At the end of each of the 3 years of the Fellowship, the European Research Council requests to submit a report detailing the various activities of the projects, main results, future plans, problems etc. Here below I show my Periodic Report (end of the second year) for the project RAPIDEVO, it may help some of the fellows who are struggling to write their report (clearly in addition to people closely following my research) - guidelines are in italics
1. PUBLISHABLE SUMMARY
This section normally should not exceed 2 pages.
It shall be of suitable quality to enable direct publication by the REA or the Commission. You may extract this wholly or partially from the website of the project, if suitable, but please ensure that this is set out and formatted so that it can be printed as a stand-alone paper document.
Please include:
• a summary description of the project objectives,
• a description of the work performed since the beginning of the project,
• a description of the main results achieved so far,
• the expected final results and their potential impact and use (including the socio-economic impact and the wider societal implications of the project so far).
You should update this publishable summary at the end of each reporting period.
Please include also, as appropriate, diagrams or photographs illustrating and promoting the work of the project, the project logo and relevant contact details.
Please ensure that all publishable reports submitted to the REA for publication are of a suitable quality to permit direct publication without any additional editing. By submitting the publishable reports to the REA, you are also certifying that they include no confidential material.
The address of the project public website should also be indicated, if applicable.
The internet address should be active.
• Summary description of the project objectives
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 application of models of rapid evolutionary responses to climate change integrating genetics, demography and climate prediction is essential to understand the future genetic composition and shaping of life histories of species in a climate change scenario. In particular, theoretical and empirical investigations on the complex eco-evolutionary dynamics associated with adaptations and responses to extreme events – which are predicted to increase in frequency and intensity with climate change - are urgent and essential, both to advance theory and to inform management of species.
I use marble trout (Salmo marmoratus) as a model system in the Marie Curie IOF-project RAPIDEVO, which has the main goal of understanding and predicting the genetic and demographic consequences of extreme events on natural populations. Marble trout live in Western Slovenian streams that are frequently affected by extreme flood events causing massive mortalities. However, despite very low population sizes (from 30 to 1000 individuals), little genetic variability and no immigration, these populations have surprisingly persisted for centuries. Whether marble trout will be able to cope with the predicted increase in the frequency and intensity of flood events is unclear. This model system provides 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, integration of field and experimental data, and my deep knowledge of the system.
• Description of the work performed since the beginning of the project
In 2013-2014, I carried out research on genetic and demographic aspects of marble trout along with purely theoretical studies that provided testable predictions on genetic and life-history adaptations, and demographic responses to extreme events. In particular, during the first two years of the project RAPIDEVO, I carried out (not necessarily in chronological order) (i) SNP discovery in three marble trout populations using Next Generation Sequencing (NGS)-generated data (8 individuals per population have been sequenced so far), (ii) analysis of genetic differentiation among populations and inbreeding, (iii) estimation of vital traits such as survival, movement and growth in all seven remnant marble trout populations (plus two newly created populations), (iv) prediction of demographic and genetic dynamics in an environment characterized by the occurrence of extreme events using one of the marble trout populations (Zakojska) as model population, (v) theoretical work on adaptive processes in response to extreme events.
I provide updates on my research related to the RAPIDEVO project at simonevincenzi.com/blog/ (tag: Marie Curie)
• Description of the main results achieved so far
I have selected population-specific panels of SNPs (from 70 to 100) that have been used to develop assays that provide multi-locus genotypes for three marble trout populations (Lipovscek, Trebuscica, Zadlascica). In the first months of 2015, assays will be developed for the populations of Idrijca, Svenica and Studenc. In addition, I have developed a genetic marker for determining sex in marble trout. Morphologically, male and female marble trout are indistinguishable, thus the development of the genetic marker allowed us to determine the sex of individuals. Knowing the sex of the fish is important for pedigree reconstruction as well to test for differences in growth and survival between males and females.
I have analyzed genetic differentiation at the SNP loci at local geographic scales using population samples of marble trout from the seven remnant pure marble trout populations. I found a very high (and almost unique for such a narrowly endemic species) genetic differentiation between populations (pairwise FST ranging from 0.4 to 0.84) and generally high inbreeding (population-specific coefficient of inbreeding ranging from 0.55 to 0.85) (the work is still unpublished).
Using a combination of empirical research, mathematical modeling and computer simulations, I have found that for marble trout - given a growth-mortality trade-off - extreme events (i.e. floods inducing massive mortalities) tend to select for phenotypes with faster life histories (i.e. earlier reproduction, faster growth and higher mortality risk due to the growth-mortality trade-off), as predicted by life-history theory (Vincenzi et al. 2014a).
I also obtained exceptional insights on the determinants of individual variation in growth and its implication for life-history and population processes (Vincenzi et al. 2014b). In this work, I developed a novel statistical approach using the empirical Bayes method to estimate and separate the contribution of intrinsic and environmental factors to lifetime growth trajectories of marble trout, and generate hypotheses concerning the life-history strategies of organisms. I showed that using the novel method I developed, the growth model predicts the future growth of organisms with substantially greater accuracy than using historical information on growth at the population level, and help identify year-class effects, probably associated with climatic vagaries, as the most important environmental determinant of growth in marble trout.
In addition to empirical research, I have also carried out theoretical studies with the goal of identifying key pieces of empirical information that are required for advancing understanding on the demographic and genetic consequences of extreme events on natural populations. In particular, I used numerical simulations to understand and predict the consequences of directional trend and increased variability of a climate variable, increased probability of occurrence of point extreme events (e.g. floods), selection pressure and effect size of mutations on a quantitative trait determining individual fitness, as well as the their effects on the population and genetic dynamics of a population of moderate size (Vincenzi 2014). I found that the interaction among climate trend, variability and probability of point extremes had a minor effect on risk of extinction, time to extinction and distribution of the trait after accounting for their independent effects. The survival chances of a population strongly decreased with increasing strength of selection, as well as with increasing climate trend and variability. Climate trend and strength of selection largely determined the shift of the mean phenotype in the population.
References
Vincenzi, S. (2014). Extinction risk and eco-evolutionary dynamics in a variable environment with increasing frequency of extreme events. Journal of the Royal Society, Interface / the Royal Society, 11, 20140441.
Vincenzi, S., Crivelli, A.J., Satterthwaite, W.H. & Mangel, M. (2014a). Eco-evolutionary dynamics induced by massive mortality events. Journal of Fish Biology, 85, 8–30.
Vincenzi, S., Mangel, M., Crivelli, A.J., Munch, S. & Skaug, H.J. (2014b). Determining individual variation in growth and its implication for life-history and population processes using the Empirical Bayes method. PLoS Computational Biology, 10, e1003828.
• Expected final results and their potential impact and use (including the socio-economic impact and the wider societal implications of the project so far)
So far, only a few studies have explored the adaptive mechanisms helping population recovery after massive mortality events as well as the role of extreme events (i.e. floods, fires, diseases) in shaping the genetic traits and life histories of affected populations. Given the predicted intensification of weather extremes with climate change, theoretical and empirical investigations on the complex eco-evolutionary dynamics associated with adaptations and responses to extreme events are urgent and essential, both to advance theory and to inform management of species. These studies require a combination of genomic and demographic data, statistical and eco-evolutionary modeling, and characterization of weather extremes.
The expected final result of the project is to provide - to my knowledge for the first time - an overarching study of the historical and future consequences of extreme events on population and genetic dynamics of an animal species. As explained above, this is a crucial – albeit understudied - aspect of the scientific research on the consequences of climate change on natural populations. In addition, the basic research questions motivating RAPIDEVO have led to the development of innovative statistical and mathematical methods, such as the application of the Empirical Bayes method to the estimation of individual variation in growth and its consequences for life-history and population processes in fish populations. I expect my model to be widely used by other biologists who are trying to better estimate within-population individual variability in growth and vital traits and understand their consequences for population and genetic dynamics.
2.PROJECT OBJECTIVES FOR THE PERIOD
Please provide an overview of the project objectives for the reporting period in question, as included in Annex I of the Grant Agreement. These objectives are required so that this report is a stand-alone document.
Please include a summary of the recommendations from the previous reviews (if any) and indicate how these have been taken into account.
The interdisciplinary approach proposed in the project RAPIDEVO combines (1) molecular genetics, (2) demographic analysis and characterization of temporal and spatial patterns of flood events, and (3) life-history, demographic and eco-evolutionary modeling. Goals for the reporting period in question (first 2 years of the project, i.e. years 2014 and 2015) are reported below.
1. Genetic markers.
1A. Investigate adaptive evolution in space (adaptive divergence) in marble trout populations living in Slovenian streams using molecular genetic markers
1B. Test adaptive evolution in marble trout, particularly after the occurrence of severe flood events
1C. Parentage analysis using molecular data
2A. Analysis of population structure, population dynamics, traits and compensatory responses of marble trout
2B. Analysis of common-garden experiment
2C. Analysis of flood events
3A. Development of a model of marble trout population dynamics living in Slovenian streams, with only a demographic module
There were no recommendations from previous reviews.
3.WORK PROGRESS AND ACHIEVEMENTS DURING THE PERIOD
Please provide a concise overview of the progress of the work in line with the structure of Annex I of the Grant Agreement - except project management, which will be reported in section 6.
• A summary of progress towards objectives and details for each task;
• A summary of the progress of the researcher training activities/transfer of knowledge activities/integration activities (as it applies for the MC action);
• Highlight clearly significant results;
• If applicable, explain the reasons for deviations from Annex I and their impact on other tasks as well as on available resources and planning;
• If applicable, explain the reasons for failing to achieve critical objectives and/or not being on schedule and explain the impact on other tasks as well as on available resources and planning (the explanations should be coherent with the declaration by the scientist in charge) ;
• A statement on the use of resources, in particular highlighting and explaining deviations between actual and planned researcher-months in Annex 1 (Description of Work)
• If applicable, propose corrective actions.
• A summary of progress towards objectives and details for each task
1. Genetic markers: I have selected population-specific panels of SNPs (from 70 to 100) that have been used to develop assays that provide multi-locus genotypes for three marble trout populations (Lipovscek, Trebuscica, Zadlascica). In the first months of 2015, assays will be developed for the populations of Idrijca, Svenica and Studenc. In addition, I have developed a genetic marker for determining sex in marble trout. Morphologically, male and female marble trout are indistinguishable, thus the development of the genetic marker allowed us to determine the sex of the individual analyzed. Knowing the sex of the fish is important for pedigree reconstruction, and test for differences in growth and survival between males and females. The work is still unpublished.
1A. Investigate adaptive evolution in space (adaptive divergence) in marble trout populations living in Slovenian streams using molecular genetic markers: I have analyzed genetic differentiation at the SNP loci at local geographic scales using population samples of marble trout from the seven pure marble trout populations (on average, 8 individuals per population have been sequenced using the Illumina MiSeq sequencer). I have calculated pairwise genetic distances (FST), inbreeding, and carried out model-based clustering (i.e., structure software, PCA, multidimensional scaling). I also used state-of-the-art software, such as BayeScan, DetSel, Arlequin 3.5, Lositan, to identify SNPs characterized by higher or lower levels of population divergence than strictly neutral loci, suggestive of diversifying or balancing selection, respectively. The work is still unpublished.
1B. Test adaptive evolution in marble trout, particularly after the occurrence of severe flood events: I am testing for rapid adaptive shifts in genetic composition and diversity within marble trout populations (and evaluate the possible existence of bottlenecks/population declines) by estimating genetic changes in samples collected during the study period, in particular in the population of Lipovscek, namely: prior to and right after the 2007 floods, and prior to and right after the 2009 floods. The work is completed, but still unpublished.
1C. Parentage analysis using molecular data: I used (and still using) the SNP multilocus genotypes for parentage inference to identify maternity, paternity and other relationships and construct multi-generation pedigrees. So far, I have reconstructed multi-generation pedigrees in Lipovscek and I am in the process of reconstructing pedigrees in Trebuscica and Zadlascica. This will allow us to: (i) infer mating patterns and average family size; (ii) infer heritability of life-history traits; (iii) study the association between fitness traits (survival and growth, in particular) and particular genotypes at the individual and family level.
2. Demographic analysis and statistical characterization of temporal and spatial patterns of flood events
2A. Analysis of population structure, population dynamics, traits and compensatory responses of marble trout: I used the extensive data set provided by the field monitoring program to investigate demographic trends, age- and size-distribution of the seven marble trout populations and to estimate survival probabilities, body growth rates and compensatory processes for each population. In addition, I am in the process of investigating morphological differences in individuals living in different populations. I presented results on body growth dynamics of marble trout in a talk I gave at the International Statistical Ecology Conference in Montpellier, France (July 2014) and preliminary results on variation in survival probabilities among marble trout populations in a talk I was invited to give at UC Berkeley in October 2014.
2B. Analysis of common-garden experiment: So far, I prepared the data set provided by the common garden experiment to test for differences among and within the marble trout populations in age and size at maturity, timing of spawning, occurrence of semelparity or iteroparity, size-dependent fecundities.
2C. Analysis of flood events: I acquired from the Slovenian Agency for Environment the available rainfall data for more than 200 meteorological stations, starting from the 1960s.
3. Life-history, demographic and eco-evolutionary modelling
3A. Development of a model of marble trout population dynamics living in Slovenian streams, with only a demographic module: I developed and parameterized a model, including a genetic module, to predict the evolution of life histories and the consequences of evolutionary processes on population persistence. The genetic module was parameterized without specific reference to the insights provided by the research activities 1A,B,C and 2A,B,C.
• A summary of the progress of the researcher training activities/transfer of knowledge activities/integration activities (as it applies for the MC action)
At UCSC, under the expert guidance of Prof. Marc Mangel and Dr. Carlos Garza I complemented my expertise in basic ecology and population dynamics through training with new genetic, data analysis and statistical methods.
In particular, in 2013-2014 I have been trained for the genetic part in genomics, Next-Generation Sequencing and following downstream analyses (SNP identification and validation, methods to estimate genetic structure among populations and inbreeding within populations, pedigree reconstruction using SNPs, etc.), and classical genetics. For the data analysis and statistical methods part of my training program, I have been mostly trained in Bayesian methods for parameter estimation and model selection.
More in detail, for the genetic part I have received hands-on training on the use to Next-Generation sequencer Illumina MiSeq, on software for SNPs identification (mostly the Stacks suite, which has been chosen as the default option for the analysis of sequencing data at the Southwest Fisheries Science Center in Santa Cruz), software for data manipulation, summary statistics, and estimation of parameters in genetic studies (e.g. Arlequin 3.5, Genepop, plink), outlier locus detection (e.g. BayeScan, DetSel 1.0, Lositan), genetic structure (e.g. structure, GeneLand, plink).
For the data analysis and statistical methods part, I have been trained in Bayesian methods (in particular the Empirical Bayes method) and the use of software ADMB-RE by Prof. Hans Skaug of the University of Bergen, Norway, who visited the Southwest Fisheries Science Center in Santa Cruz during a sabbatical year (year 2013). I received additional training in the use of ADMB-RE at a two-day workshop organized by Hans Skaug and other statisticians during the International Statistical Ecology Conference in Montpellier (July 2014).
In 2013-2014, I took part to the weekly meetings of the Mathematical Biology Research Group led by Marc Mangel at UCSC and of the Molecular Ecology and Genetic Analysis team led by Carlos Garza at the Southwest Fisheries Science Center (Santa Cruz, CA). In 2014, I took part to the monthly joint meetings of the molecular ecology and genetic analysis team of the Southwest Fisheries Science Center and the Paleogenomics group led by Beth Shapiro and Ed Green at USCS.
In 2013, I took part to the weekly Applied Mathematics Club meetings led by Steve Munch at the Southwest Fisheries Science Center.
In October-December 2014 I mentored PhD student Camille Musseau (University of Toulouse, France), who is studying the trophic niche of marble trout in her PhD studies.
• Highlight clearly significant results
I have found that for marble trout - given a growth-mortality trade-off - extreme events (i.e. floods inducing massive mortalities) tend to select for phenotypes with faster life histories (i.e. earlier reproduction, faster growth and higher mortality risk due to the growth-mortality trade-off), as predicted by life-history theory (Vincenzi et al. 2014a). However, the evolution of faster life histories does not increase the resilience of marble trout populations to massive mortality events with respect to a scenario in which life histories are fixed and cannot evolve (Vincenzi et al. 2014a). This happens because the relaxation of density dependence after massive mortality events increases growth and decreases early mortality and possibly age at sexual maturity in both scenarios. Then, given the relatively high egg production of marble trout at low densities with respect to the number of fish needed to reach a safe population size, a few females may be sufficient in either scenario for a fast recovery to a safe population size in a few years. Thus, this is a very interesting scenario in which the adaptive evolution of a trait does not confer an increased resilience to extreme events, since the environment in selective just after the massive mortality event.
I also obtained exceptional insights on the determinants of individual variation in growth and its implication for life-history and population processes (Vincenzi et al. 2014b). The paper describing the research has been published on PLoS Computational Biology in September 2014 and in less than four months it has been viewed almost 2,000 times (http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003828). In this work, I developed a novel statistical approach using the empirical Bayes method to estimate and separate the contribution of intrinsic and environmental factors to lifetime growth trajectories of marble trout, and generate hypotheses concerning the life-history strategies of organisms. I showed that using the novel method I developed, the growth model predicts the future growth of organisms with substantially greater accuracy than using historical information on growth at the population level, and help identify year-class effects, probably associated with climatic vagaries, as the most important environmental determinant of growth in marble trout. In this context, I am also currently investigating trade-offs between model complexity, biological interpretability of parameters, and goodness of fit in random-effects models of growth of fish, using marble trout as my model system. In particular, I am exploring how different formulations of the von Bertalanffy growth function with individual random effects and environmental predictors of function’s parameters affect these trade-offs. Studying the determinants of growth – and thus developing appropriate models and methods to estimate model parameters – is crucial, since growth is one of the traits in which adaptation to extreme events is more likely to occur. I found that adding additional complexity in the form of individual variation in multiple parameters of the von Bertalanffy growth function may offer advantages in terms of model accuracy, although the interpretation of model parameters may become more challenging. The manuscript is currently under review at Fish and Fisheries, which is - according to Impact Factor - the journal ranked number one in Fisheries.
In addition to empirical research, I have also carried out theoretical studies with the goal of identifying key pieces of empirical information that are required for advancing understanding on the demographic and genetic consequences of extreme events on natural populations. In particular, I used numerical simulations to understand and predict the consequences of directional trend and increased variability of a climate variable, increased probability of occurrence of point extreme events (e.g. floods), selection pressure and effect size of mutations on a quantitative trait determining individual fitness, as well as the their effects on the population and genetic dynamics of a population of moderate size (Vincenzi 2014). Briefly, I found that the interaction among climate trend, variability and probability of point extremes had a minor effect on risk of extinction, time to extinction and distribution of the trait after accounting for their independent effects. The survival chances of a population strongly and linearly decreased with increasing strength of selection, as well as with increasing climate trend and variability. Climate trend and strength of selection largely determined the shift of the mean phenotype in the population.
In addition, due to my broad interests on the effects of extreme events, I was invited to submit a contribution to a special issue of the journal Plant Ecology on the effects of extreme events on plants (Vincenzi & Piotti 2014). Although this contribution was not among the goals of the RAPIDEVO project, I consider it helpful for advancing the scientific dialogue on the effects of extreme events on evolutionary and demographic processes in natural populations.
References
Vincenzi, S. (2014). Extinction risk and eco-evolutionary dynamics in a variable environment with increasing frequency of extreme events. Journal of the Royal Society, Interface / the Royal Society, 11, 20140441.
Vincenzi, S., Crivelli, A.J., Satterthwaite, W.H. & Mangel, M. (2014a). Eco-evolutionary dynamics induced by massive mortality events. Journal of Fish Biology, 85, 8–30.
Vincenzi, S., Mangel, M., Crivelli, A.J., Munch, S. & Skaug, H.J. (2014b). Determining individual variation in growth and its implication for life-history and population processes using the Empirical Bayes method. PLoS Computational Biology, 10, e1003828.
Vincenzi, S. & Piotti, A. (2014). Evolution of serotiny in maritime pine (Pinus pinaster) in the light of increasing frequency of fires. Plant Ecology, 215, 689-701.
• If applicable, explain the reasons for deviations from Annex I and their impact on other tasks as well as on available resources and planning
There were no deviations from Annex I.
• If applicable, explain the reasons for failing to achieve critical objectives and/or not being on schedule and explain the impact on other tasks as well as on available resources and planning (the explanations should be coherent with the declaration by the scientist in charge)
Not Applicable
• A statement on the use of resources, in particular highlighting and explaining deviations between actual and planned researcher-months in Annex 1 (Description of Work)
There were no deviations between actual and planned researcher-months
• If applicable, propose corrective actions
No corrective actions are proposed.
4. ADDITIONAL INFORMATION
5. DISSEMINATION ACTIVITIES
Use this section to summarise all dissemination activities executed during the reporting period as well as activities planned for next period.
In terms of dissemination activities, I have mostly contributed to make the results of my work public thorough my presentations, seminar, and talks at department seminar series and international scientific meetings. Some of my talks can be found at https://simonevincenzi.com/talks/
Main talks
- Invited talk at the Wildlife & Conservation Biology Seminar series at UC Berkeley. Genetic and life-history variation in small populations living in stochastic environments. October 2014.
- Talk at the International Statistical Ecology Conference in Montpellier, France. Determining individual variation in growth and its implication for life history and population processes using the Empirical Bayes method. July 2014.
- Invited talk at EURAXESS event in New York City. Shaken, burned, drowned, but still there: how species survive catastrophic events in an increasingly extreme world. March 2014. Talk is online at https://www.youtube.com/watch?v=sp6xW67sC0I
- Invited talk at the 2013 SIAM meeting in San Diego. Spatial features of density dependence and weather extremes in population models. July 2013.
Others
Since winning my Marie Curie IOF in late 2011, I have been helping several scientists preparing their applications to European Union research calls. I use my blog to offer advice on how to apply to MC Actions and ERA Starting Research Grants (https://simonevincenzi.com/category/marie-curie/), including how to prepare applications and suggestions on the number and quality of publications allowing the applicant to be competitive. I also uploaded on my website my winning Marie Curie IOF application, free for the public and fellow scientists.
6. PROJECT MANAGEMENT
Please provide a concise overview of the progress of the work in line with the structure of Annex I of the Grant Agreement - except project management, which will be reported in section 6.
• A summary of progress towards objectives and details for each task;
• A summary of the progress of the researcher training activities/transfer of knowledge activities/integration activities (as it applies for the MC action);
• Highlight clearly significant results;
• If applicable, explain the reasons for deviations from Annex I and their impact on other tasks as well as on available resources and planning;
• If applicable, explain the reasons for failing to achieve critical objectives and/or not being on schedule and explain the impact on other tasks as well as on available resources and planning (the explanations should be coherent with the declaration by the scientist in charge) ;
• A statement on the use of resources, in particular highlighting and explaining deviations between actual and planned researcher-months in Annex 1 (Description of Work)
• If applicable, propose corrective actions.
• Project planning and status – from management point of view
According to the GANTT presented in Annex I of the RAPIDEVO project, the project is respecting deadlines and milestones. Here below are reported the planned activities for the third and last year of the project (year 2015).
1. Genetic markers: I am currently selecting a panel of SNPs for other 3 populations (Idirijca, Svenica, Studenc), while for one population (Huda Grapa) we have faced great challenges in the development assays that have determined by the exceptionally low genetic variability found among fish in Huda Grapa. With my colleagues, I am currently considering using another sequencer (Illumina HiSeq) for sequencing Huda Grapa individuals, although it is still unclear whether we will be able to find sufficient genetic variability to develop assays for pedigree reconstruction. In the first months of 2015, SNP assays will be developed for the populations of Idirijca, Svenica, Studenc. I will submit a manuscript for publication before the end of June 2015 of SNP discovery in marble trout.
1A. Investigate adaptive evolution in space (adaptive divergence) in marble trout populations living in Slovenian streams using molecular genetic markers: The work presented in Section 4 of this report is still unpublished; a manuscript on adaptive and neutral genetic differences marble trout populations living in Slovenian streams will be submitted for publication before the end of March 2015.
1B. Test adaptive evolution in marble trout, particularly after the occurrence of severe flood events: The work described in Section 4 of this report is still unpublished, although preliminary results have been presented in a talk I was invited to give at UC Berkeley in October 2014; I plan to submit a manuscript before the end of February 2015.
1C. Parentage analysis using molecular data: The work described in Section 4 of this report will be finished in the first 6 months of 2015 and a manuscript will be submitted for publication shortly after finishing the parentage analysis.
2. Demographic analysis and statistical characterization of temporal and spatial patterns of flood events
2A. Analysis of population structure, population dynamics, traits and compensatory responses of marble trout: I plan to submit a manuscript on differences in survival, growth, morphology and compensatory responses among marble trout populations for publication before the end of April 2015.
2B. Analysis of common-garden experiment: I will proceed with the analysis of data from the common-garden experiment in the second half of 2015.
2C. Analysis of flood events: I will proceed with the analysis of rainfall and flood data in the second half of 2015.
3. Life-history, demographic and eco-evolutionary modelling
3B. Development of an eco-evolutionary model for marble trout with genetic and life-history modules: In the second half of 2015 I plan to develop an eco-evolutionary model on the basis of the results and feedbacks provided by the research activities 1A,B,C and 2A,B,C. The model will be parameterized with population-specific genetic (e.g., alleles, heterozigosity, etc.) and life-history attributes. In particular, I will use Forward Stochastic Simulations to estimate the future evolutionary trajectories of marble trout living in the monitored streams, taking into account the likely climate change-induced intensification and altered timing of flood events.
• Problems which have occurred and how they were solved or envisaged solutions
No particular problems have occurred in 2013-2014.
• Changes to the legal status of any of the beneficiaries, in particular, SME status
There were no changes in legal status of any of the beneficiaries
• Impact of possible deviations from the planned milestones and deliverables, if any
There were no deviation from the planned milestones and deliverables
• Development of the project website (if applicable)
The project website is at www.simonevincenzi.com. Updated on research are provided at www.simonevincenzi.com/blog/ (tag: Marie Curie)
• Gender issues; Ethical issues
There were neither gender nor ethical issues.
• Justification of subcontracting (if applicable)
Not applicable.
• Justification of real costs (management costs)
Not applicable.