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RAPIDEVO Résumé de rapport

Project ID: 300077
Financé au titre de: FP7-PEOPLE
Pays: Italy

Final Report Summary - RAPIDEVO (Rapid evolutionary responses to climate change in natural populations: Integrating molecular genetics, climate predictions and demography into an eco-evolutionary modelling framework)

Climate change poses a serious threat to species persistence, as it will force species to experience natural selection in new directions and at new and greater intensities. The empirical and theoretical research on the ecological and genetic effects (e.g. changes in population size and spatial distribution, age-structure, genetic variability, life histories) of a changing climate has mostly focused on trends of the mean of climate variables, such as temperature or rainfall, over seasons or years. These ecological and genetic effects are reasonably well understood over various time scales. However, one of the most dramatic effects of climate change is the observed increase in the frequency and intensity of extreme climatic events, such as floods, storms, droughts etc.
Life-history theory predicts a prevalence of opportunistic life histories in species that are affected by events strongly reducing population size. Low generation times and high reproductive effort tend to provide higher population growth rates than longer generation times and lower reproductive effort. Those “opportunistic” traits and life histories may explain why, even after almost complete population collapses, some species are able to bounce back to safe abundances from a handful of surviving individuals. However, empirical tests on why and how certain species possess traits that allow them to persist when teetering on the verge of extinction have been lacking. Since climate change is predicted to increase the frequency and intensity of extreme climatic events, the population responses to such events should be carefully investigated by integrating genetic and demographic analysis in a life-history theory framework.
The Marie Curie IOF project RAPIDEVO used marble trout Salmo marmoratus as a model system mainly for understanding and predicting the genetic, demographic, and life-history consequences of extreme events on natural populations. Marble trout is a species of great conservation concern, given its restricted geographical distribution and the risk of hybridization with alien brown trout Salmo trutta L. Only eight genetically pure relict (Lipovscek, Trebuscica, Studenc, Svenica, Lower Idrijca, Upper Idrijca, Zadlascica, Huda) and two re-introduced (Zakojska, Gacnick) populations of marble trout are located in the Adriatic basin of Slovenia, persisting above barriers that have prevented the upstream movement of brown trout or marble-brown trout hybrids living in the lower stream reaches. Marble trout populations are threatened by extreme climatic events, such as flash floods, debris flows, and landslides; since the start in 1993 of the program for the conservation of marble trout led by the Biological Institute of Tour Du Valat (France) and the Tolmin Angling Association (Slovenia), such extreme events have caused the extinction of two populations (Predelica in 2000, Gorska in 2004) as well as crashes in other populations (Zakojska, Lipovscek, Zadlascica).
This model system provided a unique opportunity to investigate the effects of extreme events across populations of the same species, due to the long-term monitoring and sampling of multiple populations, the collection of an exceptional dataset of demographic and genetic information at the individual level, the occurrence of multiple flood events in the last 15 years, and my deep knowledge of the system.

The following have been the main scientific results of RAPIDEVO.

The development of random-effects models of growth in size that can help us estimate differences in growth before/after an extreme event, as well as estimate individual variability in growth and determine its causes, such as different life-history strategies, variation in early environmental conditions, dominance. The models applied the Empirical Bayes method to the estimation of model parameters; I expect my growth models to be widely used by other biologists who are trying to better estimate within-population individual variability in growth. The models I developed provide an excellent combination of interpretability of model parameters and accuracy in the prediction of future growth trajectories.

The estimation of among- and within-population variation in vital rates, life histories, and population dynamics in the 10 populations of marble trout, as well as the advancement of hypotheses on the determinants of this variation. I was able to identify a trade-off between growth in size and mortality at the population level, which may have consequences on the chances of population recovery after a population collapse and should help develop better population-specific conservation strategies. In particular, I found, that across populations and in the long-term, populations with faster average growth tended to show lower average survival

The estimation of the genetic, demographic, and life-history effects of floods events on marble trout, using the populations of Lipovscek and Zakojska as model systems. The populations were reduced in size to a handful of fish after the flash floods of September 2007 (both populations) and December 2009 (Lipovscek). Lipovscek recovered, while the population of Zakojska is still struggling to bounce back to the pre-event population size. Using single-nucleotide polymorphisms (SNPs) developed from Next-Generation Sequencing (NGS) data, I genotyped more than 500 fish from Lipovscek and almost 1,000 fish from Zakojska. When a population was affected by a flood causing massive mortalities, within that population the following occurred for 2-3 years after the flood: 1) survival substantially increased, 2) body growth was much faster than before the flood (both 1 and 2 were caused by lower densities after the floods), 3) age at reproduction decreased as predicted by life-history theory and size-dependent sexual maturity. Finally, 4) genetic variability (e.g. mean heterozigosity within a cohort) decreased in the second generation after the flood, thus pointing to a reduced adaptive potential as a consequence of population and genetic bottlenecks caused by the floods.

The fine-grained analyses of genetic differences among marble trout populations, using both NGS data and a panel of ~250 SNPs tested on at least 16 samples per population. I found an additional evolutionary unit (the population of Svenica), which was previously grouped together with 3 other populations (Studenc, Trebuscica, Idrijca). I also found extremely high genetic differences among marble trout populations (pairwise FST ranging from 0.4 to 0.84, with the exception of Lower and Upper Idrijca, which are basically the same population) and extremely high coefficients of inbreeding (population-specific coefficients of inbreeding FIS ranging from 0.55 to 0.85), both mostly caused by low population size, low movement of marble trout, and historical isolation of the populations.

As for the socio-economic implications of my work, the project RAPIDEVO provided - to my knowledge for the first time - an overarching study of the historical and future consequences of extreme events on the population dynamics and genetic dynamics of an animal species. Despite being a crucial aspect of the scientific research on the consequences of climate change on natural populations, the consequences of extreme events are currently understudied, mostly because finding the right model system and posing tractable questions when dealing with extreme events is challenging. Through my presentations at scientific meetings, informal talks, use of social media, and of my website ( HYPERLINK "" I was able to inform the public at large of the effects of extreme events on natural populations.
Finally, the results of my studies will help develop more data-driven and effective conservation strategies for marble trout.

Informations connexes


Fabio Conti, (Chief Financial Officer)
Tél.: +39 2 23993431
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Numéro d'enregistrement: 184103 / Dernière mise à jour le: 2016-06-02