Magnus Löf
email: magnus.lof@ess.slu.se

Thierry Améglio

André Granier

Catherine Collet

EFFECT OF FIELD VEGETATION CONTROL ON WATER FLUX IN OAK SEEDLINGS EVALUATED BY THE HEAT BALANCE METHOD

Introduction

In Europe, oak species are among the preferred species in terms of sustainable land use. Oaks are grown at fertile sites, where the development of natural vegetation is abundant. One of the major problems in the regeneration of oak stands is the competition with natural vegetation (Collet et al. 1996, Davis 1985). When explaining growth in seedlings during competition between herbaceous vegetation and seedlings, soil water content is often used to define the availability of water (Löf 2000). The rate of photosynthesis is correlated to transpiration rate and studies shows a strong relationship between growth of plants and the amount of water consumed (Hanks and Rasmussen 1982). However, seedling transpiration does not necessary follows the availability of soil water content (Améglio et al. 1999, Löf andWelander 2000) and it is important to measure seedling transpiration in order to evaluate the importance of water competition in the seedling-grass interaction.

The constant stem heat balance method that was first implemented on small plants by Sakuratani (1981Sakuratani ( , 1984)). It was later developed and commercialized (Baker andVan Bavel 1987, Steinberg et al. 1990). However, one disadvantage with this commercially available technique is that heat storage of the stem is not taken into account, something that may lead to incorrect results. This has been taken into consideration when the method has been improved by measuring heat storage (Valancogne and Nasr 1993).

In this study we used the latter method for measuring the response in seedling transpiration to four different treatments of vegetation control. The specific objectives of the study were: 1) to examine whether grass limit water uptake in seedlings; 2) to figure out if it is possible to use the technique for measuring transpiration in small seedlings over long periods.

Materials and Methods

The experiment was set up at a field near Nancy, eastern France. In May 1998 one-year-old bare root oak seedlings (Quercus petraea) and grass (Deschampsia cespitosa) were planted in clay soil. Two treatments (bare soil and grass) were applied from spring 1998 until autumn 2000. Both treatments were regularly irrigated during summer to avoid soil water deficit. In spring 2001, only half the plots were irrigated for obtaining dry conditions in half of the experiment. Thus, in 2001 the treatments were: 1) Irrigated bare soil; 2) Bare soil; 3) Irrigated grass and 4) grass.

In the summer of 2001, seedling transpiration was measured with the heat balance method according to Valancogne and Nasr (1993). In each of the treatments, three seedlings, with a basal diameter ranging from 1 to 2 cm were selected. The sap-flow sensors were installed at the end of June 2001 and measurements were taken from the middle of August to the middle of September. Only one level of heating power was used during day and night. The measurement system consisted of a series of thermocouples and a heating system installed at seedling base, and connected to a datalogger and a multiplexor (Campbell, Scientific Inc., UK). Measurements were made every minute and 10-minute-average values were collected.

A high number of seedlings presented a multiple-stemmed morphology. On these seedlings, sap flow was measured on one stem, and whole seedling transpiration was calculated by multiplying the values obtained on the selected stem by the ratio of total seedling leaf area to the leaf area on the selected stem. The leaf area on the selected stem and of the whole seedling were calculated using dry mass of leaves and the leaf area ratio of sub-samples.

Results and Discussion

An example of sap flow (≈ transpiration) is given in Figure 1. Mean sap flow followed vapour pressure deficit during day time with a large variability among seedlings. The bare soil treatments resulted in higher sap flow in seedlings than in the grass treatments, irrespectively if combined with irrigation or not (Figure 1). However, during other days these differences were equalized (data not shown). The amount of water consumed per seedling was correlated to total leaf area without distinct differences between treatments (Figure 2). Total leaf area was reduced in treatments with grass.

In the end of August, soil samples were taken in the two grass treatments. Drought was recorded in one layer at about 20 cm soil depth in the part that was not irrigated. However, the growing season of 2001 was wet and cold and probably no large differences in soil moisture occurred between the four treatments. We conclude that the heat balance method is a valuable tool in studies of competition between herbaceous vegetation and seedlings. Principally, since it give very detailed information on transpiration. However, problems occur when information on transpiration is needed over long time periods. First, several tree species have a periodic shoot elongation with several flushes. Thus, total leaf area of seedlings has to be measured continuously over the measurement period. Secondly, in treatments with rapid growth the stem diameter change.

Stem diameter is one of the base-variables for calculating the heat fluxes in the heat-balance method. This means that a variable stem diameter has to be used for the calculations or even that the sensor may need to be changed to adjust a larger diameter. Finally, we observed secondary root growth and fungus on the stem when the sensors were taken away after the experiment, but we do not know if that can modify the calculation of the transpiration.

Figure 1 .

 1 Figure 1. Mean (n=3, in each treatment) sap flow in four treatments during a sunny day in August 2001. Sap flow=cm 3 (water) per cm 2 (leaf area) per minute.

Figure 2 .

 2 Figure 2. Mean daily transpiration in relationship to seedling leaf area in four treatments during a sunny day in August 2001. Each point represent one seedling.


M Chevalier

C Bernard

Luciana Parisi

C Audrain

M Tellier

Francois Laurens

Pathogenicity of virulent Venturia inaequalis on four apple clones

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


Marion Desquilbet

Stéphane Lemarié

Fabrice Levert

farmers and upstream companies : an ex ante evaluation

Keywords: StéphaneLemarié, INRAESR, UniversitéPierreMendèsFrance, BP47, 38040Grenoble

à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

assume that the innovator introducing the GM program will have a behavior of profit maximization at the scale of France. The analysis we propose here allows to give an estimation of the profit level of this innovator, for different levels of price premia on the GM seed. It will then be possible to give an estimation of the profit of this innovator for different levels of the price premium on the GM seed, and to show the one that maximizes its profit.

2. Assumptions and framework 2.1. General assumptions Simulations are conducted under five restrictive assumptions.

-We ignore the potential price decrease in farm prices and re-allocation of farm areas between crops. In a general way, in our framework, a farmer decides to adopt a GM variety on a given cop if the adoption leads to productivity gains, by a decrease in production costs and/or an increase in yield. At given farm prices, the profitability of this crop increases for farmers having adopted the GM variety. This may lead to an increase in the aggregate supply level of this crop, at given farm prices, for two reasons. Farmers may increase the area allocated to the considered crop, to the detriment of other crops, because of the increase in its profitability. This effect may be reinforced by an increase in yield. The adjustment towards a new equilibrium between supply an demand leads to a decrease in the farm price of the considered crop. The size of the effects on areas and prices depends on different factors, notably the nature of the change in the relation price -supplied quantity due to GM adoption, the relation pricequantity demanded, the public policy instruments used on the crop considered. Here, we examine the incentive to adopt for different kinds of farmers, given the expected effect on GMOs on their production costs, but we do not examine the aggregate effect of adoption at the national level on adjustment of supply and prices.

-We do not take into account negative externalities, from risks of gene transfer towards weeds.

-'We do not take into account indirect effects. Some farmers may find it interesting to adopt GMOs because they have an interesting indirect effect (e.9., a gain in time at a critic period).

Our simulations on GM adoption by farmers are only based on direct effects of GMOs on the profit level, by economies in herbicide use.

-The effect on herbicide prices is exogenous. As will be shown, for given prices of conventional herbicides, GMOs lead to a decrease in herbicide sells. In reaction, the optimal price of the GMO innovation tends to decrease too. Rigorously, the work on the GM tariffication must then rely on an analysis of market equilibrium displacement. In this paper, we only consider scenarios ofexogenous decrease in conventional herbicide prices.

-The cost of segregation of GM and non-GM channels is ignored. The estimated impact of GMOs assumes that farm production is sold on the standard market, and that the diffusion of GMOs does not affect the cost of other crops. If we assume GM diffusion in France, the most probable scenario is one where a GM and a non-GM channel co-exist. Having a GM production would then lead to an increase in the cost of segregation of these two channels.

This effect is ignored here.

In our analysis, we retain three types of actors:

-Farmers. Each farmer arbitrates between the choice of a conventional plant protection program and a GMO plant protection program. His choice will go to the program appearing as the most profitable one. Because the GMO program is new, the farmer however may possibly stay on the conventional program if the gain brought about by the GMO program is not sufficiently high.

-Suppliers of conventional herbicides. We assume that they gain a constant margin from selling conventional herbicides. Given the lack of information on these margins, we were constrained to assume an identical margin on all products. In first place, we assume that the same conventional herbicides are supplied with the same price. Then, we assume that they react by decreasing their prices.

-The innovator. This actor supplies the event of transformation that allows to conduct a GMO-type program of plant protection. We assume here that the event of transformation has already created with sunk costs of research and development. In the case of an HT crop, simultaneolls use of the GM seed and the total herbicide to which this seed is tolerant (called GMO herbicide" for simplicity reasons) are needed in the GMO program. The profit of the innovator is the sum of profits gained from selling GM seed, plus, possibly, profits gained from selling the complementary herbicide (different cases will be studied). The price premium paid on the GM seed is supposed to be a total gain for the innovator because the production cost of the GM seed is approximately equal to the production cost of the conventional seed. We consider that the innovator maximizes its profit by choosing the GM seed price premium level while he cannot change the price of the GMO herbicide. At least, for the time being, we assume that there is only one innovator.

Three types of actors are ignored:

-Seed producers.In reality, seed producers sign a license agreement with the innovator who allows them to use the GM event of transformation in their varieties. By assuming that all the price premium on the GM seed is a profit for the innovator, we assume that: (i) the license agreement stipulates the existence of royalties on each bag of GM seed, (ii) seed producers are in perfect competition on the supply of the GM event of transformation and are constrained to sell the GM seed at a price equal to the sum of the price of the conventional seed and the royalties that will be paid to the innovator. In other words, once royalties deduced, the seed producer has the same margin by bag of seed, whether GMO or conventional. This is an extreme assumption: we know from the American experience that the innovator is constrained to give an additional margin to the seed producer, in order that this seed prodr"rcer is willing to rcalize the necessary investments to integrate the event of transformation is it varieties. The few available data suggest however that the margin given to the seed producer are small (around l0 to 20Vo of the price premium on the GM seed).

-distributors distribute GM or conventional seed and herbicides. Nothing lets believe that the margin they are rcalizing is higher for GMO solutions compared with non conventional solutions.

-Downstream actors. As indicated above, farm production prices are assumed constant. Then, no surplus transfer happens towards actors downstream to the farmer. In addition, downstream actors are assumed to yield the same utility from farm production, whether it comes from GM or conventional crops.

In summary, we adopted some reductive assumptions to keep our framework simple. Then, it is necessary to keep three observations in mind:

-What we consider here as the innovator profit actually covers the innovator profit and the profit of seed producers who create OGM, with the part going to seed producers being small.

-The innovator profit remunerates some sunk costs that have been encountered to bring the innovation on the market, i.e. research costs and costs of tests necessary to bring the innovation on the market.

-Gains of farmers do not take into account transfers to the downstream sectors that will happen if there is a price decrease. In other words, the gain of farmers should rather be considered as the gain of farmers and downstream actors.

Under this set of assumptions, we now define the simulation method. We start by an observation on the conventional program used by each farmer and its per hectare cost. For each type of conventional program, an alternative GMO program allowing to reach the same yield is proposed. In other words, farm gain relies only on a decrease in weeding costs.

Depending on the cost decrease (or cost increase) of the GMO program compared with the conventional program, the farmer chooses to keep the same conventional program or to adopt the alternative GMO program. After aggregating farmers'choices, it is possible to draw the curve of demand for GM seed as a function of the price premium of the GM seed compared with the conventional seed, and to estimate the gains of the innovator and the losses of suppliers of conventional herbicides.

Even with this simplified framework, estimations depend on many variables, among which some are known better than others, with three cases:

-Some variables are well known and should not change much after the introduction of GMOs. They are the per hectare quantities of herbicides and the correspondence between conventional and GMO programs. These variables keep the same value in all our estimations.

-Some variables are not very well known or may change once GMOs are introduced. They are the margin on herbicides, the minimal gain that farmer anticipates to choose to adopt the GMO program, and the price of conventional herbicides that may decrease after the introduction of GMOs. For each of these variables, we conduct a sensitivity analysis.

-The price premium on the GM seed is endogenous in our model. Results are presented with a large range of values of this variable or at the optimum of the innovator (i.e. when the price premium on the GM seed maximizes the profit of the innovator).

Analytical framework

We use index .i for farmers; index ft of the type of rapeseed, taking two values, c for conventional rapeseed and g for GM rapeseed; index I for conventional herbicides. We let p denote the farm output price; wf denote the additional price paid on the GM seed compared with the conventional seed (latter called "license price"); wi denote the vector of prices of conventional herbicides ( wi, being the price of conventional herbicide l); wf denote the price of the GMO herbicide g (i.e., the total herbicide to which GM rapeseed is tolerant); A denote additional profit for which the farmer adopts GM rapeseed. Variables specific to farmer j are yy, denoting yield obtained by farmer j (assumed identical for GMO and conventional rapeseed); si , denoting rapeseed area for farmer j; hi, denoting per hectare quantity of conventional herbicide iby farmer j; hf , denoting per hectare quantity of GMO herbicide g by farmer l; c; , denoting all other costs of farmer j including the cost of the conventional seed. Total area allocated to rapeseed is constant and given by ,S = I r, .

Farmer.i 's profit on one hectare of conventional rapeseed is "quut to his revenue (price multiplied by yield) minus his costs ( cost of conventional herbicides, all other costs): /T'j( p,w;,w,, )= p ! 1-\{*;, h", )-c, Farmer.i 's profit on one hectare of GM rapeseed is equal to his revenue (price multiplied vby yield) minus his costs (GMO herbicide cost, GM seed license price, all other costs): ni( P,*i,wl,w, )= P ! i -*i, h; -wÏ -c i These profits are functions of input and output prices. In the case of a conventional program, per hectare quantities of conventional herbicide h'u are assumed optimal for the farmer given his specific characteristics and given output and input prices.

In the case of GMO program, we establish a correspondence between the characteristics of the conventional program initially conducted and the characteristics of the GMO program appearing as optimal. This correspondence was established in link with the French technical institute for oilseeds, Centre Technique Interprofessionnel des Oléagineux Métropolitains (CETIOM). It depends on the number of herbicide applications.

Adoption condition

Farmer.i adopts if the profit with the best GMO program yields an additional profit at least equal to ^ compared with the profit obtained with the best conventional program.

Equivalently, farmer.i adopts the GMO program if it yields a cost economy at least equal to À compared with the best conventional program.

ni( p,wi,,w.! )-ir:( p,wi, )> A * I( wi,, h'u )-wf, h: -w! > a Note that our comparison in profit levels is equivalent to a comparison in cost levels for two reasons: (i) we assume identical yields for both programs, (ii) we assume an identical output price for both types ofrapeseed.

The preceding equation may also be written as:

xi( p,wT,,wT )-f i( p,w;, )> A ë )rl < 1,.;, h'u )-wt hi -a
Wedefineavariable Tsequal tol if farmerjadoptstheGMOprogramand0if farmerT stays on a conventional program:

T i=l e r* . r( wi, hi, )-wf hi -a Ti =O ë w"s >\{*'r, h'u )-wf, h: -A

In what follows, we analyze adoption as a function of the GMO seed license price, w.f , for given price levels of other inputs. For farmer j, the preceding equation shows that adoption occurs only when wi if less than a threshold valuo, given by Z(*;, h'u)-wf, hT -A. This threshold value is different among farmers. Moreover, it is a function of prices of conventional herbicides, wi, price of the GMO herbicide, wf , and the minimal additional profit level, A.

Besides, we note in the preceding equation that the value of parameter T1 (0 or 1) does not depend on variables wf and A independently, but depends on the sum of these two variables, ( w.l + A). Let us then consider the effect of an increase in parameter À from an initial value Ar to a final value Az (i.e. an increase in the additional profit needed to "convince" farmers to adopt the GMO program). All other things equal, the adoption condition for farmer i stays unchanged if: (w;l IA,=wlr+4), i.e., if the GM seed license price decreases from an initial value ryf, to a final value wf, = vvf,+ 4-4.

Adoption rate When adopted by a farmer, the GMO program is adopted to its whole area allocated to rapeseed, s, . The GMO adoption rate is defined as the share of total rapeseed area where the GMO program is adopted: n4=1Iu., .

S a" r

(From what precedes, we note that, all other things equal, the GMO adoption rate stays unchanged when parameter  increases from A1 to L2, if the GMO seed license price decreases from wl to w!, = wi + 4-D.

Input demand

The total GMO area is the sum of GMO areas for farmers adopting the GMO program:

,s* =)r, s, Total sales of the GMO herbicide are equal the sum of per hectare quantities used multiplied by areas adopting the GMO program:

O* =I v hl s ^LJ' J .I J i 10
Total sales of each conventional herbicide I are equal to the sum of per hectare quantities used multiplied by areas staying in a conventional program: Qï =\{t-71 ) h'u s, i Profits Here, we make the three following assumptions. The company selling the GMO innovation also sells the GMO herbicide. The margin rate on herbicides, denoted by Q, is identical for all products. The production cost of the GM seed is equal to the production cost of the conventional seed (in other words, the margin on sales on the GMO is equal to lÙOVo).

The profit of the innovator selling the GM seed is equal to the sum of profits from sales of GM seeds (GM seed license price multiplied by the toal GMO area) and profits from sales of the GMO herbicide (margin rate on the GMO herbicide multiplied by the total quantity of GMO herbicide that is sold). II'=wl Ss +wl QQt .

Profits from sales of the conventional herbicide i are equal to the margin rate on conventional herbicide I multiplied by the total quantity of herbicide I that is sold: il, =w,i QQi .

Total profits of farmers on rapeseed are equal to the sum of profits of farmers adopting the GMO program and profits of farmers staying on a conventional program: n,, =Lr ,W, n; +îy ,hr:l i This total profit may be written as: lI" -n; -CHo , where IIf; is the total margin realized by farmers on rapeseed before deducting herbicide costs, and CI{ is the sum of weeding expenses for all farmers: II,',' =\s,( p y j -c i) .

.i Under our assumptions, lIfi is a constant independent on the adoption rate of GMO programs.

CH" =Zrl, ,wi hi +w,, nl )+(t-Ti,[If r;, n; nr, r;)] iL = rry,l s* +wl, er *Z*i e,

The sum of weeding expenses is composed of two terms. The first one is equal to total expenses on the GMO herbicide. The second one is equal to total expenses on conventional herbicides.

Simulations

3.1. Data Our analysis is led using a data from the farm survey "charte environnement" from CETIOM led in 1999 (1999 harvest). Our database is composed of 1238 farms covering atotal rapeseed area of around 32 000 hectares (2.47o of the French rapeseed area). Sampling bias was corrected attributing a weight to each farm in order to ensure national representativeness of French geographic departments and of rapeseed area classes. Then, results presented here are national projections on the i.369 millions hectares of rapeseed in France.

The distribution of weeding costs in the sample (Figure 1) shows the important diversity of conventional strategies of plant protection. Globally weeding expenses vary between 0 and 1300 F/ha, with a mean of 541 Flha. It rnay take up to three applications to weed rapeseed, at the following stages: pre-sowing, pre-emergence, and post-emergence. Each type of program was then defined by a three-digit code, each digit indicating whether there was application (code l) or no application (code 2) at the pre-sowing stage (first digit), pre-emergence stage (second digit) or post-emergence stage (third digit). For example, a program "101" corresponds to two applications, the first one àt the pre-sowing stage, the second one at the post-emergence stage. The GMO program range of herbicide costs (FFlha) considered here is a program combining the total herbicide Roundup (glyphosate) with a rape seed resistant to Roundup (or Roundup-Ready@ seed). Strategies of conventional/GMO replacement (Table 1) have been defined using Gigandon and Pilorge (1991) and CETIOM data (2000). The herbicide cost of the GMO program varies between 100 and 2Û0F/hectarc, the average price used for RoundUp (whr) being equal to 50 F/1. Figure 2 and Figure 3 indicate the cost distribution of the two sub-samples corresponding to GMO programs with respectively one and two RoundUp applications. In our first simulations, before the sensitivity analysis, prices of conventional herbicides are assumed constant and margin rate on conventional herbicides is assumed equal to 50%o. * The absence of post-emergence application may result from the absence of an fficient product. In this case, a second application with the total herbicide could be pertinent. We do not account for this fact here. Figure 3. Distribution of herbicide costs for programs 101 , 0l 1 , and 1 1 1 (corresponding to an two-application GMO program)

Base case

Adoption of GMOs

Figure 4 represents the adoption curve of GMOs as a function of the GM seed license price (w8,). When the GM seed price is equal to the conventional seed price (w8.,=0), the adoption rate is higher than 90Vo.In this case, the cost of a GMO herbicide program varies between 100 and 200Elha. Then, from the conventional herbicide cost distribution (Figure 1), it is clear that GMOs are generating cost savings for many farmers. On the opposite, for a GM seed license price exceeding 600 F/ha, the adoption rate is less than lOVo. Here too, from

Farmers' herbicide expenses

To begin with, we study the evolution of farmers'herbicide expenses for different levels of the GM seed license price (i.e., for different levels of adoption of GMOs).

On the right of Figure 5, the GM seed license price is very high and deters all farmers from adopting, even farmers with high conventional herbicido expenses. All farmers keep their conventional herbicide cost: this is the reference situation of the survey, where total herbicide expenses are around 750 MF.

When going to the left, the GM seed license price decreases and becomes attractive for some farmers. These farmers adopt as soon as the cost of the GMO program equals the cost of conventional herbicides. When adopting, farmers stop having expenses on conventional herbicides. Weeding expenses then are composed of expenses on conventional herbicides, expenses on the GMO herbicide, and additional expenses due to the GM seed license cost.

Then, as the GM seed license price decreases, the increasing adoption leads to a high decrease in total weeding expenses by farmers. Under our assumptions, the expenses decrease from 750 MF to 200 MF when the GM seed price equals the conventional seed price. Gains and losses of upstream companies

Here we assume that the innovator sets the GM seed license price in order to maximize its profits. Then, he arbitrates between a small license price allowing a large adoption of the innovation but yielding a small unit margin, and a high license allowing a large unit margin but restricting the adoption of GMOs.

Figure 5 gives a first indication on this optimum.

If the profit of the innovator is only based on royalties on sales of GM seeds, a maximum is reached for a GM seed license price equal to 321Flha. The profit of the innovator is then equal to 329 MF and GM varieties are adopted on75Vo of French areas (Figure 4). Assuming that the innovator's profit also includes gains on sales of the complementary GMO herbicide (Figure 6), then the optimum GM seed license price is also equal to 321Flha.In other words, counting or not margins on sales of the GMO herbicide in the innovator's profit does not change the optimal GM seed license price. This results is due to the low price of the complementary GMO herbicide.

I6

Figure 6. Gains of the innovator, with or without taking into account revenues from sales of the GMO herbicide

Let us now consider the competitors on conventional herbicides. Assuming a margin rate (/) equal to 50Vo,losses of upstream companies on conventional herbicides increase from 0 to 371MF when the GM seed license price decreases from 1000F/ha to 0F/ha. When the innovator chooses the optimal price (w's=321F/ha),losses are equal to32I MF, i.e. 85Vo of the initial profit. Then, it can be expected that conventional herbicide sellers react by decreasing their prices. This case will be studied latter (sensitivity analysis). Figure 8 sums up gains and losses by all upstream companies. For a GM seed license price smaller Than 228 FF/ha, losses on conventional herbicides are higher than gains of the GMO innovator. The upstream sector is then globally loosing compared with the reference situation.

On the opposite, if the GM seed license price is higher than 228 FF/ha, then the upstream sector globally wins compared with the initial situation. This situation is due to a smaller herbicide production costs for the GMO program compared with conventional programs.

Effectively, the production cost of the GM seed is equal to the production cost of the conventional seed. The production cost of the GM herbicide represents 50 to 100 F/ha depending on the type of GMO program (l or 2 applications). The production cost of conventional herbicides represents 50Vo of sales of conventional herbicides and is generally higher than 100 F/ha. Note, however, that these estimations depend on the rather arbitrary assumption of an identical margin rate on all conventional pesticides. This will be discussed Iatter with the sensitivity analysis. innovator's prof it on GM seed license and GIVIO herbicide minus losses of sellers of conventional herbicides 400

Global assessment of gains and losses Table 2 summarizes gains and losses of different actors by combining the reference situation with the situation in which the GM seed license price is set to its optimal level by the innovator (321F/ha). The adoption of GMO programs leads to a global gain of 245.3MF.

Two thirds of these gains are transmitted to farmers while one third of these gains accrues to upstream companies. A high share of the innovator's gains is realized to the detriment of upstream companies. Their profit decreases by around 32ll|dF, which is roughly equivalent to gain on the GM seed. Farmers'weeding costs +161 Total in the situation with GMOs +245 * The GM seed license price is equal to 32lF/ha.

Impact on the use of conventional herbicides

We observed that commercialization of GMOs with a GM seed license price equal to 321Flha leads to a 85To decrease in total sales of conventional herbicides. This decrease, however, is not homogenous on all products (Table 3). Thus, among the main conventional products, Colzor and Novall suffer a higher decrease (95Eo) than Treflan and Fusilade (707o).

This difference is mainly explained by the cost of these herbicides in a conventional weeding program. Based on the average per hectare quantity in conventional programs (before the introduction of GMO), Colzor and Novall represent a cost higher than 450 F/ha, while Tréflan and Fusilade represent a cost smaller than 150 F/ha. Thus, when a product represents a high cost, he is mainly used in high cost conventional programs, which will be more easily replaced by GMO programs. * The GM seed license price is equal to 32IF/ha.

Sensitivity analysis

Sensitivity to the additional profit at which farmers adopt GMO programs (^)

Figure 9 gives some indications on the sensitivity of our results to the minimal gain that has to be anticipated by the farmer in order to adopt (variable A). As shown in section 2, the adoption rate stays unchanged when the GM seed license price, wf , decreases by Â.. This leads to a translation of the demand curve to the left (when À increases). The estimated adoption loss when  increases by 100 F/ha varies between lOVo and 25Vo depending on the GM seed license price. In the same way, we could observe that the curve of conventional weeding costs (Figure 4) translates to the left by Â.. The profit curve of the innovator (Figure 10) decreases because of a given license price the adoption rate is always smaller. The maximum of these curves translates to the left when  increases: in reaction to the more difficult adoption of GMOs, the innovator increases its profit if he decreases the GM seed license price by À. Then, the adoption rate at the optimum stays unchanged. When we examine the global balance of gains and losses of different actors (Table 4), we note that an increase in À leads to a surplus transfer of some of the innovator's gains to 2I farmers. This transfer is integral and the global surplus variation stays unchanged. We note that in this case, the surplus variation of upstream companies is negative. The observation made in Figure 8 that the innovator's gains are higher than the losses of sellers of conventional herbicides is not confirmed here.

Sensitivity to the margin rate on conventional herbicides (0) The margin rate on conventional herbicides (/) does not affect the adoption curve (Figure 4) and has a limited effect on the innovator's profit curve, so that the optimal level of the GM seed license price stays unchanged. The adoption rate of GMOs is then unchanged.

The effect of a change in Q on gains and losses of different actors is illustrated in Table 5.

In the case studied here, estimations corresponding to the reference situation (before the introduction of GMOs) are also modified. Farmers'gains and innovator's gains on sales of the GM seed are unchanged. However, because the margin rate is smaller, the loss of sellers of conventional herbicides is less important. Under these conditions, the gain of upstream actors is more important and this directly affects the total gain. The share of farmers in the total gains is now smaller. As indicated below, we may think that sellers of conventional herbicides would decrease their prices in reaction to a loss of 85Vo of their sales. We have to limit our analysis here to the very simple case where all farmers staying on a conventional program always choose the same application program. This assumption is verified if we assume an homothetical decrease in prices of all products. We present here some results assuming a 40Vo decrease in prices of conventional herbicides. The adoption curve of GMOs is translated to the left: for a given GM seed license price, much less farmers adopt (Figure l1). This has a direct effect on the profit of the innovator, which also decreases, leading to a displacement of the optimal GM seed license price to the left. When the price of conventional pesticides decreases by 4OVo, the optimal level of the GM seed license price decreases from32l F/ha to 153 F/ha. In this case, counting or not counting gains on GMO herbicide sales has a higher effect on the optimal GM seed license price. This price decreases from 153 F/ha to 138F/tra when these sales are taken into account. This decrease in the GM seed license price almost compensates the translation on the adoption curve, in the sense that GMO adoption now attains 6l%o of areas wit a GM seed license price equal ro 153 F/ha. Table 6 shows the effect on gains and losses of different actors. The decrease in the license price and the decrease in the herbicide prices lead to a clear gain for farmers, from +161 MF to +378 MF. This figure represents not only the gain of adopters, but also the gain of non adopters. It should be noted however that the highest share of farmers'gains goes to adopters who benefit from the important decrease in the license price, while the increase in gains for non adopters is only equal to 10 MF. The gain for upstream companies diminishes clearly.

For conventional herbicide sellers, the loss is higher than it was with unchanged prices. This follows from the very high decrease in the margin rate, from 50Vo to I7Vo. A 40Vo decrease in prices, then, does not allow these actors to limit their losses. However, it is possible that a less important decrease would allow them not to loose so much. For the innovator, benefits decrease clearly, because of the decrease in the price of the GM seed. Here again, we note that the innovator's gain no more compensates the losses for conventional herbicide sellers.

Table 6. Gains and losses with a decrease in conventional herbicide prices (MF) Variation Variation tB-Al tc-Al

Revenue on the GM seed license +328.9 +140.4 Revenue on sales of the GMO herbicide +75.8 +65.4

Revenue on sales of conventional herbicides -321.0 -357.5

Farmers'weeding costs +161.6 +378.9

Total gain (from A to B or from +245.3 +227.2 AtoC * The GM seed license price is equal to 32lF/ha.

'k The GM seed license price is equal to I53F/ha.

Conclusion

Here, we always consider the case where the innovator applies the optimal level of the GM seed license price. The sensitivity analysis allows to bring out several conclusions (Table 7):

-The important adoption level observed in the base case (75Vo) is roughly confirmed in all cases. We saw that changing the additional profit at which farmers adopt the GMO program (Â) or changing the price of conventional herbicides leads to an important translation in the adoption curve. Yet, in both cases, the innovator adjusts his choice by decreasing its license price, so that the adoption rate at the optimum changes very little. Thus, the observation on the adoption rate seems quite robust.

-The global estimated gain does not change much from on case to the other, because the change in parameters mainly leads to transfers between actors. It should be noted however that the assumption on the margin rate on herbicides has an important effect on the global gain: the smaller this margin rate is, the smaller are the losses on conventional herbicides, and the higher is the total gain. 374.2 53.2 16.1 -148.5 -586.9 -369.6

Figure 1 .

 1 Figure 1. Distribution of conventional herbicide costs in the sample

Figure 2 .

 2 Figure 2. Distribution of herbicide costs for programs 100, 010, 110 and 001 (corresponding to an one-application GMO program)

  Figure l, not many farmers would be interested by a GMO program costing around 700 to 800 F/ha. Between these two extreme values, the slope of the adoption curve takes high values (especially between 300 F/ha and 500 F/ha), leading to decreases of around 3500 ha (or 0.25Vo of French areas) by additional Franc on the GM seed.

Figure 4 .

 4 Figure 4. Adoption curve of GMOs as a function of the GM seed license price

Figure 5 .

 5 Figure 5. Evolution in weeding expenses for farmers in the sample

Figure

  Figure 7. Losses of sellers of conventional herbicides

Figure 8 .

 8 Figure 8. Gains and losses of all upstream companies

Figure 9 .

 9 Figure 9. Sensitivity of the adoption curve to A

Figure 10 .

 10 Figure 10. Sensitivity of the innovator's profit to A

Figure

  Figure I l. Impact of the decrease in conventional herbicide prices on the adoption curve

Table l .

 l Replacement of conventional programs by GMO programs

		GMO program
	Code Area Average
	herbicide
	cost
	100x 6Vo 248 010x lTVo 521 110* 24%o 508 001 2Vo 538 101 16Vo 450	One application, 2L/ha(h8=2)
		Two applications,
	111 24Vo 674	2llhaeach ( h8= 4)

Table 2 .

 2 Gains and losses due to the GMO adoption (MF)

		Reference with GMO*	Variation
	Revenue on the GM seed license	0	328,9	+328
	Revenue on sales of the GMO herbicide		75,8	+75,8
	Revenue on sales of conventional herbicides	374,2	53	-321
		-1	-586.9

Table 3 .

 3 Impact of GMO introduction on sales of conventional pesticides

	Product	Price	Per	Initial	Initial sales Sales after	Losses in
		(F/l or	hectare	market		GMO	sales in
		F/kg)	quantity (Vha or	share		introduction *	link with GMOs
			kdha)
	Colzor	99	5,0	36,4570 212 836 465	14 843 8r2	-95Vo
	Butisan S	234	7,4	20,0370	t49 894 335 28 903 9r1	-8lVo
	Novall	250	1,8	12,50%	93 593 180	45337r1	-95Vo
	Tréflan Devrinol	28 170	2,4 2,0	6,9470 5,92Vo	5t 925 414 16 266 073 44301 tst ll 729 254	-69Vo -'74Vo
	Fusilade X2	358	0,4	3,1970	23 900 530	6 482 120	-'7370
	Targa D+ Pilot	610 221	0.4 0,1	2,50Vo 2,3670	18 729 3r2 lt 691 892 2743 8rr 1 487 264	-92Vo -84Vo
	Eloge	510	0,3	2.II7o	15 783 686	3 197 996	-76Vo
	Stratos Ultra	137	1,2	2,OlVo	15 057 311	3 636 853	-'767o
	Aeil	344	0,4	r,36Vo	t0 216 389	I 948 409	-8lVo
	Brassix

Table 5 .

 5 Gains and losses with a smaller margin rate on conventional pesticides

-Farmers'gains in the base case correspond to a lower limit. Adopters'gains increase clearly when a change in a parameter brings the innovator to decrease the GM seed license price.

-Estimating losses of conventional herbicide sellers is tricky because they depend on the margin rate on which we don't have accurate information. The higher the margin rate is, the higher the losses will be. We may note however that the losses are always the same in proportion (857o decrease in sales).

-The gains of the innovator are very sensitive to assumptions made on  and on the reaction of conventional herbicide sellers. The estimations realized here are rather an upper limit.

-The gains of the innovator are in some cases higher, and in some cases smaller, than the Iosses of conventional herbicide sellers. The reason is that estimations of gains/losses for upstream companies are very sensitive to parameters, so that the difference between the two is also sensitive.


Biological control of

  Plutella xylostella (L.) Elisabeth Tabone, Clément Bardon, -Lezcano N., Bernard Pintureau, Laurent Lapchin To cite this version: Elisabeth Tabone, Clément Bardon, -Lezcano N., Bernard Pintureau, Laurent Lapchin. Biological control of Plutella xylostella (L.): Selection of the best trichogramma strains from biological characteristics. International Symposium, Oct 2002, Montpellier, France. Proceeding of the International Symposium, 2002. hal-02832942


The delegation was warmly welcomed with the presence, at the seminar, of the Indian Minister of Agriculture, who opened the working session. This seminar was seen as a clear sign of the willingness of strengthening the partnership between France (Europe) and India for agronomic research. The agronomic research sensu lato is indeed at the crossing point of two Indian priorities: the rural and agricultural development associated with poverty alleviation, and the highlevel scientific research .,

The seminar programme included four working groups with the objective of identifying and deciding research areas for joint collaboration. Four main themes of common interest were identified plant and animal genomics, environment, nutrition and food safety, economics and social sciences. Several sub-themes were also defined, as well as respective resource-persons within each Institute, for further development through follow-up talks among the scientists after this seminar. Some funding sources were also mentioned , either for supporting common research projects (CEFIPRA-IFCPAR UE, etc.) or personnel exchange and training (Embassies ; Marie-Curie Grants ; etc.).

The seminar was concluded by the signature of a tripa rtite agreement of cooperation between ICAR, CIRAD and INRA ---oo00oo---

3-Memorandum of agreement : ICAR -INRA-CIRAD

At the last ICAR GIRAD INRA meeting of November 2002, it was established that the hierarchy of agreements and contract documents in the field of agriculture was the following

Documents

Partners Duration

MOA (Memorandum of Agreement)

Ministry of Agriculture of France and India The memorandum of agreement between ICAR, CIRAD and INRA, after obtaining the visa from the French and Indian Authorities, was signed by the three parties on April 17th, 2003. The agreement was to be signed in three versions (hindi, english and french) ; the French version remains to be elaborated and signed by the three pa rties (exchange of documents by courrier).

4-Indo-French Seminar on Agricultural Research

This seminar was organised under the aegis of the Ministry of Agriculture of India, the 16 th and 17 1. Genome analysis and functional genomics . to be applied to several plants and traits to be defined in common by ICAR, INRA and GIRAD : wheat, sugarcane, cotton, citrus, and the priority traits resistance to temperature, salt and drought (wheat and citrus) ; resistance to virus (banana) , fiber quality (cotton) ; resistance to diseases (sugarcane) (contacts G

Riba [I NRA] -J Meunier [GIRAD] -G. Kalloo [ICAR])

4.2.

the organisation of an "Indo-French seminar on the property rights for genes, living materials and regional products". This concept is supported by the MoST of India, by the Embassy of France, by the Ministry of Agriculture of France and CEFIPRA-IFCPAR.

4.3.

In the area of institutional strengthening, it is proposed to organise a return meeting in France, in 2004, in coordination with CIRAD, INRA, Agropolis, IRD and Cemagref, with the suppo rt of the Ministry of Foreign Affairs of France.

4.4.

Modalities :

The above priorities are to be included in the Work Plan for the next four years. The resource-persons indicated above are thus invited to exchange opinions and availability with their counterparts in order to define a consensual document for each discipline to be included in the Work Plan. These exchanges can take place in 2003 so that the Work Plan is ready for signature by late 2003 or beginning 2004. Once the Work Plan is signed, the Institutes agrees to seek appropriate funding, in the form of "seed money", in order to initiate the collaborative activities.

The seminar and the work of the working groups allowed to identify five broad scientific themes, which were agreed upon by the President of INRA, the representative of CIRAD and the Director General of ICAR a. Milk sector, from production to processing, transformation and conditioning. A multidisciplinary approach was identified for this subject, including animal genetic improvement for milk production, production systems, post-harvest processing and transformation, pathology and socio-economics analysis (INRA contact : J.L. Maubois ; CIRAD contact : B. Faye).

b. Water and aquatic resources: resource management, water treatment, aquaculture in brackish and fresh water, decision making tools, socio-economic aspects. This subject could make pa rt of a joint "network research project" in the context of the project call of the With regard to the Sixth European Programme on Science and Technology, Indian organisations will also have access pa rticular to all the 8 thematic priorities of the Programme 2002-2006 i.e.:

genomics and biotechnology for health, information society technologies, nanotechnologies, intelligent materials and new production processes, aeronautics and space, food safety and health risks, sustainable development and global change, citizens and governance in the European knowledgebased society.

On a bilateral basis, CEFIPRA or IFCPAR, the Indo-French Centre for Promotion of Advanced Science, is a programme of cooperation supported by the Ministry of Science and Technology of India and the Ministry of Foreign Affairs of France. Among its objectivs Promotion of the Indo-French cooperation in science of excellence including agronomy and industrial science ;

Assistance to the joint projects with financial and intellectual suppo rt.

Organisation of scientific events such as conferences or seminar .

Its annual budget is 2,57 M€. Several projects from INRA and CIRAD have been or are being supported, with an average contribution between 30 and 45 K€ .

The CEFIPRA director met with the French delegation for a reciprocal introduction and an exchange about programmes and priorities.

CEFIPRA is guided in its scientific priorities by the Indo-French Commission for Science and Technology. This latter is coordinated by the Ministry of Science and Technology of India and the Ministry of Foreign Affairs of France.

The recent official agreement between ICAR, INRA and CIRAD should put the agricultural sciences in good position within this programme.

7-Follow-up action

Actions

In charge Calendar

To

"

  Project documents" Institutes and University of ICARdepartements of CIRAD and/or INRA According to the project Agreement presently under negotiation AGR^UnvauR>bl t 7 , 2003, NEW DE Or by i , " iItuf ^vemment of Ind ia, Ministry of Agri ,-Department of ^^icultural Research an Signature of the memorandum of agreement

1 .

 1 th of April, 2003, with two main objectives : (i) Presenting the activities and orientations of the scientific departments of the three Institutions , (ii) Identifying broad common priority themes of cooperation for the three Institutions. In this respect, four working groups were constituted Working Group 1: Biotechnology, nutrition, post-harvesting and food safety. Working Group 2: Environment and natural resource management Working Group 3: Socio-economics and modelling Working Group 4 . Co-operation and research management Intellectual property rights, human resources development . Each group included representatives of the ICAR institutes and representatives of INRA and GIRAD (list below) The four working groups produced recommendations on the following collaboration themes Biotechnology, nutrition post-harvest and food safety 1.

Economy of family farm agriculture and organisation of agricultural industry in the world economy.

  This includes aspects from modelling of agricultural production sectors such as the milk sector, and the simulation of the impact on economy of agricultural policy changes (CIRAD Amis / Ecopol projet with IARI -CASS 2 ; CIRAD contact : P.Y. Durand).e. Genome analysis and functional genomics: to be applied to several animal and plant species, identified in common by ICAR, Cirad and INRA, such as Sugar cane, Cotton, Citrus sp. (CIRAD and INRA contact : PY Durand ; ICAR contact : JS Samra) Further to the EU-India Science and Technology agreement signed on November 23, 2001, two new context were defined for the pa rticipation of Indian teams in European programmes, and reciprocally.The first is in the context of the "Co-operation for development" programme of the EU's research Framework Programmes. In the recent years, the Community and India carried out a successful research co-operation focused on sustainable development key themes (health, agriculture, natural resources management). In the last 6 years, for instance, 42 projects, worth EUR 23 million, including EU and Indian scientists (as well as scientists from other developing countries, especially from Asia) have been supported by the Union .Since then, "Thanks to a landmark agreement on scientific and technological co-operation adopted by the EU Council on 25th June 2002, this co-operation will be brought a step further and extended to all the fields Indian and European scientists feel they can work together. The agreement is based on the principle of mutual benefit, reciprocal opportunities for access to each other's programmes and activities relevant to the purpose of the agreement, non-discrimination,and the effective protection of intellectual property and equitable sharing of intellectual property rights. It will allow participation of Indian scientists to all the Union's research activities, and, reciprocally, will give access to European scientists in similar Indian programmes" (citation from

	6-Potential funding sources
	http://europa.eu.int/comm/research/iscp/countries/india/in-docl.pdf, 13.09.2002).

Ministry of Foreign Affairs of

France and Ministry of Science and Technology of India (I NRA and CIRAD contact : S. Kaushik). c. Environment, climatic changes, natural and cultivated ecosystems and natural resources management, including pesticide impacts on agriculture and agro-ecology in mountain zones to (INRA contact : J. Berge, ICAR contact : JS. Samra, CIRAD contact : F. Forest) d.

  prepare the French version of the memorandum of agreement Indo-French seminar on Intellectual property rights and protection of genetics obtentions and living materials, in coordination with the Embassies of India and France .

		CIRAD DREI +	Oct. 2003
		INRA DRI
	To prepare the Work Plan, including the list of areas of	CIRAD DREI +	Oct.-Nov.
	collaboration and intellectual and germplasm exchange	INRA DRI + ICAR	2003
	conditions
	Preparation of a Services of	Dates to be
		CIRAD + INRA +	agreed
		ICAR
	In coordination with Agropolis, preparation of a return meeting	Services CIRAD +	2004
	in France on agricultural research	INRA + Agropolis
	L	et ICAR

IARI -CASS : Indian Agricultural Research Institute / Centre of Agricultural System Simulation -New Delhi .

A joint INRA-CIRAD delegation led by the INRA President Prof. Bertrand Hervieu carried out in April 2003 a mission in India with the objective of identifying themes and modalities of strengthening the scientific co-operation. For INRA, the delegation included a-Pursuing the initiative taken in July and November 2002 by ICAR, CIRAD and INRA to structure and strengthen the scientific partnership among them • Signing of a Memorandum of Agreement ICAR -INRA -CIRAD ■ Definition of a "Work Plan" ICAR -INRA -CIRAD • Negotiation for the installation of a Indo-French Bureau for Agricultural Research.

b-Aside from the seminar, this visit was also the occasion for INRA and CIRAD to follow-up other initiatives in India (April 10-16th) • For INRA . follow-up of the joint research project on waste-water treatment at the Anna University, which includes a French Ph.D. posted in Madras .. • For GIRAD . negotiation with IARI (Indian Agricultural Research Institute) for initiating a joint project CIRAD -CASS (Centre of Agricultural Systems Simulation), as soon as the Work Plan ICAR-INRA-GIRAD is signed ; ■ Meeting with the French Institute of Pondicherry