4-month internship (M1): To breed or not to breed – A dilemma in the Dalmatian Pelican’s life

SupervisionOlivier Gimenez & Alain Crivelli

Description: Life history theory predicts that individuals balance costs and benefits associated with trade-offs between current and future reproduction. If breeding early does not reduce future reproduction, then individuals reproducing early in life should have a better fitness than individuals delaying their reproduction. This delayed reproduction is often associated with long life or limited ressources.

Here, we will study the costs of reproduction as a function of age at first reproduction in the Dalmatian Pelican (Pelecanus crispus) as well as other potential drivers such as density and food availability. The study site is Amvrakikos in Greece. More than 900 chicks have been marked, and almost 800 nesting individuals have been detected. For almost 300 of these individuals, we were able to determine breeding success over life. Over 25 years of study, more than 4000 observations have been recorded.



Cubaynes, Doherty, Schreiber & Gimenez (2011). To breed or not to breed: seabirds response to extreme climatic events. Biology Letters 7: 303-306.

Desprez, Pradel, Cam, Monnat & Gimenez (2011). Now you see him, now you don’t: Experience, not age, is related to reproduction in Kittiwakes. Proc. of the Royal Soc. B 278: 3060-3066

Doxa, Theodorou, Hatzilacou, Crivelli & Robert (2010). Joint effects of inverse density-dependence and extreme environmental variation on the viability of a social bird species. EcoScience 17: 203-2015.

Gimenez & cie (2013). How can quantitative ecology be attractive to young scientists? Balancing computer/desk work with fieldwork. Animal Conservation 16:134-136.


PhD position in Biodemography

Below is a PhD position in which our team will be largely involved. Feel free to apply!

PhD Position in Biodemography at Centre d’Etudes Biologiques de Chizé ‐ CNRS, France
We are looking for one PhD student – funded by CNRS through the European Research Council (ERC) program EARLYLIFE (PI H. Weimerskirch) – to contribute to our research program investigating the foraging behaviour and demography of the early life of long lived marine mammals and seabirds.

A major goal in biodiversity conservation is to predict responses of populations to environmental change. To achieve this goal, quantitative information on juvenile and immature stages is essential because their mortality controls recruitment to reproductive stages and the future of populations, but also because it is young individuals that disperse most and have the potential to emigrate and colonise new environments. In this research program (EARLYLIFE) we investigate how young individuals respond to environmental changes in terms of foraging skills, foraging ecology and demography and how this affects the population dynamics. For this, we employ biodemographic analysis of long‐term data from natural populations of long‐lived marine top predators (seabirds ands seals) and extensive tracking data on juveniles and adults.

Towards these goals, a PhD position will take the lead on the analysis of juvenile survival and recruitment processes and on the effects of juvenile individual characteristics (body size, body condition, foraging skills, habitat use) and environmental factors on these demographic rates. Telemetry data will allow making inferences on the spatio‐temporal mortality of juveniles and on the variables of the physical environment affecting juvenile mortality. In the light of these results a retrospective analysis of our long term demographic database will allow to test the effects of environmental conditions encountered during early life on juvenile survival and recruitment processes and to estimate the genetic component of foraging tactics.

The student will work with advanced statistical models to investigate juvenile survival and recruitment processes (e.g., multistate, multievent and known‐fate capture recapture models, integrated population models, state‐space models), with long‐term capture recapture time series (from 20 to 40 years) of seabirds (albatrosses and petrels), and with tracking data (newly developed loggers using the GPS and Argos technology). Possibility to contribute to fieldwork on albatrosses and petrels, although not compulsory.

• MSc degree (or equivalent) in population ecology, biostatistics, evolutionary biology, or a relevant field.
• Solid knowledge of and demonstrated interest in population ecology and population dynamics in changing environments.
• Strong quantitative skills, proficiency in statistical analysis and demographic modelling in R or Matlab, and good experience in capture recapture modelling.

The PhD will be based at Centre d’Etudes Biologiques de Chizé (CNRS, Chizé, France) under the supervision of Christophe Barbraud and Henri Weimerskirch with ample collaboration with biostatisticians from Centre d’Ecologie Fonctionnelle et Evolutive (CNRS, Montpellier, France) and with ecologists at CNRS Chizé. Net Salary will be c. 1500€.

Please send the following material in a single PDF file to Christophe Barbraud, Henri Weimerskirch and Olivier Gimenez. Screening of applicants will start October 2nd, 2013 and continue until the position is filled.
• Cover letter indicating your motivation and expectations from this PhD
• Detailed CV
• One page summary of your MSc degree
• Contact information for two references

Complex decisions made simple

A new paper by a former PhD student of the team, Lucile Marescot, now a post-doc at UC Davis.

Marescot, L., Chapron, G., Chadès, I., Fackler, P., Duchamp, C., Marboutin, E. and O. Gimenez (2013). Complex decisions made simple: A primer on stochastic dynamic programming. Methods in Ecology and Evolution. In press. DOI: 10.1111/2041-210X.12082. PDF on request.

This review and tutorial paper (with R code) is about dynamic programming, a powerful mathematical technique to make decisions in presence of uncertainty. This paper would not have been born without the help of Guillaume Chapron, population modeller and large carnivores specialist, as well as Iadine Chadès and Paul Fackler both world experts in the field of decision making.

1. Under increasing environmental and financial constraints, ecologists are faced with making decisions about dynamic and uncertain biological systems. To do so, stochastic dynamic programming (SDP) is the most relevant tool for determining an optimal sequence of decisions over time.
2. Despite an increasing number of applications in ecology, SDP still suffers from a lack of widespread understanding. The required mathematical and programming knowledge as well as the absence of introductory material provide plausible explanations for this.
3. Here, we fill this gap by explaining the main concepts of SDP and providing useful guidelines to implement this technique, including R code.
4. We illustrate each step of SDP required to derive an optimal strategy using a wildlife management problem of the French wolf population. Our results show how the determination of optimal policies is sensitive to the incorporation of uncertainty.
5. SDP is a powerful technique to make decisions in presence of uncertainty about biological stochastic systems changing through time. We hope this review will provide an entry point into the technical literature about SDP and will improve its application in ecology.

How to attract young scientists to quantitative ecology?

This paper is the reason why we, as past and present members of a research team, started this blog. We started discussing the challenging Possingham’s (2012) proclamation that

conservation needs more analysts, not more field data

which, he says,

invariably elicits a hostile reception among field ecologists.

We took the opposite view and claimed: let’s collect data, and try to balance quantitative ecology with fieldwork! This was a very exciting experience along which we learnt a lot from each other by sharing confronting, structuring and synthesizing ideas. We would like to pursue the venture through this blog. Surprisingly to us, this short contribution got some coverage:

F1000 review – Good for Teaching, Interesting Hypothesis by J. Claudet and E. Darling: This commentary puts forward a vision that balances quantitative analyses of existing datasets with fieldwork in order to train young scientists in data-driven conservation. As a response to an equally invigorating commentary by Hugh Possingham, the authors acknowledge the need to train young scientists as ‘quantitative analysts’ that can monitor, model and evaluate conservation actions. At the same time, the authors emphasize that fieldwork experience is essential to remain biologically relevant – getting your feet wet and being out in the field helps understand both your study system and the value of collected data. This paper provides a compelling argument that desk-based analyses and field science are important for both new (and established) scientists in quantitative ecology and conservation.