@article {8752,
	title = {Modelling past migrations to determine efficient management rules favouring silver eel escapement from a large regulated Floodplain Lake},
	journal = {Journal for Nature Conservation},
	volume = {67},
	year = {2022},
	month = {Jan-06-2022},
	pages = {126192},
	abstract = {As human activities caused a dramatic decline of European eel population since the 1970\&nbsp;s, the European Union has set targets to ensure a 40\%\&nbsp;escapement\&nbsp;to the sea of the silver eel biomass by considerably reducing anthropogenic impact. Thus, human obstacles to fish migration like dams and hydropower plants should enable efficient management measures ensuring safe passage for eels during the migration. In order to provide a quick and efficient assessment of eel conservation measure applied to the\&nbsp;sluice gates\&nbsp;of a large\&nbsp;floodplain\&nbsp;lake, we implemented a novel evaluation method using predictions on past migration seasons when no management measure were applied. For this purpose, we collected acoustic\&nbsp;telemetry\&nbsp;monitoring data over three migration seasons and fitted a predictive model based on Boosted Regression Trees (BRTs) to describe the influence of environmental parameters on migration. The water level difference over two days proved to be decisive, along with early migration occasions in the season, as an increase of at least 10\&nbsp;cm water level was associated with a sharp increase of migration probability. We then used the BRT model to predict migration occasions at the dam over 8 past seasons and forecast the impact on escapement of management measures if they had been applied. Thanks to this original prospective assessment of dam management measures, we identified an enhanced opening decision rule, capable of increasing the eel escapement for each year of the study. The management measure is particularly efficient during the years with poor hydrological conditions (i.e. droughts), that is the periods with the lowest initial escapement rates. Finally, efficient management measures to increase silver eel escapement were based on increasing the number of\&nbsp;gate opening\&nbsp;days by only a few days per year (c.a. 15\%). However, the management measure only focused on silver eel migration, so that further investigations should consider the impacts of other threats occurring during the life cycle. This study also provides a highly operational approach for fast evaluation of conservation measures, avoiding lengthy and expensive monitoring campaigns of classical ex-post assessments.},
	keywords = {Eel conservation, fish migration, Predictive model, Reservoir management},
	issn = {16171381},
	doi = {10.1016/j.jnc.2022.126192},
	url = {https://linkinghub.elsevier.com/retrieve/pii/S1617138122000656},
	author = {Bourgeaux, Jacques and Teichert, Nils and Gillier, Jean-Marc and Danet, Valentin and Eric Feunteun and Acou, Anthony and Charrier, Fabien and Mazel, Virgile and Alexandre Carpentier and Trancart, Thomas}
}
@article {7026,
	title = {Towards transferability in fish migration models: A generic operational tool for predicting silver eel migration in rivers},
	journal = {Science of The Total Environment},
	volume = {739},
	year = {2020},
	month = {Jan-10-2020},
	pages = {140069},
	abstract = {In the global context of river fragmentation, predicting fish migration is urgent to implement management actions aimed at protecting and promoting the free movement of diadromous fish. However, large-scale applicability of conservation measures requires transferable models that enable prediction of migration even in data-poor regions. Here, we surveyed 12 contrasted European river sites to predict the activity peaks of silver eels (Anguilla anguilla) during river migration towards spawning areas through an ensemble modelling approach. Site-specific Boosted Regression Tree (BRT) models were adjusted using standardized hydrological variables to predict migration probability, which were aggregated in consensus predictions. Results of independent cross-validations demonstrated that silver eel migration runs were accurately predicted in response to changes in river discharge. Transferability and predictive performance were improved by considering catchment-size dissimilarity between river sites (85 to 109 930 km{\texttwosuperior}) when combining the site-specific predictions. Nevertheless, we provided two examples for which the effects of human actions on flow conditions were so high that they prevented reliable predictions of migration runs. Further contributions should thus take advantage of the flexibility of our approach for updating model collection with new sites to extend the predictive performance under a larger range of ecological conditions. Our transferable hydrological-based modelling framework offers an opportunity to implement large-scale management strategies for eel conservation, even in rivers where eel monitoring data lack. The BRT models and prediction functions were compiled in an R package named {\textquoteleft}silvRpeak{\textquoteright} to facilitate operational implementation by end-user managers, which can determine when mitigation measures should be implemented to improve river continuity (e.g. turbine shutdown and sluice gate opening) and balance their economic activity towards eel conservation. The only input required is discharge records that are widely available across European hydrological stations.},
	keywords = {eel runs prediction, ensemble modelling, European eel management, fish migration, model transferability, river obstacle},
	issn = {00489697},
	doi = {10.1016/j.scitotenv.2020.140069},
	url = {https://linkinghub.elsevier.com/retrieve/pii/S0048969720335890},
	author = {Teichert, Nils and T{\'e}tard, St{\'e}phane and Thomas Trancart and de Oliveira, Eric and Anthony Acou and Alexandre Carpentier and Bourillon, Bastien and Eric Feunteun}
}
