Etienne Rivot

Estimates of the mortality and the duration of the trans-Atlantic migration of European eel Anguilla anguilla leptocephali using a particle tracking model

Using Lagrangian simulations, based on circulation models over three different hydroclimatic periods in the last 45 years in the North Atlantic Ocean, the trans-Atlantic migration of the European eel Anguilla anguilla leptocephali was simulated via the passive drift of particles released in the spawning area. Three different behaviours were modelled: drifting at fixed depth, undergoing a vertical migration or choosing the fastest currents. Simulations included mortality hypotheses to estimate a realistic mean migration duration and relative survival of A. anguilla larvae. The mean migration duration was estimated as 21 months and the mortality rate as 3.8 per year, i.e. < 0.2% of A. anguilla larvae may typically survive the trans-Atlantic migration.

Effect of water temperature and density of juvenile salmonids on growth of young‐of‐the‐year Atlantic salmon Salmo salar

A von Bertalanffy growth model for young-of the-year Atlantic salmon Salmo salar in a small French coastal stream was fitted using water temperatures and densities of juvenile salmonids (S. salar and brown trout Salmo trutta) as covariates influencing daily growth rate. The Bayesian framework was used as a template to integrate prior information from external data sets. The relative influence of the covariates on parr growth was quantified and results showed that growth of S. salar juveniles depended on both water temperatures and densities, but that most of the spatiotemporal variability of growth resulted from local spatiotemporal variations of 0+ age salmonid (S. salar and S. trutta) densities. Further analysis revealed that the fluctuations in young-of-the-year salmonid densities are likely to dominate the effects of potential future warming of water temperature due to climate change. It is concluded that factors that could affect salmonid densities might well have a greater effect on S. salar population dynamics than factors influencing water temperatures.

A hierarchical Bayesian model for embedding larval drift and habitat models in integrated life cycles for exploited fish

This paper proposes a hierarchical Bayesian framework for modeling the life cycle of marine exploited fish with a spatial perspective. The application was developed for a nursery-dependent fish species, the common sole (Solea solea), on the Eastern Channel population (Western Europe). The approach combined processes of different natures and various sources of observations within an integrated framework for life-cycle modeling: (1) outputs of an individual-based model for larval drift and survival that provided yearly estimates of the dispersion and mortality of eggs and larvae, from spawning grounds to settlement in several coastal nurseries; (2) a habitat suitability model, based on juvenile trawl surveys coupled with a geographic information system, to estimate juvenile densities and surface areas of suitable juvenile habitat in each nursery sector; (3) a statistical catch-at-age model for the estimation of the numbers-at-age and the fishing mortality on subadults and adults. The approach provided estimates of hidden variables and parameters of key biological significance. A simulation approach provided insight to the robustness of the approach when only weak data are available. Estimates of spawning biomass, fishing mortality, and recruitment were close to the estimations derived from stock-assessment working groups. In addition, the model quantified mortality along the life cycle, and estimated site-specific density-dependent mortalities between settled larvae and age-0 juveniles in each nursery ground. This provided a better understanding of the productivity and the specific contribution of each nursery ground toward recruitment and population renewal. Perspectives include further development of the modeling framework on the common sole and applications to other fish species to disentangle the effects of multiple interacting stress factors (e.g., estuarine and coastal nursery habitat degradation, fishing pressure) on population renewal and to develop risk analysis in the context of marine spatial planning for sustainable management of fish resources.

Accounting for Age Uncertainty in Growth Modeling, the Case Study of Yellowfin Tuna (Thunnus albacares) of the Indian Ocean

Age estimates, typically determined by counting periodic growth increments in calcified structures of vertebrates, are the basis of population dynamics models used for managing exploited or threatened species. In fisheries research, the use of otolith growth rings as an indicator of fish age has increased considerably in recent decades. However, otolith readings include various sources of uncertainty. Current ageing methods, which converts an average count of rings into age, only provide periodic age estimates in which the range of uncertainty is fully ignored. In this study, we describe a hierarchical model for estimating individual ages from repeated otolith readings. The model was developed within a Bayesian framework to explicitly represent the sources of uncertainty associated with age estimation, to allow for individual variations and to include knowledge on parameters from expertise. The performance of the proposed model was examined through simulations, and then it was coupled to a two-stanza somatic growth model to evaluate the impact of the age estimation method on the age composition of commercial fisheries catches. We illustrate our approach using the saggital otoliths of yellowfin tuna of the Indian Ocean collected through large-scale mark-recapture experiments. The simulation performance suggested that the ageing error model was able to estimate the ageing biases and provide accurate age estimates, regardless of the age of the fish. Coupled with the growth model, this approach appeared suitable for modeling the growth of Indian Ocean yellowfin and is consistent with findings of previous studies. The simulations showed that the choice of the ageing method can strongly affect growth estimates with subsequent implications for age-structured data used as inputs for population models. Finally, our modeling approach revealed particularly useful to reflect uncertainty around age estimates into the process of growth estimation and it can be applied to any study relying on age estimation.

Assessing stocks in data-poor African fisheries: a case study on the white grouper Epinephelus aeneus of Mauritania

The lack of reliable stock assessment for numerous exploited stocks in West Africa often results from poor-quality data, high multi-specificity of captures, and the heterogeneity of exploitation methods. However, many signs of overexploitation exist, particularly for demersal resources, highlighting the urgent need for a more quantitative and comprehensive evaluation of these resources. This study aims to show how, in such a context of poor-quality data and high uncertainty, a multi-method approach for stock assessment can generate a consistent diagnosis of the condition of a resource. As a case study, several methods were combined to assess the stock status of the white grouper Epinephelus aeneus, a flagship species in West Africa that is exploited by industrial and small-scale fisheries in Mauritania. These were estimation of abundance indices using delta generalised linear models; a biomass production model using a pseudo-equilibrium method and including an environmental effect of upwelling intensity; a dynamic biomass production model fitted in a Bayesian framework also including an environmental effect; and an age-structured model based on a modified pseudo-cohort analysis. Sensitivity analyses were performed for most of these assessment methods. Results show that the white grouper stock is highly overexploited due to an excess in the fishing effort estimated at between 30% and 50%, depending on the model used to estimate the effort at maximum sustainable yield.

A hierarchical bayesian model to quantify uncertainty of stream water temperature forecasts.

Providing generic and cost effective modelling approaches to reconstruct and forecast freshwater temperature using predictors as air temperature and water discharge is a prerequisite to understanding ecological processes underlying the impact of water temperature and of global warming on continental aquatic ecosystems. Using air temperature as a simple linear predictor of water temperature can lead to significant bias in forecasts as it does not disentangle seasonality and long term trends in the signal. Here, we develop an alternative approach based on hierarchical Bayesian statistical time series modelling of water temperature, air temperature and water discharge using seasonal sinusoidal periodic signals and time varying means and amplitudes. Fitting and forecasting performances of this approach are compared with that of simple linear regression between water and air temperatures using i) an emotive simulated example, ii) application to three French coastal streams with contrasting bio-geographical conditions and sizes. The time series modelling approach better fit data and does not exhibit forecasting bias in long term trends contrary to the linear regression. This new model also allows for more accurate forecasts of water temperature than linear regression together with a fair assessment of the uncertainty around forecasting. Warming of water temperature forecast by our hierarchical Bayesian model was slower and more uncertain than that expected with the classical regression approach. These new forecasts are in a form that is readily usable in further ecological analyses and will allow weighting of outcomes from different scenarios to manage climate change impacts on freshwater wildlife.

Evidence for long-term change in length, mass and migration phenology of anadromous spawners in French Atlantic salmon Salmo salar

This study provides new data on Atlantic salmon Salmo salar life-history traits across France. Using a long-term recreational angling database (1987-2013) covering 34 rivers in three regions (genetic units), a decline in individual length, mass and a delayed adult return to French rivers was reported. Temporal similarities in trait variations between regions may be attributed to common change in environmental conditions at sea. The relative rate of change in phenotypic traits was more pronounced in early maturing fish [1 sea-winter (1SW) fish] than in late maturing fish (2SW fish). Such contrasted response within populations highlights the need to account for the diversity in life histories when exploring mechanisms of phenotypic change in S. salar. Such detailed life-history data on returning S. salar have not previously been reported from France. This study on French populations also contributes to reducing the gap in knowledge by providing further empirical evidence of a global pattern in S. salar across its distribution range. Results are consistent with the hypothesis that the observed changes in life-history traits are primarily associated with environmental changes in the North Atlantic Ocean. They also emphasize the presence of less important, but still significant contrasts between region and life history.