Xiaoxian Huang

Aurore Pelissier
email: pelissier.aurore@gmail.com

Martine Audibert

Jacky Mathonnat

With Ningshan Chen

Anning Ma

Décembre

A Pélissier

Elvire Aronica

The Impact of the New Rural Cooperative Medical Scheme on Activities and Financing of Township Hospitals in Weifang, China

Keywords: JEL Classification: G22, I1, I38, O12 China, New Rural Cooperative Medical Scheme, Impact analysis, Township Hospitals

We would like also to express our deep

Introduction

Two important links of the Chinese rural health insurance system are at the origin of this paper:

the New Rural Cooperative Medical System (NRCMS) and the township hospitals (THs).

Since the beginning of the 21 st century, China is committed into vast social reforms, particularly addressed to the rural population. In 2003, this surge is expressed by the beginning of the implementation of a new health insurance system for the rural population: the NRCMS. During the Tenth National People's Congress on March 2007, the Prime Minister Wen Jiabao confirmed the strong commitment of the Government to develop quickly health insurance in rural areas. Taking into account the evolution of health insurance system since 1950s as well as the specific role accorded to THs3 , two objectives were assigned to the reform. On the one hand, the reform of the insurance system targets to improve rural people's access to health care and to reduce financial burden caused by the cost of health services On the other hand, the reform also aims to enforce the performance of THs, by re-orientating patients to THs rather than to county hospitals (Weifang Health Bureau).

The choice of TH as the object of this study is relevant for three reasons. First, they are a target of the NRCMS. Second, they serve mainly rural residents who are also a target of NRCMS reform. This constructs a straight linkage between the insurer (NRCMS) and the service provider (THs). Finally, NRCMS aims at increasing the rural population's access to basic medical services, and the THs play an important role in delivering this kind of services beside village health stations. THs are also the first referral facilities above village health stations and the first one to deliver general surgical services, before county level. By studying the impact of the implementation of NRCMS on the activities, efficiency and financial structure of THs, it permits to measure the distance between political expectation and practical results and thus gives inspiration for future health and social policy orientation.

In order to asses this objective, the paper is organized in 6 sections. Section 2 describes the context in which the NRCMS was implemented in Weifang prefecture. Based on a longitudinal survey, sections 3 and 4 respectively present the data and the methodology. Results are listed in Section 5 and discussions and conclusion end the paper in section 6.

Background of the NRCMS reform in Weifang

Weifang is a city-prefecture of Shandong province located in the northeast of China. It is composed of 16 county-level administrative divisions4 . These counties have jurisdiction over 148 townships (or districts) and 9285 villages. The total population is 8.5 million, in which 6.22 million are rural population, accounting for 73% of total. In terms of health infrastructures, there are 6384 health facilities, including 61 county-or-above-level hospitals and 194 THs (Weifang Health Bureau).

The reform proceeds in a gradual way in rural areas since 2003. At the initial stage, the Weifang government has chosen some pilots counties, each of them selecting a number of townships for applying the reform. New counties and townships were involved into the reform in the following years. Until 2006, all the municipalities and counties in Weifang are eligible to the insurance reform.

In 2010, 99% of the rural households are involved into the NRCMS (Weifang Health Bureau).

As each county can modulate the NRCMS, the insurance system in Weifang possesses its own characteristics. with the number of participates. At the initial stage, funds are divided into two accounts: a personal medical saving account (MSA) for outpatient spending and a mutual assistant fund for expenditures on more complicated treatments (such as the treatment for chronic diseases or hospitalization). However, since 2009, the accounts are pooled at county level and then split into outpatient fund and hospitalization fund. The first one accounts for about 30% of the total funds while the second one represents 67%. The rest 3% is set as a risk fund.

Second, the reimbursement process is quite complex. Deductibles, caps and co-insurance ratios are specified for expenditures at different health facilities level. As treatment costs at lower level hospitals are cheaper than at higher level ones, the insurance is much more generous for the use of health service at lower-level hospitals. Precisely, the deductible is set at 100 to 300 Yuans for the consultation at first-level hospital (corresponding to TH), 400 to 600 Yuans at second-level hospitals, and 1500 Yuans at third-level hospitals. The cap is 40,000 Yuans per person per year whatever health facilities. The co-insurance for hospitalization is 60 to 70% at first-level hospital. For higher level hospitals, co-insurance rate changes according to total expenditure and is generally less than 60% if expenditures are lower than 5000 Yuans. The reimbursement for outpatient is confined to the consultation at first-level hospitals or health stations and reimbursement ratio is set around 20% (Weifang Health Bureau). In 2009, the share of reimbursement in total health expenditure in Weifang was around 35%.

Third, several measures are adopted as incentives to join the insurance scheme. For example, an annual free health exam is organized for the insured whose have not used the insurance during the covered year. An office of NRCMS is set inside of the TH to perform the reimbursement on the spot.

Before 2008, the insured need to seek the medical consultation at designated hospitals. However, great discrepancy in the quality of services offered by designated and non designated hospitals in some townships makes households bypass the former at the expense of giving up insurance reimbursement.

In return, they are reluctant to continue the adherence due to the lack of benefits obtained from the insurance. Since 2008, the rule of designated hospitals is released. The patient can choose any hospital inside of the county and get the reimbursement, leading to some kind of competition among hospitals.

Data

The dataset

This

Zhongzi X X Guan Gong Zhen X X X Jingshi X X X Lin Wu X X X Wu Shan Zhen X X X Xin An X X X Anqui (2003) Zhe Shan Zhen X X X Liu Tan X X Changyi (2004) Xia Dian Zhen X X X Cai Gou Zhen X X X Da Mou Jia Zhen X X X X Jing Gou Zhen X X X X Gaomi (2005) Kan Jia Zhen X X X X Dong Xia Zhen X X X X X X Gao Liu Zhen X X X He Guan Zhen X X X Shao Zhuang Zhen X X X X Tan Fang Zhen X X X X Qinzhou (2003) Wang Fen Zhen X X X X Dao Tian Zhen X X X X X Hou Zhen X X X X X Shouguang (2004) Tian Liu Zhen X X X Bai Chi He X X X X Zhucheng (2004)
Ma Zhuang Zhen X X X Note: the entry date of county into the reform is in the parentheses. In our sample, not all townships entered the reform at the same date that the county which they belong to. Before 2003, none counties or townships were involved into the NRCMS.

No NRCMS.

Township is covered by NRCMS. X: 90% or more of NRCMS participant in the township. Source: Authors' database.

Fig. 1 Phasing-in of the rural health insurance reform in the selected townships

Descriptive statistics

The main descriptive statistics are presented in table 1. On average, townships contain 13,603 households with 92% of rural population and the rural net income per capita amounts 4581 Yuans5 over the sample period. The number of households and the farmer's net income per capita increased over the period; the share of rural population remained quite stable.

Regarding the size of THs, on average, a TH holds about 40 beds and 50 health care professionals. This size increased over the sample period, especially after 2003. From 2003 to 2008, the average numbers of beds and health professionals increased by 64% and 37% separately. This rise is mainly due to the augmentation of intermediate and junior professionals 6 , from 7 to 13 staff members for the former and 40 to 52 for the latter. In contrast, the number of senior professionals remains low and stable, about 1 person per TH.

Hospital activities consist of outpatient, inpatient 7 and preventive 8 activities. Outpatient visits turn out to be the main activities of THs. It accounts for 74% of all the three activities. Globally, THs activities increased significantly since 2003. All the three indicators have doubled between 2003 and 2008, whereas they stayed quite stable during the three years preceding the reform.

In terms of the performance of hospitals, the average bed occupancy ratio has almost doubled between 2003 and 2008 (from 38% to 61%), while it has slightly declined (from 42% to 38%) in the pre-reform period (2000)(2001)(2002)(2003). As far as ALOS is concerned, patients stay on average five days at THs. It remains quite stable over the period.

Business income 9 of hospitals has tripled between 2003 and 2008, while it stagnated during the prereform period (2000)(2001)(2002)(2003). A great part of this increase comes from the selling of drugs, which was multiplied by four. Subsidies increased also strongly, more than doubling between 2003 and 2008.

Nevertheless, the business income remains the most important financial resource, about 92% of total.

The average of reimbursement is much higher in 2008 comparing to that in 2003: reimbursement for outpatient and inpatient increased respectively by 10 and 5 times, from 113200 Yuan in 2000 to 120180 Yuan in 2008 for outpatient reimbursement and from 159100 Yuan in 2003 to 692200 Yuan in 2008, for inpatient reimbursement. 7 Inpatient activities are measured by the number of discharged patient. 8 Preventive activities are measured by the number of vaccinations. 9 Business income is computed from medical treatment income and drug income.

Objective and Methodology

The objective of the study is to estimate the impact of the NRCMS on activities, efficiency and financing structure of THs. Five outcome variables are selected. Medical activities are measured by the number of outpatient visits and the number of discharged patients12 whereas efficiency is measured by proxies as the ALOS and the bed occupancy ratio. Changes in financial structure are measured by the share of drugs selling in business income.

Econometric Model

In order to estimate the NRCMS impact, the generalization of the double-difference method is used. This quasi-experimental approach allows exploiting the panel dataset and the gradual implementation of the health insurance reform over time.

THs not yet covered by the reform are used as a comparison group for THs covered by the NRCMS. Typically, the within estimator is used. Let Y it be the outcomes variables for TH i at time t. As there is only one TH per township in our sample, we use "i" to represent either TH or township. Let P it be a dummy variable equals to one if in year t the township i is covered by the NRCMS, and 0 otherwise. The coefficient of P it , δ, is the estimator of interest. It represents the estimated average effect of the NRCMS implementation on hospital outcomes. The basic model to be estimated is the following:

(1)

Where u i and v t are the THs fixed-effects and the year fixed-effects respectively. The former controls for time-invariant individual characteristics whereas the latter captures THs common characteristics varying over years. ε it is the error term, assumed to be iid.

As positive serial correlation is detected in our data13 , the model 1 is estimated via first-differences rather than fixed-effect estimator. The first differences estimator is more efficient than the within one in the presence of serial correlation [START_REF] Jeffrey | Econometric analysis of cross section and panel data[END_REF][START_REF] Jenny | Information from Markets Near and Far: The Impact of Mobile Phones on Grain Markets in Niger[END_REF]. The estimated model is the following:

(2)

Data for t=2000 are dropped and the panel contains now 8 years (2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008). Standard errors are corrected for heteroskedasticity and clustered at township level.

Identification

In order to obtain an unbiased and consistent estimator of the program impact based on equation

(2), several assumptions need to be verified: i) the parallel trend assumption (PTA), ii) the exogeneity of the order in which the reform was implemented, and iii) the absence of migration.

The parallel trend hypothesis

The validity of the double-differenced estimator requires that the difference between before and after in the comparison group is a good counterfactual for the treatment group [START_REF] Sadoulet | Impact handout #5[END_REF]. PTA states that the intrinsic evolution of the outcomes of THs should be independent of NRCMS implementation. One conventional way to test the existence of PTA is to compare the preintervention trends of hospital outcomes between the regions which enter into the program at different time [START_REF] Jenny | Information from Markets Near and Far: The Impact of Mobile Phones on Grain Markets in Niger[END_REF][START_REF] Wagstaff | Europe and central Asia's great post-communist social health insurance experiment: Aggregate impacts on health sector outcomes[END_REF][START_REF] Barham | A healthier start: The effect of conditional cash transfers on neonatal and infant mortality in rural Mexico[END_REF]). The hypothesis is that the preintervention trends of TH outcomes would be the same in the post-intervention period if the program were not introduced. This will be the case if, other things equal; the pre-intervention trends are not significantly different among the regions with different entry dates to the NRCMS. Inspired by [START_REF] Barham | A healthier start: The effect of conditional cash transfers on neonatal and infant mortality in rural Mexico[END_REF], the test of PTA is conducted with the following specification:

(3) The model is estimated by OLS with county fixed-effects because TH fixed-effects lead to a huge loss of degree-of-freedom. Moreover, the county level is relevant because: i) the decisional power concerning the NRCMS reform is set at county level, ii) in a county, townships are relatively homogeneous.

The exogeneity of the reform

The model requires that the assignment of the program is exogenous across space and over time.

NRCMS is a national policy which is expected to be adapted in all rural areas in China. Therefore the potential endogeneity comes rather from the date in which counties enter into the reform rather than of their eligibility. There are two sources of potential selection bias: the reverse causality and the omitted variables.

Reverse causality refers to the situation where the outcome of THs influence the order that the NRCMS is implemented in corresponding township. Hospitals with more activities, for example, may be better organized and thus have higher efficiency. Therefore at the initial stage of the reform, the authority may prefer to choose the areas where hospitals have better performance. As a consequence, areas where the hospitals have more activities have more chance to be chosen first. It may also be the case that the variation in hospital outcome influences the chance that the township should be chosen into the program. If, for instance, the TH has encountered rapid decrease of the number of patients in the preceding years of the reform, the township may be more motivated to participate to the program, in hoping that it should bring more patients. In these cases, the date of introduction of the reform is not independent from the outcome of the hospital.

Regarding to the problem of omitted variables, the FD model (or FE model) controls for the timeinvariant characteristics of THs and so assumes a time-invariant selection bias (Ravallion 2007). But, it is possible that variables which vary across time and THs have effects on both outcomes variables and program implementation. The income of rural household, for example, is a variable varying across townships and years. It can be correlated with TH activities, or financing, because this variable reflects the capacity of household to pay for health care services and also the living standard of the township.

But it can also be correlated with the interest variable, P it , because poorer townships can have implemented the reform in first and richer in last, as NRCMS aims to increase healthcare access for the poor. This problem can be solved by adding control variables into the regression, to avoid the artificial relation caused by omitted variables [START_REF] Jenny | Information from Markets Near and Far: The Impact of Mobile Phones on Grain Markets in Niger[END_REF][START_REF] Guido | Nonparametric estimations of average treatment effects under exogeneity: a review[END_REF]. The model 2 is then augmented:

(4)

The list of control variables can be identified by comparing the means of a comprehensive list of township and TH characteristics between townships hospitals chosen for the first year of implementation of the health insurance reform and townships that entered into the insurance program later on [START_REF] Jenny | Information from Markets Near and Far: The Impact of Mobile Phones on Grain Markets in Niger[END_REF][START_REF] Jenny | Information from Markets Near and Far: The Impact of Mobile Phones on Grain Markets in Niger[END_REF]. According to the strategy of [START_REF] Jenny | Information from Markets Near and Far: The Impact of Mobile Phones on Grain Markets in Niger[END_REF][START_REF] Jenny | Information from Markets Near and Far: The Impact of Mobile Phones on Grain Markets in Niger[END_REF] 3, seven covariates are to be included. At township level, the surface, the number of households, the number of village health stations and the rural net income per capita. At TH level, the number of total staff and that of operational beds, and the total amount of subsidies received. To test the existence of reverse causality, two strategies are adopted. The first one is adapted to test whether the NRCMS implementation decision is correlated with the variation of outcome variables during the preceding years of reform. The test is performed on a pre-reform period sample. For each township, it consists of the data for the three years before the implementation of the NRCMS14 . The following specification is used to test the assumption (Gruber and Hanratty 1995, De Janvry et al.

2009):

(5)

Where: year -l,it takes the value 1 if at year t, the reform will be implemented in l years for township i, and 0 otherwise, l = 1, 2 or 3 (year -3, it is dropped because it is the reference period). County and year fixed effects are included, noted as w j and v t respectively15 . κ l are the coefficients of interest. If κ l are statistically significant, it suggests that the entrance dates of THs are subject to the evolution of outcomes during the three years before the implementation of the NRCMS. The results are presented in Table 4. None of the coefficients are significant, which implies that the date of NRCMS placement is not driven by evolution of outcome trends during the three years before the implementation of the reform. ; ** at 5%; and, * at 10%. The five specifications are estimated on a sample consisted of the three years preceding the entrance date into the reform of each township. The model is estimated by OLS with county and year fixed-effects because TH fixed-effects lead to a huge loss of degree-of-freedom. Moreover, the county level is relevant because: i) the decisional power concerning the NRCMS reform is set at county level, ii) in a county, townships are relatively homogeneous.

Second, the reverse causality is checked with the test proposed by [START_REF] Gruber | The Labor-Market Effects of Introduction National Health Insurance: Evidence from Canada[END_REF] and also applied in the study of [START_REF] Wagstaff | Europe and central Asia's great post-communist social health insurance experiment: Aggregate impacts on health sector outcomes[END_REF]. The reverse causality is tested by adding to the model a dummy variable reflecting the implementation of the reform in the next year

(P it+1 ): (6)
There is no problem of reverse causality when coefficient on P it+1 , noted δ' is not statistically significant. Coefficient on the added variable (participation in the next year) is not significant in any regressions 16 .

Migration

The last issue which can potentially biased the result concerns the problem of selective migration [START_REF] Galiani | School decentralization: helping the good get better, but leaving the poor behind[END_REF]. The change of outcome may issues from the change of characteristic of the target population due to the implementation of the program, rather than the effect of reform itself. In our sample, different townships enter into the program at different time. Therefore, at a given period, residents in townships which are not yet covered by insurance may want to go to townships that are covered, to benefit from the system. It will bias results if the immigrates are significantly different from the local population. If, for instance, they are sicker than local people and therefore have more important needs for medical services, the increase of medical activities in the insured TH will not be due to the reform but rather to the characteristic of the immigrated patient. This is not the case in this sample, because the beneficiary status depends on the resident place of the population. People in the township which is not covered by NRMCS will not be able to benefit from the insurance, even if they seek medical consultation at covered hospitals. Another possibility is that people move into the covered region. However, in China, the residence status is generally linked with the birth place. It is costly to change the living place, even if possible.

Results

The impact of the NRCMS

Table 5 lists the results. Column 1 presents the results of equation 2. In others columns, townships' and THs' characteristics are included (equation 4). In columns 4 and 5, the introduction of the insurance system is measured by two others indicators. First, it is replaced by the share of the population covered by the NRCMS in the township (column 4) in order to capture the intensity of the reform [START_REF] Wagstaff | Europe and central Asia's great post-communist social health insurance experiment: Aggregate impacts on health sector outcomes[END_REF]. Second, the reimbursement rate at TH level for outpatient activities (outpatient estimation) or for inpatient activities (inpatient, ALOS and the bed occupancy rate estimations) allows measuring the depth of the insurance coverage (column 5). In columns 1, 2, 4 and 5, standard errors are corrected for heteroskedasticity and clustered at township level. In order to check the consistency of the standard errors, column 3 shows results with bootstrap standard errors (reps=1000).

The introduction of the NRCMS has an impact on THs' activities (columns 1, 2 and 3). Although significance and coefficients are not very stable for outpatient activities and ALOS, estimations clearly show that the NRCMS has a positive impact on the inpatient activity and the bed occupancy ratio (columns 1-3). When the dummy "participation" is replaced (columns 4 and 5), significance and sign are similar to those obtained from the basic model, except for outpatient estimation.

For THs covered by the NRCMS, the number of discharged patients increases by 58% 17 and that of the bed occupancy ratio by 25%. Significance of coefficients increases with bootstrap standard errors (column3). So, inpatient activities and the bed occupancy ratio increase when the coverage or the reimbursement rate of the NRCMS increased. For outpatient activities, the positive coefficient on the participation dummy is significant only in column 3 and only at 10% level. Nevertheless, the coefficient on the share of coverage is significant and positive (at 10% level). Moreover, the impact of insurance coverage is smaller for outpatient visits than for inpatient visits. By contrast, the coefficient on ALOS, which is not significant in the column 1, becomes significant when covariates are added to the model (columns 2 and 3). As covariates are added to ensure that participation is exogenous, the significant and negative coefficient allows confirming that the NRCMS leads to a decrease of the ALOS for THs by 9%. Similarly, coefficients on the two others insurance indicators are significant and negative: the ALOS decreases when the coverage or the depth of insurance increased, suggesting a positive effect of insurance on efficiency of TH 18 . To conclude, the coefficient on the share of the business income generated by the sale of drug is not significant, suggesting that this outcome was not impacted by the reform, what is interesting to notice as the health bureau took measures to reduce the growth of drug expenditures, for patients. 18 The issue of efficiency is addressed in another paper written by the authors: Efficiency Analysis of Township Hospitals in Weifang, China, available at Cerdi website as a working paper.

Heterogeneity of the impact

The previous analysis supposes that the impact of NRCMS is homogenous. This section investigates the potential heterogeneous impacts of reform across space and over time. Results are listed in Table 6.

First, the incentive brought by the new insurance system is different for the population with different socio-economic characteristics. It can be expected that the price effect of insurance to increase healthcare demand and then, TH activities, is less important for people in rich townships than those in poor townships. In order to check these differentiated impacts across space and socioeconomic conditions, a dummy variable "poor" 19 is interacted with P ijt . Poor is calculated from the rural net income per capita. The "poor" dummy alone has not to be included into the model since it is captured by the income variable. According to table 6, the reform shows higher impacts on discharged patient in poor townships than in non-poor ones. For the bed occupancy ratio, the interactive variable is significant and positive whereas the participation dummy is not. It indicates that the reform has a positive impact on the bed occupancy ratio only for THs located in poor townships. In contrast, impact is not significantly different for the ALOS of THs in poor and non-poor zone, suggesting a homogenous pattern of disease for poor and rich. The NRCMS has neither average impact nor heterogeneous impact on the outpatient activities and on the share of drug income of THs in poor and non-poor zone.

Second, there are two types of THs: general and central. Theoretically, their missions and responsibilities are complementary. Central THs are better equipped to treat discharged patients than general hospitals. The former also brings technical support to the latter. In practice, our Chinese partners reveal that this distinction is not as clear. Central and general THs compete for patients. By interacting the participation variable with a dummy reflecting the hospital level (1 for central THs, and 0 otherwise, i.e. for general THs), it is possible to check if there is a differentiated impact of the NRCMS as regard to the type of the TH. The result of our estimation shows no evidence of the heterogeneous impacts of insurance between general and central hospitals.

Third, the effect of the NRCMS can be different over the time. The experience under the scheme can influence the impact of the NRCMS. It is therefore expected that the insurance has more influence on local agents' behaviors in places which have more experience with reform. Inspired by [START_REF] Gruber | The Labor-Market Effects of Introduction National Health Insurance: Evidence from Canada[END_REF] and [START_REF] Galiani | School decentralization: helping the good get better, but leaving the poor behind[END_REF], this paper investigates experience effect in two ways. On the one hand, cumulative effects of the reform are captured by the introduction of two dummies: 1 year 19 Poor is calculated from the rural net income per capita of the township. A township is considered as poor when it belongs to the quintile 1 (townships belonging to the 20% of the poorest townships). after the reform", "2 years or more after the reform"20 . On the other hand, a discrete variable from 0 to 5, reflects the number of years of coverage by the insurance system: 0 for the year in which the NRCMS is implemented, 1 when NRCMS is implemented since one year, 2 when the NRCMS is implemented since two years, etc. It assumes that there is a linear trend in the impact of the NRCMS.

Results show that the impact of the NRCMS on outpatient visits, on the number of discharged patient and on the bed occupancy ratio decrease over time. The volume of outpatient and inpatient activities and the bed occupancy ratio continue to increase over time but at a lower rate of growth: the marginal impact of the NRCMS is decreasing. For ALOS estimation, the impact of the NRCMS seems to remain stable over time.

Discussion and conclusion

Chinese government began in 2003 the gradual implementation of the NRCMS, a medical insurance system for rural population. This analysis aims to assess the impact of the introduction of NRCMS on THs in Weifang prefecture. Based on a sample of randomly selected 24 THs over a nine years period, the impact of NRCMS on THs outcomes is estimated with first difference method, after having checked all the assumptions for the model with staggered entry.

Estimations confirm that insurance reform increases THs activities. These results are particularly interesting from a policy point of view and are consistent with those presented in the literature about the impact of the health insurance introduction (Wagstaff and[START_REF] Wagstaff | Europe and central Asia's great post-communist social health insurance experiment: Aggregate impacts on health sector outcomes[END_REF]. First, insurance impact is significant for hospitalization (discharged patients) but there are no clear effects for outpatient visits. It fits with expectation, because the design of the reform is merely focused on alleviating hospitalization costs borne by patients, these cost being much more expensive in average than outpatient visits. As the volume of hospitalization rises, the bed occupancy ratio increases as well. Second, results show the ALOS significantly decreased with the introduction of the reform. In order to control cost, the insurance scheme set reimbursement ceiling and Health Bureau took great effort to control drugs and service prices. These measures incite THs to reduce ALOS.

Nevertheless, complementary information is needed to assess whether the reduction of ALOS is accompanied with a lower quality of health care.

The share of the business income generated by the drug sales reflects the financial structure of THs.

The modification of THs' income structure is not a primary target of the reform, but it can be indirectly affected by the evolution of medical activities. In fact, medical activities bring two kinds of income: the sale of services and drugs. In China, the sale of drugs is more profitable for hospitals than the sales of services, especially those which are not associated with high-tech diagnosis. Therefore, hospitals tend to over-prescribe drugs [START_REF] Liu | Evaluating Payment Mechanisms: How Can We Measure Unnecessary Care?[END_REF]. Insurance is expected to encourage the sale of services because it incites people to seek medical consultation. However, as long as the profit margin of the sale of drugs is higher than that of the sale of services, the increase of the sale of services would proportionally increase the sale of drugs. The results of our estimation confirmed that insurance does not change the structure of TH's business income. The sale of drug continues to be the main source of business income.

Finally, estimations show that the impact can be heterogeneous across space and time, especially for hospitalization. On the one hand, discharged patients increase more in poor townships after the implementation of insurance than that in non-poor townships. Such results are not surprising because income is often the main obstacle to hospitalization, and the price elasticity of demand is higher for poor households. As insurance scheme gives similar financial support to all the insured, it represents a more important proportion of capacity to pay for the poor than for non-poor. Nevertheless, we can't infer from this point that catastrophic health care expenditures have been drastically reduced. Wagstaff et al. (2009) found that in Gansu province medical insurance had lead households to search for more specialized and costly care. As a result, they detected an increase in catastrophic expenditure.

On the other hand, the influence of the NRCMS also changes over time because of the extension of the coverage rates and accumulated experience, the marginal effect being decreasing. However a longer period is necessary to assess the long term impact of the reform. An "∩" curve for activities could be observed in the coming years, although unlikely, if the quality of care deteriorates.

Two precautions needed to be highlighted. First, obviously the demand for healthcare at THs has increased thanks to the reform. But we don't know to what extend it implies a net increase of demand, or if a share of this demand is stemming from a transfer of demand from the upper level hospitals, as NCMS increase the gap between the cost of care at township and county hospitals. Second, this study is based on a relatively small sample of 24 THs. Although this shortcoming is partly "compensated" by randomized process of selection of the hospitals and by the nine years of the survey period, it would be desirable to check the results with a larger sample. Lastly, as all the selected THs are from Weifang prefecture, the results cannot be directly generalized for other regions in China.

  First, contribution was 10 Yuans per person in 2003 and gradually rose to 25 Yuans by 2009. Correspondingly, local and central governments' subsidies increased from 20 Yuans to 40 Yuans per person respectively. The total contribution reached 105 Yuans per person by 2009. Once individual's contributions collected, the subsidies from local and central governments are allocated in accordance

  study uses an original dataset, built from a survey conducted in collaboration with the Studies and Researches Center in International Development (CERDI) of Auvergne University, the Weifang Health Bureau, and the Medical University of Weifang. It is a longitudinal survey covering the period from 2000 to 2008 for Weifang prefecture and containing 24 THs randomly selected and belonging to 6 counties. The NRCMS is implemented gradually among the sample, from 2003 to 2006 (Fig.1).

  based on Imbens and Wooldridge work (2007), the differences in means of covariates between townships entered into the reform in 2003 and those which entered later are calculated. Then, they are divided by standard deviation of the 2003 group. Covariates with score higher than 0.25 (in absolute value) are considered to be significantly different, and thus will be entered into the model (Imbens and Wooldridge 2007, Aker 2008). Mean tests are performed on the pre-reform period. According to Table

Table 1 -Descriptive Statistics

 1

		Total sample (2000 -2008)	YEAR 2000	YEAR 2003	YEAR 2008
	Variables 10	Mean	Std. Dev.	Mean	Std. Dev.	Mean	Std. Dev.	Mean	Std. Dev.
			Township characteristics'
	# of households 11	1.36	0.68	1.09	0.54	1.26	0.61	1.79	0.83
	Share of rural (%)	92.80	4.38	93.46	3.98	93.56	4.17	92.57	4.46
	Rural net income per capita	0.45	0.12	0.33	0.05	0.38	0.06	0.63	0.09
			Township hospitals characteristics'
	# of beds	40.62	19.17	34.78	13.02	35.92	13.43	59.08	32.35
	# of professionals	51.64	31.49	46.00	25.83	49.13	29.61	66.96	42.32
	# of seniors	1.15	1.29	1.09	1.19	1.17	1.53	1.17	1.11
	# of intermediate	8.30	8.19	5.96	7.16	7.25	7.36	12.79	9.90
	# of juniors	41.16	23.60	37.7	19.12	39.67	22.33	52.17	33.97
	# of outpatient visits	30196.21 24882.01 25395.26 21332.54 25350.04 21182.67 48244.58 32582.50
	# of discharged patients 1271.42	892.17	958.87	642.79	912.29	712.21	2184.00 1077.56
	# of actual vaccination	9122.75 9523.00 6795.26 4991.84 7362.79 5329.86 14860.88 18529.26
	ALOS (in days)	5.03	1.42	5.29	2.43	5.21	1.52	5.12	0.92
	Bed occupancy ratio (in days)	0.47	0.24	0.44	1.25	0.38	0.24	0.61	0.19
	Total subsidies	16.55	22.07	15.54	14.78	14.26	14.62	37.17	47.60
	Business income	202.48	195.4	133.28	99.72	129.34	99.81	418.69	311.31
	Medical treatment income	78.99	88.29	50.42	47.24	48.4	47.31	152.8	138.06
	Drug income	123.49	112.18	82.85	56.77	80.94	56.28	265.88	181.39
	NRCMS reimbursement	86.22	114.74	-	-	26.93	32.03	190.96	182.17
	for inpatient	32.84	48.91	-	-	15.91	20.24	69.22	71.50
	for outpatient	53.11	71.57	-	-	11.32	15.05	120.18	119.63

  Where t=2001-2002 (pre-intervention period, 2000 is drop because it is the reference period), k=2004-2006 (period after the first intervention in 2003) and NRCMS k equals to one if the TH enters in the reform during year k, 0 otherwise. dyear t are year dummies which captures the period specific effect of 2001 and 2002. θ tk represents, at year t, the additional period effect hold by the regions which enter into NRCMS program in year k. If θ tk are not significantly different from zero, PTA is assumed and

pre-intervention trends can be considered similar between THs that applied the reform at various years. Groups of THs are comparable and so a group of comparison which is composed by THs not yet treated are relevant counterfactual for groups of THs treated. Results are summarized in Table

2

. In all cases, the test supports the assumption that pre-intervention trends of outcomes are similar across groups which entered at different time in the reform.

Table 2 -Test of the PTA

 2 Standard errors (in parentheses) are corrected for heteroskedasticity and clustered at township level. *** indicates significance at 1%; ** at 5%; and, * at 10%. Test is performed on a sample from 2000 to 2003, i.e. the pre-reform period.

	Pre-intervention years	Ln (outpatient)	Ln (discharged patient)	Ln (ALOS)	Ln(Bed occupancy rate)	Ln(Share of drug income)
			Township hospitals which implemented NRCMS in 2003
	2001	0.0445	0.0951	0.00567	0.00961	-3.594
		(0.0595)	(0.0658)	(0.152)	(0.0274)	(3.385)
	2002	-0.0310	0.0743	-0.00677	0.0510	-0.501
		(0.0593)	(0.414)	(0.158)	(0.140)	(4.114)
			Township hospitals which implemented NRCMS in 2004
	2001	0.0668	0.0555	-0.0674	0.0474	6.965
		(0.120)	(0.145)	(0.166)	(0.0618)	(4.130)
	2002	0.194	-0.170	0.0221	-0.0540	2.429
		(0.132)	(0.469)	(0.169)	(0.155)	(4.979)
			Township hospitals which implemented NRCMS in 2005
	2001	-0.0945	-0.0512	-0.0396	0.0449	4.635
		(0.0859)	(0.116)	(0.153)	(0.0388)	(5.025)
	2002	-0.0783	-0.101	-0.0566	0.00544	-0.808
		(0.118)	(0.424)	(0.162)	(0.143)	(4.786)
			Township hospitals which implemented NRCMS in 2006
	2001	-0.0205	-0.0683	0.105	-0.0893	4.345
		(0.119)	(0.197)	(0.172)	(0.0546)	(3.453)
	2002	-0.0278	-0.278	0.0549	-0.148	3.646
		(0.141)	(0.473)	(0.187)	(0.158)	(4.586)
	Note:

Table 3 -Mean tests

 3

		Year reform 2003 Mean Sd. Mean Sd. Year reform 2004	Year reform 2005 (2003) Mean Sd. Diff/Sd.	Year reform 2006 (2003) Mean Diff/Sd. Sd.	Diff/Sd. (2003)
			Township characteristics
	Surface	110.45 57.78 95.57 28.27	0.26	95.31 10.44	0.26	95.23 42.05	0.26
	# of households	1.07	0.24 1.31 0.33	-0.96	1.05 0.21	0.09	1.25	0.82	-0.73
	# of health stations	27.72	3.17 34.67 19.02	-2.19	26.73 17.44	0.31	22.79 15.42	1.56
	Share of rural population	93.27	2.79 93.83 2.64	-0.2	93.76 4.77	-0.17	93.24 4.89	0.01
	Rural net income per capita	0.31	0.05 0.37 0.05	-1.33	0.32 0.01	-0.35	0.35	0.06	-0.89
			Township hospital characteristics
	# of beds	29.33	2.51 32.07 12.09	-0.09	35.00 11.34 -2.26	35.96 15.41	-2.64
	# of staff	28.50	9.28 43.20 14.31	-0.52	44.67 22.42 -1.74	44.63 48.97	-1.74
	Subsidies	5.82	3.66 30.45 22.09	-4.23	14.37 2.91	-2.34	13.90 11.43	-2.21

Note: Diff equals the differences in means of covariates between townships entered in the reform in 2003 and those which entered later. Sd. (

2003

) refers to the standard deviation of covariates for townships entered in the reform in 2003.

Table 4 -Test of reverse causality

 4

		Ln (outpatient)	Ln (discharged patient)	Ln (ALOS)	Ln(Bed occupancy rate)	Ln(Share of drug income)
	year1_before	0.0280	0.132	-0.0382	0.0315	-0.365
		(0.378)	(0.530)	(0.182)	(0.0819)	(3.596)
	year2_before	0.0784	0.108	-0.0101	0.0155	-1.674
		(0.189)	(0.293)	(0.0959)	(0.0511)	(1.910)
	Note: Standard errors (in parentheses) are corrected for heteroskedasticity and clustered at township level. ***
	indicates significance at 1%

Table 5 -Impact of the NRCMS

 5

		(1)	(2)	(3)	(4)	(5)
			Ln(outpatient)
	Participation	0.151	0.149	0.149*
		(0.0899)	(0.0925)	(0.0782)
	NRCMS coverage				0.00201*
					(0.00116)
	OP reimbursement rate					0.00739
						(0.00479)
	Observations	192	192	192	192	192
	R-squared	0.192	0.232	0.232	0.239	0.233
	X(it)	N	Y	Y	Y	Y
			Ln(inpatient)
	Participation	0.478**	0.456**	0.456***
		(0.172)	(0.170)	(0.159)
	NRCMS coverage				0.00523**
					(0.00208)
	IP reimbursement rate					0.0107**
						(0.00400)
	Observations	192	192	192	192	192
	R-squared	0.191	0.221	0.221	0.215	0.213
	X(it)	N	Y	Y	Y	Y
			Ln(bed occupancy rate)
	Participation	0.244**	0.224**	0.224**
		(0.0899)	(0.0988)	(0.104)
	NRCMS coverage				0.00211*
					(0.00110)
	IP reimbursement rate					0.00545**
						(0.00232)
	Observations	192	192	192	192	192
	R-squared	0.171	0.199	0.199	0.190	0.198
	X(it)	N	Y	Y	Y	Y
			Ln(ALOS)
	Participation	-0.0697	-0.0826*	-0.0826**
		(0.0455)	(0.0441)	(0.0417)
	NRCMS coverage				-0.00101*
					(0.000494)
	IP reimbursement rate					-0.00211*
						(0.00120)
	Observations	192	192	192	192	192
	R-squared	0.067	0.137	0.137	0.138	0.138
	X(it)	N	Y	Y	Y	Y
			Ln(share of drug income)
	Participation	0.0165	0.0176	0.0176
		(0.0248)	(0.0250)	(0.0242)
	NRCMS coverage				0.000256
					(0.000314)
	Observations	192	192	192	192
	R-squared	0.109	0.144	0.144	0.146
	X(it)	N	Y	Y	Y
	Note: Standard errors (in parentheses) are corrected for heteroskedasticity and clustered at township level. ***
	indicates significance at 1%; ** at 5%; and, * at 10%. The model is estimated by OLS with year fixed-effects.

Table 6 -Heterogeneous impact of the NRCMS

 6 Standard errors (in parentheses) are corrected for heteroskedasticity and clustered at township level. *** indicates significance at 1%; ** at 5%; and, * at 10%. The model is estimated by OLS with year fixed-effects.

	Ln(outpatient)		Ln(inpatient)	Ln(ALOS)	Ln(occupancy bed rate)	Ln(share drug income)
	Participation	0.150	0.395**	-0.0807*	0.156	0.0161
		(0.0971)	(0.170)	(0.0446)	(0.0970)	(0.0244)
	P*Poor	-0.00721	0.297*	-0.00932	0.328***	0.00751
	(1=poor, 0=non poor)	(0.142)	(0.172)	(0.0582)	(0.106)	(0.0397)
	Participation	0.209	0.386**	-0.0951*	0.296**	-0.00370
		(0.123)	(0.164)	(0.0522)	(0.132)	(0.0302)
	P*hospital level	-0.160	0.187	0.0332	-0.191	0.0566
	(1=central, 0=general)	(0.142)	(0.381)	(0.0783)	(0.162)	(0.0400)
	1 year after NRCMS	-0.0357	-0.145**	-0.00627	-0.0216	0.0320
		(0.0615)	(0.0566)	(0.0454)	(0.0729)	(0.0313)
	2 NRCMS years or more after	-0.170*	-0.529***	0.0504	-0.309**	0.0783**
		(0.0968)	(0.103)	(0.0711)	(0.111)	(0.0358)
	# of years after NRCMS	-0.129**	-0.287***	0.0289	-0.215***	-0.00290
		(0.0527)	(0.0969)	(0.0520)	(0.0659)	(0.0213)
	Note:

For more details about the evolution of the health care system in China, please see:[START_REF] Eggleston | Health Service delivery in China: a literature review[END_REF],[START_REF] Hillier | Health care systems in transition: People's Republic of China. Part I: An overview of China's health care system[END_REF][START_REF] William | Transformation of health care in China[END_REF], 1995),[START_REF] Liu | Reforming China's 50,000 Township Hospitals: Effectiveness, Challenges, and Opportunities[END_REF],[START_REF] Liu | People's Republic of China. Toward Establishing A Rural Health Protection System[END_REF]), World Bank (1997[START_REF] Washington | Reforming China's Rural Health System. Direction in development Human development[END_REF] and[START_REF] Yip | The Chinese health system at a crossroads[END_REF].

They are composed of four districts, six cities, two counties, three development zones and one economic zone.

All the monetary terms are in 2000 constant prices.

Junior and intermediate health workers have generally a medical formation less than university degree.

All monetary variables are in 10000 Yuan and normalized to 2000 constant prices.

Unit: 10000 households.

It is a conventional indicator to measure the volume of inpatient.

The Wooldridge test(2002), the Baltagi-Wu LBI statistic and the[START_REF] Bhargava | Serial correlation and the fixed effects model[END_REF] Durbin-Watson statistic were performed. All conclude that error terms are positively serially correlated. Results of tests are available upon request.

As the dataset begins in 2000 and the reform begins in 2003, for townships that first implemented NRCMS in 2003, the information on the period before the implementation of reform is available for maximum three years. In order to keep the same quantity of information for all the townships whatever their entry dates into the reform, we choose the three years before the implementation to construct pre-reform dataset.

County fixed effects rather than township ones are included into the model due to the small sample size of the sample.

P_value on tested variable is not listed here, results are available upon request.

"1 year after the reform" equals to 1 if the township has been in the program since one year, 0 otherwise; "2 years or more after the reform" equals to 1 if reform as implemented in the township since two years or more, 0 otherwise.

Acknowledgements

and A. Ma is Vice-President of He was Director of Weifang Health Bureau during the period of the study. This study is part of a research program in collaboration with the Weifang Health Bureau and the Weifang Medical University in Shandong Province, PR of China.

The authors want to thank warmly the Embassy of France in Beijing, more specifically


Michele Benzi

New block preconditioners for saddle point problems

New block preconditioners for saddle point problems

List of authors: Michele Benzi 1

In this talk I will describe a class of block preconditioners for linear systems in saddle point form. The main focus is on the solution of Stokes and Oseen problems from incompressible fluid dynamics; however, the techniques can be applied to other saddle point problems as well. The main idea is to split the coefficient matrix into the sum of two matrices (three for 3D problems), each of which contains only operators corresponding to components of the solution associated with one space variable. The resulting preconditioner requires the (uncoupled) solution of discretized scalar elliptic PDEs, which can be accomplished using standard algebraic multilevel solvers. The performance of the preconditioner can be improved by means of a relaxation parameter, which can be chosen on the basis of a local Fourier analysis.

The robustness of these preconditioners with respect to problem parameters will be discussed, together with the effect of inexact solves. This is joint work with Michael Ng, Qiang Niu and Zhen Wang.

1 Emory University. benzi@mathcs.emory.edu 1


Cerastoderma Edule Laurent Dabouineau

Alain Ponsero

Synthesis on biology of Common European Cockle

• The two valves are quite similar, but inequilateral • Broadly oval, up to 50mm long

-Distribution

The Cockle (Cerastoderma edule) is one of the most common and widely distributed bivalve species on tidal flats along the coast of most of european countries. Its distribution area extends from Norway to Senegal. It's an ubiquist species which can be found in estuaries and sandy bays [START_REF] Tebble | British bivale seashells[END_REF], particulary in sandy mud, sand or fine gravel.

Main stocks are in Netherlands (Waddenze, Zeelande), United Kingdom (Wash, Thames estuary, Horecambe and Caenarfon bays), in Spain (Galice, Mediterranean coast). In France, Cockle is widely distributed along the coastline. From north to south, the more constant and regular stocks are: around Dunkerque, Bays of Canche, Somme, Seine, Veys, Mont Saint-Michel, Saint-Brieuc and many others bays of northern Britanny. Further south, Cockle can be found in Bay of Vilaine, Baule, Loire estuary, Bassin de Marennes-Oléron, Bassin d'Arcachon (Quéro & Wayne, 1998). Cockle are found on a large part of the intertidal area. For a given geographical location, for example the scale of a bay, the distribution is aggregative (Fig. 3) as for many endogean benthic species [START_REF] Reys | Analyses statistiques de la microdistribution des espèces benthiques de la région de Marseille[END_REF]Elliot, 1979;[START_REF] Downing | Aggregation, transformation and the design of benthos sampling programs[END_REF]. Densities can vary from a few individuals per square meters to thousands. For example, the maximum density observed in the Bay of Saint-Brieuc is 2752 individuals/m² in 2008. Densities of 5000 individuals/m² have been observed at Oostershelde in Belgium in 1985 [START_REF] Coosen | Variability in stock assessment of cockles (Cerastoderma edule l.) in the oosterschelde (in 1980-1990)[END_REF]. Higher densities are observed around the mid-tidal level (Fig. 4).

-Lifestyle

The Cockle is a burrowing animal. By means of its muscular foot the cockle burrows rapidly in the sediment (Fig. 5). Thus, cockle is protected from waves as many aquatic and terrestrial predators: crabs, waders, humans...

Diet: active suspension feeder

The Cockle filters actively water thanks to its two siphons (inhalant and exhalant) positionned on the surface of the sediment. Water is filtered through gills to keep phytoplancton, zooplancton and organic particles. These elements are grouped together into a mucus and make for the mouth thanks to cilias, like on a conveyor belt.

Digestion takes place in an intestine to enzymes and bacteria. The crystal-line style is translucent like a glass rod (fig. 6). It's an enzyme reserve used progressively by the cockle during the digestion.

Alive cockles can be found on the sediment surface on the intertidal zone (Fig. 7). They generally represent a little part of the global population. These cockles themselves come back up to the surface of the sediment, or have come loose due to displacement of sediment, caused for example by modifications of the banks of the rivers which go all over the intertidal zone. These cockles are generally very weakened and have lost their burrowing capacities.

The burrowing capacity is here compared on an experimental basis. Cockles are placed on the sediment (5cm deep) under 5cm of water, and spaced out a few centimeters from each other. Burrowed cockles are counted 2 hours later. Results are shown fig. 8. To confirm that these cockles are weakened and not capable to burrow, a condition index (Ic) is calculated to get valuation of the state of their health. The IC is the flesh-to-shell ratio. It enables to bring out the loss of weight (fig. 9). Cockles found on the surface of the sediment weigh 25% less than ones found burrowed in the sediment (dry weight). These cockles are very weakened, probably dying.

-Reproduction

Cockles generally live two to four years on average, but they can exceptionally reach ten years old. The phenomena of reproduction are clearly influenced by the physical environment, notably the increase of the temperature, more than an absolute value of it. The sexual maturity is generally reached during the second year (size between 13 and 16 mm, 15 to 18 months). Some authors have noticed a reproduction during the first year if cockles grow very fast [START_REF] Seed | A comparison of the reproductive cycles of Modiolus modiolus (L.), Cerastoderma (=Cardium) edule (L.), and Mytilus edulis L. in Strangford Lough, Northern Ireland[END_REF]. It seems that, sexual maturity depends on the size more than the age of individuals [START_REF] Kristensen | Differences in density and growth in a cockle population in the Dutch Wadden Sea[END_REF]Handcock & Franklin, 1972;[START_REF] Sauriau | Les mollusques benthiques du basin de Marennes-Oléron : estimation et cartographie des stocks non cultivés, compétition spatiale et trophique, dynamique de population de Cerastoderma edule[END_REF]. Sexual maturity can be reached in a few months in the bay of Sommes [START_REF] Lemoigne | Exploitation des ressources en bivalves de la baie de Somme. Aménagement de la pêche à pied et état de la ressource en coques[END_REF] and up to 2 years in Northern Ireland [START_REF] Seed | A comparison of the reproductive cycles of Modiolus modiolus (L.), Cerastoderma (=Cardium) edule (L.), and Mytilus edulis L. in Strangford Lough, Northern Ireland[END_REF].

Cockles are gonochorics (sexes are distinct). On medium latitude, many phases of laying can be identified during the year: -Early layings (frebruary-marsh), particularly for old individuals [START_REF] Guillou | Les modalités de la reproduction de la coque (Cerastoderma edule) sur le littoral français de la Manche et de l'Atlantique[END_REF]) -Spring layings (april-june), generally the most important -Summer layings, all the more important if the spring layings have been low -Late autumn layings (end of September-November) not always intense On more nordic latitude (higher than 55°N), only one reproduction period is observed. It's a short period, synchronised with the most favorable nutritive and thermic conditions. In the South, from Northern Ireland latitude, the strategy of reproduction is modified. Gametogenesis occurs in spring-summer but the repetitive characteristics of laying become more constant [START_REF] Seed | Growth as a strategy for survival in two marine bivalves, Cerastoderma edule and Moiolus modiolus[END_REF]. For medium latitudes, up to Galice, it occurs earlier and earlier and layings are repetitive.

The intensity of laying is generally conversely linked with the intensity of the previous laying. Thus, the intensity of autumn laying is conversely linked with the intensity of the summer laying, as it has been observed in the bay of Somme [START_REF] Desprez | Crise de la production des coques (Cerastoderma edule) en baie de Somme. I. Synthèse des connaissances biologiques[END_REF]. Literature is unanimous to say that a harsh winter stimulate reproduction, synchronising male and female emissions of gametes and insuring a better fertility (Handcock, 1973).

Ovocyt production depends on the size of individuals. For a female of about 18 to 38 mm, ovocyt production varies from 5600 to 52 000 ova [START_REF] Kristensen | Differences in density and growth in a cockle population in the Dutch Wadden Sea[END_REF]. Gametes are emitted in the pallial cavity. Thanks to water currents created by gills, gametes will go into the sea water through the exhalant syphon. Sperm will then fecond ova and form eggs (50 to 60 µm). Eggs will develop to form a planctonic larva, named trocophore and Velliger (fig. 10). In 3 days, planctonic larvae will develop a minuscule shell and reach the size of 270 µm in 3 to 5 weeks (Creek, 1960). In three month, the larva measure 1mm.

-Settlement

Settlement refers to the the settling of larvae in the sediment. Young larvae of 1 mm with small shells settle on the surface of the sediment and try to burrow using their foot. It occurs in May-June for most of cockles from medium latitudes, and to a lesser extent, up to September. Bouma has shown that important densities of cockle settlement are correlated with areas where the silt is maximal during the tidal cycle, at the bathymetric and granulometric levels [START_REF] Bouma | Spatial pattern of early recruitment of Macoma balthica (L.) and Cerastoderma edule (L.) in relation to sediment dynamics on a highly dynamic intertidal sandflat[END_REF]. Sediment must have propitious granulometric characteristics for water fixing: between 50 and 200 µm in the Bay of Somme [START_REF] Lemoigne | Exploitation des ressources en bivalves de la baie de Somme. Aménagement de la pêche à pied et état de la ressource en coques[END_REF], between 100 and 125 µm in the bay of Saint-Brieuc, because the survival of youngs depends on a good water retention (humidity between 30 and 35% for settlement sites in the bay of Saint-Brieuc). Settlement areas are generally restricted. For example, they represent about 1000 ha in the bay of Saint-Brieuc. The global stock represents 3000 ha, and areas with a density of young cockles in

Crown of cilia

excess of 100 individuals/m² only represent 400 ha (excluding exceptional year with high settlement) [START_REF] Ponsero | Modelling of the Cockle (Cerastoderma edule L.) fishing grounds in a purpose of sustainable management of traditional harvesting[END_REF]. Temperature seems to be a primary factor for the survival of the planctonic larvae [START_REF] Baggerman | Spatfall and transport of Cardium edule[END_REF], particularly during the implantation in the sediment. If conditions are not combined, the young cockle can look for a better site. To find a new site, the young cockle makes some byssus, like proteic filaments, which makes its bearing surface increase to get hanging in water easier, and is transported by current to new sites. This displacement is named "bisso-pelagic migration" (Moutaudouin, 1997;[START_REF] Huxham | Can postlarval bivalves select sediment type during settlement? A field test with Macoma balthica (L.) and Cerastoderma edule (L.)[END_REF].

An important or a very important settlement is generally followed by a low one the year after. For example, in the bay of Saint-Brieuc in 2005, the settlement was lower than 20% of the average observed between 2001 and 2008, after a very important settlement, rate of 220%, which occured in 2004 [START_REF] Ponsero | Modelling of the Cockle (Cerastoderma edule L.) fishing grounds in a purpose of sustainable management of traditional harvesting[END_REF].

-Growth

Cerastoderma edule follow a very fast growth the first two years which then declines (fig. 11). Cockles growth modeling can be adjusted to the Von Bertalanfy model ( 1938). It's generally used to compare mollusc growth rate [START_REF] Ramon | Population dynamics and secondary production of the cockle Cerastoderma edule (L.) in backbarrier tidal flat of the Wadden[END_REF].

The model of growth in length, at t time, has for equation: L t = l ∞ (1-e -k(t-t0) ) with l ∞ : asymptote of the curve (often called "maximal length") k : initial growth coefficient t 0 : theoretical date of birth Many factors influence the growth of cockles : the season, the location [START_REF] Hancock | Growth and mesh selection in the edible cockle (Cardium edule L.)[END_REF][START_REF] Ducrotoy | A comparison of the population dynamics of the cockle (Cerastoderma edule) in North-Western Europe[END_REF], water temperature [START_REF] Smaal | Seasonal variation in physiological energetics of Mytilus edulis and Cerastoderma edule of different size classes[END_REF], food availability or cockle density [START_REF] Jensen | Density dependant growth in cockles (Cerastoderma edule): evidence from interannual comparisons[END_REF], Montaudoin & Bachelet, 1996).

In the bay of Arcachon Montaudoin & [START_REF] Montaudouin | Experimental evidence of complex interactions between biotic and abiotic factors in the dynamics of an interdial population of the bivalve Cerastoderma edule[END_REF] have shown that the cockle growth was linked with their position on the intertidal area. On low foreshore levels, cockles grow faster because they suffer less tides and can spend more time filtering and feeding. Thus, growth rate depends as well on immersion time. In the bay of Saint-Brieuc, we show that the doubling of immersion time explains about 30% of the increase of growth for the first winter rings, 20% for the second winter rings, and 10% for the third winter ones. That can be brought to the fore with the comparison of the k parameter values (growth coefficient) of the Von Bertalanfy model estimated in stations characterised by different hypsometric levels.

Fig. 12 : K parameter value of the Von-Bertallanfy model in the bay of Saint-Brieuc modelised according to hyspometric level (m) [START_REF] Ponsero | Modelling of the Cockle (Cerastoderma edule L.) fishing grounds in a purpose of sustainable management of traditional harvesting[END_REF].

Seasonal growth starts in May in Wales, it reaches its maximum from June to August, and it's negligible after [START_REF] Seed | A comparison of the reproductive cycles of Modiolus modiolus (L.), Cerastoderma (=Cardium) edule (L.), and Mytilus edulis L. in Strangford Lough, Northern Ireland[END_REF][START_REF] Hancock | Seasonal changes in the condition of the edible cockle Cardium edule (L.)[END_REF]. Cockles generally lose weight during winter and support the theory of important mortality due to winter harshness. In regions characterised by marked cycles of temperature, seasonal rhythms of growth are visible in mineralised tissues.

The fluctuation of growth speed causes an alternation of fast growth zones and slow growth on shells. Sometimes, the growth can stop, waiting for better conditions. This seasonnal growth causes rings of growth on shells (fig. 13). Thus, it became possible to determine the age of the cockle reading and counting these rings, and analyse the differencial growth of populations in a second time [START_REF] Richardson | The use of tidal growth bands in the shell of Cerastoderma edule to measure seasonal growth rates under cool temperate and sub-arctic conditions[END_REF][START_REF] Jones | Monitoring and surveillance of sandy shores using the bivalve Cerastoderma edule (L.)[END_REF]. However, rings reading remains difficult because of additional rings caused by growth variations during the same year [START_REF] Ramon | Population dynamics and secondary production of the cockle Cerastoderma edule (L.) in backbarrier tidal flat of the Wadden[END_REF], all the more when winter temperatures remain high (low latitudes).

-Biomass and production

Cockles can represent up to 60% of the benthos biomass [START_REF] Ramon | Population dynamics and secondary production of the cockle Cerastoderma edule (L.) in backbarrier tidal flat of the Wadden[END_REF] and play an important role in the intertidal ecosystem functioning [START_REF] Beukema | Annual cockle Cerastoderma edule production in the Wadden Sea usually fails to sustain both wintering birds and a commercial fishery Marine ecology[END_REF]. In the bay of Saint-Brieuc, cockles represent 62% of the bivalves biomass (2007).

The producted biomass (grams of dry matter per square meter ou g.AFDW. m -2 ) is about from 10 to 40g, and can reach up to 100 g.AFDW. m -2 ). In the bay of Marennes-Oléron, biomass is evaluated to 32,5 g.AFDW. m -2 [START_REF] Sauriau | Les mollusques benthiques du basin de Marennes-Oléron : estimation et cartographie des stocks non cultivés, compétition spatiale et trophique, dynamique de population de Cerastoderma edule[END_REF]. In the Wadden sea, the production varies from 7,6 to 101,6 g.AFDW. m -2 [START_REF] Beukema | Annual cockle Cerastoderma edule production in the Wadden Sea usually fails to sustain both wintering birds and a commercial fishery Marine ecology[END_REF]. In the bay of Saint-Brieuc the biomass average of the site, varies in function of year between 6,01g.AFDW. m -2 and 14,52 g.AFDW. m -2 (average 10,349 ± 2,713), with maximums that vary from 43 to 388,55 g.AFDW. m -2 . To sum up, production depends on many factors and strong year-to-year variations are usually observed.

-Structure of the population

Class size histograms are generally polymodal (fig. 14) with an overlapping of different cohorts for the highest age classes [START_REF] Ramon | Population dynamics and secondary production of the cockle Cerastoderma edule (L.) in backbarrier tidal flat of the Wadden[END_REF][START_REF] Ponsero | Modelling of the Cockle (Cerastoderma edule L.) fishing grounds in a purpose of sustainable management of traditional harvesting[END_REF]. To differentiate the membership probability of cockles of one cohort or other, the probability of each cockle being linked with a cohort can be calculated using its size and consulting the normal curve of different cohorts obtained with the analysis of growth rings [START_REF] Ponsero | Modelling of the Cockle (Cerastoderma edule L.) fishing grounds in a purpose of sustainable management of traditional harvesting[END_REF]. Parameters of cohort composing the demographic structure established each year are optimized by the maximum of likely methods [START_REF] Hasselblad | Estimation of parameters for a mixture of normal distribution[END_REF]. One of the cockle particularity is certainely the flexibility of its demographic strategy [START_REF] Seed | Growth as a strategy for survival in two marine bivalves, Cerastoderma edule and Moiolus modiolus[END_REF][START_REF] Sauriau | Les mollusques benthiques du basin de Marennes-Oléron : estimation et cartographie des stocks non cultivés, compétition spatiale et trophique, dynamique de population de Cerastoderma edule[END_REF]). That's why biologic parameter assessment of a population must be realised with a sampling protocol adpated to the spatial scattering and the year-to-year variations.

-Spatial distribution

A spacial segregation of generations can be observed, as this has been highlighted in many sites for Macoma balthica [START_REF] Bachelet | Dynamique de la macrofaune benthique et production des lamellibranches de l'estuaire de la Gironde[END_REF]Hiddink & Wolf, 2002) and C. Edule [START_REF] Sutherland | Spatial variation in the predation of cockles by oystercatchers at Traeth Melynog. Anglesey. I. the cockle population[END_REF]. Spacial distribution varies with the size of individuals. Higher class sizes are at lower bathymetric levels. A correlation exists between the medium size of cockles per station and the bathymetric level of stations. Generally, cockle stocks are characterized by a strong spacial heterogeneity of densities and biomasses [START_REF] Farrow | On the ecology and sedimentation of the Cardium shellsands and transgressive shellblanks of traigh Mhor, Island of Barra, Outer Hebrides[END_REF]. Unlike what is observed in the bay of Somme [START_REF] Desprez | Fonctionnement biologique des gisements de coques de la baie de Sommes (France) à la suite du recrutement massif de 1987 : recrutement de 1988 et 1989, environnement bio-sédimentaire[END_REF] or in Scotland [START_REF] Farrow | On the ecology and sedimentation of the Cardium shellsands and transgressive shellblanks of traigh Mhor, Island of Barra, Outer Hebrides[END_REF], this spacial structuring is quite constant in the bay of Saint-Brieuc under eight years of monitoring. Settlement areas are geographically well defined and localized at mid-tide level in limited areas (excepted during exeptional settling phases). Cohorts 4+ and 5+ are below this level (fig. 15).

-Population dynamic

Cockle numbers can vary year-to-year on some sites or keep constant during larger periods on others. Different factors are described as acting on settlement, growth and natural population mortality. The diagram below, extracted from the thesis of [START_REF] Montaudouin | Etude expérimentale de l'impact de facteurs biotiques et abiotiques sur le recrutement, la croissance et la survie des coques Cerastoderma edule (Mollusque-Bivalve[END_REF], shows the synthetic (fig. 16).

Fig. 16:

Factors regulating the population dynamics of cockles (Montaudoin, 1995).

Density Individual biomass

Settlement Growth

Habitat accessibility

Depends on: Hydrodynamics Nature of sediment Competition Bioturbation

Accessibility to food ressources

Depends on: Duration of emersion Competion Macrophyts (alguae)

Mortality-Emigration

Predation Fisching Age Macrophyts (Alguae) Hydrodynamics Parasitism Pollution

-Mortality

The long-term monitoring of the population dynamics of the cockles in the bay of Saint-Brieuc shows that the medium mortality from one year to another is an overall constant during the cockle life: between 50% and 70% of the number of the previuous year before [START_REF] Ponsero | Modelling of the Cockle (Cerastoderma edule L.) fishing grounds in a purpose of sustainable management of traditional harvesting[END_REF]. In this case, the mortality is considered complete because it includes all of the anthropic or natural causes. Many authors have been interested in the predation that occured on juveniles. [START_REF] Reise | Tidal Flat Ecology: An Experimental Approach to Species Interactions[END_REF] shows clearly that the pression of predation is focused on first stages of growth and then decreases with cockle growth. For example, predation by the European flounder (Platichthys flesus) on the cockle seed (Wolf et al., 1981), and the shore crab (Carcinus maenas) (Brock, 1980;Sanchez-Salazar et al., 1987a,b) have been highlighted. Predation by waders, particularly by European oystercatcher (Haematopus ostalegus) occurs on individuals of about 2 cm long, either on one year and half old cockles [START_REF] Triplet | Comment les huîtriers-pies Haematopus ostralegus consommateurs de coques Cerastoderma edule évitent les relations intra spécifiques[END_REF]Triplet et al., 1999a) or between 15 and 30mm according to [START_REF] West | Predicting site quality for shorebird communities: A case study on the Wash embayment, UK[END_REF]. Leftover cockles were found in the faeces of waders, as Dunlin Calidris alpina [START_REF] Durell | Diets of Dunlin Calidris alpina and Grey plover Pluvialis squatarola on the Wash as determined by dropping analysis[END_REF][START_REF] Drean Quenec'hdu | Les limicoles séjournant dans les traicts du Croisic (Presqu'île Guérandaise, Loire-Atlantique) : Régime alimentaire et impact sur les populations de mollusques bivalves[END_REF][START_REF] Cabral | The impact of macroalgal blooms on the use of the intertidal area and feeding behaviour of waders (Charadrii) in the Montego estuary (west Portugal)[END_REF], Red knots Calidris canutus [START_REF] Dekinga | Reconstructing diet composition on the basis of faeces in a mollusceating wader, the Knot Calidris canutus[END_REF], Bar-tailed Godwit Limosa lapponica [START_REF] Goss-Custard | The ecology of the Wash II. Seasonal variation in the feeding conditions of wading birds (Charadrii)[END_REF]Scheiffart, 2001), Eurasian curlew Numenius arquata (Le Drean Quenec'hdu & Maheo, 1997), Avocet Recuvirostra recuvirostra [START_REF] Moreira | The winter feeding ecology of Avocets Recurvirostra avosetta on intertidal areas. II. Diet and feeding mechanisms[END_REF].

Extreme temperatures play an important role in the mortality of different age classes. The winter mortality particularly affects the smallest individuals [START_REF] Sauriau | Les mollusques benthiques du basin de Marennes-Oléron : estimation et cartographie des stocks non cultivés, compétition spatiale et trophique, dynamique de population de Cerastoderma edule[END_REF]. Populations can be affected when the temperature of the sediment decreases below 7°C. [START_REF] Kristensen | Differences in density and growth in a cockle population in the Dutch Wadden Sea[END_REF] showed that the tolerance of cockle is about 34°C with a lethal step at 36°C, and that seed resists better to high temperature than adults.

It's difficult to assess the impact of professional or recreational harvesting. However, these activities can have a significant impact on population dynamics (next chapter). The impact of parasitism is rarely mentionned in studies focused on the population dynamics of bivalves. Chapter 14 highlights the importance of this phenomenon without assessing the impact. Note that an accidental or diffuse pollution can weaken individuals which will become less resistant, and more sensitive to attacks by parasits or predators. Thus, the impact of these interacting factors is more important than the sum of the two.

-Harvesting and managment of the bed

In all european sites studied where an important harvesting activity occurs, a demographic structure truncated beyond the commercial size is observed, whatever the growth rate of individuals of these populations [START_REF] Hancock | Growth and mesh selection in the edible cockle (Cardium edule L.)[END_REF][START_REF] Franklin | The cockles and its fisheries[END_REF][START_REF] Gordo | Aspects of the growth and density of Cerastoderma edule in the Alvor Salt Marsh South Portugal[END_REF]. [START_REF] Sauriau | Les mollusques benthiques du basin de Marennes-Oléron : estimation et cartographie des stocks non cultivés, compétition spatiale et trophique, dynamique de population de Cerastoderma edule[END_REF] mentions that the demographic structure of a stock under heavy harvesting pressure presents less than 5% of individuals measuring 30mm.

In France up to 2006, the harvesting impact (professional or recreational) occurs on class sizes greater than or equal to 30mm, corresponding to 3 years old individuals and over. One can hypothesize that the increase of mortality of this class age could be attributed to harvesting. In autumn 2006, the legal harvesting size has changed from 30mm to 27mm (corresponding to two and a half years old individuals). It is possible that this decision had an impact on the demographic structure of the population. In the future, this modification of the harvesting size will probably influence the 1∞ modelised value, as it has been highlighted by [START_REF] Hancock | Growth and mesh selection in the edible cockle (Cardium edule L.)[END_REF], and that, whatever the growth rate of individuals of population. This harvesting size decrease, that seems negligible, causes a doubling of harvestable stock [START_REF] Ponsero | Modelling of the Cockle (Cerastoderma edule L.) fishing grounds in a purpose of sustainable management of traditional harvesting[END_REF].

-Cockles parasitism

Cockles are, as other animals, a living environment for other organisms which depend totally on the first. This phenomenon is called parasitism. The parasit lives in its host, in this case the cockle, and reduces more or less the fitness of the host. Many parasits are known for the cockle. Can find ciliated protozoa living in the water-intake valves, crustaceans in the intestin, and several flatworms attached to the plathelminth phylum (digenian trematodes) in different bodies. These flatworms follow very complex biologic cycles.

A -Digenian trematode parasits

The adult of the parasit lives in vertebrates ( bird or fish which is named definitive host (DH)) and lays eggs that will join the water by the faeces of the vertebrate. A small larva (miracidium) is born from this egg and immediately looks for a second host (intermediate host 1, IH1) to multiply, usually a mollusc. Cockle can be this PH1. A large numbers of larvae is producted by asexual reproduction, and then runs into water.

A third host (intermediate host 2, IH2) is used by larvae to join the definitive host easily. By feeding PH2, the DH swallows the parasite at the same time, and becomes contaminated. At this moment, the larval form of the parastite is different because it aims to wait and does not try to multiply as in PH1. Thus, the parasite lives in three different hosts (Fig. 18). Generally low prevalence in cockle, but can reach 50% at Arcachon. In the bay of Saint-Brieuc, prevalence varies from 2 to 20% depending on sites [START_REF] Montaudouin | Digenean trematode species in the cockle Cerastoderma edule: identification key and distribution along the north-eastern Atlantic shoreline[END_REF].

Intensive multiplication in hemolymph (blood), gonad or digestive gland of the cockles which dies. Note on the right picture, high concentrations of parasits for only one cockle. Cercariae leave cockle and look actively for a gobby (PH2) to penetrate it by the base of fins or gills (Malek, 2001). These larvae, then, are stored in the fish's liver.

When an infested gobby is consumed by a Sea bass, it is infested in turn and the parasite takes its adult form. . -Crustacean

A small elongated crustacean (2mm long) can be found, again in the intestine: Mytilicola intestinalis. As its name indicates, it particularly likes the intestine of mussels ("cola": which likes; "mytili": mussel; "intestinalis": intestine).

-Ciliated protozoan

Ciliated protozoans are animals made of only one cell, therefore very small and invisible to the naked eye.

The cilia that characterize the phylum of ciliates can be easily observed under the microscope.

C -To conclude

Others macroparasites have been found in the cockles of the bay of Saint-Brieuc, for example: Meiogymnoplallus minutus. This species is located at the hinge in a vesicule tissue of the host. It is present in large quantities and with a high prevalence. The first intermediate host is the Peppery furrow shell (Scrobicularia plana), very common in the bay of Saint-Brieuc. The definitive host can be the European oystercatcher or some anatidae.

The impact of parasitism generally depends on the numbers of parasites present in the host. In scientific literature, several cases of weakening effects are mentioned. Strong mortality can occur (Jonnsson & André, 1992), and sometimes a destruction of gonads which causes the castration of some individuals, and thus decreases the stock of breeding [START_REF] Boyden | Relationschip of size to age in the cockles Cerastoderma edule and C. glaucum from the river Crouch Estuary, Essex[END_REF].

When cockle is the first intermediate host, there is an outbreak that causes the death of the host, but with a relatively low prevalence. IH1 is used to multiplicate asexually intensively the parasite and provide a very large number of infective forms that will stay in the second intermediate host.

When cockle is the second intermediate host, it serves to convey parasites and send them to the definitive host. In this case, the virulence of the parasite is low because it must not cause the death of the host, which will cause its own at the same time. There is a low pathogenecity, but a high prevalence, which will increase the probability that the definitive host becomes infested by eating IH2.

We observed in the bay of Saint-Brieuc that the cockles found on the surface of the sediment (ascending cockles) were more infested by cysts of Himasthala (Fig. 26). That indicates a nefast effect of the parasite on the weakened animal. Some authors interpret this as a strategy of the parasite. Indeed, it is not by chance if the parasite is in the foot of the cockle. We can suppose that it causes a decrease of its burrowing capacities. It thus becomes more accessible to the bird (definitive host). This phenomenon is called "favorisation" mechanism [START_REF] Combes | Interactions durables. Ecologie et évolution du parasitisme[END_REF]. Parasitism is not the only factor that can explain the rise of cockles on the sediment surface. The lack of oxygen is the most implicated factor. We note a lower resistance to thermal stress (heatwave for example) when cockles are infested by Himasthla spp. [START_REF] Lauckner | Diseases of Mollusca: Bivalvia[END_REF]. Indeed they die more quickly that uninfested ones. Parasites represent a serious cause of direct mortality (especially the first year), and thus a factor of regulation of populations. It seems as well to make them more sensitive to environmental disturbances (climate, pollution...) or decrease the growth rate [START_REF] Lauckner | Diseases of Mollusca: Bivalvia[END_REF][START_REF] Jonsson | Mass mortality of the bivalve Cerastoderma edule on the Swedish west coast caused by infestation with the digenean trematode Cercaria cerastodermae L[END_REF][START_REF] Wegeberg | In situ growth of juvenile cockles, Cerastoderma edule, experimentally infected with larval trematodes (Himasthla interrupta)[END_REF]Thielges, 2006). Thus, the impact of pollutions could be amplified by an important parasitism.

A second question facing us: Can the parasitic infestation and the induced mortality be considered as a consequence of a weakening of animals caused by ecosytem dysfunctions (pollutions, or disturbance of balances)? Weakened cockles, with immunity deficiency, will be more easily attacked by parasites. Further studies are necessary to attempt to provide some answers to these questions.

Finally, no studies have shown that these parasites could be transmitted to humans and cause disease. Even in the absence of cooking, they are destroyed by the acidity of the stomac and by digestive enzymes.

Credits photos : e-mail : laurent.dabouineau@uco.fr alain.ponsero@espaces-naturels.fr

•

  Fig. 1 The two valves of a closed Cockle. The broad ribs, the ligament and the hinge are conspicuous

FigFig. 3 :Fig. 4 :

 34 Fig. 2 : Main stocks of Cockle (Cerastoderma edule) in France[START_REF] Quéro | Les fruits de la mer et les plantes marines des pêches françaises[END_REF]

Fig. 6 :Fig. 7 :Fig. 5 :Fig. 8 :

 6758 Fig. 6: enzymatic cristal-line style (extrated from the digestive tract for the picture)

Fig. 9 :

 9 Fig. 9: condition index (IC= ash free dry mass of flesh / dry mass of shell) ± standard-Error of Cockles found burrowed in the sediment (n=60) and on the surface (n=61), (Anova test p<0,01). (U.C.O., june 2003, not published)

Fig. 10

 10 Fig. 10 schema of the trocophore larva (Biodidac, Ottawa University)

Fig. 13 :

 13 Growth rings (cockle size: 4,2 cm) Relationships which link individual size (mm) with the mass of living matter produced (mass of ash free dry mass) can be analysed in this form: W=aL b . W: ash free dry mass (g.m -2 ) L: size of individuals (mm) a and b: parameters of the equation etablished for the site

Fig. 14 :

 14 Fig. 14 : Size-frequency bar charts observed in the bay of Saint-Brieuc from 2001 to 2008, expressed as a percentage of total

Fig. 15 :

 15 Fig. 15 : Spacial distribution map of the different cohorts in the bay of Saint-Brieuc (average values modeled from 2001 to 2008 by Kriging)

Fig. 17 :

 17 Fig. 17: Diagram shows the variations of an hypothetic cohort over time (with a constant medium interannual mortality of 60%).

Fig. 18 :

 18 Fig. 18: Example of three successive hosts which enable to close the biological cycle of a digenian trematode parasite

Fig. 20 :Fig. 19 :Fig. 21 :Fig. 22 :

 20192122 Fig. 20: Labratrema minimus larvae of 0,2mm with 2 longs tentacles used to adhere to gobby mucus.

Fig. 23 :Fig. 24 :

 2324 Fig. 23: Paravortex cardii (2 mm)

Fig. 25 :

 25 Fig. 25 : Trichodina sp (50 µm) Long cilias around the animal can be observed.

  Université U.C.O. Bretagne Nord -Laurent DABOUINEAU Réserve Naturelle Nationale baie de Saint-Brieuc -Alain PONSERO Reference of this article : Dabouineau, L. & Ponsero, A., 2009. Synthesis on biology of Common European Cockle Cerastoderma edule. Second edition Université Catholique de l'Ouest -Réserve Naturelle Nationale Baie de St-Brieuc, 23 pages.

Fig. 26 :

 26 Fig. 26: Average number of cysts in the foot ± standard error (cockle found on the sediment n=35, found in the sediment (n=40), size: around 3cm. U.C.O, June 2003, not published)

Table 1 :

 1 Total numbers (*10 6 ) of the cockles stock of the bay of Saint-Brieuc, and numbers (*10 6 ) of the first year cohort assessed by modelisation (kriging)

	Year	total	0	%
	2001	1546	1156	74,81
	2002	1355	393	29,00
	2003	1619	1279	79,02
	2004	5158	3972	77,00
	2005	2051	380	18,53
	2006	1870	968	51,76
	2007	858	115	13,41
	2008	6297	6067	96,34
	mean	2594	1791	55
	sd	1990	2109	31

Table 2 :

 2 Comparison of cockle growth modelisation in different european sites (K: initial growth coefficient, 1∞ asymptote value, t o length to the origin. Some authors do not model this value and prefer the set to 0.• growth index : • = 2 log 10 (1∞)+ log 10 (k) according to Pauly &[START_REF] Morgan | Length-based methods in fisheries research[END_REF]

	Sites	k	l ∞	t0	φ'	source
	Denmark (Langerak)	0.248 0.386	54 40.7	-0.2 -0.34	2.86 2.81	(Brock 1980)
	Germany (Wadden sea)	0.404	40	-	2.81	(Ramon 2003)
	England Wales (Llanrhidian sand)	0.59	31.5	-	2.77	(Hancock 1965),
	Ireland (Dundalk bay)	0.4364	49.1	-.03995	3.02	(Fahy et al. 2005)
	France (Saint-Brieuc bay)	0.64	34.36	-	2.88
	France (Marenne-Oleron)	0.068	30.87	-2.11	1.82	(Sauriau 1992)
	north Spain (rias Altas)	1.609	26.5	0.104	3.05	(Catoria et al. 1984)
	north Spain (rias Arosa)	0.951	41.226	0.083	3.21	(Pérez Camacho & Román 1984)
	north Spain (Mundaca estuary)	0.026	28.27	8.998	1.32	(Iglesias & Navarro 1990)
	south Spain (Algeciras bay)	0.18	36	-0.05	2.37	(Guevara & Niell 1989)

Table 3 :

 3 Comparison of the modeling parameters of the size-mass relationship in different sites.