Clother Coste

New ecology and new classification for phytosociology of hydrophilic lichens in acid watercourses in France

New ecology and new classification for phytosociology of hydrophilic lichens in acid watercourses in France

Introduction

The study of the ecology of lichen communities on siliceous rocks started in 2003 by work in the Tarn Department of France, expanding over the next six years to several other French Departments. The reason behind this work is that few European publications are devoted to this subject and none involve France. Several articles have provided interesting data on the distribution of hydrophilic lichens but only a handful dealt with the general and comparative ecology of varied aquatic lichen communities.

Published data, the methods used for taking and processing samples, as well as the analysis of the results are presented in this note, whose aim is to propose a new ecological conception and a new nomenclature of hydrophilic lichen communities in acid continental aquatic ecosystems. It concludes with research perspectives arising from these new data.

Method

Lichens depend on alternating dry and wet periods, but excessive hydration and permanent desiccation are harmful (Ried, 1960;[START_REF] Dietz | The effect of abscisic acid on chlorophyll fluorescence in lichens under extreme water regimes[END_REF]. Their symbiosis provides a high after growth capacity and a very broad range of habitats. They can colonise virtually all supports in all environments: from the banks of watercourses to the most varied terrestrial ecosystems. There are many zones of ecological contacts among ecosystems [START_REF] James | Lichen communities in the British Isles : a preliminary conspectus[END_REF] but the compositions of terrestrial and aquatic flora are very different. Aquatic lichens have an ecological specificity.

There are two groups of aquatic lichens, called ekreophilic when they are on rocks subjected to prolonged water flows, and hydrophilic when they colonise supports subjected to periodic immersion by watercourses [START_REF] James | Lichen communities in the British Isles : a preliminary conspectus[END_REF][START_REF] Cl | Catalogue des lichens et champignons lichénicoles de la région Languedoc-Roussillon (France méridionale)[END_REF].

One factor determining the structure of hydrophilic lichen communities is the duration of immersion by watercourses [START_REF] Santesson | Uber der zonationverhältnisse der lacustrinen flechten einiger Seen in Anebodegebeit[END_REF]. Several publications have described a transversal zonation of lichens in watercourse beds (Fig. 1) (or in lakes) with respect to the immersion duration of the species in question [START_REF] Beschel | Die stüfung der flechtenvegetation an den Inn. Ufermauern in Innsbruck[END_REF][START_REF] Gilbert | The Lichen Vegetation of Chalk and Limestone Streams in Britain[END_REF][START_REF] Gilbert | The Lichen Vegetation of Chalk and Limestone Streams in Britain[END_REF]Giavarini, 1997, 2000;Aptroot and Seaward, 2003). These zonations are based primarily on the European system of the yearly fraction of time during which rocks are immersed vs. their distance from the mid-point of watercourses (Fig 2).

On-site experiments [START_REF] Keller | Zur Verbreitung von Wasserflechten in Abhängigkeit zur jährlichen Überflutungsdauer im Flüelatal (Schweiz, Kanton Graubünden)[END_REF] or specific studies [START_REF] Valcarcel | Liquenes pirenocarpicos de los rios y arroyos de Galicia (Espana)[END_REF] have provided quantitative data on the immersion times of river bank rocks colonised by lichens. Three transversal zones have been defined on the basis of annual immersion periods: more than 10 months, between 3 and 10 months and less than 3 months.

These results confirm the proposal of [START_REF] Santesson | Uber der zonationverhältnisse der lacustrinen flechten einiger Seen in Anebodegebeit[END_REF].

The period of immersion is not the only parameter determining hydrophilic communities, since the rate of rock surface drying also plays a non-negligible role [START_REF] Coste | Lichens et communautés lichéniques hydrophiles et subhydrophiles saxicolescalcifuges du département du Tarn (France)[END_REF]. In addition, there are so-called riparian "buffer" zones where the lack of immersion is compensated by the excessively shaded location of rocks [START_REF] Nascimbene | Freshwater lichens in a small riparian Naturel Reserve of the Northern Italy : species richness and conservation issues[END_REF] that protects from desiccation, confirming prior results [START_REF] Coste | Lichens et communautés lichéniques hydrophiles et subhydrophiles saxicolescalcifuges du département du Tarn (France)[END_REF].

Hydrophilic lichen communities are impacted by many ecological factors other than the duration of immersion or the rate of desiccation of supports (Perreira, 1992;Krzewicka and Galas, 2006;Thüs and Schultz, 2009). Thus, the structure of hydrophilic lichen communities is determined by the chemical nature of the water, current strength, the type and stability of rocks, the sediment load of the water and temperature [START_REF] James | Lichen communities in the British Isles : a preliminary conspectus[END_REF][START_REF] Thüs | Taxonomie, Verbreitung und Ökologie silicoler Süsswasserflechten im ausseralpinen Mitteleuropa[END_REF]Aptroot and Seaward, 2003;[START_REF] Coste | Lichens et communautés lichéniques hydrophiles et subhydrophiles saxicolescalcifuges du département du Tarn (France)[END_REF].

There are two basic methods applied to ecology studies, the so-called "classical" method of partial sample gathering [START_REF] Wirth | Die Silikatflechten-Gemeinschaften im ausseralpinen Zentraleuropa[END_REF] and the total sampling method [START_REF] Roux | Échantillonage de la végétation lichénique et approche critique des méthodes de relevés[END_REF]. The first has been and is still used in studies of plant communities, or phytosociology. The second method was recently applied to hydrophilic lichens communities on siliceous rocks in the Tarn Department of France [START_REF] Coste | Lichens et communautés lichéniques hydrophiles et subhydrophiles saxicolescalcifuges du département du Tarn (France)[END_REF]. Although this method is rapidly implemented in the field, it requires long and fastidious prior laboratory work. This method provides very precise results on ecology and flora that give rise to interesting hierarchic rankings. Three hundred samples were taken at varying distances from the centre of watercourses: in the low-flow channel, the lower part of the minor bed and the upper part of the minor bed.

These three zones are involved by the above-mentioned annual immersion times of rocks: more than 10 months, between 3 and 10 months and less than 3 months. Samples were taken in several French Departments (Fig 3) and were analysed using statistical processing software (R software).

Results

The canonical analysis of the results (Fig 4) shows that the localisation of samples with respect to the centre of watercourses determines the structure of lichen communities (Fig 5).

The compositions of flora in samples from the three support immersion zones exhibit highly significant differences. An NMDS (non-metric multidimensional scaling) classification also showed that the flora compositions of the three groups differ as a function of the bioclimatic stage.

Field observations often find communities in the lower part of the minor bed of watercourses that are normally found in the low-flow channel. This illustrates buffer zones where the lack of immersion is compensated by local protection from desiccation of rock surfaces. These features are minimised by the use of statistical tools. Good understanding of species and long field experience are necessary to avoid the ecological consolidation of communities based on features of the terrain.

Conclusions, discussion and perspectives

Examining prior work has led to the differentiation of lichens on rocks subjected to relatively constant water flows and those on rocks undergoing periodic immersion in watercourses, respectively called ekreophilic and hydrophilic groups that can also be called aquatic or amphibious. This older work pointed out the existence of several lichen communities whose structure depends on their duration of immersion. Statistical analyses of the 300 samples taken in the present work have confirmed this assertion and have defined three groups, each specific to a zone of immersion. Even though results of field observations were somewhat minimised by the statistical tool used, they showed the existence of buffer zones. This involves not only the duration of immersion that determines the structure of lichen communities, but also the drying rate of rock surfaces. It is recommended to use the term "duration of contact with water" rather than "duration of immersion". As a result, a new nomenclature of hydrophilic lichen communities should be considered. It is proposed to call lichens in the contact zone of more than 10 months, between 3 and 10 months and less than 3 months "hyper-hydrophilic", "meso-hydrophilic" and "sub-hydrophilic", with some minor variation related to the existence of buffer zones. Figure 6 summarises the ecological conception of hydrophilic lichen communities.

The structure of each of these groups identified is also determined by climatic conditions related to vegetation stages, making it possible to propose an overall phytosociology profile (figure 7). One group of species is found in all samples regardless of contact times with water.

These lichens can be considered as representatives of the phytosociology class of hydrophilic lichens on siliceous rocks. A second group is found only in one of the three immersions zones, and these species can be considered as representatives of the phytosociology order.

Finally, each order defined contains specific groups of species per bioclimatic stage and can be considered as representatives of phytosociological alliances. These alliances contain the combination of two or even three species, depending on very strict local ecological characteristics. Only hyper-hydrophilic groups do not involve associations and all samples contained a dispersion of species. In contrast to sub-hydrophilic and meso-hydrophilic groups, this dispersion of species may have two origins: either hyper-hydrophilic associations in France at the limit of the area of distribution, or there are no climactic associations in the lowflow channel. Although hydrophilic lichen associations in France are at the limits of the zone, they probably reach a climactic stage in other regions of Europe, e.g. central Europe. Specific work in these regions should confirm or refute this opinion. A climactic stage is characterised by small heterogeneous ecological niches, high biomass production and a complex and diversified trophic system [START_REF] Dajoz | Précis d'écologie[END_REF]. In the low-flow channel, however, ecological niches are large and homogeneous, biomass is low and the food chain is reduced to only fresh water invertebrate. Hyper-hydrophilic associations apparently do not exist and can be considered as "permanent pioneer" groups.

For each phytosociological unit thus defined, the list of all species characteristic of each group thus defined will be the subject of a future publication.

For each group defined, it is also necessary to identify the physiological specificities involved in adaptation to ecological conditions, in particular photosynthesis in aquatic and open air environments, and its role in the food chain and biogeochemical cycles.

The present results will lead to a better understanding of the passage of lichens from aquatic to terrestrial life, and more broadly the comprehension of the role of lichens and symbiotic organisms in general, in the colonisation by higher plants of land exposed by receding waters. [START_REF] Gilbert | The Lichen Vegetation of Chalk and Limestone Streams in Britain[END_REF][START_REF] Gilbert | The Lichen Vegetation of Acid Watercourses in England[END_REF]Aptroot et Seaward -2003 Vertical [START_REF] Gilbert | The Lichen Vegetation of Chalk and Limestone Streams in Britain[END_REF] and [START_REF] Gilbert | The Lichen Vegetation of Acid Watercourses in England[END_REF], used by Aptroot and Seaward (2003).

Fig. 1 :

 1 Fig.1: Zonation according to[START_REF] Gilbert | The Lichen Vegetation of Chalk and Limestone Streams in Britain[END_REF] and[START_REF] Gilbert | The Lichen Vegetation of Acid Watercourses in England[END_REF], used by

Fig. 2 :

 2 Fig. 2 : Correlation between distance of substrates and percentage of yearly immersion times.

Fig. 3 :Fig. 4 :

 34 Fig. 3 : Sampling sites in France.

Fig. 5 :

 5 Fig. 5 : Example of hydrophilic lichen communities.

Fig. 6 :

 6 Fig. 6 : Ecological description of lichen groups on the banks of watercourses.

Acknowledgments

The authors thank Marie-Hélène O'Donoghue, information specialist of the library of the Laboratory of Functional Ecology (Ecolab) and Williams Exbrayat, of the library of the Midi-Pyrenees Observatory for their invaluable help in literature searches. We thank Professor Micky Tackx (Ecolab) for her relevant remarks to the first draft of the manuscript.


Annemarie Kökösy

Franck-Olivier Defaux
email: defauxfo@hotmail.com

Annemarie Kokosy
email: annemarie.kokosy@isen.fr

Wilfrid Perruquetti
email: wilfrid.perruquetti@ec-lille.fr

Autonomous navigation of a nonholonomic mobile robot in a complex environment

Keywords: robot navigation, non linear optimization, flatness, supervisor, nonholonomic robot, path planning, complex environment

published or not. The documents may come

Autonomous navigation of a nonholonomic mobile robot in a environment

I. INTRODUCTION

The autonomous navigation of mobile robots in an environment with obstacles is a problem on which many works have currently been carried out and this for more than twenty years. When the robot does not know in advance the obstacles in the environment, it must use its sensors to be located and perceive the environment and to react accordingly. Two approaches can be found in the literature. In the first one, the robot uses the local sensory information in a sheer reactive way. Algorithms Bug1 and Bug2, presented in [START_REF] Lumelsky | Path-planning strategies for a point automaton moving amidst unknown obstacles of arbitrary shape[END_REF] only use position and contact sensors. These algorithms consist of two reactive modes of motion: moving directly towards the target and following an obstacle boundary, and a transition condition to switch between them. When the robot hits an obstacle, it switches from the mode moving towards a target to the mode following a boundary. It moves away from the obstacle boundary when a leaving condition, which ensures that the distance to the target decreases, holds. These algorithms guarantee the global convergence to the target, but their performances depend on the complexity of the map. In particular, the introduction in the environment of nonconvex obstacles can sometimes be catastrophic for the algorithms results. It also should be noted that the direction followed to make the turn around the obstacle boundary is arbitrary and it is impossible to know if it is the best choice. However, the original Bug algorithms do not make the best use of the available sensory data to produce short path. In the VisBug algorithm, presented in [START_REF] Lumelsky | Incorporating range sensing in the robot navigation function[END_REF], the robot has a distance sensor enabling it to know which distance separates it from an obstacle, in all directions. The robot uses this distance information to find many shortcuts and to test a leaving condition compared to the Bug2 algorithm. One of the limits of the VisBug algorithm is that it makes only use of the data of the distance sensors with an aim at reducing the path between the initial and final points found by the Bug2 algorithm. The TangentBug algorithm, presented in [START_REF] Kamon | A new range-sensor based globally convergent navigation algorithm for mobile robots[END_REF], will more specifically exploit these data by building the local tangent graph. The convergence of this algorithm is guaranteed. Various properties of the TangentBug algorithm are shown. In particular, simple conditions to detect that the target is unattainable are given, as well as a higher limit on the total way crossed according to the perimeter of the obstacles and the number of local minima met. Various examples and simulation results highlight the interest of this algorithm compared to VisBug. The authors of the algorithm CautiousBug [START_REF] Magid | Cautiousbug: a competitive algorithm for sensory-based robot navigation[END_REF] highlight an important limitation of the various Bug methods: at the time of the meeting of an obstacle, the choice of the boundary-following direction is based on local information. This choice may be wrong in the sense that it will result in a longer path. They propose a simple method which will allow, in many cases, to guarantee better performances, as well as a factor of competitiveness to compare the results of the various algorithms (it consists of the relationship between the length of the way crossed by the studied algorithm and the length of the optimal way, obtained when the map is entirely known). The algorithm is based, following the example of TangentBug algorithm, on the local graph of the tangents. The difference will be made on the choice of the direction followed when a local minimum is detected. Instead of basing itself on local information, the robot will carry out a research in spiral. Nevertheless, this research in spiral requires to make manoeuvrers with the robot, which in the case of a point robot do not have any importance, but which, in the case of a nonholonomic robot, can reduce the optimality of run time (difficulty in making half-turn, even impossibility in a reduced space). In conclusion, the Bug algorithms give excellent results for the completely unknown environment, because they always make it possible to converge towards the target or to find that the target is unreachable. However, the path carried out can be in many cases far from optimality. Moreover, these algorithms would require a strong theoretical development taking account of the uncertainties of the sensors and kinematics and dynamic constraints of the robots. In the second approach, the robot will plan its trajectory in the environment. It is the case of work exploiting the deformable virtual zones (DVZ) [START_REF] Zapata | Simultaneous path following and obstacle avoidance control of unicycle-type robot[END_REF], [START_REF] Pinto | Vers une architecture de commande des robots mobiles coopérants non holonomes[END_REF] which as are developed in [START_REF] Defoort | Performance-based reactive navigation for non-holonomic mobile robots[END_REF]. In the DVZ algorithm, the robot to be moved will be surrounded by a virtual envelope, typically in an elliptical shape. This envelope could be deformed in two ways: either in an internal way (the variables of the robot model employed act on its form), or in an external way (when an obstacle enters the virtual zone). The goal of the robot control using the DVZ method will then be to minimize the deformation due to the obstacles. The robot model which is used for the path planning optimization in [START_REF] Pinto | Vers une architecture de commande des robots mobiles coopérants non holonomes[END_REF] is a car like. The advantages of this method are that it does not require important computing time and can be implemented in real-time. It also allows the use of a kinematic model of robot, which facilitates the application to a real system. However, it requires many parameters of adjustments and does not guarantee the convergence of the robot towards the objective. The path planning algorithm presented in [START_REF] Defoort | Performance-based reactive navigation for non-holonomic mobile robots[END_REF] guarantees the autonomous navigation of a nonholonomic robot in an unknown environment with obstacles of circular shape or which can be included in circles. The algorithm takes account of the kinematics constraints of the robot as well as of its physical limitations (maximal speed). The trajectory is calculated by using the property of flatness of the system and can be implemented in real-time, because the optimal problem is calculated on a reducing horizon. However, it does not allow to take into account complex shapes of obstacles, since only the circular obstacles can be taken into account. The outline of this paper is as follows. The problem statement is given in Section II. Section III gives the main results. Simulation results are detailed in Section IV.

II. PROBLEM STATEMENT

The robot is represented by a disc located at the mass center (x, y) and of radius r (Fig. 1). q = [x, y, θ] T and U = [v, w] T respectively denote the state variables and the control inputs (linear and angular velocities). The kinematic equations of the system under the nonholonomic constraint of pure rolling and no slipping can be written as follows:

ẋ = v cos θ ẏ = v sin θ θ = w (1)
The robot must evolve in an autonomous way of an initial given point to a final known point while avoiding collision with the unknown obstacles met on its way. It is therefore necessary to construct a robot control able of guaranteeing its navigation without collisions while taking into account the robot physical limitations.

III. MAIN RESULTS

A. Motion planning [7]

The goal is to generate a feasible quasi-minimum time trajectory that satisfies the environmental constraints: obstacle avoidance and also the physical constraints due to the limitations on the velocities. The optimal control problem is to find the control inputs which minimize:

J = t f τi dt, (2)
where the initial time is τ 0 = 0, τ i = t i + δt and t f is the unknown final time. The trajectory must join the known states q(τ i ), q(t f ) and satisfy the constraints, ∀t ∈ [τ i , t f ]: C1 the optimal trajectory and the optimal control are solutions of the cinematic model of the robot (1). C2 the control bounds:

|v| ≤ v max -ǫ v , |w| ≤ w max -ǫ w ,
where ǫ v and ǫ w are positive control parameters. The inclusion of these constants in the constraints of the motion planning generator guarantees that there is sufficient control authority to track the trajectory. C3 the collision avoidance with the N o detected obstacles which can be included in a circle:

∀m ∈ {1, . . . , N o }, (x -x o m ) 2 + (y -y o m ) 2 ≥ r+r o m with r o m > 0.

B. Taking into account of obstacles with general shape

In order to take into account obstacles of more general forms in the problem of path planning, a modeling of the obstacles in the form of polygons was used. This modeling has the advantage, compared with modeling by circles [START_REF] Defoort | Performance-based reactive navigation for non-holonomic mobile robots[END_REF],

of being able to be used for all shapes of obstacles which can be included in a polygone, by respecting its contour as well as possible, which limits the unused space for the robot displacement. One can notice that the more the number of segments used to model the obstacle will be important, the more this obstacle will be represented accurately. An obstacle O i defines an inaccessible zone for the robot in its environment. The complex contour of the obstacle can be approximated by a succession of N i segments S ij . Each one of these segments is represented by its two ends points A ij and B ij . These points have respectively (x Aij , y Aij ) and (x Bij , y Bij ) as coordinates.

Fig. 2. Approximation of obstacles with complex shape

It is possible to define obstacle O i like the meeting between its contour o i and its interior O 0 i :

O i = o i ∪ O 0 i , o i = ∪ j=Ni j=1 S ij , (3)
We note N p the number of obstacles other than circular ones in the sensor range of the robot. The whole of the N p detected obstacles of the robot environment is the union of the O i .

The obstacles are supposed to have a closed contour:

∀S ij ∈ O i , ∃S ik , k ∈ 1, ..., N i , k = j such that A ik ≡ A ij or B ik ≡ A ij ∃S il , l ∈ 1, ..., N i , l = j such that A il ≡ B ij or B il ≡ B ij .
In practice, this modeling in the form of a polygon will result from an perception algorithm of the robot (using a video camera, or a lidar or a rangefinder). The path planning algorithm must take into account the uncertainties of the perception algorithm. So, we replace the previous relations by a new one defined by equation ( 4):

A ik ≡ A ij ⇔ d(A ik , A ij ) < ǫ (4)
where d(A ik , A ij ) is the euclidian distance between A ik and A ij :

d(A ik , A ij ) = (x A ik -x Aij ) 2 + (y A ik -y Aij ) 2 (5)
The robot position is defined by the coordinates of the point R(x, y). The distance between the robot and the segment S ij is defined by d(R, S ij ), (6):

d(R, S ij ) = min M∈Sij d(R, M ) (6)
Let segment S ij be defined by its end points

A ij et B ij . Distance d(R, S ij ), (6)
is calculated according to the robot position compared to segment S ij . Three cases are to be distinguished (i.e. Figure 3) :

---→ A ij R • ----→ A ij B ij ≤ 0, α > π 2
, then R and B ij are on both sides of ∆ A , the line perpendicular to S ij which passes by A ij (case R = N 0 on Figure 3), so

d(R, S ij ) = A ij -R . If not, if ---→ B ij R • ----→ B ij A ij ≤ 0, β > π 2 , then R and A ij are on both sides of ∆ B , the line perpendicular to (A ij B ij ) which passes by B ij (case R = N 2 on Figure 3), so d(R, S ij ) = B ij -R . If not 0 < α, β < π 2 , (case R = N 1 on Figure 3) d(R, S ij ) = A ij -N ′ .
So, the definition of the distance between robot R and segment S ij is given by equation ( 7):

d(R, S ij ) =        d(R, S ij ) = A ij -R , if α > π 2 d(R, S ij ) = B ij -R , if β > π 2 d(R, S ij ) = A ij -R sin(α) = B ij -R sin(β), 0 < α, β < π 2 (7)
As this distance belongs to the constraints to be introduced into the path planification algorithm, which calculates the optimal trajectory of the robot, it is necessary that it is of class C 1 . It is thus necessary to check its continuity and its derivability when α = π 2 or β = π 2 . It is easy to prove that the distance defined by equation ( 7) belongs to class C 1 . The proof is omitted due to the paper limitation.

Let d(R, O i ) the distance between the robot and the visible part by the robot sensors of obstacle O i . This distance is defined by equation (8):

d(R, O i ) = min j d(R, S ij ), j ∈ 1, ..., N i . (8)
We can now add to the optimal control problem a new constraint which allows the avoidance of collision with polygonal obstacles : C4 The distance between the robot and the N p polygonal obstacles must obey to the following condition:

d(R, O i ) > ζ > 0, ∀i ∈ 1, ..., N p , (9)
where the distance d(R, O i ) is calculated by using equations ( 5), ( 6), ( 7) and (8). Now, the path planning problem is completely defined: find an optimal control and an optimal trajectory which minimise the optimal cost (2), constraits C1 to C4 and the terminal constraint q(t 0 ) = q 0 , the initial point. This problem is solved by using the flatness property of the system, the B-spline parametrization and constrained feasible sequential quadratic programming (for details see [START_REF] Defoort | Performance-based reactive navigation for non-holonomic mobile robots[END_REF]).

C. Supervisor

The algorithm of trajectory planning enables us to find a trajectory for the robot between a starting point D and the point of arrival G in the space of the configuration which guarantees:

• the acceptable controls for the robots (which take into account the nonholonomic constraint and the maximum speed) • the avoidance of circular and polygonal obstacles. The representation of more complex obstacles by the segments involves the appearance of local minima for the function d(R, G), [START_REF] Zapata | Simultaneous path following and obstacle avoidance control of unicycle-type robot[END_REF]. This function defines the distance between the current location of the robot and the objective to be reached. The problem of these local minima cannot be solved by the path planning algorithm. The idea that we have developed is to introduce a supervisor which according to the situation created by the obstacles, will give the robot some intermediate objectives. This supervisor must enable the robot to achieve the final goal by avoiding situations of local minima. The reach of the intermediate objectives is ensured by the path planning algorithm, which guarantees the respect of constraints. The supervisor acts according to the data received by the robot (its position and visible obstacles). It will then choose an intermediate objective for the robot. The trajectory between the current robot position and the intermediate objective is calculated by the path planning algorithm. Thus this trajectory will respect the various constraints imposed on the robot. The operation of the supervisor is inspired by the TangentBug algorithm. Just like this algorithm, the supervisor will switch between two operating processes: right mode towards the target and following an obstacle boundary mode. With each one of its interventions, the supervisor initially tests in which mode it must act, then it determines its intermediary objective following this mode.

1) Right towards the target mode: At each instant, the robot sees n s segments S j , which define the graph G 0 , (10):

G 0 = {A j , B j ∀j ∈ {1, ..., n s }} ∪ T if define (10)
This graph contains:

• ends points of segments which define the obstacles in the range of the robot sensors • the intersection point T between the line (RG) and the range of robot sensors when no visible obstacle cuts [RG]. The segments can no longer be identified as belonging to a particular obstacle since the knowledge of the environment is reduced to a local aspect. The algorithm defines the subgraph G 1 in the following way:

G 1 = {V ∈ G 0 | d(V, G) ≤ min (d(R, G), d Leave )} (11)
In fonction of the content of subgraph G 1 , (11), two cases can appear:

1. G 1 is empty The robot is then in the zone of attraction of a local minimum created by a single segment (i.e. Figure 4). The supervisor passes then in mode "following an obstacle boundary" after having saved the value of the local minimum:

d min = d(I min , G) (12)
with

I min the intersection point between [V 1 V 2 ]
and the line passing by point G and perpendicular with b. The robot is in the zone of attraction of a local minimum created by two segments (i.e. Figure 6). This situation appears if the vertex V p ∈ G 1 nearest to the objective belongs to two distinct segments S 1 and S 2 . The supervisor passes then in mode "following an obstacle boundary" after having saved the value of the local minimum d min :

(V 1 V 2 ).
d min = min (d(V p , G), d(G, S 1 ), d(G, S 2 )) (13)
c. If there is a segment blocking the vision of the objective (Figure 5), and if this one creates a local minimum, then the robot passes in mode "following an obstacle boundary" after having saved the value of the local minimum in d min . d. Lastly, if none of the preceding cases is presented, the robot moves towards the locally optimal direction, defined by V p , the nearest point to the objective belonging to G 1 . 2) Following an obstacle boundary mode: When the robot is not in the right towards the target mode, it is in the following obstacle boundary mode. This behavioral change happens when the robot meets a local minimum, of which it saves the value d min . In this mode, the robot will move along the contour of the obstacle while following an arbitrary direction (either definite according to local information, or fixed at the beginning). It still makes use of the local tangent graph to find shortcuts. It will switch in right towards the target mode once it finds a vertex V in its local graph of the tangents such that On the example given in Figure 7, the robot leaves the point D, in right mode towards the target. In a, it meets the local minimum P and passes in skirting mode of the obstacle while running to the left. It then follows the under-objective S G1 . It continues skirting while passing by S G2 . In b, the robot finds a point closer to the objective than the local minimum P in its graph. Then it switches to right towards the target mode while following the under-objective S G3 . Once in c, it sees G, the objective and joins it.

d(V, G) < d min (14)
The operating of the following an obstacle boundary mode is shown in the following organization chart (Figure 8):

IV. SIMULATION RESULTS

A. Comparison between the DVZ algorithm and the new path planning algorithm

The algorithm of planning trajectory based on the deformable virtual zones (DVZ) was tested in order to be able to compare it with the new proposed path planning algorithm using a supervisor. This one makes it possible to obtain good performances for simple scenes, containing convex obstacles.

The following example shows a use of this algorithm for a more complex scene containing a concave obstacle, forming a broad zone of minimum local. One can see on Figure 9 trajectories generated by the DVZ algorithm and by the algorithm of the supervisor to go from the starting point [START_REF] Kamon | A new range-sensor based globally convergent navigation algorithm for mobile robots[END_REF][START_REF] Magid | Cautiousbug: a competitive algorithm for sensory-based robot navigation[END_REF] to the arrival point (19, 19). The dotted line shows the trajectory generated by the DVZ method and the continuous line shows the trajectory generated by the new supervisor algorithm. The trajectory generated by the DVZ algorithm is far from optimality. However, the target is reached after a broad turning run time of 199 seconds. The algorithm of the supervisor will escape from the local minimum as soon as it has detected it, thus reducing waste of time in the zone of attraction. Run time is 107 seconds.

In the simulation presented on Figure 10, the conditions are identical, but, the objective to reach was moved into (20, 15). In this example, we can see that the DVZ algorithm does not manage to achieve the goal, and that the trajectory remains blocked in the zone of attraction of the local minimum (dashed line in Figure 10). The algorithm of the supervisor manages to escape from this minimum, after having detected it. The difference between these two algorithms is that the supervisor takes into account in its reasoning the knowledge of the obstacles structure in a general way, by knowing that if there is a blocking on the contour of the obstacle, it is possible to find a solution by moving around the obstacle. The DVZ algorithm is obstinate to approach the target, without taking into account this more abstract information concerning the case studied. There may be a configuration of the parameters of the DVZ bringing the robot to the objective, but for this same configuration, there would be a scene for which the robot would be blocked.

B. Simulation results for the new supervisor algorithm in complex map

We will test the effectiveness of our new path planning algorithm in a complex scene where the robot will often be in zones of attraction of the local minima. For simulations we consider that the range of robot sensors is 2 meters. The maximum speed value is 0.3m/s. All the programs are written in C. The first map configuration and robot displacement are shown in Figure 11. The robot puts 73.5 second to move between its initial position and its final position on the unknown map. the robot is practically always at maximum Figure 12 illustrates the robot movement in another complex unknown map. It must go from the initial point (4, 1) to the final point (13, 14). It reaches that point in 95,9 seconds. During the skirting of the second obstacle, it seems obvious to us that the choice of skirting is bad. However, provided only with local information, the robot can only have one locally optimal decision. This paper proposed a new path planning algorithm for a nonholonomic mobile robot moving in an unknown environment which contains obstacles. This algorithm is a generalization of the algorithm proposed in [START_REF] Defoort | Performance-based reactive navigation for non-holonomic mobile robots[END_REF]. The new algorithm takes into account obstacles which can be included in a polygon. For example it allows navigation in a labyrinth, which was impossible to realize by using the algorithm presented in [START_REF] Defoort | Performance-based reactive navigation for non-holonomic mobile robots[END_REF]. In order to solve problems of local minima, an architecture on two levels was developed. Indeed, a supervisor detects the problems of local minima and according to the nature of the problem met, it either goes right towards the target, or gets around the obstacle while following its contour. Effectiveness of the new algorithm was tested thereafter in simulation.

We compared it with algorithm DVZ because this algorithm is the only one which remains competitive compared to our starting criteria (take into account of the model of the robot and its physical constraints, avoidance of obstacles with unspecified shape and possibility of the implementation of the algorithm in real-time). These two algorithms were put in competition in the same environment. For a simple scene, method DVZ remains competitive, but in a little more complex environment, it does not manage any more to find a way to take the robot to its final point. Then, the algorithm of the supervisor was tested in more complex scenes in order to highlight its effectiveness. The algorithm proposed can be implemented in real-time, because the calculation of the optimal trajectory is done by using a receding horizon. It will be tested thereafter on a unicycle type robot.

Fig. 1 .

 1 Fig. 1. The car like robot

Fig. 3 .

 3 Fig. 3. The three cases for distance calculation

Fig. 4 .

 4 Fig. 4. Local minimum created by a single segment

Fig. 5 .Fig. 6 .

 56 Fig. 5. The local minimum created by 2 segments, local minimum on the segment

Fig. 7 .

 7 Fig. 7. Example of supervisor operating

Fig. 8 .

 8 Fig. 8. Organization chart of the following an obstacle boundary mode

Fig. 9 .

 9 Fig. 9. Comparison between the DVZ algorithm and the supervisor algorithm : first case

Fig. 10 .

 10 Fig.10.Comparison between the DVZ algorithm and the supervisor algorithm : second case

Fig. 11 .Fig. 12 .

 1112 Fig. 11. Simulation result by using the supervisor path planning algorithm : first map configuration

ACKNOWLEDGMENT

This paper was partially supported by the "Ensemble Innovons" Programme of Catholic University of Lille.


Sylvestre ; Delmotte

Santiago ; Lopez-Ridaura

Jean-Marc M ; Barbier

Jacques Wery

How to evaluate the impacts

Keywords: Prospective, Integrated, Multiscale, Participatory, Scenario evaluation, Agroecosystem Indicator, Model

The Camargue, South of France, is an agricultural region highly multifunctional and with strong issues linking the environment and the society. Evaluating scenarios of alternative agricultural systems extension in this region imply to use tools that allow Prospective, Integrated, Multiscale and Participatory Assessment of Agricultural Systems (PIMPAAS). In this paper, we reviewed the use of three approaches (BEM, ABM and LUCC) for PIMPAAS. After a presentation of the three approaches, we analyzed their advantages and drawbacks, and possible complementarities. As it is not possible to implement the three approaches together at one time, our aim was to make a choice for the Camargue. We found LUCC to be the least suitable approach, mainly because it does not allow participatory processes at farm scale. BEM and MAS appeared to be the most suitable tools as they allow quantitative and ex-ante studies and are able to incorporate the three sustainability domains. Their ways of up-scaling are complementary: BEM seems efficient for up-scaling from field to farm and field to region, whereas MAS allow up-scaling without aggregation from farm to region. We believe that the combination of the two approaches will enable highly participatory evaluations of alternative farming systems. Using the results of this analysis, we recommend using a combination of MAS and BEM in a global framework. We are currently implementing a framework in the Camargue to test this combination and to evaluate its suitability for prospective, multiscale, multicriteria and participatory evaluation.

INTRODUCTION

Linking agricultural production and nature conservation is one of the greatest challenges of land use systems nowadays, and the design of innovative, multifunctional, farming systems is a possible solution. The implementation of such innovative farming systems requires a set of coordinated actions at different scales to make sure that innovations (i) contribute to the economic and environmental objectives on a given region (increasingly important for the whole agricultural profession) and (ii) do fit in with the functioning of the farm as a whole and are compatible with the farmers' policy setting. Evaluating the impacts of the extension of innovative farming systems at regional scale requires a prospective analysis to shed light on the plausible consequences of their adoption at different scales and to identify the main opportunities and bottlenecks in their implementation. The views and evaluation criteria of different stakeholders operating at different scales (from farm to region) must be taken into account to enhance the chances of success in the implementation of such innovative farming systems. In the next paragraph, we argue why a Prospective, Integrated, Multiscale and Participative Assessment of Agricultural Systems (PIMPAAS) must be carried out. The approach is illustrated using the Camargue case study. The Camargue is a deltaic region in the South of France of 167 000ha among which around 70 000 are cultivated. Agriculture plays a crucial role in the economic, ecologic and social equilibrium of the region. It has been labeled as a reserve of biosphere (Man And Biosphere Program of UNESCO) since 1977, and it hosts also a Natural Regional Park, a National Reserve and many other associative or private protected areas. Several fauna and flora species are protected and eco tourism is an important activity.

Agriculture in the Camargue plays a crucial role in the water dynamics as most land is at sea level and salinisation is a natural process due to the negative water balance between rainfall and evapo-transpiration in this windy Mediterranean climate. Figure 1 shows a map of salt pressure in the Camargue. Salt pressure is closely associated to altitude being the lowlands the most exposed to this problem. In the Camargue, about 20 000 ha are devoted each year to rice production. It is the only place where rice production is done in continental France. Irrigation of rice plays a key role in desalinating the soils as fresh water from the Rhone river enters the delta (Figure 2). However, continuous rice production uses large quantities of pesticides, notably herbicides. These pesticides disperse throughout the environment and, given the high diversity and interest of the local fauna and flora, ecologists have long called for a reduction in the use of pesticides. Comparing figures 1 and 2, it can be seen that most continuous rice cropping systems does not necessarily takes place where maximum salt pressure occur. Re-allocating intensive (continuous) rice cropping systems in areas with high salt pressure and more extensive (with lower use of pesticides, eg. Organic) rice production systems in areas with less salt pressure, may represent a solution to both, salt pressure and pesticide use. This salt pressure and pesticide issue, is only an example of the kind of issues that require a PIMPAAS approach. The plausible consequences of the extension or redistribution of different agricultural alternatives must be analyzed at different scales, with a multicriteria perspective and in close interaction with local actors taking into account their individual values and strategies.

Organic farming in Camargue: need for PIMPAAS Prospective Organic farming has been presented as a potential way of reducing the externalities of actual agricultural practices, The French government has launched a program to reach 6% of the farm land converted to organic by 2012 and 20% by 2020 [START_REF] Barnier | Agriculture Biologique Horizon 2012[END_REF]. Organic farming represents yet nearly 5% of the total area of cultivated land in the Camargue; however rising 20% in 10 years poses new questions. An extension of the area will certainly have multiple impacts in the region: technical issues will arise such as the need of organic fertilizers in high quantity or the impacts of a decrease in irrigated area linked to the reduction of rice frequency in the rotations. Scenario evaluation of organic agricultural systems in this region implies the use of available data that are dispersed in term of origin and are scale specific: for example, data exists from experiments at field scale and many experts have knowledge about constraints and opportunities for the adoption of organic agriculture. There is then a need for a methodology that would help organizing these data for a prospective study. Integrated As shown in other European regions, the development of organic farming will have an important influence in the economy of farmers [START_REF] Darnhofer | Conventionalisation of organic farming practices: from structural criteria towards an assessment based on organic principles[END_REF]. However, it may also impact the economic, social and environmental equilibrium of the region through, for example the generation of employment, the quantity of rice available for cooperatives and processing industries, and the visibility of the region through an aura of 'organic region', what would certainly encourage green tourism and activities oriented to nature. Indicators must then be calculated for each of t the three sustainability domains: economic, social and environmental.

Coping with this multitude of criteria and indicators implies the use of integrated approaches, including knowledge from different disciplines such as economy, ecology and social sciences.

Multiscale

The organic option for rice production in the Camargue to avoid the build up of weeds and pathogens in the rice fields, is to break the continuous rice cropping and lengthen the rotations with dry crops (cereals and leguminous such as wheat and alfalfa). The extension of these systems in the region would certainly imply a decrease in the area of irrigated rice and therefore the quantity of fresh water entering the delta [START_REF] Chauvelon | A wetland managed for agriculture as an interface between the Rhône river and the Vaccarès lagoon (Camargue, France): transfers of water and nutrients[END_REF]. In fact, organic rice has to be rotated with other crops over five years [START_REF] Mouret | An integrated study of the development of organic rice cultivation in the Camargue (France)Challenges and opportunities for sustainable rice-based production systems[END_REF], whereas in conventional cropping systems, it is possible to grow rice continuously by using herbicides. If rice is included less frequently in the rotation, the quantity of irrigated fresh water will decrease, with possible consequences on the salinity of the Vaccares lake and on the area for feeding and reproduction of wild birds. As this last example shows, the decision of adopting or not organic farming is usually taken at farm scale and implemented at field scale, while the impacts of this adoption must be studied at farm and regional scale. The evaluation of the economic performance of a farm is commonly conducted on a yearly basis, whereas at the regional scale, the evaluation of economic performance of the agricultural sector is often averaged per decades. Therefore, a multi-scale approach in term of space and time is needed to study the plausible consequences of such conversion to organic agriculture in Camargue.

Participative

Multiple stakeholders have to be taken into account in the analysis of scenarios related to the extension of organic farming in the Camargue. Even if the farmers remain the main decisionmakers on which agricultural activities are carried out, other stakeholders can influence them through regulations, incentives, prices and services. For example, hunters pay farmers in the Camargue to keep rice fields flooded during winter making it impossible to grow a rainfed winter or spring crops in the following year. In the economic balance of the farm, it is then important to consider this side-activity and its impact on farmer's income and therefore choice for land-use. To take into account in the evaluation such local specificities, it is necessary to associate the stakeholders strongly in the evaluation of scenarios. This would ensure the consideration of local knowledge and perceptions, the identification of possible conflicts among interest of different stakeholders as well as possible synergies. Participative studies have been conducted in the Camargue to understand the links between fishermen, reed harvesters, hunters and ecologists [START_REF] Mathevet | Agent-based simulations of interactions between duck population, farming decisions and leasing of hunting rights in the Camargue (Southern France)[END_REF]. It becomes now important to expand such approach to the links between agriculture and environment in this territory. Carrying out a PIMPAAS in the Camargue has become necessary as the future of agriculture in this territory faces new challenges concerning the co-habitation of agricultural activities and nature conservation goals.

Based on a literature review (Delmotte et al., Submitted), we identified three approaches commonly used for scenario analysis in relation to agricultural systems and land use. They are based on modeling which is necessary for quantitative and explorative studies: (i) Bioeconomic models (BEM), (ii) Multi-agent models (MAS) and (iii) Land use/cover change models (LUCC). The objectives of this paper are (i) to present a comparative analysis of these three approaches (ii) to identifying their main advantages and drawbacks as well as possible complementarities, and (iii) to develop and apply a participatory, multi-scale, multicriteria method for scenario analysis of organic farming systems extension in the Camargue region, South of France

PRESENTATION OF THE THREE APPROACHES

Land Use / Land Cover Change models

Definition

The objective of Land Use/Land Cover Change (LUCC) studies is to describe the actual land use and to give insights on the possible changes of land use pattern that would occur in the near future following either some biophysical or demographic changes [START_REF] Veldkamp | CLUE-CR: An integrated multi-scale model to simulate land use change scenarios in Costa Rica[END_REF] or economic and structural changes [START_REF] Verburg | Land use change modelling: current practice and research priorities[END_REF]. LUCC approaches cover a wide range of methods but most of them are "descriptive models that aim at simulating the functioning of the land use system and the spatially explicit simulation of near future land use patterns" [START_REF] Verburg | Land use change modelling: current practice and research priorities[END_REF]. Land use is generally described in a raster based geographical information system. Each cell contains different economic, social and biophysical information such as population, land use, distance to the roads or markets. Statistical analyses are conducted to identify the drivers that are correlated with the observed past or current land use. These driving factors can be socio-economic aspects, such as demography and infrastructure (road, presence of a market for example), or biophysical aspects such as type of soil and climate. For scenario analyses, the demand of commodities is assumed as one of the main drivers for land use change. For each scenario, a new demand for each time-step of the simulation is formulated from past trends, experts knowledge or stakeholders opinions [START_REF] Veldkamp | CLUE-CR: An integrated multi-scale model to simulate land use change scenarios in Costa Rica[END_REF]. This demand is then converted quantitatively in area of land that has to be allocated to a specific land use. On the basis of the statistical relationship derived from the past and actual land use, probable hotspots of land use change are identified.

Applications

Different models exists in the literature for deforestation (GEOMOD 2, [START_REF] Pontius | Modeling the spatial pattern of land-use change with GEOMOD2: application and validation for Costa Rica[END_REF]), urban extension [START_REF] White | High-resolution integrated modelling of the spatial dynamics of urban and regional systems[END_REF] and agriculture (CLUE-S [START_REF] Verburg | Modeling the Spatial Dynamics of Regional Land Use: The CLUE-S Model[END_REF]). In CLUE (Conversion of Land Use and its Effect), correlations between the actual land use and biophysical and socio-economics factors are tested. These correlations are used to evaluate what would be the plausible change in land use following for example a change in commodity demand, policy instruments and, infrastructure development, [START_REF] De Koning | Multi-scale modelling of land use change dynamics in Ecuador[END_REF].

Bio-Economic Modelling

Definition

Bio-Economic Models (BEM) are economic models that include a biological component to take into account temporal variation of agricultural activities performance and impacts due to climate and soil factors variability. BEM aim at identifying optimum combinations of agricultural activities that maximize or minimize an objective. Optimum systems are often obtained using a Multiple Goal Linear Programming (MGLP) model where one goal is defined by an objective function, the others being described in constraint functions [START_REF] Janssen | Assessing farm innovations and responses to policies: A review of bio-economic farm models[END_REF]. This optimization has been done for objectives defined at different scales, most commonly at the farm (Janssen and van Ittersum, 2007) and regional scale [START_REF] Laborte | Multi-scale analysis of agricultural development: A modelling approach for Ilocos Norte, Philippines[END_REF]. In BEM, agricultural activities are quantitatively described at the field or livestock unit scale by their inputs and outputs (called technical coefficient) representing their performance in terms of desired goods and the environmental externalities attached to them. Commonly, each activity can be described by a set of data that give information on labor, nutrients balances, greenhouse gas emissions, use of inputs, expected performance considering interannual variations, and many others. These data can be obtained from different data sources such as interviews with farmers, experimental data [START_REF] Roetter | Combining farm and regional level modelling for Integrated Resource Management in East and South-east Asia[END_REF], expert knowledge [START_REF] Kerselaers | Modelling farm-level economic potential for conversion to organic farming[END_REF] and models (crop, livestock, soil dynamics models) [START_REF] Van Ittersum | Integrated assessment of agricultural systems -A component-based framework for the European Union (SEAMLESS)[END_REF]. Technical coefficients generators [START_REF] Hengsdijk | Quantification of land use systems using technical coefficient generators: a case study for the Northern Atlantic zone of Costa Rica[END_REF] can be developed that summarize the main processes and generate the inputs and outputs used for optimization models.

Applications

Mathematical programming, at the basis of BEM, has become a common tool in agricultural sciences in the last decades in support for decision-making and assessment of agricultural systems. Mathematical programming offers several optimization techniques being Linear Programming (LP) the most commonly used. LP has been widely used in agricultural economics with the objective function representing the economic rationale of the farmer's decision process, and the optimization aims at identifying the combination of agricultural activities that maximize an utility function. The utility function is defined in monetary terms, meaning that all objectives and constraints, as well as the technical coefficients describing the activities, have to be converted into money. In BEM, MGLP models are commonly used where objective functions and constraints are represented in separate equations keeping their own units allowing then a multi-criteria analysis taking into account indicators hardly convertible in money.

Agent Based Models

Definition

Agent Based Models (ABM) represents systems as agents in interactions, with a social structure, and using resources in an environment. Agents perceive, self-represent and act in its environment by taking decision and interact with other agents. Each agent has its own tendencies and objectives [START_REF] Ferber | Concepts et méthodologies multi-agents[END_REF]. ABM is an approach originally developed from computer sciences to study the dynamics of complex systems and reproduce phenomenon that emerge from the addition and interactions of individual behaviors. ABM can be based on multiple formalisms for representing the decision-making by the agents. This usually requires How to evaluate the impacts of the extension of alternative farming systems at regional scale? Delmotte, S. ; Lopez-Ridaura, S. ; Barbier, J.M. ; Wery, J.

a high quantity of information, as the behavior of each agent has to be defined. In case of human agents, decision-rules are often defined with thresholds and if-then rules (conditional). When agents are representing bio-physical components of the system, such as animals or abiotic resource, some more mechanistic models of the processes can be used. It can be seen as a very flexible tool, one of the main advantage remain the possibility to explicitly represent the interaction between agents and one or multiple natural resources and among different agents.

Applications

This individual centered approaches are increasingly used to represent nature-society interactions [START_REF] Ligtenberg | A design and application of a multi-agent system for simulation of multi-actor spatial planning[END_REF][START_REF] Monticino | Coupled human and natural systems: A multi-agent-based approach[END_REF], in particular in the domain of natural resources management (NRM) [START_REF] Mathevet | Agent-based simulations of interactions between duck population, farming decisions and leasing of hunting rights in the Camargue (Southern France)[END_REF][START_REF] Bousquet | Multi-agent simulations and ecosystem management: a review[END_REF]. Specific platforms such as CORMAS [START_REF] Bousquet | Cormas: common-pool resources and multiagent Systems[END_REF] or NetLogo allow to create simulations where agents are interacting with one or more resources. In the context of NRM systems, ABM often couples a cellular automaton representing a spatial area of land with a multi-agent model to represent the decision-making process of individuals deciding on the use of these spatial units [START_REF] Bousquet | Multi-agent simulations and ecosystem management: a review[END_REF]. This arrangement of models allows studying the interaction between the resources and the decisions in a dynamic manner. An agent is often linked to a specific area on which he is acting and his behavior will depend on its own objectives and on its interactions with the environment and with the other agents.

COMPARISON OF THE APPROACHES FOR PIMPAAS

In this part, we compare the 3 approaches on the basis of their suitability for PIMPAAS evaluations (Figure 3) (Delmotte et al., Submitted). The three methodologies compared here are not targeted to the same type of studies. LUCC aims at studying where land use change is the more probable to occur, while BEM aims to study what kind of agricultural activities are plausible for a given future and ABM are targeted to explore different pathways and natural resource management systems. For prospective assessment of agricultural systems, the previous paragraphs analysis have shown that BEM and ABM are the more suitable. Complementarities can even be thought such as the use of BEM for identifying plausible combinations of agricultural systems and ABM for identifying and simulating interactions between decision makers and stakeholders that could enhance the attainment of common objectives for a future. LUCC does not seems suitable for prospective evaluation of agricultural systems due to the inadequacy of the formalism for alternative systems, as it is based on statistical analysis between actual land use and drivers, and use projections.

In LUCC, main efforts have been directed towards improving the confidence on the probabilities for land use change. Less emphasis has been given to quantifying the impacts of such change and therefore integrated analysis of the consequences of such land use change is not carried out in LUCC studies. BEM and ABM both intrinsically incorporate multiple indicators: ABM in the form of criteria used by agents to take their decisions (normally not only one criteria) and BEM in the form of objective functions and constraints in the optimization. LUCC approaches are mostly carried out at high spatial scales ((sub/supra)national) and at long time horizon (eg. 30 years). For agricultural systems assessment, farm scale consideration is essential, a scale that LUCC can hardly incorporate because it is based on past regional trends ignoring decision making by farmers. Both BEM and ABM have been applied at different time and space scales, from the farm to the large region, from one to several year horizons. As these two approaches are able to take into account decisions of actors, including farmers, they appear more suitable for agricultural systems assessment. LUCC can be characterized as a top-down approach, meaning that it is devoted to policy makers giving instructions or ideas for management at low scale. BEM can be top-down or bottom-up depending on the choice done. In case it is bottom-up, the idea is that decisions and viewpoints at low scale can guide decision-making at higher scale. ABM as an individual based approach is always a bottom-up approach. As changes in agricultural systems are expected to come from farmers choices, a bottom-up approach seems to be more relevant, even if top-down approaches can give interesting insights on the systems behavior [START_REF] Castella | Combining topdown and bottom-up modelling approaches of land use/cover change to support public policies: Application to sustainable management of natural resources in northern Vietnam[END_REF]. No experience of LUCC approach applied in a participatory manner have been found in the literature. For BEM, results of participatory use are mixed as shown before, while ABM have good capabilities for participatory processes.

LUCC BEM ABM Prospective

Integrated

Multiscale

Participative

In conclusion of this comparison, BEM and ABM seem more suitable for PIMPAAS. However, each of the two approaches mentioned above have their own limits and complementarities between them have to be identified. In the next part, we propose a method for applying a PIMPAAS in the Camargue.

PROPOSITION OF A METHOD FOR PIMPAAS

Phase 1. From systems characterization to indicators selection

The first phase of the PIMPAAS approach is the characterization of the systems by each stakeholder and farmer. An exhaustive list of actors is built from different expert knowledge. Each actor is consulted individually to characterize its vision of the system and identify its scales of analysis. Some conceptual models are developed at the different actors' scales on the basis of a systems approach. The limits of the system, the internal components comprising biophysical aspects, actors and resources are identified and the elements of the environment representing the exogenous factors influencing the system are represented. The current and alternative agricultural activities at field scale or management systems at higher scale are identified through interviews with the different actors. While talking about alternative activities, actors are expected to expose and classify their visions of the future under the 'desired', 'undesired' and 'expected' classification. This helps in the next phases to build scenarios. Soil and farm typologies are also built during that phase. Finally, each actor proposes indicators at different scales of analysis for evaluating the different scenarios and they are discussed to be sure that we can calculate them. This first phase make emphasizes the participative nature of the evaluation as it is expected to allow the actors to explain and share their perceptions and visions of the systems. The first interactions are conducted in the form of individual interviews during which the whole framework is presented and first discussions on system characterization are conducted. A second interview with each actor is devoted to the identification of current and alternatives activities and indicators. The aim is to ensure, from the beginning of the process, a good representation of the actors view in the system's definition. Participation at this phase also ensure credibility for the models and calculations and allow to create a group of stakeholders for further collaboration.

Phase 2. Quantification of activities and main processes of the system

The second phase consists in data collection for the quantitative description of current and alternatives activities at different scales. Current activities refer to the main animal and cropping activities, including pastures, perennial crops and vegetable production. Alternatives activities refer to new practices, eventually conducted by some farmers but not developed in the region. It can be new crop rotations, new low input systems and more or less intensive livestock production systems for example. For this objective, existing crop models, data base, hydrological models, interviews and statistics are used, completed by expert knowledge in case of data unavailability. Some summary models [START_REF] Tittonell | FIELD--A summary simulation model of the soil-crop system to analyse long-term resource interactions and use efficiencies at farm scale[END_REF] are being developed for certain processes such as water balance at the regional scale. A technical coefficient generator is being developed consisting on a table with each possible agricultural activity described by its inputs and (desired or undesired) outputs [START_REF] Hengsdijk | Quantification of land use systems using technical coefficient generators: a case study for the Northern Atlantic zone of Costa Rica[END_REF]. Examples of input coefficients can be the quantity of nitrogen used and the working time; examples of output coefficients can be yield and grain quality for the performance of the activities, and greenhouse gases emission for its impacts. All the basic information necessary for the technical coefficient generator is obtained using the different tools presented above. For this phase, besides the use of direct information and models, experts are interviewed to complete and validate the initial quantification of the current and alternatives activities. Some of the actors engaged in the whole process of scenario evaluation are interviewed as experts in a specific domain (for example cropping systems) or for a specific compartment of the system (such as wildlife or surface water). At the end of this step, we plan to carry out a collective information meeting in order to (i) present and share the different views of the system (see Phase 1) and (ii) validate and legitimate the data and indicators calculation through a presentation and discussion of models and basic data.

Phase 3. Models for simulation of system's behavior and indicators assessment

The third step is to build the models for scenarios analysis through the indicators calculation. We reviewed different potential methods for PIMPAAS and identified possible complementarities between Bio-Economic Models (BEM) and Agent Based Model (ABM). Up to now, the literature of BEM-ABM coupled approach often refers to linear programming or recursive linear programming. However it seems more accurate for agricultural questions to use Multiple Goal Linear Programming in order to include empirical constraints and perceptions of actors through multiple indicators and multiple scale in the optimization process and not using an utility function [START_REF] Van Keulen | Quantitative analyses of natural resource management options at different scales[END_REF]. Coupling MGLP and an ABM would allow to gain in the simulation of the complexity of the systems at stakes and to simulate scenarios. The experience gained in research with use of ABM to organize actors interactions and negotiation could be used on the same way with a hybrid BEM-ABM approach. Experiences with ABM have yet been conducted in the area of Camargue [START_REF] Mathevet | Agent-based simulations of interactions between duck population, farming decisions and leasing of hunting rights in the Camargue (Southern France)[END_REF] and the possibility to use a BEM to identify the windows of opportunities in relation to several objectives for different stakeholders can be a strong advantage for its use in a participative manner. ABM would allow to simulate the impacts of land use decisions on the territory environment and would serve as support for role playing game. An ABM is built based on a real map of the Camargue with all fields delineated and incorporating information such as soil type, altitude, salinity pressure or distance to the closest road. The allocation of activities simulated by BEM for each farm type can be projected on maps to take into account of sub-regional biophysical particularities.

Phase 4. Scenarios assessment with indicators

The last phase consist in the scenarios assessments using the indicators and different representation of the systems at different scales (for example maps). The scenarios are built through the first two phases, starting from the main features of plausible futures from different actors point of view identified in the first phase. For example, farmers may expect an increase of input prices in parallel with a decrease of cereals prices, whereas a nature protection institution may expect an increase of supports for organic farming development or a new legislation concerning pesticides use. The scenarios will be finally defined in detail in the first collective meeting of this phase. The first evaluation of scenarios is conducted through realistic role playing games. Indicators value is calculated using the ABM and from the quantitative data collected in phase 2. Actors have to specify which decision they would take in front of different situation that could happen. For example, farmers have to explain which activity they choice for their lands considering a change of price of rice. In the quest for realism in the system's representation it is expected that decision will be complex. In this phase, complementarities between BEM and ABM will be studied. For example, BEM could be used as a decision support tool for the different actors while they are playing role playing games. BEM can be used for analyzing conflicting objectives through trade offs curves, possible impacts of change in prices on the land use and impacts of policies and regulations. ABM would serve in that case as a support tool for the role playing game, calculating indicators resulting from actors decision concerning activities. We will also study the possible coupling techniques between BEM and ABM to calculate the indicators at different scales for the different scenarios, the decisions of which activities being simulated by BEM. Finally, quantitative assessment of scenarios is conducted using the two kind of models, and actors are consulted in focus groups to give their opinion about the performance of the systems in the different scenarios. During the focus groups, they are invited to negotiate and define new scenarios to be evaluated in the next focus group. At least two sessions of focus group are expected for scenario evaluation. We expect to gain strong quantitative insights on plausible consequences of different alternatives agro-ecosystem and to identify the opportunities and bottlenecks for their development.

CONCLUSIONS

New CAP reform, volatility of commodities and input prices, climate change, and many other expected and unexpected changes will be responsible for agricultural changes. For farmers, as for other stakeholders of the Camargue, it becomes necessary to get prepared to this unpredictable future. At the same time, policies for sustainable agriculture are being developed as well as new alternatives, often poorly adopted by farmers. Our position is that a dialogue has to be set up between stakeholders acting at local/regional scales and the final users of the lands, i.e. the farmers, to evaluate plausible futures and negotiate consensus on a better way to manage the agricultural lands. This requires to develop an approach in the region of study for PIMPAAS. As different approaches have yet intended to assess alternatives systems with limited success, we started by reviewing their ability for PIMPAAS. Among the three approaches studied, i.e. LUCC, BEM and ABM, a great variety of methods, case-studies and experiences are available and well documented in the literature. BEM and ABM seem to be the most suitable approaches for prospective studies, LUCC being limited by its formalisms based on statistical regressions. ABM and BEM have a clear advantages concerning integrated aspects, compared to LUCC. All three approaches are highly suitable for multi-scale analysis, however the non-explicit consideration of the farm scale and the spatial extent of LUCC does not seems appropriate for assessing agricultural systems. Finally, ABM has a clear advantages over the other two approaches to carry out participative analysis and include several actors in a negotiation or vision sharing process. This review showed that complementarities have to be found between BEM and ABM and we proposed a new framework where we use these complementarities for PIMPAAS. This framework is being implemented and tested in the Camargue, and further developments will allow its evaluation.

Fig. 1 .

 1 Fig. 1. Cartography of salt pressure in the Camargue territory. Salt pressure is closely associated to altitude, the low lands being the most exposed to salt.

Fig. 3 :

 3 Fig.3 : Appropriateness of the three approaches for PIMPAAS.

ISDA 2010, Montpellier, June[28][29][30] 2010


Christian Sallé

Philippe Grosseau
email: grosseau@emse.fr

Bernard Guilhot

Philibert Iacconi

Mourad Benabdesselam

Gilbert Fantozzi

Guilhot Bernard

Detection of tetragonal zirconia in alumina-zirconia powders by thermoluminescence

Keywords: Al 2 O 3, Composites, Defects, Thermoluminescence, ZrO 2

I. Introduction

The objective of this work is to show that the thermoluminescence (TL) allows the detection of the zirconia tetragonal phase in the alumina matrix with a higher sensitivity than the X-rays diffraction technique (XRD). In order to discuss if we have the right conditions to favour the presence of the tetragonal phase of zirconia in our composites, we need to call back some well-known results on the appearance of the tetragonal phase, and its behaviour in the alumina matrix. Zirconia (ZrO 2 ) is monoclinic (m-ZrO 2 ) below 1170 °C, tetragonal (t-ZrO 2 ) up to 2370 °C, and then cubic (c-ZrO 2 ) at high temperature up to the melting point (2680 °C). [START_REF] Subarao | Phase transformations in Zirconia[END_REF] The tetragonal→monoclinic (t→m) phase transformation is martensitic [START_REF] Bansal | On a martensitic phase transformation in Zirconia (ZrO 2 ): I, metallographic evidence[END_REF] and has been widely studied because of its anisotropic behaviour and of the large volume increase (between 3 and 5%) which is involved [START_REF] Wolten | Diffusionless phase transformations in zirconia and hafnia[END_REF]. This transformation can be used for the strengthening of Al 2 O 3 -ZrO 2 composites ("transformation toughening"). This toughening can by due either to the transformation toughening or micro-cracking, depending on the size, amount and solute content of zirconia particles [START_REF] Hori | Mechanical properties of ZrO 2 -toughened Al 2 O 3 ceramics from CVD powders[END_REF].

The presence of zirconia particles, for an amount of ZrO 2 equal to 5 vol.% at least, [5 and 6] limits the abnormal grain growth of alumina during the sintering of the material. In Al 2 O 3 -ZrO 2 composites, the tetragonal phase is stable at room temperature only if the zirconia grain size lies between two critical values (from about 0.1 μm up to 0.5 μm), which depend on strains in the alumina matrix and on the amount of zirconia. [START_REF] Heuer | Stability of tetragonal ZrO 2 particles in ceramics matrices[END_REF] The fraction of tetragonal phase increases when the quantity of zirconia decreases (30% of tetragonal phase for 5 vol.% of ZrO 2 , but only 5% of tetragonal phase for 20 vol.% of ZrO 2 ) [8 and 9].

II. Experimental procedure

γ-Alumina used in this study is a commercial powder supplied by Baikowski Chimie, France, and synthesised by thermal decomposition of ammonium alum (NH 4 Al(SO 4 ) 2 •12H 2 O), process used to produce highly pure alumina (>99.99% Al 2 O 3 ). Then α-alumina is obtained by a thermal treatment of γ-alumina at 1400 °C under controlled atmosphere (oxygen). The zirconia is a commercial powder (supplied by Rhône-Alpes Chimie, France) and its purity is higher than 99%. XRD analysis shows that this zirconia powder exists in the form of monoclinic phase (baddeleyite). The mixtures of oxides, α-Al 2 O 3 and ZrO 2 , were wet ground in an organic solvent (acetone), with continuous stirring. Various mixtures are used: 1, 5, 10…wt.% of ZrO 2 . Five grams of each mixture were prepared. Then half part of these mixtures undergoes a thermal treatment under controlled atmosphere (oxygen), in order to reveal and study, by the techniques of X-ray diffraction and thermoluminescence, the effect of doping by zirconia on the alumina crystalline structure. This treatment is conducted by the procedure described in Figure 1. X-ray diffraction (XRD) experiments have been performed with a "Siemens D5000″ diffractometer using Cu-K α radiation (λ Kα =0.15406 nm) in a θ/2θ configuration. A database on CD-ROM is used for searching and retrieving X-ray powder diffraction patterns. For semiconducting or insulating solid crystals, the valence and the conduction bands are separated by an energy gap (Figure 2). When the crystal is submitted to ionising radiation (UV, X-ray, γ…), an electron-hole pair is formed in the valence band. The electron is free to travel through the conduction band and to fall into an electron trap. While, the hole travels through the valence band and falls into a hole trap. After irradiation, the trapped charges may escape if the temperature of the crystal is raised and may recombine together on a centre, which de-excites by photon emission. If the heating rate of the sample is constant and if the emitted luminous intensity is measured using a photomultiplier tube (PMT) linked to a pico-ammeter, some peaks are observed. Their temperature position is characteristic of the trap nature and their intensity depends on concentrations of both the traps and the recombination centres. For the irradiation, we expose the samples one minute under a UV lamp (λ=253.7 nm), or 5 min under a W-target (45 kV, 2 mA), at -190 °C, and then we keep the samples two minutes in the dark. The samples are then heated at 60 °C/mn in the case of UV exposure, and at 30 °C/mn in the case of X-ray irradiation. The emission is then detected by a Hamamatsu R562 PMT with a spectral response between 160 and 850 nm.

III. Experimental results

The TL of monoclinic zirconia has already been studied. [10, 11 and 12] Six peaks were found at -170, -140, -85, -30, 10 and 110 °C, [START_REF] Iacconi | Traps and emission centres in thermoluminescent ZrO 2[END_REF] (for a measurement at 30 °C/mn) and one of them (-30 °C) was attributed to the presence of tetragonal zirconia, which is present as foreign phase in the sample of monoclinic zirconia [12 and 13]. Each pure oxide was studied by TL after UV irradiation, before and after the thermal treatment (Figure 3). One can notice that the studied α-alumina presents no peak after UV irradiation. The monoclinic zirconia, which is used in this study, presents 6 TL peaks after UV irradiation situated at -170, -145, -90, -35, 0 and 95 °C, but the peak at -35 °C disappears after the thermal treatment. In the case of alumina-zirconia mixtures (before thermal treatment), we observe the same peaks as for pure zirconia, except the one at -35 °C which does not appear. On the other hand, the peak at -35 °C appears on the TL glow curve (Figure 4) obtained, after thermal treatment at 1400 °C under oxygen, from the same mixtures. Above 1170 °C, the stable phase of zirconia is the tetragonal one. The presence of tetragonal zirconia in the powder is detected by XRD, for mixtures realised with an amount of zirconia higher or equal to 10 wt.% and treated at 1400 °C (Figure 5): XRD being not sensitive enough to detect tetragonal zirconia for lower amount of zirconia the mixtures. In order to verify that the peak at -35 °C is due to the presence of the tetragonal phase, some experiments were done: Analyses achieved on mixtures by TL after X-ray irradiation, before and after the thermal treatment (Figure 6), lead to a glow curve presenting peaks of very weak intensity (150 times less intense than after UV irradiation). These peaks appear at the same temperatures than the peaks obtained under UV irradiation, and phenomena observed in that case (appearance of the -35 °C peak after the thermal treatment) are similar to those described first. After X-ray irradiation, peaks would have been very intense if they were due to the alumina, this material being more sensitive to the X-ray than to the UV irradiation (α-alumina obtained under oxidant atmosphere, is not thermoluminescent after UV irradiation). Thus, it can be concluded that all the observed peaks, particularly that at -35 °C, are due to the zirconia. We have also studied a commercial mixture (containing 10 vol.% of m-ZrO 2 ), allowing the stabilisation of zirconia in tetragonal form after sintering. This mixture is prepared in the following manner: an alumina powder (>99.9 wt.% purity) is homogeneously mixed with a monoclinic zirconia (> 99.9 wt.% purity) in distilled water, with a conventional mixingmilling technique. Subsequently, they are spray-dried. The final size of the grains in the mixture was measured between 0.33 and 0.40 μm. This mixture was characterised by TL and XRD, before and after the thermal treatment (with 1400 °C under oxygen). Before the thermal treatment, we observe by TL (Figure 7) an intense peak at -145 °C, a peak towards -50 °C, and a peak at 0 °C which is probably the characteristic peak of monoclinic zirconia at 0 °C. After thermal treatment, the peaks at -50 and 0 °C disappear, the one at -145 °C decreases and the peak at -35 °C appears. We observe by X-ray diffraction the presence of the monoclinic phase. But after the thermal treatment, almost all the monoclinic zirconia disappears and we observe a strong prevalence of the tetragonal zirconia (Figure 8). Complementary analyses were carried out on a mixture containing alumina with 5 wt.% of cubic zirconia, and on pure cubic zirconia, before and after the thermal treatment. The cubic zirconia presents no peak in TL after UV irradiation. The TL of the mixture does not present emission either. We can thus conclude that the peak at -35 °C was not due to the presence of cubic zirconia.

IV. Discussion

The thermal treatment of α-Al 2 O 3 -m-ZrO 2 mixtures allows us to reveal the appearance of a peak at -35 °C by low temperature TL after UV irradiation. This peak is not due to the presence of alumina as it is shown by the TL glow curve obtained after X-rays irradiation. For the commercial mixture, the zirconia monoclinic phase disappearance, after the thermal treatment, coincides with the disappearance of the TL peak at 0 °C, and with the appearance of an intense peak at -35 °C. So this peak is not due to the presence of monoclinic zirconia. After complementary experiments carried out with a cubic zirconia, for which no light emission by TL is observed, it is reasonable to attribute the appearance of the TL peak at -35 °C to the presence of tetragonal zirconia stabilised by the alumina. Society, 2003, 23(5), 667-73, doi:10.1016/S0955-2219(02)00161-9 4 Furthermore the presence of the peak at -35 °C in the thermogramme of the pure monoclinic zirconia (Figure 2), can be explained by the presence of tetragonal zirconia in our commercial monoclinic zirconia. Indeed, thermal treatment led to grain growth in zirconia. The grain size becomes higher than the critical size which the zirconia remains tetragonal at ambient temperature. The small amount of tetragonal zirconia is thus transformed into monoclinic zirconia. Then the disappearance of the peak at -35 °C in the thermogramme of the thermally treated powder is observed.

Journal of the European Ceramic

V. Conclusion

The presence of zirconia tetragonal phase stabilized by alumina can be detected in aluminazirconia composites by the thermoluminescence technique. Moreover, the detection limit of this technique is appreciably better than with the X-rays diffraction technique. Indeed, for an amount of zirconia lower than 10 wt.% in the composite, XRD does not allow to detect the presence of tetragonal zirconia, while the peak at -35 °C is still appearing for only 1 wt.% of zirconia by TL method.

Figures 5 F

 5 Figures