Previous Research

Science Advisor, Climate Change Science (2025-):

LWOP due to relocation of spouse (2023-2025)

Research in the DFO Gulf region (2015-2023):

+ Population dynamics of Atlantic salmon in the Miramichi and Restigouche Rivers

    Supervisor: Rick Cunjak

    Additional collaborative: Gerald Chaput

Atlantic salmon populations have been steadily decreasing since the 1980’s. Estimates for 2014 represent historic lows for returning spawners. Consequently, there has been a widespread call to address the decline and devise a comprehensive conservation plan for Atlantic salmon. Key to such an effort is a thorough analysis of the freshwater data to identify temporal and spatial trends in stock recruitment dynamics, and potential bottlenecks to production (e.g. climate warming). Working with DFO and CRI researchers, a three-year, rigorous analysis of DFO’s long-term, electrofishing data and returning adult salmon numbers in the Miramichi and Restigouche Rivers will be carried out. Using field surveys, statistical analyses and hierarchical (Bayesian) modeling, we will determine whether spawner estimates correlate with indices of juvenile (parr) abundance and freshwater production (smolts). Our efforts will also assess the efficacy of past ASCF-funded projects to enhance salmon abundance, and recommend a standardized electrofishing methodology to ensure compatibility of data generated from restoration efforts.

Previous Research:

+ Management Strategy evaluations of groundfish stocks in the Northwest Atlantic 

    Supervisor: Peter Shelton

    Additional collaborative: Joanne Morgan 

Post-Doc at DFO St. John's (NL) on recovery strategies for 2 straddling stocks: 3LNO American plaice(Hippoglossoides platessoides) and 3NO cod (Gadus morhua).

+ Dauphin, G.J.R., Shelton, P.A. and Morgan, M.J. 2013. A preliminary study regarding a Management Strategy Evaluation for 3LNO American plaice. NAFO SCR Doc. 13/049.

+ Poster presented at CCFFR

(Canadian Conference For Fisheries Research, Windsor, ON, January 3-5, 2013)

+ Collaboration with the Ministère du Développement durable, de l'environnement, de la Faune et des Parcs: Stock Recruitment relationships of A. salmon populations in Québec

    Main collaborative:  Mélanie Dionne

    Additional collaboratives: Etienne Prévost & Gérald Chaput

Atlantic salmon populations have been declining since the 1970's . Commercial fisheries have been closed since 2000 in Canada while angling remains and generate important income in the Quebec province.

the current management plan involves conservation limits defined for each river. These conservation limits are obtained by using a stock-recruitment model developed in the 1990's. As a consequence of the changes in the population abundances observed in the last decades, it is important to update the stock recruitment model by incorporating recent dataset now available and new statistical modelling tool now available.

The main objective of this project is to update the stock-recruitment model presently used in the Québec Atlantic salmon management plan.

+ Post-Doc Position at the INRA (UMR 1224 ECOBIOP, Saint Pee sur Nivelle),  2010-2012

   Supervisor: Etienne Prévost

The Allier river’s Atlantic salmon (Salmo Salar L.) population presents unique features among European populations. This population is characterized by a long distance freshwater migration to reach the spawning grounds (more than 700km from the Loire estuary to the first spawning grounds in the Allier River) as well as a prolonged marine life-stage for most of the individuals (2 to 3 years at sea). In addition, recent genetic studies have also shown that the Allier population presents unique genetic characteristics in comparison to other French or European population. For these reasons this population has a strong conservation value. Following the decline of catches, important efforts such as closure of fisheries in 1994, the erasing of dams or installation of fish pass to facilitate salmon migration, as well as an intensive juvenile salmon stocking program have been undertaken. Despite these measures, the size of the population remains small in comparison to historical levels.

Due to its conservation value, this population has been monitored and several datasets have been collected from 1975 to present. They are principally composed of fisheries catches, spawning nest (redd) counts, juvenile index of abundance and the number and life-stage (egg, fry and smolt) of salmon stocked every year. These datasets are often collected at different spatial and temporal scale: some datasets cover the whole time-series while some only cover a couple of years and some datasets look at the population as a whole at a broad scale while others have a much finer spatial resolution. The collection protocols may have changed through time and space according to technology development and operational constraints. In addition, missing data are commonplace. Synthesizing the information brought by these heterogeneous data sources in a formal statistical modelling framework is a difficult task. In order to reflect the natural process governing the population renewal it is also important to account for regulation mechanism such as density dependence as well as variability in the different transition parameters such as survival. Hierarchical Bayesian modelling (HBM) offers an efficient way to deal with such constraints while accounting for various forms of uncertainty.

The model built during this study will bring together 35 years of heterogeneous data in a coherent framework while accounting for uncertainty. The results will show a retrospective estimation of the past abundance of Atlantic salmon in three different spatial areas of the Allier River as well as the intergenerational renewal rate of the population. One of the main challenges of this modelling exercise is to incorporate the annual stocking data. The model will provide estimates of the contribution of the different categories of salmon life-stage stocked (egg, fry and smolt) over the time series considered. These results will provide useful information to the managers to apprehend the impact of the different restoration program over the last decades in the Allier River and make decision about the future programs.

+ Link to the project page on the Plan Loire website (most of the items and presentations are in french)

+ Short communication booklet about the project (2014) Viabilite de la population naturelle de saumons atlantiques du bassin de l'Allier (in French)

+ Final report (2013) Viability analysis of the natural population of Atlantic salmon (Salmo salar L.) in the Allier catchment - Scientific Report (executive summary in French)

+ Communication sheet about the project (in French)

+ Short article about the project released in "Paroles de migrateurs" N°5 (in French)  

+ Presentation to the scientific committee (in English, February 2012)

+ Ph.D. at the University of Glasgow (Scotland) and Loughs Agency (Northern Ireland),  2005-2009

   Supervisors: Colin Adams, Patrick Boylan and Etienne Prévost

Population dynamics is the study of the abundance of a species at different life stages of a species, the interactions between these life stages and sometimes the interactions with other species. Stage-structured modelling is a popular approach for population dynamics studies. This approach examines populations based on their ecology and allows the incorporation of complex dynamic processes. Model outputs are sensitive to the parameter values. It then becomes crucial to accommodate and quantify parameter uncertainty. This is of particular importance when the population of interest is exploited and the risk of over-exploitaion or  extinction needs to be assessed.

When studying real world examples of populations exploited by fisheries, several additional problems often arise such as: multiple and heterogeneous sources of information (e.g. datasets collected at different spatial and temporal scales), missing observations, life stages of interest not directly observable. The Bayesian framework allows all of these issues to be handled within the general framework. Thus has proven its particular value in studying the dynamics of exploited populations. Indeed, unknown quantities have associated probability distributions reflecting their uncertainty. Dealing with variations in the interactions/processes between life stages or limited and indirect ecological data is also facilitated by Bayesian modelling.

During my Ph.D., I examined a large Atlantic salmon population located in the Foyle catchment (Ireland). This population has been exploited for several centuries and particularly during the 20th century. This study focused on the period from 1959 to present for which most monitoring data is available from the Loughs Agency (formerly the Foyle Fisheries Commission). The Loughs Agency is responsible for the management of the salmon population. The aim of the agency is “to manage [the] fisheries towards maximum sustainable exploitation for commercial and recreational purposes”. In order to do so, it is important to understand the regulatory mechanisms occurring in the population in order to (i) estimate the number of fish returning to river, i.e. pre-fishery abundances (PFAs), and (ii) to derive standard reference points  for assessing the population status with regards to its sustainable exploitation.

To this end, a state-space model is implemented within a Bayesian framework. A life stage and spatially structured dynamic model describes the life-cycle of the Main components of Atlantic salmon in the Foyle catchment. Several empirical datasets related to the abundances of the stages at different scales of space and time, over a period of 50 years are brought together. Observations and process errors are taken into account ultimately allowing PFAs to be estimated. A retrospective analysis was also carried out providing insights on the historical status of the population and its exploitation.

+ Early stuff (Master's degree) 2005

   Supervisors: Patrick Coquillard and Eric Wajnberg

Trissolcus basalis (Hymenoptera: Scelionidae) is an egg parasitoid(1) that recognizes kairomones left by its host Nezara viridula (Heteroptera: Pentatomidae) as clues to find egg masses to attack. Recent experiments indicated that females of this wasp species are able to learn the features of their environment allowing them to adjust their foraging time on the patches of kairomones they are visiting, depending on whether host eggs are found or not. In order to assess the impact of such learning ability, a Monte Carlo, spatially-explicit, individual-based simulation model was elaborate to quantify the foraging efficiency of T. basalis females in different environments showing different levels of hosts richness and distribution.

In all environment tested, we compared the foraging efficiency of simulated T. basalis females being able to learn or not. In all cases, learning females visited a higher number of kairomone patches and attacked a higher number of hosts than non-learning females.

+ link to a presentation (in french)

+ Eric Wajnberg's webpage