[END_REF][START_REF] Dalal | Aggregation and organic matter storage in sub-humid and semi-arid soils[END_REF], the importance of Al-containing crystalline sesquioxides, as observed in the present study, has not been strongly supported by the literature. The effectiveness of gibbsite in maintaining soil aggregation has been reported to be higher than that of Fe-oxides [START_REF] El-Swaify | Changes in the physical properties of soil clays due to precipitated aluminum and iron hydroxides: swelling and aggregate stability after drying[END_REF]. However, correlation between Al CBD and macroaggregation could not be attributed to gibbsite because: (i) gibbsite is little attacked by CBD thus releases little Al CBD (Jackon et al., 1986), and (ii) Al CBD was maximum in Congolese samples, which did not include gibbsite. Aluminium-substituted crystalline hematite and goethite are dissolved by CBD [START_REF] Jackson | Oxides, hydroxides, and aluminosilicates[END_REF], and were probably the main sources of non-oxalate extractable Al CBD in the studied samples. As macroaggregate content correlated moderately with Fe CBD , the aggregating role of crystalline Fe-sesquioxides seemed to result principally from the degree of Al-for-Fe substitution in their structure. Indeed, several authors reported that the specific surface area of crystalline Fe-sesquioxides increases with Al-substitution, mainly due to decreasing crystallite size [START_REF] Schwertmann | Iron oxides[END_REF][START_REF] Ruan | Dehydroxylation of aluminous goethite: unit cell dimensions, crystal size and surface area[END_REF]. As aggregation relates to specific surface area [START_REF] Goldberg | Factors affecting clay dispersion and aggregate stability of arid-zone soils[END_REF][START_REF] Bissonnais | Soil characteristics and aggregate stability[END_REF][START_REF] Amézketa | Soil aggregate stability: a review[END_REF], the increase in stable macroaggregates with Al CBD might thus result from the increase in specific surface area with Al-substitution on crystalline Fe-sesquioxides.

Influence of sesquioxides on soil organic matter

The present study also showed close relationships between organic constituents and Al-containing sesquioxides, coarse fractions (> 20 µm) relating with non-crystalline compounds preferentially (Al OX ), and fine fractions (< 20 µm), much more closely, with both crystalline and non-crystalline ones (Al CBD ). The affinity of OM to Al-and Fe-sesquioxides, either crystalline or non-crystalline, has been reported in the literature, regarding fine organic fractions as well as incompletely humified residues, which can be stabilized by sorption, by entrapment, or by complexation [START_REF] Guggenberger | Effect of mineral colloids on biogeochemical cycling of C, N, P, and S in soil[END_REF].

The role of amorphous Al and Fe in soil OM protection against biodegradation, through the formation of organo-mineral complexes, has been highlighted by numerous authors [START_REF] Boudot | Carbon mineralization in Andosols and aluminium-rich highland soils[END_REF][START_REF] Baldock | Role of the soil matrix and minerals in protecting natural organic materials against biological attack[END_REF]2000;[START_REF] Guggenberger | Effect of mineral colloids on biogeochemical cycling of C, N, P, and S in soil[END_REF]. [START_REF] Baldock | Role of the soil matrix and minerals in protecting natural organic materials against biological attack[END_REF] reported that Al-complexes resulted in a greater stabilization of OM than Fe-complexes, as observed in the present study: C amount in every dispersed fraction correlated more closely with Al OX than with Fe OX . Moreover, it is likely that the main sources of non-oxalate extractable Al CBD in the studied samples were Al-substituted crystalline Fe-sesquioxides, as mentioned in the previous section. As also mentioned, the increase in Al-for-Fe substitution causes an increase in specific surface area, and this in turn causes an increase in OM stabilization [START_REF] Baldock | Role of the soil matrix and minerals in protecting natural organic materials against biological attack[END_REF]2000;[START_REF] Kaiser | Mineral surfaces and soil organic matter[END_REF]. This helped to explain the correlations between Al CBD and Ct or fraction C amounts. Considering that micropores are preferential sites for OM sorption [START_REF] Kaiser | Mineral surfaces and soil organic matter[END_REF], the particular affinity of organic particles < 20 µm to non-oxalate extractable Al CBD might be due to the small crystallite size of Al-substituted Fe-sesquioxides, the micropores of which are accessible to small particles only.

Studying the mineral association of OM in the surface horizons of an Alfisol and an Oxisol, [START_REF] Shang | Organic matter stabilization in two semiarid tropical soils: size, density, and magnetic separations[END_REF] also observed the enrichment of the fine fractions in Al CBD , while Al OX was particularly concentrated in the light fractions (i.e. including coarse organic particles mainly).

Determinants of soil aggregation and organic matter content

Many authors observed positive correlations between stable macroaggregation and OM, which were attributed to the aggregating role of OM and to physical protection of OM within aggregates [START_REF] Feller | Physical control of soil organic matter dynamics in the tropics[END_REF][START_REF] Angers | Dynamics of soil aggregation and C sequestration[END_REF][START_REF] Six | Soil organic matter, biota and aggregation in temperate and tropical soils -Effect of no-tillage[END_REF]. Several works reported that some organic fractions, such as polysaccharides or particulate OM, were particularly involved in these relationships (Tisdall and Oades, 1982;[START_REF] Kouakoua | Relations entre stabilité de l'agrégation et matière organique totale et soluble à l'eau chaude dans des sols ferrallitiques argileux (Congo, Brésil)[END_REF][START_REF] Baldock | Interactions of organic materials and microorganisms with minerals in the stabilization of soil structure[END_REF]. This was not supported by the present results, macroaggregation being more closely correlated with Ct than with any organic size fraction.

Moreover, considering all 18 soil samples, stable macroaggregation was more closely linked with Al CBD than with other parameters, organic ones especially. Tisdall and Oades (1982) already underlined that organic materials were not necessarily the main aggregating agents, especially in soils that included more than 10% sesquioxides. [START_REF] Oades | Aggregate hierarchy in soils[END_REF] also suggested that oxides were dominant stabilizing agents in the Oxisol they studied. [START_REF] Six | Soil organic matter, biota and aggregation in temperate and tropical soils -Effect of no-tillage[END_REF] similarly hypothesized that stable macroaggregation was less dependent on OM in highly weathered tropical soils than in temperate ones, because the formers had a greater potential to form physicochemical macroaggregates, in the presence of oxides especially. Moreover, C amount in any dispersed fraction was more closely linked with Al CBD or Al OX than with macroaggregation or texture. This suggested that the stability of OM was more dependent on its association with Al-containing sesquioxides than on physical protection within stable aggregates or sorption to clay particles. It could thus be assumed that Al-containing sesquioxides were the main determinants of stable macroaggregation and OM content in the LAC tropical soils under study. However, when each location was considered separately, the influence of land use increased markedly. The negative consequences of land use intensification (i.e. cultivation, tillage, reduced surface cover) on many soil properties are fairly well established. As far as tropical soils are concerned, they have been reported for topsoil aggregation [START_REF] Resck | Impact of conversion of Brazilian Cerrados to cropland and pastureland on soil carbon pool and dynamics[END_REF]Spaccini et al., 2001) and for total and fraction C [START_REF] Feller | Physical control of soil organic matter dynamics in the tropics[END_REF]Solomon et al., 2002;Vågen et al., 2005). This underlines that at the local scale, due to rather homogeneous mineralogical properties, land use remains an important determinant of soil OM content and aggregation.

Conclusion

Over the range of LAC tropical soils that were studied, aggregate distributions were dominated by stable macroaggregates (> 200 µm), and C distributions in primary particles by fine fraction C (< 20 µm). Macroaggregation was not clearly affected by texture, whereas total C and fine fraction C increased with clay plus fine silts. The results also suggested that Al-containing sesquioxides were major determinants of macroaggregate and OM stability. Indeed, macroaggregate content correlated positively with Ct and with C in every fraction, with fine fraction C especially, but it correlated more closely with CBD-extractable Al. This suggested that Al-containing sesquioxides had a more important aggregating role than OM in LAC tropical soils. Moreover, C amounts in fine (< 20 µm) and coarse (> 20 µm) fractions related more closely with CBD-and oxalate-extractable Al, respectively, than with stable macroaggregate content or texture. Thus the stability of soil OM was more influenced by its association with Al-containing sesquioxides than by physical protection within stable macroaggregates or sorption to clay particles. It could also be assumed that Al-containing sesquioxides played a dominant role in the relations between OM and aggregation. However, considering each location separately, soil content in sesquioxides varied within narrow ranges, and as it cannot be managed easily, the importance of land use on OM and aggregation remained fundamental. Solomon, D., Fritzsche, F., Lehmann, J., Tekalign, M. and Zech, W., 2002. Soil organic matter dynamics in the subhumid agroecosystems of the Ethiopian highlands: evidence from natural 13 C abundance and particle-size fractionation. Soil Sci. Soc. Am. J., 66: 969-978. Spaccini, R., Zena, A., Igwe, C.A., Mbagwu, J.S.C. and Piccolo, A., 2001. Carbohydrates in water-stable aggregates and particle size fractions of forested and cultivated soils in two contrasting tropical ecosystems. Biogeochemistry, 53: 1-22. Tisdall, J.M. and Oades, J.M., 1982. Organic matter andwater-stable aggregation in soils. J. Soil Sci., 33: 141-163. Vågen, T.G., Lal, R. andSingh, B.R., 2005. Soil

Fraction

  ** 0.653** 0.759*** 0.611** 0.760*** 0.632** * p < 0.05; ** p < 0.01; *** p < 0.001.

Figure 1 .Figure 2 .Figure 3 .

 123 Figure 1. Relationships between clay plus fine silts (< 20 µm), citrate-bicarbonate-dithioniteextractable Al (Al CBD ), oxalate-extractable Al (Al OX ), on the one hand, and: 1a, soil content in water-stable macroaggregates (> 200 µm); 1b, total soil C content (Ct); and 1c, C amount in the dispersed fraction < 20 µm (Cgo, Ben, Goi, SPau and Par represent samples from Congo, Benin, Goiás, São Paulo and Paraná, respectively).

Figure 4 .

 4 Figure 4. Principal component analysis (PCA) with seven active variables, in bold, and six supplementary variables, in italics (C>200, C20-200 and C<20 represent C amount in the dispersed fractions > 200, 20-200 and < 20 µm, respectively).

Table 1 .

 1 carbon sequestration in sub-Saharan Africa: a review. Land Degrad. Dev., 16: 53-71. Presentation of the studied sites, soils, and plots.

	Country	Latitude,	Mean annual	Soil type	a	Texture		Clay mineralogy	Land use	No
	(state),	longitude	rainfall and	(and parent material)
	city		temperature				K	H	Go	Gi
	Congo-	04°00'S,	1100 mm	Typic Haplorthox	Clayey	+++	0	++	0	Savanna	1
	Brazzaville,	13°30'E	25°C	Orthic Ferralsol						Cassava	2
	Loudima		(schisto-calcareous sediment)						Natural fallow	3
	Congo-	04°10'S,	1400 mm	Typic Haplorthox	Clayey	+++	0	++	0	Savanna	4
	Brazzaville,	13°30'E	25°C	Orthic Ferralsol						Cassava	5
	Mantsoumba		(schisto-calcareous sediment)
	Benin,	06°24'N,	1200 mm	Typic Tropudult	Sandy	+++	++	++	0	Maize, no input	6
	Cotonou	02°20'E	27°C	Dystric Nitisol	clay loam					Fertilized maize	7
				(sandy clay sediment)						Maize-legume intercrop	8
											Rotation of maize & maize-legume intercrop	9
	Brazil	16°S,	1500 mm	Typic Haplustox	Clayey	+++	++	++	++	Bush savanna	10
	(Goiás),	49°30'W	23°C	Orthic Ferralsol						Maize/bean rotation	11
	Goiânia		(detritic-lateritic sediment)						Bracharia pasture	12
	Brazil	21°22'S,	1600 mm	Typic Hapludox	Clayey	+++	++	0	++	Sugarcane (residue burning)	13
	(São Paulo),	48°03'W	23°C	Orthic Ferralsol
	Pradópolis			(basalt)
	Brazil	21°36'S,	1500 mm	Typic Hapludult	Sandy	+++	++	++	0	Sugarcane (residue burning)	14
	(São Paulo),	48°22'W	23°C	Orthic Acrisol	clay loam
	Matão			(sandstone)
	Brazil	21°12'S,	1500 mm	Typic Quartzipsamment	Sandy	+++	+	+	+	Sugarcane (residue burning)	15
	(São Paulo),	47°35'W	23°C	Ferralic Arenosol
	Serrana			(sandstone)
	Brazil	23°23'S,	1600 mm	Typic Haplorthox	Clayey	+++	++	++	++	Forest	16
	(Paraná),	51°11'W	21°C	Rhodic Ferralsol						Oat	17
	Londrina			(basalt)							Citrus orchard with legume intercropping	18
	a Soil Survey Staff (1999) and FAO-ISRIC-ISSS (1998).
	K: kaolinite; H: hematite; Go: goethite; Gi: gibbsite.	+++: dominant; ++: present; +: traces; 0: absent.

Table 2 .

 2 Size distributions of aggregate and dispersed fractions, C contents of whole soil and dispersed fractions, and whole soil pH (in water) and contents in citrate-bicarbonate-dithionite-and oxalate-extractable iron and aluminium (for No, see Table1).

	No		Mass of			Mass of			Total soil	C concentration of		C amount in	pH	Fe CBD Al CBD Fe OX Al OX
		dispersed fractions	aggregate fractions	a	C content	dispersed fractions	dispersed fractions	(H 2 O)
			(g kg	-1 soil)			(g kg	-1 soil)			(g C kg	-1 soil)	(g C kg	-1 fraction)	(g C kg	-1 soil)	(g kg	-1 soil)
		> 200 20-200 < 20	> 200 20-200	< 20			> 200 20-200 < 20	> 200 20-200 < 20
		µm	µm	µm	µm	µm	µm			µm	µm	µm	µm	µm	µm
	1	38	104	857	669	238	55	35.0	76.2	32.1	27.6	2.9	3.3	23.7	5.0	30.4 6.4	1.3	2.1
	2	40	188	775	571	354	48	21.8	34.7	11.8	21.5	1.4	2.2	16.7	6.0	35.6 6.8	1.4	2.2
	3	31	201	760	621	309	41	36.4	69.0	27.8	36.6	2.1	5.6	27.8	5.5	32.0 7.6	1.5	3.3
	4	93	260	632	746	154	7	42.5	72.0	39.5	35.5	6.7	10.3	22.4	5.0	33.7 6.9	2.9	5.8
	5	32	179	771	585	366	17	18.8	51.0	13.5	18.6	1.6	2.4	14.4	4.4	nd	nd	1.2	1.9
	6	524	202	226	164	207	18	5.1	1.4	4.5	11.1	0.7	0.9	2.9	5.1	9.0	0.7	0.5	0.4
	7	625	216	145	210	132	13	6.5	1.3	6.9	22.8	0.8	1.5	3.3	5.2	7.7	0.7	0.4	0.4
	8	611	202	175	238	97	11	11.4	2.1	11.4	30.3	1.3	2.3	5.3	5.0	8.6	0.7	0.4	0.5
	9	590	208	192	246	148	17	8.5	1.5	7.7	21.4	0.9	1.6	4.1	5.2	8.4	1.0	0.4	0.4
	10	81	449	469	615	313	2	22.6	21.3	8.0	34.0	1.7	3.6	15.9	5.5	35.0 4.8	2.2	nd
	11	47	383	571	541	382	10	21.4	25.3	3.9	29.9	1.2	1.5	17.1	5.2	38.9 4.7	1.9	4.9
	12	67	456	477	623	276	8	22.0	22.8	3.7	34.9	1.5	1.7	16.6	5.9	29.9 5.4	1.9	3.9
	13	78	325	597	661	246	20	20.7	11.1	16.9	21.1	0.9	5.5	12.6	nd	98.8 6.0	1.7	3.1
	14	503	300	192	329	143	12	7.4	1.4	4.8	27.2	0.7	1.5	5.2	nd	15.1 2.5	0.5	0.7
	15	411	505	83	298	320	15	7.0	1.6	4.4	49.2	0.7	2.2	4.1	nd	11.2 1.5	1.0	0.6
	16	47	146	766	752	189	13	30.8	118.1	35.3	22.6	2.6	5.2	17.3	6.8	87.1 5.1	5.3	5.4
	17	39	101	868	551	388	23	17.8	71.9	21.7	14.9	0.5	2.2	12.9	5.7	70.6 4.5	5.3	2.7
	18	29	122	834	639	309	30	23.0	87.4	18.9	18.9	1.1	2.3	15.7	5.9	72.0 5.1	5.2	2.8
	nd: not determined.
	a aggregate fraction > 200 µm did not include coarse sands; aggregate fractions 20-200 and < 20 µm included primary particles of the same size.

Table 3 .

 3 Main correlations between the studied variables (C concentration in g kg -1 fraction, C amount and other variables in g kg -1 soil < 2 mm).

	Dispersed fraction mass	Macroag-	Ct	Fraction C concentration	Fraction C amount	Fe CBD	Al CBD	Fe OX
	> 200	20-200	< 20	gregates		> 200	20-200	< 20	> 200	20-200	< 20
	µm	µm	µm			µm	µm	µm	µm	µm	µm

Acknowledgements

The authors thank Vincent Eschenbrenner for his help regarding the clay mineralogy of the Brazilian samples, and two anonymous referees for their helpful comments.