No abstract

The Nivelle River, a typical Pyrenean mountainous watershed reaching the Bay of Biscay (Atlantic Ocean), was sampled with high resolution during 1996. The particulate organic carbon (POC) contents during successive floods shows that there is a graduated impoverishment of the organic fraction of suspended particulate matter (SPM) from the first flood to the next ones, reaching a threshold value (3%) attributed to allochtonous fraction (soil). On the basis of the high frequency data of water discharge and POC concentration, an annual POC flux was established: 845 tons, corresponding to a specific POC flux of 5.3 tC km À2 yr À1 . This value was obtained during a dry period and must be considered as a minimum value for longer time scale. The POC originated mostly from soil (55%) and riparian/litter ($40%) with a very minor (<5%) contribution of autochthonous POC. Thirty-two percent of the annual POC flux was carried in 1% of time and 66% in 10% of time. The specific POC yield, 5.3 tC km À2 yr À1 , if extended to the whole mountainous area of the southern coast of the Bay of Biscay (19,000 km 2 ), leads to an estimated POC flux around 100,000 t yr À1 . Although small Cantabrian mountainous rivers contributed to only 28% of the freshwater discharge in the Bay of Biscay, their POC load was estimated to account for 70% of the total POC inputs in the Bay.

Eo. In these rivers, management based on supplementation of native populations with foreign stocks was carried out for more than one decade. Population genetic patterns expressed in terms of allele frequencies, mean heterozygosity and conformity to Hardy-Weinberg equilibrium, were significantly different between populations. Relevant temporal changes of genetic variability were reported. Evidence that foreign stocking has disturbed the genetic patterns of some of the studied populations is presented. # 2005 The Fisheries Society of the British Isles

We present an application of Bayesian hierarchical modelling of stock–recruitment (SR) relationships aiming at estimating Biological Reference Points (BRP) for European Atlantic salmon (Salmo salar) stocks. The structure of the hierarchical SR model developed distinguishes two nested levels of randomness, within-river and between rivers. It is an extension of the classical Ricker model, where the parameters of the Ricker function are assumed to be different between rivers, but drawn from a common probability distribution conditionally on two covariates: river size and latitude. The output of ultimate interest is the posterior predictive distribution of the SR parameters and their associated BRP for a new river with no SR data. The flexible framework of the Bayesian hierarchical SR analysis is a step towards making the most comprehensive use of detailed stock monitoring programs for improving management advice. Posterior predictive inferences may be imprecise due to the relative paucity of information introduced in the analysis compared to the variability of the stochastic process modeled. Even in such cases, direct extrapolation of results from local data-rich stocks should be dismissed as it can lead to a major underestimation of our uncertainty about management parameters in sparse-data situations. The aggregation of several stocks under a regional complex improves the precision of the posterior predictive inferences. When several stocks are managed jointly, even imprecise knowledge about each component of the aggregate can be valuable. The introduction of covariates to explain between stock variations provides a significant gain in the precision of the posterior predictive inferences. Because we must be able to measure the covariates for all the stocks of interest, i.e. mostly sparse-data cases, the number of covariates which can be used in practice is limited. The definition of the assemblage of stocks which we model as exchangeable units, conditionally on the covariates, remains the most influential choice to be made when attempting to transfer information from data-rich to sparse-data situations.