Silvana Guitarra
email: sguitarra@usfq.edu.ec

Laurent Raymond

Lionel Trojman

Stochastic multiscale model for HfO 2 -based resistive random access memories with 1T1R configuration

Keywords: Resistive random access memory (ReRAM), HfO 2 -based memory, stochastic model, 1T1R configuration, intrinsic parameters

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Stochastic multiscale model for HfO2-based resistive random access memories with 1T1R configuration

Introduction

Resistive Random Access Memories (ReRAM) are potential candidates to be part of the next generation of non-volatile memory technology due to their promising characteristics: good cycling endurance, high speed, short switching time, low voltage operation and specially, its compatibility with CMOS industrial processes [START_REF] Chen | Endurance/retention trade-off on HfO 2 /Metal 1T1R bipolar RRAM[END_REF][START_REF] Lee | Evidence and solution of over-RESET problem for HfO x based resistive memory with sub-ns switching speed and high endurance[END_REF][START_REF] Ielmini | Resistive switching memories based on metal oxides: mechanisms, reliability and scaling[END_REF][START_REF] Wong | Metal-oxide RRAM[END_REF]. However, alike the conventional memories, the electrical response of ReRAM devices shows a stochastic behavior that can be enhanced by the type of material [START_REF] Balatti | Set variability and failure induced by complementary switching in bipolar RRAM[END_REF][START_REF] Ambrogio | Understanding switching variability and random telegraph noise in resistive RAM[END_REF]. This characteristic produces variability and makes it difficult to build an adequate predictive model.

ReRAM devices are simple MIM structure, two metallic electrodes sandwiching a transition oxide. Its memory concept is based on the resistive switching of the oxide layer by applying electrical stress. Two states, high resistive state (HRS) and low resistive state (LRS), are then possible. The transition from HRS to LRS is called SET, while the transition from LRS to HRS is called RESET. When opposite bias polarity is required for the resistive switching, the ReRAM is called bipolar.

In this work, we developed two stochastic models to understand and reliably predict the resistive switching of bipolar ReRAM devices. To do it, we examined the electrical IV curves of ReRAM cells of nine different areas. Among all possible insulator materials, we worked with Hafnium oxide (HfO 2 ) since it is a well-known metal-oxide material employed in the semiconductor industry [START_REF] Walczyk | Impact of temperature on the resistive switching behavior of embedded HfO 2 -based RRAM devices[END_REF][START_REF] Yu | Conduction mechanism of TiN/HfO x /Pt resistive switching memory: A trap-assisted-tunneling model[END_REF][START_REF] Privitera | Conductive filament structure in HfO 2 resistive switching memory devices[END_REF]. HfO 2 -based ReRAM devices have a filament conduction that is activated just after the electroforming process. During this step, electromigration of oxygen vacancies creates a conductive filament (CF) inside the insulator that enables electrical conduction between the two metallic electrodes [START_REF] Waser | Redox-based resistive switching memories -nanoionic mechanisms, prospects, and challenges[END_REF]. Therefore, the resistive switching is possible thanks to the local formation (set) and rupture (reset) of these filaments, driven by the applied electric field.

In the literature, models with different approaches and degrees of accuracy have been developed to simulate the resistive switching of specific ReRAM devices [START_REF] Jiang | A compact model for metal-oxide resistive random access memory with experiment verification[END_REF][START_REF] Guan | A spice compact model of metal oxide resistive switching memory with variations[END_REF][START_REF] Bocquet | Robust compact model for bipolar oxide-based resistive switching memories[END_REF][START_REF] Noh | Development of a semiempirical compact model for DC/AC cell operation of HfO x -based ReRAMs[END_REF]. However, in this work we give an unified approach which 4. Finally, there is a discussion of results in Sec. 5 and the conclusions in Sec.6.

Electrical characterization

We work with HfO 2 -based ReRAM diveces with one-transistor one-resistor (1T1R) architecture (see Fig. 1). Their structure consist of TiN(30nm) \HfO 2 (5nm) \Hf(10nm) \TiN(30nm) stacks whose areas are: 55x55nm 2 , 65x65nm 2 , 75x75nm 2 , 85x85nm 2 , 105x105nm 2 , 135x135nm 2 , 1x1µm 2 , 3x3µm 2 and 5x5µm 2 . For this, the samples will be divided into two groups: nm-size samples and µm size samples.

All devices were electroformed using positive bias voltage with a compliance current of 5mA. The forming voltage was between 2V and 2.8V in nm-size samples and between 1V and 1.8V in µm-size. This difference could be attributed to the reduced number of intrinsic defects in fresh samples, especially in the smallest ones. Once the CF was formed inside the insulator, the current-voltage characteristics were measured under dc voltage sweep at room temperature. In both kind of samples, the electrical response has the typical bipolar resistive switching behavior with an asymmetric IV curve (see Fig. 2). This curves show the already known cycle to cycle variability [START_REF] Brivio | Formation and disruption of conductive filaments in a HfO 2 /TiN structure[END_REF], especially in nm-size samples. Further, small samples show higher resistance window (I ON /I OF F ) compared to big samples. This factor is essential to allow a high read margin between the two resistive states and to avoid fluctuations during operation [START_REF] Ambrogio | Noiseinduced resistance broadening in resistive switching memory-part ii: Array statistics[END_REF].

-2 -1 0 1 Voltage [ V ]
10 -5

10 -3

10 -1

10 1 10 3 Current [ µA ] V set V reset (a) 85x85nm 2 -2 -1 0 1 Voltage [ V ]
10 -5

10 -3

10 -1

10 1 10 3 Current [ µA ] V set V reset (b) 5x5µm 2

Switching parameters

From IV curves, we extracted five parameters to characterize the resistive switching. The first two are set and reset the transition voltages, V set and V reset , that are identified by the abrupt current jump. The other three parameters are related to the conduction mechanisms.

Although the electrical response of ReRAM devices is controlled by conduction processes happening simultaneously inside the CF and the insulator, the current-voltage characteristic can be related to a specific model. In the case of HfO 2 -based ReRAM, the quantum point contact model (QPC) [START_REF] Miranda | Model for the resistive switching effect in HfO 2 MIM structures based on the transmission properties of narrow constrictions[END_REF] is the best choice as already demonstrated by Procel et al. [START_REF] Prócel | Experimental evidence of the quantum point contact theory in the conduction mechanism of bipolar HfO 2 -based resistive random access memories[END_REF]. This model states that CF behaves as a quantum wire that allows conduction according to a potential barrier that limits the flow of electrons. In HRS the potential barrier is high and the current becomes a strongly nonlinear function of the applied voltage, while in LRS the potential barrier is below the electrons energy and the conduction is ohmic. In this work, for HRS the current-voltage dependency has been defined by a hyperbolic sine function that includes the IV response under positive and negative voltages. This dependency is given by:

I = I o sinh(αV ) (1)
where I o and α are two parameters to be determined. In LRS, the IV relationship is ohmic and described by:

I = GV (2)
where G is the CF conductance.

All the parameters described above, V set , V reset , G, I o and α, were extracted independently from 150 curves for each sample. In all cases, there is a wide distribution of data that were submitted to a statistical analysis in order to determine their characteristic values and their variability. The proposed model works with the stochastic behavior of the ReRAM, so it is important to include this feature in the assessment of the electrical parameters.

In all samples, V set and V reset distributions can be described as unimodal,

where the mean value is the most suitable measure to describe each group.

Normality tests were used to determine if data set in both cases is normally distributed (see insets Fig. 3a and3b). Comparing all samples, there are two mean values of set voltage, V set =0.673±0.047V for nm-size samples and V set =0.480±0.007V for µm-size, while there is only one mean value of reset voltage V reset =-1.151±0.114 V (Fig. 3a and3b).

To characterize the conduction mechanism, we determined the conductance As one can see in Fig. 3c, the characteristic value for nm-size samples is G=176±8.8

Area [m 2 ] -1.8 -1.6 -1.4 -1.2 -1.0 -0.8 -0.6 -0.4 Vreset [V] nm 2 µm 2 -1.5 -1.0 -0.5 Vset [V] Freq. 85x85nm 2 (b) Vreset 0.5 1.0 1.5 2.0 2.5 3.0 Area [m 2 ] ×10 -14 1 2 3 4 5 G [µS] ×10 2 G = 176 µS nm 2 10 -11 0.5 1.0 1.5 ×10 3 µm 2 G = 960µS (c) G 10 -15 10 -14 Area [m 2 ] 0 1 2 3 4 Io [A] ×10 -5 Io= 2.42x10 -23 A -1.2 10 -13 10 -12 10 -11 Area [m 2 ] 1 2 3 Io [A] ×10 -4 Io= 3x10 -4 A 0.03 (d) Io 10 -15 10 -14 10 -13 Area [m 2 ] 1.0 1.5 2.0 2.5 3.0 3.5 α [1/V] α=0.27log(A)+10.6 10 -12 10 -10 Area [m 2 ] 1.0 1.5 2.0 2.5 α [1/V] α=0.009log(A)+1.74 (e) α)
µS while in µm-size samples is G=960±36 µS. In HRS, by the fitting of the IV curves with Eq. 1, the values of I o and α were determined. The large distribution of data is an evidence of the system variability in this state. Further, I o and α 100 are strongly dependent on the area (see Fig. 3d and3e).

Intrinsic switching parameters

It is important to note that the conventional characterization of ReRAM devices relies on the use of one transistor (1T) to control current and protect devices from hard dielectric breakdown (see Fig. 1). This element helps to cell

The current controlled by the transistor is limited by an external parasitic effect that can be represented by a series resistance R s [START_REF] Fantini | Intrinsic switching behavior in HfO 2 RRAM by fast electrical measurements on novel 2R test structures[END_REF]. Thus, to find the intrinsic switching characteristics of the ReRAM devices, the voltage drop over this R s has been subtracted from IV curves [START_REF] Shirasawa | Kinetic monte carlo simulation for switching probability of reram[END_REF]. We identified this contribution by the small linear relationship after set transition in the experimental IV curves (in black) in Fig. 4, where intrinsic IV response (in red) has also been included. As expected, R s contribution is more important in small samples. Again, we extract the intrinsic parameters to describe the resistive switching:

V set , V reset , G, I o and α, from the intrinsic IV curves. We found that V set and V reset trigger to a constant threshold voltage independently of the sample area (see Fig. 5a and5b), as it has been previously reported by Fantini [START_REF] Fantini | Intrinsic switching behavior in HfO 2 RRAM by fast electrical measurements on novel 2R test structures[END_REF]. I o and α were extracted by the fitting of the intrinsic curves with Eq. 1. Both of them are strongly dependent on the area device (see Fig. 5d and5e). Finally, to determine intrinsic conductance (G int ), we extract series conductance (G s = 1 Rs ) from the total conductance G determined before (Fig. 3c), by applying eq. 3:

1 G int = 1 G - 1 G s (3)
There is one characteristic value for each kind of sample (see Fig. 5c). In Fig 5,

we can compare the intrinsic parameters and those reported in section 2.1. It allow us to appreciate the real characteristics of the dielectric.

Stochastic model

This paper proposes a model for the resistive switching of bipolar ReRAM device. This model works with the narrowest region of the CF, that in the following will be called active region. As shown in Fig. 6, this region is represented by a parallel network of chains, each one composes of three electrical elements.

Those elements connected with the region of the filament that does not undergo any significant change during switching are always low resistance (LR), meanwhile, the middle element acts as a breaker that has two resistance states, low (LR) and high resistance (HR). The electric field mainly affects the active region and cause the changing of breaker state. Previously in the literature, a local geometrical constriction has been proposed in the hour glass model [START_REF] Degraeve | Hourglass concept for RRAM: A dynamic and statistical device model[END_REF] or in the quantum point contact model [START_REF] Prócel | Experimental evidence of the quantum point contact theory in the conduction mechanism of bipolar HfO 2 -based resistive random access memories[END_REF][START_REF] Miranda | Model for the resistive switching effect in HfO 2 MIM structures based on the transmission properties of narrow constrictions[END_REF]. Experimentally, a truncated cone shape conductive filament has been reported [START_REF] Celano | Three-dimensional observation of the conductive filament in nanoscaled resistive memory devices[END_REF][START_REF] Privitera | Microscopy study of the conductive filament in HfO 2 resistive switching memory devices[END_REF].

In IV curves (Fig. 2), the resistive switching occurs around one threshold voltage, V set or V reset , after some intermediate jumps. The model can simulate this progressive switching with several vertical chains in the active region. Thus, set and reset transitions are the result of the gradual activation, or deactivation, of the breakers in the active region. Nevertheless, only a stochastic process could explain the cycle to cycle variability. This characteristic has been included in our model by imposing a smooth switching probability, P s , to control the change 145 of breaker state: P set for set process and P reset for reset process. A suitable mathematical expression for P s is a sigmoid function [START_REF] Kyurkchiev | Sigmoid Functions Some Approximation and Modelling Aspects: Some Moduli in Programming Environment MATHE-MATICA[END_REF], given by eq. 4:

P S = 1 2 {1 + tanh [C s (V link -V ref )]} (4)
where V ref and C s are two parameters that need to be determined for set and reset processes independently. V ref is V set or V reset , according to the process, and their values can be determined from experimental data. C s is the slope 150 of the probability function and changes the direction and the steepness of the function. For set process the slope will be positive and open to the right, and for reset, it will be negative and open to the left (see Fig. 6b). Greater values of |C s | implying a very narrow transition, while the smaller ones, broader the transition. P s also depends on the voltage drop along the breaker, V link , that can be determined by V link = V i -V j , where i and j are the nodes of the chains (see Fig. 6a). Therefore, for each external voltage, the values of V i and current thought the system (I) are computed by solving Kirchhoff's equation at each node: I i = I i-j + I i-m = 0, where, I i-j and I i-m must be written according to the state of elements inside the chain. Thus, if the breaker is HR, the current at node i is the sum of ohmic and tunneling conduction (eq. 5), while if the breaker is LR, it is the sum of two ohmic contributions (eq. 6). This agrees with the dominant conduction mechanisms determined in section 2 for the HfO 2 -based ReRAM.

I i = σ im (V i -V m ) + I o sinh(α(V i -V j )) (5)
I i = σ im (V i -V m ) + σ ij (V i -V j )) (6)
In this N-chain model with two conduction mechanisms, Kirchhoff's equations result in a system of nonlinear equations that are solved by the Newton-Raphson method.

Set process is simulated following the flowchart presented in Fig. 7a. Initially, all breakers are HR and the external voltage (V ext ) is applied. Then, the current (I) through the chains and the node voltages (V i ) are computed by solving the system of equations given by Eq. 5 and 6. After, the value of I is compared with the compliance current (I comp ). Only if the current is smaller than I comp , the process can continue, such as occurs in real systems to prevent dielectric breakdown of the device. Then, the drop voltage across the breaker (V link ) and set probability (P set ) are computed. Afterward (P set ) is compared with a computer-generated random number p, and only if P set is bigger than p, the breaker state changes to LR, otherwise the state remains as HR and V ext is increased. Once all elements in the active region are LR, the entire ReRAM is in LRS. For reset process, initially, all breakers are LR and negative bias is applied over the system. The computer simulation follows the steps depicted in the flowchart in Fig. 7b.

Simulation results

First, we compared experimental data with simulation results. There is an example for one sample of each kind in Fig. 8. Several cycles have been included, in light blue experimental curves, with the mean value in blue, and in grey simulated curves with the mean value in black. For model calibration, seven parameters are required: V set , V reset , G, I o , α, C set and C reset . They have been obtained independently for both kind of samples from the IV experimental curves (section 2). It must be noted that although both kind of samples follow similar behavior, the model was calibrated independently. As one can see inf Fig. 3, there are three parameters that are appreciably different: the conductance G, the current I o and the factor α. They all characterize the CF conditions in LRS and HRS, thus one could suggest that even if the conduction is localized in the CF, it has different size between both kinds of samples. As expected, the model can reproduce the gradual switching. Nevertheless, the flexibility of this model allows it to simulate an abrupt transition, like those observed in Cu/WOx/TiN ReRAM [START_REF] Masashi | Switching operation and degradation of resistive random access memory composed of tungsten oxide and copper investigated using in-situ tem[END_REF], if it works with one chain in the active region. Both kinds of switching, gradual or abrupt, have been reported in the literature and they are closely related to the initial CF resistance [START_REF] Cüppers | Exploiting the switching dynamics of hfo2-based reram devices for reliable analog memristive behavior[END_REF].

1T1R Model

Most of the models proposed in the literature for resistive switching of ReRAM devices do not consider the electrical response of the series resistance R s , associated with the 1T1R configuration used for measurement [START_REF] Bocquet | Robust compact model for bipolar oxide-based resistive switching memories[END_REF][START_REF] Miranda | Model for the resistive switching effect in HfO 2 MIM structures based on the transmission properties of narrow constrictions[END_REF]. Here, the model proposed in section 3 has been modified to include the series resistance (R s ). The schema of this 1T1R model is presented in Fig. 9, where there is a new node corresponding to the connection with series element, of conductance G s (G s =1/R s ). Such as in the previous case, Kirchhoff's equations at each node must to be solved according with the state of the breaker: Ohmic or TAT conduction, given by eq. 5 and 6. This model has been implemented in a Python-based script, and calibrated with data of Table 1 that summarize all intrinsic values. The values were devided in two groups according with

Discussion

In this work, we analyze the resistive switching of ReRAM devices with only five parameters that can be extracted directly by experimental curves. Further, in order to address the intrinsic properties of the dielectric, we extracted the the signal of the transistor used in 1T1R configuration. We found that intrinsic V set and V reset are dependent on the dielectric material instead of the samples size (Fig. 5b and5b) while intrinsic G, I o and α (see Fig. 5c, 5d and 5e) are dependent on the device area. This behavior could be related with the size of the CF region where the resistive switching takes place.

The variability of IV curves (Fig. 2 and4) and, therefore, the variability of the switching parameters, is a characteristic of ReRAM devices attributed to the stochastic nature of the switching process. These feature is more evident in HRS, as has been proven by the statistical analysis of I o and α. This result could be interpreted by a higher distribution of energy barriers for defect migration that controls the reset process [START_REF] Ambrogio | Understanding switching variability and random telegraph noise in resistive RAM[END_REF]. According to QPC model, the conduction during HRS includes multiple nonlinear and closely coupled parameters, such as the energy of the electrons, the potential barrier height, the shape of the barrier, a series resistance external, among others [START_REF] Prócel | Experimental evidence of the quantum point contact theory in the conduction mechanism of bipolar HfO 2 -based resistive random access memories[END_REF][START_REF] Miranda | Model for the resistive switching effect in HfO 2 MIM structures based on the transmission properties of narrow constrictions[END_REF]. In this work, we have taken the QPC arguments but we have extracted only few electrical parameters (G, I 0 and α) to reproduce the conduction mechanism of HfO 2 ReRAMs due to the macroscopic evidence. In simulation, the model works properly with devices of two different scales, nm 2 -size and µm 2 -size, although the parameters used for calibration have been divided in two groups. In this sense, the impact of the area on the resistive properties has been evaluate in HfO 2 -based ReRAM devices.

Regarding to the model, there is a direct relationship between ReRAM devices and the active region. Our samples have a bilayer structure HfO 2 /Hf that allows the formation of a sub-stoichiometric region at this interface that acts as an oxygen reservoir for the resistive switching [START_REF] Govoreanu | 10x10nm 2 Hf/HfO x crossbar resistive RAM with excellent performance, reliability and low-energy operation[END_REF]. According to the conductive filament mechanism, the CF could be localized inside the dielectric but composed of different paths of oxygen vacancies. These paths are reconnected or disconnected due to the effect of the electric field and provokes set and reset transition due to the movement of oxygen vacancies. This fact has been experimentally confirmed in the HfO 2 /TiN structure [START_REF] Brivio | Formation and disruption of conductive filaments in a HfO 2 /TiN structure[END_REF] and in the NiO-based system [START_REF] Sun-Young | Resistive switching behaviors of nio films with controlled number of conducting filaments[END_REF]. The interpretation of the resistive switching obtained from this model is as follows: if a positive voltage is applied and reaches the V set , the changing to LRS occurs because of the random connection of some paths due to oxidation/reduction processes of oxygen anions and vacancies [START_REF] Bersuker | Metal oxide resistive memory switching mechanism based on conductive filament properties[END_REF][START_REF] Long | A model for the set statistics of RRAM inspired in the percolation model of oxide breakdown[END_REF]. This transition is produced in the model by the activation of all breakers. Contrary, when the negative voltage is applied and reaches the V reset , the rupture of the filament is caused by the filling up of the oxygen vacancies due to the drift of oxygen ions or the diffusion of oxygen ions caused by the concentration gradient of oxygen [START_REF] Long | Voltage and power-controlled regimes in the progressive unipolar reset transition of HfO x -based RRAM[END_REF][START_REF] Russo | Self-accelerated thermal dissolution model for reset programming in unipolar resistive-switching memory (RRAM) devices[END_REF][START_REF] Yu | A phenomenological model for the reset mechanism of metal oxide rram[END_REF]]. In the model, it means the deactivation of the breakers and the transition to HRS.

In this report we propose a new modeling approach for resistive switching that incorporate the electrical signal of the measurement element (1T). This 1T1R model is consistent with the QPC model in the sense that it works with the narrow zone of the filament and also includes the series resistance external to the constriction [START_REF] Prócel | Experimental evidence of the quantum point contact theory in the conduction mechanism of bipolar HfO 2 -based resistive random access memories[END_REF][START_REF] Miranda | Model for the resistive switching effect in HfO 2 MIM structures based on the transmission properties of narrow constrictions[END_REF][START_REF] Long | Quantum-size effects in hafnium-oxide resistive switching[END_REF]. With this change, in the modeling, we work directly with the intrinsic characteristics of ReRAM, and improve the simulation results.

Both models, the stochastic model and the 1T1R model, can simulate the variability reported in most of ReRAM devices. To do it, models work with a switching probability, P s , that reproduces the variability in a natural way since the algorithm includes the stochastic behavior of the process. Although a switching probability for ReRAM commutation has been proposed before in Kinetic Monte Carlo simulation [START_REF] Shirasawa | Kinetic monte carlo simulation for switching probability of reram[END_REF], working with P s at the level of circuit simulation is a new proposal. Furthermore, the calibration of this function can be done directly from the experimental evidence, such as in this work. This technique could be easily applied to other electronic devices that have random electrical behavior.

Finally, working with a switching probability to control the change of state and including the signal of the measurement element are two new good proposals in the field of memory studies that allow improving simulation results while generating variability.

Conclusion

We have developed two stochastic models for the resistive switching of ReRAM devices, that can simulate the IV response of bipolar cells. One of the models includes the electrical signal of the measurement element which is a new approach in the field of ReRAM simulation.

In simulation, both models work properly with devices of two different scales, nm 2 and µm 2 . Although the parameters used for calibration has been divided in two groups, working with few parameter allow a quantitative description of resistive switching. Both models are able to reproduce the electrical variability observed in all ReRAM devices by using a switching probability to control the change of system state.

Due to the versatility of the proposed models, they could be powerful tool for simulation and studying of other tochastic devices, such as the case of the CBRAM.

Figure 1 :

 1 Figure 1: 1T1R ReRAM memory array

Figure 2 :

 2 Figure 2: Current-voltage characteristics of HfO 2 -based ReRAM devices of 85x85nm 2 and 5x5µm 2 , during one experiment of ten cycles.

Figure 3 :

 3 Figure 3: (a) Vset and (b) Vreset as a function of the device area. Inset: Statistical distribution of Vset and (b) Vreset for the sample of 85x85nm 2 . In LRS the dominant conduction mechanism is ohmic, given by I = GV , where G is the conductance. In HRS the conduction mechanism is tunneling, that can be studied by a relationship I = Io sinh(αV ). The values of (a) G, (b) Io and (c) α as a function of area device are presented. Insets: response of µm-size samples

Figure 4 :

 4 Figure 4: Experimental IV curves in grey, with mean value in black, along with the the intrinsic electrical response in yellow, with mean value in red, for the HfO 2 -based ReRAM.

10 Area [m 2 ]Figure 5 :

 1025 Figure 5: Intrinsic parameters of HfO 2 -based ReRAM as a function of the area.

  (a) Active region (b) Set and reset probability

Figure 6 :

 6 Figure 6: (a) Schematic representation of the active region composed of N-chains, each one with of three electrical elements that are low resistance (LR) or high resistance (HR), and (b) Set and reset probability.

Figure 7 :

 7 Figure 7: Flowchart used in simulation for (a)set and (b)reset processes.

Figure 8 :

 8 Figure 8: Model and experimental current-voltage response of HfO 2 ReRAM devices. Grey lines correspond to the model with mean value in black, while light blue lines correspond to experimental data with the mean value in blue.

I 0

 0 [µA] I o = 3.07x10 -16 A -0.73 I o = 3x10 -4 A 0.03 α [1/V] α = 0.038 log(A) + 3.56 α = 0.038 log(A) + 3.56 sample-size.

Figure 9 :

 9 Figure 9: Schematic representation of the 1T1R Model composed of N-Chains an the series resistance Rs.

Figure 10 :

 10 Figure 10: Model and experimental current-voltage response of HfO 2 ReRAM devices. Grey lines correspond to the model and light blue lines correspond to experimental curves.

Table 1 :

 1 Intrinsic parameters of HfO 2 -based ReRAM.

	Parameter	nm-size samples	µm-size samples
	V set [V]	0.337	0.337
	V reset [V]	-0.226	-0.226
	R s [Ω]	4184.40	816.49
	G [µS]	694.11	4363.79

performance and reliability characterization, but it could also generate their own electrical signal which avoid the real characterization of the ReRAM element.

value in blue. A good relationship between the experimental and the simulated curves is found in all cases.Comparing Fig.8and Fig.10, the incorporation of R s in the model has improved the simulation, especially in the HRS.


Jérôme Cortet
email: jerome.cortet@univ-montp3.fr

Dominique Gillon

Richard Joffre

Jean-Marc Ourcival

Nicole Poinsot-Balaguer

Effects of pesticides on organic matter recycling and microarthropods in a maize field: use and discussion of the litterbag methodology

Keywords: Microarthropods, Litterbags, Maize, Nitrogen, Spectrophotometry, Pesticides

The effects of two herbicides (atrazine and alachlore) and two insecticides (fipronil and carbofuran) on organic matter decomposition and soil mesofauna were evaluated in a maize field under normal agriculture conditions. Soil mesofauna were studied using the litterbag method. Near infrared reflectance spectrophotometry was used to study the effects on decomposition parameters (litter mass and nitrogen dynamic). The effects on soil microarthropods varied depending on both taxon and pesticide, with fipronil having a particularly strong effect. Differences were also observed between treatments for organic matter decomposition parameters, especially with the use of alachlore. Therefore, the analysis of microarthropods and the decomposition parameters provides complementary information on the effects of these chemical treatments.

Introduction

The effects of chemicals, particularly pesticides, on microarthropods have been well studied. However, the majority of the previous studies have been laboratory based.

Of those experiments carried out in the field, few have been under real agricultural use conditions (i.e., normal pesticide doses and other agricultural practices). Further, few have focused on the relation between microarthropod effects and the dysfunction of soil biological processes (see reviews in [START_REF] Cortet | The use of invertebrate soil fauna in monitoring pollutant effects[END_REF] and [START_REF] Hopkin | Biology of the Springtails (Insecta: Collembola)[END_REF]).

In the present study, we use and evaluate the litterbag methodology [START_REF] Crossley | A litterbag method for the study of microarthropods inhabiting leaf litter[END_REF], in combination with near infrared reflectance spectrometry analysis [START_REF] Joffre | The use of near Infrared reflectance spectroscopy in litter decomposition studies[END_REF], to analyse the effects of different pesticides on decomposition parameters (litter mass loss and nitrogen dynamic) in relation to the colonisation of the litterbags by microarthropods.

Materials and methods

Study site and field experiments

The site is located on an experimental farm in La Côte Saint André (Department of Isère, Rhône-Alpes region, France). Experimentation was carried out in a 1600 m 2 field of cultivated maize (Zea mays L.) [START_REF] Bally | Effet de l'application de produits phytosanitaires sur le fonctionnement biologique des sols : mise en évidence d'indicateurs biologiques permettant d'évaluer leur impact en zones de grandes cultures[END_REF][START_REF] Cortet | Impact de produits phytopharmaceutiques sur les microarthropodes du sol en culture de maïs irrigué : approche fonctionnelle par la méthode des sacs de litière[END_REF]. Maize had been cultivated in this field for 8 years, with the exception of 1995 when tobacco was introduced. The soil is a typical hapludalf (Orthic luvisol). The two-leaf step was observed on 16 May, and the six-maize-leaf step was reached on 6 June 1997. Nitrogen (240 kg ha -1 ), phosphorus (45 kg ha -1 ) and potassium (300 kg ha -1 ) were added to the field. The maize was harvested between 20 and 24 October 1997, and was regularly irrigated during the summer.

The field was divided into two sections. The first section was used for the 'herbicide test', and the second for the 'insecticide test'. Each section was divided into 12 elementary plots in a randomised block design. Each plot measured 12.8*20 m, and contained 16 maize rows.

Atrazine (chloro-2 éthylamino-4 isopropylamino-6 triazine-1,3,5) and alachlore [chloro-2N-(diethyl-2,6 phenyl) N-methoxymethyl acetamide] were compared on the herbicide section. Each herbicide was tested on four plots. The remaining four plots were used as a control. No insecticides and fungicides were used in the herbicide area. However, as the testing area was too big to eliminate arable weed flora by hand, another herbicide, pyridate [0-(6chloro-3 phenyl-4-pyridazinyl) carbothiolate n-octyl], was used. This was sprayed all over the herbicide section, including the control plots. Atrazine (1 kg ha -1 ) and alachlore (2.4 kg ha -1 ) were sprayed after sowing and before the appearance of the first maize leaves. Pyridate (0.9 kg ha -1 ) was sprayed at the six-maize-leaf step. These are the normal recommended concentrations in agriculture [START_REF]Association de Coordination Technique Agricole, Index Phytosanitaire[END_REF].

The insecticide section was used to test carbofuran (N-methylcarbamate de dimethyl-2,2 dihydro-2,3 benzofurannyle-7) and fipronil [5-amino-1-(2,6 dichlorox,x,x,-trifluro-p-tolyl)-4-trifluoromethylsulfinyl-pyrazole-3-carbonitrile]. Each insecticide was tested on four plots. Carbofuran (0.6 kg ha -1 ) was added to the soil in microgranule form just before sowing. Fipronil (0.2 kg ha -1 ) was sprayed on the topsoil before sowing and then added to the soil by harrowing. The harrowing was carried out on all the insecticide sections, including the four control plots. The entire insecticide section was also sprayed with two herbicides: atrazine (1 kg ha -1 ) and dimethanamide [1.44 kg ha -1 ; chloro-N (1-methyl-2-methoxyethyl)-N-(2,4dimethyl-thien-3 yl) acétamide].

Field sampling and laboratory procedures

The litterbag method was used [START_REF] Crossley | A litterbag method for the study of microarthropods inhabiting leaf litter[END_REF]. Four and a half grams of uncontaminated dried maize leaves were introduced in 12*12 cm nylon bags. The mesh of each bag was 4 mm. Thirty bags were placed on the topsoil at the centre of each plot, in the seventh and eighth rows (15 bags in each row, in the middle of the row, with a gap of 30 cm between each bag). The bags were introduced immediately following sowing, onto bare soil. The bags were then sprayed with the same doses of pesticides as the soil, except for carbofuran plots. This insecticide was introduced directly into the soil and not on the topsoil, where the bags were placed. The bags of carbofuran plots were therefore not treated. Five bags per plot were sampled at different dates: 20 May (after 18 days), 18 June (47 days), 2 July (61 days), 12 August (102 days), 11 September (132 days) and 3 October (154 days). The samples were placed in plastic bags and taken directly to the laboratory.

Mesofauna was extracted from the litterbags using the Berlese method, for four of the sampling dates (respectively, 18, 61, 102 and 134 days). Five groups were counted and identified: Collembola, Oribatida, Gamasida, 'other mites' and 'other arthropods'.

Leaves from the bags were dried (24 h, 60 ºC) and sieved (0.5 mm) to eliminate soil particles and little stones. Following this, they were milled with a Cyclotec-1093 (1 mm mesh filter). The resulting samples were analysed using a near infrared spectrophotometer (NIRS system 6500). Each sample was illuminated by a monochromatic radiation source. For each sample, two reflectance measures were carried out at each 2 nm between 400 and 2500 nm (from visible to infrared). Reflectance (R) was transformed into absorbency (A), using the following equation:

A = log (1/R).
The spectra obtained (total of 720) were analysed using ISI software [START_REF] Shenk | Population definition, sample selection, and calibration procedures for near Infrared reflectance spectroscopy[END_REF]. Abnormal spectra ('outliers') were detected using first derivatives, and samples were eliminated as a result.

Following this, samples representative of the entire population of spectra were selected for chemical analyses (ISI software; [START_REF] Joffre | The use of near Infrared reflectance spectroscopy in litter decomposition studies[END_REF]). Initial maize samples were also analysed. The quantity of ash residue was calculated for 48 samples (550 ºC for 3 h), and nitrogen content for 49 samples (using the Kjeldahl method). Using the ash and nitrogen content obtained chemically as reference values, a calibration equation was calculated for each parameter (ash and N). These equations allowed ash and N content to be estimated for all the samples. To estimate the quality of the calibration equations, the determination coefficient (r 2 ), standard error of calibration (SEC) and standard error of cross validation (SECV) were calculated. For a mean ash content of 62.48%, r 2 , SEC and SECV were 0.98, 3.077 and 5.099, respectively. For a mean N content of 3.713%, they were 0.952, 0.351and 0.494, respectively. These coefficients were judged acceptable. For each sample, the percentage of remaining litter mass (LMR) was calculated using the ash content and litter dry weight, and the N concentration ([N]) was calculated from the estimated N and ash content.

For each section (herbicide and insecticide), and for each sampling month, the differences between treatments were compared, based on an ANOVA (Statview software) of the calculated parameters LMR and [N] and the microarthropod abundances. Microarthropod abundance was expressed as mean number of individuals per bag.

Results

Litter mass remaining

The results for the remaining litter mass show few significant differences between the treatments in the herbicide section during the experiment. However, in July (61 decomposition days), decomposition was faster in the alachlore plots in comparison to the atrazine and H-control plots.

In the insecticide section, differences were observed from early on in the experiment. A greater decomposition was seen in the fipronil and I-control plots in comparison to the carbofuran plots, after 18 decomposition days. In July (61 decomposition days) and October (154 decomposition days), however, the observed decomposition was significantly greater in the carbofuran plots than in the fipronil plots.

N concentration

In the herbicide section, significant differences were observed in the N concentrations of the litter. Concentrations of N were higher in the alachlore plots than in the atrazine plots in May (18 decomposition days) and July (61 decomposition days), and greater than the H-control plots in May, July and October (154 decomposition days). Few significant differences were observed in the insecticide section. A greater N concentration is seen in the carbofuran plots in comparison to the fipronil plots in September alone (132 decomposition days) (Table 1).

Microarthropod abundance

In the herbicide section, the only significant difference was observed for the Collembola group in October, after 154 decomposition days. At this point, a greater abundance was found in the plots than in the alachlore H-control and atrazine plots (Fig. 1).

In the insecticide section, greater differences between treatments were observed after 61 and 102 decomposition days, with higher abundancies in I-control and carbofuran compared to fipronil for Oribatida. This was also observed for the 'other arthropods' group, but only at 61 days. The taxon 'other mites' was also significantly more abundant in carbofuran plots than in fipronil plots after 102 days (Fig. 2).

Discussion

Herbicide section

In this section, maize leaves treated with alachlore-pyridate mixtures decomposed faster, and had higher N concentrations than in the H-control and atrazine plots. Therefore, at the end of the experiment, after 6 months of decomposition, significant differences were observed in N dynamics. These results could indicate a higher microbiological activity in alachlore plots. This may be explained by the use of herbicides by micro-organisms, as it is well known that some species can use herbicides as a source of energy [START_REF] Neher | Biological diversity in soils of agricultural and natural ecosystems[END_REF][START_REF] Tasli | Devenir de l'atrazine en culture de maïs : étude en plein champ site de la Côte Saint André, Isère, France et au laboratoire[END_REF]. This hypothesis is confirmed by a higher observed microbial biomass in the soil after four study months on the same plots [START_REF] Bally | Effet de l'application de produits phytosanitaires sur le fonctionnement biologique des sols : mise en évidence d'indicateurs biologiques permettant d'évaluer leur impact en zones de grandes cultures[END_REF]. No differences were observed between the atrazine and H-control plots. However, as atrazine was used on this field during the preceding cultivation seasons, selection processes may have acted on some fungi or bacteria.

It is difficult to relate the results of the decomposition parameters for the herbicide section to the results of the microarthropods fauna observed in the litterbags. Differences were observed between the alachlore plots and other plots, but only for the microphytophagous group of collembola after 154 days. However, this greater abundance of collembola may be as a result of an increase in microorganisms, which constitute their main food source. No differences between treatments were observed for earthworms in the soil [START_REF] Bally | Effet de l'application de produits phytosanitaires sur le fonctionnement biologique des sols : mise en évidence d'indicateurs biologiques permettant d'évaluer leur impact en zones de grandes cultures[END_REF].

Insecticide section

Two phases could be observed in the decomposition process. At the first sampling date (18 days), a reduced level of litter decomposition was observed in the carbofuran plots when compared to I-control and fipronil. This did not result from microbial activity, as no differences were observed in the N concentration dynamics. These differences may instead have been induced by a reduction in the activity of soil macrofauna rather than mesofauna: no differences were observed in the mesofauna at this sampling interval, but a less significant earthworm abundance was observed in the carbofuran plots during the experiment [START_REF] Bally | Effet de l'application de produits phytosanitaires sur le fonctionnement biologique des sols : mise en évidence d'indicateurs biologiques permettant d'évaluer leur impact en zones de grandes cultures[END_REF].

Differences between the fipronil and carbofuran plots were observed from July onwards. However, no significant differences were observed between the decomposition parameters of the carbofuran and I-control plots, or of the fipronil and I-control plots. In comparison with the I-control plot, the results show an increase in the decomposition observed in the carbofuran plot, and a slight decrease in the decomposition in the fipronil plot. The decrease in decomposition observed in the fipronil plots may be explained by the high toxicity for the microarthropods, especially for the most important and numerous oribatida group, after 61 and 102 decomposition days. The tendency towards an increase in decomposition in the carbofuran plots may result from the application method of the carbofuran, as it was introduced directly into the soil. The litter, which was not directly contaminated, may have acted as a refuge area for microarthropods and micro-organisms, causing an increase in the decomposition parameters [START_REF] Siedentop | A litterbag test for the assessment of side effects of pesticides on soil mesofauna[END_REF].

Methodology considerations

Our results show the potential of litterbags for pesticide assessment in the field based on functional parameters. This approach allows comparisons of the differences between treatments to be made. In addition, biological activity can be controlled by using different mesh sizes. For example, in our study the mesh size was 4 mm which allowed the action of microfauna, mesofauna and macrofauna, e.g. earthworms.

Further, by studying both microarthropods and functional parameters, we have obtained complementary information, which has increased the validity of the measurable responses.

The NIRS method has been shown to be well suited for the determination of ash and N content. The calibration method allowed us to reduce the number of chemical analyses required (only 51 samples were used for chemical analyses on a total of 720 initial samples). Many samples, therefore, can be analysed in a short time, at a high resolution. The cost is also reduced, as chemical analyses are more time consuming than NIRS analyses. Further, this method is non-destructive, and samples can be re-used for further analysis. As the spectra contains all the biochemical information, nothing is lost.

Fig. 1 .

 1 Fig.1. Mean abundance of microarthropods (number of individuals/litterbag) in the herbicide section for each treatment (atrazine, alachlore, H-control) and each sampling date (18, 61, 102, 154 days). Col, Collembola; Ori, Oribatida; Gam, Gamasida; Omi, other mites; Oar, other arthropods. Significant differences between treatments (ANOVA, P < 0.05) are noted on the concerned histograms.

Fig. 2 .

 2 Fig.2. Mean abundance of microarthropods (number of individuals/litterbag) in the insecticide section for each treatment (fipronil, carbofuran, I-control) and each sampling date (18, 61, 102, 154 days). Col, Collembola; Ori, Oribatida; Gam, Gamasida; Omi, other mites; Oar, other arthropods. Significant differences between treatments (ANOVA, P < 0.05) are noted on the relevant histograms.

Table 1

 1 Litter mass remaining and nitrogen concentrations in litter maize residues for the various treatments in the herbicide part and insecticide part and the various decomposition days. LMR, percentage of litter mass remaining; [N], nitrogen concentration; Atra, atrazine; ala, alachlore; Hco, control herbicide; fip, fipronil; carb, carbofuran; Ico, control insecticide. Results are expressed as mean values with standard deviations. * P < 0.05; ** P < 0.01

	18 days	47 days	61 days	102 days	132 days	154 days
	Herbicide part LMR atrazine LMR alachlore 64 ± 8 67 ± 9 LMR H-control 67 ± 5 ANOVA ns [N] atrazine 0.60 ± 0.097 [N] alachlore 0.67 ± 0.09 [N] H-control 0.59 ± 0.072 ANOVA ala > atra* ala > Hco**	6 1 ± 4 6 0 ± 5 6 0 ± 5 ns 0.81 ± 0.12 0.85 ± 0.1 0.85 ± 0.091 ns	5 1 ± 8 4 5 ± 8 5 1 ± 7 atra > ala** Hco > ala* 0.92 ± 0.1 1.02 ± 0.11 0.93 ± 0.092 ala > atra** ala>Hco**	3 6 ± 13 3 3 ± 9 3 9 ± 13 ns 1.11 ± 0.17 1.19 ± 0.32 1.20 ± 0.25 ns	19 ± 9 2 1 ± 9 23 ± 11 ns 1.14 ± 0.23 1.13 ± 0.3 1.27 ± 0.52 ns	2 0 ± 10 2 1 ± 12 18 ± 8 ns 1.02 ± 0.15 1.16 ± 0.3 1.0098 ± 0.21 ala > Hco*
	Insecticide part LMR fipronil LMR carbofuran 73 ± 10 69 ± 4 LMR I-control 68 ± 5 ANOVA carb > fip* carb > Ico* [N] fipronil 0.60 ± 0.068 [N] carbofuran 0.59 ± 0.072 [N] I-control 0.60 ± 0.088 ANOVA ns	6 3 ± 4 62 ± 5 6 3 ± 8 ns 0.82 ± 0.13 0.80 ± 0.14 0.77 ± 0.11 ns	5 9 ± 9 5 3 ± 7 5 5 ± 8 fip > carb* 0.95 ± 0.22 0.98 ± 0.18 0.94 ± 0.16 ns	4 0 ± 14 3 4 ± 15 4 2 ± 13 ns 1.12 ± 0.25 1.15 ± 0.27 1.07 ± 0.13 ns	27 ± 13 21 ± 10 27 ± 12 ns 1.09 ± 0.22 1.30 ± 0.32 1.14 ± 0.34 carb > fip*	29 ± 16 19 ± 7 26 ± 14 fip > carb* 1.05 ± 0.14 1.06 ± 0.14 0.98 ± 0.23 ns


Jérôme Cortet
email: jerome.cortet@univ-montp3.fr

Damien Ronce

Nicole Poinsot-Balaguer

Christian Beaufreton

André Chabert

Philippe Viaux

Jorge Paulo Cancela De Fonseca

Impacts of different agricultural practices on the biodiversity of microarthropod communities in arable crop systems

Keywords: Microarthropods, Biodiversity, Low imput systems, Tillage, Pesticides, Arable crops

Two crop production systems, which differ on tillage and pesticides, were compared for biodiversity of soil microarthropod communities. A biodiversity index, which integrates different structure and density parameters (abundance, taxonomic richness, taxonomic diversity, coenotic diversity) was used. Results showed a greater biodiversity in minimum tillage systems compared to deep tillage systems. Pesticides seemed to be only a second order factor of variance on microarthropod biodiversity.

Introduction

Soil microarthropods are often used as bioindicators of agricultural soil quality. Studies have shown the impacts of soil compaction [START_REF] Hendrix | Detritus food webs in conventional and no-tillage agroecosystems[END_REF][START_REF] Neher | Diversity and function of soil mesofauna[END_REF][START_REF] Schrader | Influence of soil tillage and soil compaction on microarthropods in agricultural land[END_REF][START_REF] Sabatini | Long-term effects of three different continuous tillage practices on Collembola populations[END_REF], and others have compared different agricultural production systems, such as integrated, organic or conventional systems [START_REF] Brussaard | Biomass, composition and temporal dynamics of soil organisms of a silt loam soil under conventional and integrated management[END_REF][START_REF] Dekkers | Soil Collembola and Acari related to farming systems and crop rotations in organic farming[END_REF][START_REF] Titi | Soil fauna in sustainable agriculture: results of an integrated farming system at Lautenbach[END_REF][START_REF] Hulugalle | Residual effects of tillage and crop rotation an soil properties, soil invertebrate numbers and nutrient uptake in an irrigated vertisol sown to cotton[END_REF]. But, whereas differences in abundance or biomass are often explored, few studies have presented results on diversity.

This paper presents results of a comparison of the impact of two agricultural arable crop practices on soil microarthropod communities in two French regions, using a biodiversity index.

Materials and methods

Study site and description of cultivation systems

The study was carried out on the experimental farm of the Association de Coordination Technique Agricole (ACTA), situated in Courseulles (Calvados, Normandy), on which 10 different fields had been regularly monitored for 8 years previously, to compare two different agricultural systems: "Conventional" and "Integrated" (Table 1).

The climate is typically oceanic. During the study period, from January to June 1997, the minimum temperatures were recorded in January (with a mean of -3.7 °C for the first week), and the maximum in June (with a mean of 16.7 °C for the first week). Precipitation was irregular, being low in early-mid spring (11.6 and 11 mm, respectively, in March and April, which correspond to the minimum), and relatively high in late spring-early summer (50 mm in June, which is the maximum reached). The site overlies typical Jurassic calcareous bedrock. Three different fields were chosen for the study (Table 1). They were all sown with winter wheat (Triticum aestivum L.) during the sampling period. However, each had been cropped the year before with a different crop: fibre flax (Linum usitatissimum L.) at Grand Parc (P1), Sugar beet (Beta vulgaris var. altissima) at Carfolands (P3), spring protein peas (Pisum sativum L. arvense) at Le Meslier (P4).

Soil physico-chemical analyses showed a different texture for P1 compared to the other fields, with twice as much sand and only half the amount of silt.

Each field had been divided into two parts for 8 years, one for each system. However, each system in each field was maintained independently. Thus, sometimes, the "Integrated" part may have received more pesticides than the "Conventional" part. An average amount of pesticides, based on five cropping years and the 10 fields, has been calculated: even if the amount of herbicides is equivalent between the two systems, the amount of insecticides and fungicides is considerably reduced in the "Integrated" system. Furthermore, in 1997, the amount of herbicides was greater in the "Integrated" than in the "Conventional" system. On the other hand, in 1997, tillage was reduced in the "Integrated" systems, except in P4 that showed no differences in tillage between the systems but a supplementary harrowing in the "Integrated" one (Table 1).

Sampling methodology and statistical evaluation

For each system in the three chosen fields, and for each sampling date, five soil cores (5 cm diameter and 10 cm deep) were collected. Sampling was carried out monthly from January to June 1997, corresponding to the winter wheat growing season. After extraction using the Berlese method [START_REF] Berlèse | Apparacchio per raccogliere presto ed in gran numero piccoli arthropodi[END_REF], animals were identified, counted and classified into five different taxa: oribatid mites, gamasid mites, "other mites", collembolans and "other arthropods". The significant differences in abundance between the systems were assessed for each field and each taxon, on each sampling date (using the Mann-Whitney test, Statview software, SAS foundation).

Then, for each field, "Conventional" and "Integrated" systems were compared using the ∆V index of biodiversity for four different taxa: oribatid mites, collembolans, "other mites" (all the mites excluding oribatid mites) and "other arthropods". A complete description of the calculation of this index can be found in [START_REF] Cancela Da Fonseca | On the evaluation of spatial diversity of soil microarthropod communities[END_REF]. The main features are as follows:

DV = ͓ V͑ x ͒ + V͑ S ͒ + V͑ n ͒ + V͑ H′x ͒ + V͑ H′y ͒ ͔ /5
where x is the abundance of the taxonomic group; S is the number of taxonomic groups; n is the number of samples containing the taxon; H′x is the taxonomic diversity index; and H′y is the coenotic diversity index; and:

Vm = ͑ Cm -Im ͒/͑ Cm + Im ͒
where Cm is the parameter m value in the Conventional system (for example H′x); and Im is the parameter m value in the integrated system.

If Cm = Im, no differences can be observed between the two systems. If Cm < Im, the difference of biodiversity is negative. If Cm > Im, the difference of biodiversity is positive. Thus, the index ranges between -1 and +1.

Results

Grand Parc (P1) site

The greatest population abundance in total microarthropods was in spring, particularly in April and May (Table 2). Significant differences in abundance of microarthropods were observed between the systems, especially concerning oribatid mites, which were more abundant in the "Integrated" compared with the "Conventional" system, from January to April. "Other mites" were also more abundant in the "Integrated" system in April. Total microarthropod populations confirmed these differences in January, February and April. However, in May, differences could not be observed, and in June, greater abundance of total microarthropods was observed in the "Conventional" system. From January to June, the index ∆V indicated greater biodiversity in the "Integrated" compared to the "Conventional" system (Fig. 1). The greater differences between the systems were apparent in April and May.

Les Carfolands (P3) site

As in P1, the greatest abundance in total microarthropods was observed during spring, particularly in April (Table 2). Significant differences were observed between abundance of microarthropods, with greater abundance of oribatid mites in the "Integrated" system in January, and of other mites in February and March. The total microarthropod numbers were also significantly greater in the "Integrated" system in January. Significant differences between the systems could not be observed in April and June. However, in May, a greater population abundance was observed in the "Conventional" compared to the "Integrated" system for oribatids and total microarthropods. These results were confirmed by ∆V values, which indicated higher biodiversity in the "Integrated" system for all months, except May (Fig. 1). The most marked difference in biodiversity between systems occurred in January.

Le Meslier (P4) site

A high level of abundance of microarthropods occurred in spring (April and May), as in the other fields, and also in winter (Table 2; January and February). There were a few significant differences in abundance between the systems during the study. In January the abundance of "other mites" was greater in the "Conventional" than in the "Integrated" system. Similar results were observed in April. However, in April, the abundance of oribatids was greater in the "Integrated" than in the "Conventional" system. In June the total abundance of microarthropods was greater in the "Integrated" than in the "Conventional" system.

The ∆V index indicated greater overall biodiversity under "Conventional" than "Integrated" management in January and May, but was slightly greater in the "Integrated" than in the "Conventional" from February to April (Fig. 1). Biodiversity was similar for the two systems in June.

Discussion

Any disturbance or stress imposed on a system interacts with environmental factors, which can vary with time and space. Thus, different factors, independent of agricultural practices, influence microarthropod populations in these arable crops. This is the case for climatic factors. Thus, abundance variations occurred over time in Courseulles, with a logical increase in population densities during spring, when precipitation and temperature were high and favourable for greater biological activity.

However, even if these factors can influence and cause fluctuations in microarthropod populations, biodiversity differences between the systems are often quite stable, with, except for some months in P4 and May in P3, greater biodiversity in the "Integrated" compared to the "Conventional" system.

Results observed at Courseulles might be explained by tillage, which is known to decrease microarthropod abundance [START_REF] Neher | Diversity and function of soil mesofauna[END_REF][START_REF] Sabatini | Long-term effects of three different continuous tillage practices on Collembola populations[END_REF]. Thus, in January, which is the sampling date closest to the last soil cultivation, the biodiversity was greater in the "Integrated" system in P1 and P3 than in the "Conventional" one, but the opposite was observed in P4 site. These results are logical, since in P1 and P3, soil cultivation, particularly tillage, was more intense in the "Conventional" than in the "Integrated" system, and in P4, soil cultivation was more intense in the "Integrated" system than in the "Conventional" one. Furthermore, tillage is known to increase soil compaction that might have negatively affected microarthropod populations [START_REF] Schrader | Influence of soil tillage and soil compaction on microarthropods in agricultural land[END_REF].

At the Courseulles site, pesticides could involve variations in function of two factors: the pesticide spraying history of each field and the diversity of microarthropod reactions to any given pesticide. Indeed, the different pesticides can have different effects on soil invertebrates [START_REF] Cortet | Impact de produits phytopharmaceutiques sur les microarthropodes du sol en culture de maïs irrigué: approche fonctionnelle par la méthode des sacs de litière[END_REF]. Furthermore, even if qualitative and quantitative pesticide differences can be observed between the systems of each field, the pesticide spraying calendar should be taken into account when looking at the effects on microarthropods. Indeed, even if we can observe, from a general point of view, that pesticide use was less important in the "Integrated" than in the "Conventional" system (see the mean amount of pesticides used on ten fields during 5 years), this is not always true for each year. Thus, in 1997, the overall quantities of herbicides used were greater in the "Integrated" than in the "Conventional" system. These remarks are also valuable for each season of culture, since each system for each field was conducted independently from the other systems of other fields. Thus, for some sampling dates, particularly during spring when many pesticides were also sprayed in the "Integrated" system, the biodiversity was not always greater in the "Integrated" system, as it was observed in P3 and P4.

Physical modifications caused by soil cultivations (particularly tillage), are often considered as the more intensive [START_REF] Titi | Soil fauna in sustainable agriculture: results of an integrated farming system at Lautenbach[END_REF][START_REF] Mallow | Effects of different management practices on Collembola and acarina in corn production systems[END_REF][START_REF] Moore | Effects of different management practices on Collembola and acarina in corn production systems. I. The effects of no-tillage and atrazine[END_REF]. At the Courseulles site, it was very difficult to differentiate and appreciate the role of each disturbance factor (soil cultivation and pesticides). Indeed, the P1 field, which had the largest biodiversity differences between the systems, was also the field that had the largest differences between the systems, concerning both pesticide use and soil cultivations. But, the impact of herbicides seemed to be low, since in 1997, even with higher quantities of herbicides used in "Integrated" compared to that in "Conventional", the biodiversity is still higher in the "Integrated" system. However, analytical experiments, including a separate study of pesticides and soil cultivations would be necessary to understand the relative impacts of these two factors.

The previous types of culture should also be taken into account. At the Courseulles site, all of the sampled fields had a different previous culture that could explain in part the variations in microarthropod populations between the fields. These results agree with those obtained by Jagers op Akkerhuis et al. [START_REF] Jagers Op Akkerhuis | Soil microarthropods (Acari and Collembola) in two crop rotations on a heavy marine clay soil[END_REF], concerning the influence of type of culture and rotation on soil microarthropods. Indeed, they showed that microarthropod populations were different under different types of cultures.

Fig. 1 .

 1 Fig.1. The ∆V index of biodiversity for "Integrated" and "Conventional" systems for each sampled field (P1, P3, P4) in Courseulles, from January to June 1997. The ∆V: each parameter is calculated as the sum of means; ∆V moy: each parameter is calculated as the mean of sums. If Conventional < Integrated, the difference of biodiversity is negative. If Conventional > Integrated, the difference of biodiversity is positive.

Table 1

 1 Soil cultivation and pesticides on the Courseulles site, for each field studied in 1997 and all the fields from 1991 to 1995

	Fields	System	Tillage	Other soil	Herbicides	Insecticides	Fungicides
	(year of harvesting)			cultivation	(kg ha -1 )	(kg ha -1 )	(kg ha -1 )
	P1 Grand Parc (1997)	Con	Present	C, SPH	0.64	0.15	1.09
		Int	Absent	C, SPH	1.85	0.071	0.31
	P3 Les Carfolands (1997)	Con	Present	SH, SPH	0.58	0.084	1.96
		Int	Absent	SH, SPH	1.85	0	0.71
	P4 Le Meslier (1997)	Con	Absent	C, SPH	0.64	0.14	1.09
		Int	Absent	C, H, SPH	1.05	0	0.31
	Mean of ten fields (1991-1995) Con	Variable	Variable	1.70	0.23	1.94
		Int	Variable	Variable	1.53	0.087	0.88
	Con: Conventional ; Int: Integrated; C: cultivating ; SPH: seeding + power harrows ; SH: sugarbeets harvesting ; H: harrowing

6 ± 0.89 13.6 ± 12.5 13.8 ± 12.6 8.4 ± 5.59 0.8 ± 1.3 4.2 ± 3.56 15.8 ± 19.9 Oribatida 2.2 ± 1.48 13 ± 5.79 11.2 ± 10.8 10.2 ± 5.76 17.8 ± 8.17 9.2 ± 5.81 10 ± 3.24 16.4 ± 9.91 24 ± 20.6 1.6 ± 1.52 0.6 ± 0.

Acknowledgements

This project was performed under the ACTA programme: « Recherche d'indicateurs biologiques permettant d'évaluer l'effet de techniques et systèmes de production sur l'activité et la diversité biologique des sols ». This programme is financed by « Ministère de l'Agriculture et de la Pêche » and « Ministère de l'Education Nationale de la Recherche et de la Technologie ».


Alain Bauer

Maintaining Public Order in France: Myths and Realities

Keywords: France, law, public order, police

The maintenance of law and order in France, which was long an object of pride and a French export, has considerably evolved over time. Faced with more mobile and sometimes more violent populations, and without any means of internal control, the police have to adapt and rethink their ideology.

Whether it involves the insurrectional demonstrations of 1934 or the cobblestones thrown at police during the May 1968 events, a confused amnesia governs politicians about the very nature of maintaining public order in France.

It took a very long time for the management of demonstrations to be demilitarized and for rioting crowds to no longer be shot at (1921 and 1945, respectively). This slow de-escalation went hand in hand with the very gradual creation of specialized units that would become the Gendarmerie mobile and the CRS. Regional Compagnies d'intervention (public order forces) were also introduced, in particular in Paris. Management of the MO (Maintenance of Order) was not completely handled by experts in the field.

The principles of maintaining public order therefore adapted according to events. It reached its height in 1979 with the demonstration by steelworkers in Paris. As so often occurs, and in line with the customs of the period, this led to a duel, or a tournament, between security personnel of the CGT and the forces of law and order on a commonly defined terrain and shared timetable. This was followed by a confrontation with the rioters (known as "autonomes" or "totos" by those close to them).

1986 saw a mobilization of the student movement, and especially of highschool students, who discovered a new way of demonstrating. At the head of the procession of marchers, and in front of the security forces, a young demonstrators"nebula" stood between the CRS and the trade union security team in order to challenge them. In the years that followed, this very militant young crowd changed tactics, and took to moving along the demonstration to pillage shops or even steal from other demonstrators in the procession itself. Each tense episode (1994(CIP), 1995(Juppé Pensions), 2003(Fillon Pensions), 2006 (CPE), 2016 (El Khomri), etc.) led to a modification of procedure and to variations: these became tougher and more organized for anti-globalization gatherings and more spontaneous during the 2003 riots following the deaths of two children in an electrical substation.

On each occasion, after first being dumbfounded and then adjusting to the new situation, the forces of law and order adapted, regaining the upper hand, and a political solution took shape (usually by withdrawal of the offending provision). But, alas, there is a great ability to forget where policing is concerned-a domain that is very rarely run by the police themselves and much more often by experts in public order.

2018 was not 1934. The fascist leagues did not run the movement, but they took advantage of the opportunity. Neither was it 1968, when a process began in a high school and spread through a crisis of abundance and liberalization in a conservative society trapped in a black and white vision of the world (contrary to what is said, it led to at least three deaths). Neither was it 1986 (which had a symbolic victim). And we should not forget Vital Michalon, who died at Creys Malville in 1977, or Remi Fraisse who died at Sivens in 1994.

2018 brought together multiple grievances for the first time, yet without managing to combine disparate and often contradictory battles.

The maintenance of law and order has therefore been confronted with a crisis that is unprecedented in nature, although far from surprising for the state. Indeed, in 1987, the Prefect Massoni organized a very rare and very discreet feedback session on the events of the previous year. In addition to General Inspector Berlioz, who was at the forefront of the exercise, other experts participated in a major reorganization of the system for maintaining law and order.

The Pelotons Voltigeurs Motorisés [Motorized Squads] were abolished-this had been a temporary unit set up around sports coaches and motorcyclists from the Prefecture of Police, who operated in pairs on their vehicles, chasing and striking supposedly violent demonstrators with their "bidules" (long wooden truncheons). They were directly condemned for the death of Malik Oussekine. But, more than this, crowd management needed to be reinvented for the modern era.

The method conceived of at the time aimed to prevent Agincourt (as if it had happened a fortnight before, in Paris), Maginot (as if it were last week) and especially Waterloo (which never took place). This revolution in policing operations included mobile units used in a mobile manner, mixed units (uniformed and civilian), functioning in a legal capacity, with a process determined in agreement with the Public Prosecutor's office and under the control of district attorneys. It was designed to be preventative by anticipating places of departure, routes taken, or arrival points of participants deemed to be dangerous.

The idea of armored vehicles was quickly abandoned, because these vehicles (including those used by the gendarmerie on December 8th) are very difficult to control in towns or outside of an OPEX (exterior operations) conflict.

Although the question of cellphones and the increased mobility of crowds were envisaged, nobody foresaw the effects of social networks-evidence enough that it will be necessary to do more than simply adapt the principles for maintaining law and order. A total and rapid rethink is what will be needed-in order to guarantee the freedom to demonstrate and the right to protest; to ensure that whatever power is in place responds to the people it governs; because the security response is only ever a stopgap enabling uprisings to be contained, to reopen dialogue, and to establish consultation. But this has never prevented a Revolution.


Alain Bauer

Jacquerie 2.0 (Peasant Revolt 2.0)

Keywords: Revolt, insurrection, jacquerie, social networks, web, populism

France has had a long history of revolts and insurrections. The emergence of social networks has multiplied their capacity for action. Jacquerie is now version 2.0. And populism around the world has benefited directly from it.

France has had a long history of revolts caused by the ignorance or disdain of the aristocracy, whether it be a monarchy or a government. The trigger of resentment was always taxation. The taille land tax, the gabelle salt tax, the assembly of the Estates General of 1789 to increase the revenue of the kingdom, but also the Poujadist movement of 1953 and the bonnets rouges against ecotaxes, all lead up to the gilets jaunes (yellow vests).

As always, the gathering of angry crowds is mechanically translated into symbolic destruction. Fishermen, farmers, and truck drivers have never failed to destroy street furniture, the railings of police stations, speed cameras, porticos ... even the Parliament of Brittany, albeit through clumsiness. Gustave Le Bon explained as early as 1895 that: "Little adapted to reasoning, crowds, on the contrary, are quick to act." While the first part of this dictum could be revisited, the second part is easily and regularly demonstrated.

Festive, organized, or chaotic crowd movements adore symbolic and redemptive fires, from pyramids of tires to the stationary, but flaming, barricades erected on the Champs Élysées when the goal was to march on the presidential palace.

Of course, some instigators are more organized than others (it is not that easy to un-pave a street by hand, and equipment is needed to prevent immediate burns and the long-term effects of tear gas ... ). There is no need for the ultra-left or ultraright in order to bring together thousands of yellow vests who are not, or not yet, a Yellow Bloc, the diesel version of the Black Bloc.

In this group of frustrated retirees, stifled low-wage earners, and the peripheral "left behind," confirming the hypotheses of Guilluy, there was certainly a place for the professionals of violent protest and confrontation. Yet much less than on May 1 or during the demonstrations against the labor law. And many more prime-protesters who are in the process of building a new political generation, like in 1968, 1986, ... but not in 2005, when the riots that required a state of emergency did not lead to a structured movement. And it is regrettable, since this disorganizational disorder causes damage and victims in unexpected proportions.

However, it is probably the episode in 1995 that saw Alain Juppé get swept away by a coldly rational and hotly contested retirement reform that we must focus on in order to try to understand the irresistible impulse of most governments to pass by force what previous governments failed to accomplish.

After all, was it not to an extent symbolic posturing that drove a political heir to show that he could succeed where his predecessors had twice failed? What should we think of this truly incendiary desire to add a heavy goods vehicle tax here, a toll for entering the city there, an increase in student registration fees (just foreign students, to start), without forgetting the justice reforms that eliminated juries for the most part, and therefore jurors, or the attempt to organize mining reforms? What can be said, finally, of the curious obsession with reforming the law of 1905, mobilizing at once both ultras and moderates, secular combatants and ultras?

In other words, to press all at once on everything that irritates, harms, aggravates, or provokes. By not dealing with the essential issue: "Responding to the problems of the end of the month, not the end of the world," as cleverly stated by some "moderate" yellow vests.

And this aspect may be the most important element to appear in the background of this mobilization: A poor understanding of the process created by the destruction of intermediary bodies of which the election of Emmanuel Macron and the parliamentary raid of En Marche were thought to be the culmination. In fact, it was only the beginning of a deeper and even more uprooting movement, since it took away the last bastion of local representation: mayors, who decided to leave their positions in large numbers at, or sometimes before, the next reelection cycle, even when they did not anticipate losing the election. These processes do not leave much between the streets and chaos: No state can resort to defending itself with just its CRS and gardes mobiles, even if their skills and effectiveness have prevented large numbers of victims (and much less in any case than those caused by road rage in recent weeks, which has been shockingly overlooked by the media).

Violence is always constructed in a coherent process of violence of the institution, in the institution, and against the institution. This process often causes a reaction and a demand for Order, Authority, Justice, and Equality. And when this demand is ignored or scorned, it boils over. For at least thirty years, the political sphere has avoided facing difficult questions. And the question of insecurity, of insecurities, builds a democratic frustration that taxation ignites. Hungary, Slovakia, Poland, the Czech Republic, Italy, Australia, the United States, and Quebec showed that electoral disdain could cause a reaction by the working classes (much more than a populist reaction). What happens next is being written today.

Thinking of its tragic aspects, people say that history never repeats itself. But it does sometimes stutter.

It is not clear whether this adage will last much longer.