Category Archives: Marie Curie

Consulting for Marie Curie Individual Fellowships Applications

Starting soon (between 7 and 10 days after the publication of this post, the deadline for Marie Curie applications is early September), I will offer a consulting service for science researchers interested in applying to either the European or Global Marie Curie Individual Fellowships. Read more below.

------------------------------------------------------------------------------------------------------------------------------------------

The Marie Skłodowska-Curie Individual Fellowships (IF) are granted each year to hundreds of experienced researchers (be in possession of a doctoral degree or have at least four years of full-time equivalent research experience). They have the goal of supporting the mobility of researchers within and beyond Europe, as well as helping attract the best foreign researchers to work in the European Union. The grant usually covers two or three (for Global Fellowships) years' salary, a mobility allowance, research costs, and overheads for the host institution. All research areas can be funded.

There are two types of Individual Fellowships:

  • European Fellowships, held in the EU or associated countries and open to researchers either coming to Europe or moving within Europe.
  • Global Fellowships, which fund secondments outside Europe for researchers based in the EU or associated countries. There is a mandatory one-year return period to Europe for the researcher.

I won a Marie Curie Global Fellowship (it was called a Marie Curie International Outgoing Fellowship at the time, it is the same action) in 2011 for the project RAPIDEVO, which ended in December 2015. I prepared and completed the application in 21 grueling days, starting conceptually from another grant application that I submitted to the Italian Minister of Education and Research. Tips, tricks, insights, and example of successful applications were very hard to find, but through patient work and in almost complete absence of support (with a few, minor exceptions), I was able to prepare an application that was scored in the top 10% of all successful applications for that year (93.5/100).

Reviewers praised the clarity of language in the proposal, the organization of the application, the interdisciplinarity of the proposed research, the selection of experienced and successful scientists as supervisors.

A few months after the end of the Marie Curie Fellowship, I applied for a self-sponsored US Green Card for alien of extraordinary ability in the sciences. If you dream is to become a permanent resident in the US, a Marie Curie Fellowship, along with a good scientific CV, may substantially increase your chances of being granted a Green Card (don't forget to do your peer-reviews!). The large sum available to Marie Curie Fellows for traveling allowed me to spend time in research institutions in Europe, United States, and South America (where I spent the last 3 months of my Fellowship, presenting my work in La Habana, Cartagena, Montevideo, Buenos Aires, and Santiago de Chile). It is truly a once-in-a-lifetime opportunity that changed my life for the better. 

However, when I was preparing the application for the Marie Curie Fellowship, I wasted way too much of my research and personal time looking for a copy-editor (I found one whom I quickly fired for clear incompetence after having paid $200), pdfs of successful applications (starting from scratch is very hard), and inside baseball for more specific criteria used by reviewers for judging the applications in order to better organize my application. Looking back, I would have certainly taken advantage of the services provided by an experienced consultant. After sending the application, I had to take a week off to recover from the effort! I wrote about my experience writing the application here and here.

Starting soon (between 7 and 10 days after the publication of this post, the deadline for MC applications is early September), I will offer a consulting service for science researchers interested in applying to either the European or Global Fellowships, in particular in the biological sciences, but I can offer insights also outside of the biological sciences. I will provide (a) part B of my successful application, and (b) a 2-hour written consultation after the material is delivered via email: an early stage (1 hour) and a late stage (1 hour) review of part B of the application. I am not a copyeditor, nor an administrator. I read for organization and language, soundness of hypothesis, and overall strength of the application. I also point to useful books and articles for improving English and structure of proposals. 

In the last years, the structure of part B of the proposal slightly changed with respect to the proposal I submitted. However, the content is basically the same and the application I wrote was much longer, thus certain sections can be joined together and other parts can be discarded. It is certainly better to have more material than less.

I still provide for free the second-year Marie Curie Periodic report.

Send me an email for pricing

New pre-print

Pre-print of my last work is on biorxiv

Vital rates, source-sink dynamics, and type of competition in congeneric species

Simone Vincenzi, Dusan Jesensek, Alain J Crivelli

Abstract

The estimation of vital rates and life-history traits and how they vary with habitat and population factors are central for our understanding of population dynamics, risk of extinction, and evolution of traits in natural populations. We used long-term tag-recapture data and novel statistical and modeling techniques to investigate how population and environmental factors determine variation in vital rates and population dynamics in the population of brown trout Salmo trutta L. of Upper Volaja (Western Slovenia). Alien brown trout were introduced in the stream in the 1920s and the population has been self-sustaining since then. The population of Upper Volaja has been the subject of a monitoring program that started in 2004 and is currently on going. Upper Volaja is also a sink, receiving individuals from a source population living above an impassable waterfall. We estimated the contribution of the source population on the sink population and tested the effects of temperature, population density, and early environment on variation in vital rates and life-history traits among more than 4,000 individually tagged brown trout that have been sampled since 2004. We found that fish migrating from the source population (>30% of population size) help maintain high population densities despite poor recruitment. Neither variation in density nor in temperature explained variation in survival or growth; the best model of survival for individuals older than juveniles included cohort and time effects. Fast growth of older cohorts and higher population densities in 2004-2006 suggest very low densities in early 2000s, probably due to a flood event that caused a strong reduction in population size. Higher population densities, smaller variation in growth and weaker maintenance of size hierarchies with respect to endemic marble trout suggest that exploitative competition for food is at work in brown trout and interference competition for space is operating in marble trout.

Data is here

I will provide the R code soon

Correlation between stream temperatures in Slovenian streams in which marble trout live

This is an update on my research and I will try to post more often in these last months of my Marie Curie Fellowship. Files are hosted on my github page. Data have been collected by Alain Crivelli and Dušan Jesenšek since 1996. Some info on marble trout, the conservation program, and Western Slovenian streams here below.

1. Marble trout and Western Slovenian streams

Marble trout is a freshwater resident salmonid endemic in the Adriatic basin of Slovenia. Whether there are still pure marble trout populations living in the Po river system (Northern Italy) is subject of current research. Marble trout live in streams with mean summer temperature below 15°C and winter temperature ranging from 0 to 5 °C. Marble trout spawn in November-December and offspring emerge in May-June.
The Marble Trout Conservation Program started in 1993 in the upper reaches of the Soca River basin and its tributaries - the Idrijca and Baca Rivers - in Western Slovenia. Eight pure marble trout populations, all isolated and separated from the downstream hybrid marble-brown trout zone by impassable waterfalls, live in headwater streams in the basins of Soca, Baca, and Idrijca Rivers: Huda, Lower Idrijca, Upper Idrijca (in the map below Lower and Upper Idrijca are grouped together), Lipovesck, Studenc, Svenica, Zadlascica, Trebuscica.
Other two populations (Zakojska and Gacnik) have been created by translocating the progeny of the Zadlascica (Zakojska) and Trebuscica X Lipovesck (Gacnik) in 1996 and 1998, respectively.

DSCF2672

DSCF3188
 Allpoproadmap
2. Analyses

For some of the analyses I intended to carry out (temperature-dependent survival, growth, and recruitment), it was necessary to have complete temperature records for all streams since the start of the sampling. However, there were some missing data (sometimes whole seasons/years) in evert stream. The temperature .csv files are (stream_name)_temp.csv, the first column is the Date, the second is the mean daily temperature (Temp). Start by sourcing the file Temp.r, which is reading all the temperature files and merging them together (r scripts are here).

source("Temp.r")

The output temp.all.df (along with the production of a ten-panel plot with stream-specific monthly temperature boxplots for 2009-2013) is a data.frame with columns Date, Temp, Year, Month, Stream, Calc (Meas = temperature has been recorded, see below for other values) (see below).

Temperature_boxplot

Daily Water Temperature (C)
Date Temp Year Month Stream Calc
1996-07-04 10.98 1996 7 Zak Meas
1996-07-05 10.99 1996 7 Zak Meas
1996-07-06 11.26 1996 7 Zak Meas
1996-07-07 11.19 1996 7 Zak Meas
1996-07-08 11.06 1996 7 Zak Meas
1996-07-09 9.96 1996 7 Zak Meas
1996-07-10 9.85 1996 7 Zak Meas
1996-07-11 10.07 1996 7 Zak Meas
1996-07-12 10.51 1996 7 Zak Meas
1996-07-13 11.08 1996 7 Zak Meas

Then, I tested the correlation between stream temperatures between pair of streams (one is the target - the one with missing data - and the other is the tested). I used the temperature data of the tested stream with the highest correlation with the temperature data of the target stream to impute the missing temperature data in the tested stream.
The Temp.corr.f function tests the correlation between water temperature data recorded in different streams.

source("Temp.corr.r") # contains Temp.corr.f
Temp.tb = Temp.corr.f(temp.all.df)

The Temp.tb data.frame has columns target stream (tar), tested stream (var), correlation between stream temperature of the two streams (cor), years with common number of days with temperature recorded (common.years), years with missing data for the target stream (miss.years), and years with missing data for the target stream, but with complete data for the tested stream (miss.in.var). The years in miss.in.var can thus be used to impute the missing data.
The correlation between water temperature of streams are typically very high (mean correlation[sd] = 0.97[0.01]).

Correlation of water temperature
tar var cor years.cor common.years miss.years miss.in.var
Zak Gac 0.95 5 2001-2002-2005-2009-2013 1996-1997-1999-2000-2006-2008-2010-2011-2014 2006-2008-2010-2011
Zak Sve 0.95 3 2002-2009-2013 1996-1997-1999-2000-2006-2008-2010-2011-2014 2006-2008-2010-2011
Zak Stu 0.97 3 2005-2009-2013 1996-1997-1999-2000-2006-2008-2010-2011-2014 2006-2008-2010-2011
Zak LIdri 0.97 3 2005-2009-2013 1996-1997-1999-2000-2006-2008-2010-2011-2014 2006-2008-2010-2011
Zak UIdri 0.96 3 2003-2005-2013 1996-1997-1999-2000-2006-2008-2010-2011-2014 2006-2010-2011

In each stream, I imputed the missing data (1) using the temperature data from the tested stream with the highest correlation with the target stream and (2) by applying the best model (linear or non-linear - gam -, chosen according to best prediction) linking the water temperature data of the two streams. The r script for imputing missing data is in Temp.filling.r.

source("Temp.filling.r")

The output of the script is the data frame temp.all.df with columns: Date, Temp, Year, Month, Stream,
Calc (Meas = temperature recorded in the stream, Gac2005 = in one year (1997) we had missing data for Gac and the only acceptable data for imputing was coming from Gac in 2005, Same_as_a = Same temperature as days after (just for a few days missing), Same_as_b = Same temperature as days before (just for a few days missing), Zak2012 = in one year (1997) we had missing data for Zak and the only acceptable data for imputing was coming from Zak in 2012, Stream_name = stream whose temperature data was used to impute missing data, degree_days = degree days for the day using 5C as base temperature, Sampling_Season = Summer for June, July, September - Winter for the rest of the year). Sampling occurred either in June or September or in both.

Daily Water Temperature (C)
Date Temp Year Month Stream Calc degree_days Sampling_Season
2006-08-19 13 2006 8 Stu Meas 7.8 Summer
2006-08-20 13 2006 8 Stu Meas 7.8 Summer
2006-08-21 13 2006 8 Stu Meas 8.1 Summer
2006-08-22 13 2006 8 Stu Meas 7.6 Summer
2006-08-23 13 2006 8 Stu Meas 7.6 Summer
2006-08-24 12 2006 8 Stu Meas 7.3 Summer

Temperature data is now ready to be used to test differences in water temperature between streams, and temperature-dependent survival, growth, and recruitment.

Manuscript submitted

I recently submitted a new manuscript on vital rates and life histories in marble trout. Dense paper, lots of models, lots of results. Currently under review. Here below are the Title and Abstract.

Title

Within and among-population variation in vital rates and population dynamics in a variable environment --- Vincenzi, Mangel, Jesensek, Garza, Crivelli.

Abstract

Understanding the causes of within- and among-population differences in vital rates, life histories, and population dynamics is a central topic in ecology. In order to understand how within- and among-population variation emerge, we need long-term studies that include episodic events and contrasting environmental conditions, tag-recapture data for the estimation and characterization of individual and shared variation, and statistical models that can tease apart population-, shared-, and individual contribution to the observed variation.

We used long-term tag-recapture data and novel statistical and modeling techniques to investigate and estimate within- and among-population differences in vital rates, life histories and population dynamics of marble trout Salmo marmoratus, a narrow endemic freshwater salmonid. Only ten populations of pure marble trout still persist in Western Slovenian headwaters. Marble trout populations are also threatened by floods and landslides, which have already caused the extinction of two populations in recent years.

In particular, we estimated and determined causes of variation and trade-offs within- and among populations in growth, survival, and recruitment in response to variation in water temperature, density, sex, early conditions, and extreme events.

In all ten populations, we found that the effects of population density on traits were mostly limited to the early stages of life and that individual growth trajectories were established early in life. We found no clear effects of water temperature on survival and recruitment. Population density was variable over time in all populations, with flash floods and debris flows causing massive mortalities and threatening population persistence. Apart from flood events, variation in population density within streams was largely determined by variation in recruitment, with survival of older fish being relatively constant over time within populations, but substantially different among populations. A fast- to slow-continuum of life histories in marble trout populations seemed to emerge, with slow growth associated with higher survival at the population level, possibly determined by food conditions and age at maturity.

Our work provides unprecedented insight into the causes of variation in vital rates, life histories, and population dynamics in an endemic species that is teetering on the edge of extinction.

Paper submitted to Axios Review

A few months ago, my colleagues and I submitted to Fish and Fisheries a manuscript on the trade-offs between complexity and accuracy in random-effects models of body growth.

The paper was rejected mostly on the basis of lack of fit (i.e. the topic was only marginally interesting for the journal's readership). One Reviewer found the paper interesting and valuable, and recommended the submission of the manuscript to a more general journal, such as Ecology or Oikos. The other Reviewer commented on some unclear technical aspects of the work (the review was quite detailed and the recommendations/suggestions/critiques were valuable, thanks anonymous Reviewer).

I believe the paper should be of interest for a large audience of biologists, ecologists, computational scientists/statisticians. The main motivation of the paper is quite simple and very general: "We often face trade-offs between model complexity, biological interpretability of parameters, and goodness of fit." Then, with reference to models of growth: "Depending on formulation, parameters of some growth models may or may not be biologically interpretable. For instance the parameters of the widely used von Bertalanffy growth function (von Bertalanffy 1957) to model growth of fish may be considered either curve fitting parameters with no biological interpretation (i.e. providing phenomenological description of growth) or parameters that describe how anabolic and catabolic processes govern the growth of the organism (i.e. mechanistic description); see Mangel (2006). The classic von Bertalanffy growth function has 3 parameters: asymptotic size, growth coefficient, and theoretical age at which size is equal to 0. In the original mechanistic formulation of von Bertalanffy, asymptotic size results from the relationship between environmental conditions and behavioral traits and the growth coefficient is closely related to metabolic rates and behavioral traits (i.e. the same physiological processes affects both growth and asymptotic size). However, in the literature asymptotic size and growth rate are commonly treated as independent parameters with no connection to physiological functions, thus offering just a phenomenological description of growth."

However, I understand Editors may not fully grasp the relevance of the paper for their journal. For instance, the manuscript was previously submitted to another journal, but the Editor wrote: "I feel that the work is too specialised, as relatively few researcher work on growth curves". I might disagree on the claim that few researchers work on growth curves. I am sure that lots of scientists use growth models in their work, but I might agree on the number of people working on the development of growth models or methods for the estimation of growth model parameters (it is also quite hard).

My colleagues and I (my idea, my colleagues agreed) decided to submit the manuscript to Axios Review, a new service that should help authors publish their papers in higher profile journals. This is how it works: "Axios Review solves this problem by putting papers through rigorous external peer review and then referring them to the appropriate journal. When a journal asks the authors to revise and submit, the journal has effectively said that: i) the paper is within their scope, ii) that it is not fatally flawed, and iii) that it could be published in their journal. The Axios Review process effectively eliminates rejections on the grounds of novelty and significantly reduces the chances of rejection on quality. It’s similar to getting a ‘reject, encourage resubmission’ decision from the journal itself; for comparison, about 75% of resubmissions to top tier evolution journals get accepted. Authors submitting to Axios Review can have the reviewers comment on the suitability of their paper for any journal they choose, allowing them to aim for a high profile journal without the effort of formally submitting."

I submitted the manuscript to Axios Review a couple of days ago (target journals following an order that may or may not be the one I chose: Oikos, Ecology, Journal of Theoretical Biology, Ecological Applications). So far, communication with the Editorial staff has been excellent.

I did not upload the manuscript on arxiv or bioRxiv (I don't know where the manuscript will end up and thus which policy related to uploading of pre-print should I follow), please send an email if you'd like to read a pre-print.

 

Marie Curie Fellowship Periodic Report

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.

19th Dec 2014 - Update on research

I am currently working on pedigree reconstruction in a marble trout population (Lipovscek) that was affected by two big, destructive flash floods in 2007 and 2009, focusing in particular on the processes that helped the population bounce back to pre-flood density.

After SNPs discovery, we have successfully genotyped all the samples (~800) collected from 2006 until September 2014. The first step of the analysis is to merge together data coming from samples with different IDs, but that refer in reality to the same individual. My colleague field biologist Alain Crivelli uses Carlin tags (a metal tag that is attached with a piece of wire under the dorsal fin of the trout) only on fish longer than 110 mm; if the fish is shorter than 110 mm, a piece of the adipose fin is collected and the tube with the tissue sample is IDed. Every time a fish is provided with a Carlin tag, a piece of adipose fin is collected and the tube with the tissue sample has the same ID of the Carlin tag. Thus, the genotypes coming from the tissue sample of a fish that has first been sampled when shorter than 110 mm and later sampled when longer than 110 mm (and thus a Carlin tag was provided) should be the same, except for genotyping errors. Another instance of genotype matching occurs when a fish has lost the Carlin tag and it is later sampled and retagged with another Carling tag, since it is not possible to establish the previous ID of the fish (several fish lose their tags between sampling occasions). However, when two genotypes match, it is possible to merge together the demographic histories of the fish with different IDs, but that in reality refer to the same fish. It may happen that four different IDs refer to the same fish. For instance, a fish might have been sampled when aged 0 (i.e. before the first winter, first ID) and shorter than 110 mm, then sampled again the following year as age-1 fish shorter than 110 mm (second ID), then sampled the following year as age-2 longer than 100 mm and tagged (third ID), then sampled the following year as a fish that has already been tagged (when fish lose the tag, the scar is visible) and re-tagged (fourth ID).

Merging together fish histories and genotypes referring to the same fish is important for multiple reasons:

  • if the fish is a potential parent, it avoids not being able to assign the offspring to a parent since 2 potential parents (i.e. the same fish) have the same probability of being the true parent;
  • it avoids overestimating the production of young;
  • it helps for estimating more accurately  growth (it helps having longer fish histories) and survival probabilities (tag loss is a tricky problem, since the fish that lost the tag is "apparently" dead).

Parts of the "matching genotypes" analysis can be automated (e.g., given ~160 alleles per fish and allowing up to 2 or 3 mismatches, it is quite easy to write a script that extracts fish IDs with the same genotype), but then the demographic histories of the fish with the same genotype should be checked one by one. This was necessary as some demographic histories of fish with the same genotype made little sense (two different cohorts or IDs referred to fish sampled in the same year, but with vastly different length and weight), and thus I had to find out whether the mistake occurred in the lab or in the field.

I am getting closer to having a final, semi-clean, dataset allowing me to proceed with pedigree reconstruction.

Updating the blog and present/future research

I decided to start providing regular updates on my Marie Curie research on this blog.

These are my plans for the next 6 months, the content is basically coming from email exchanges with my collaborators.

- Pedigree reconstruction in the marble trout population of Lipovesck. We have recently genotyped the individuals that have been sampled in 2013 (June and September) and 2014 (June and September). All samples have been sexed and I am ready to carry out the pedigree reconstruction, with particular focus on the post-2009 generation. In 2009, a huge flood hit Lipovesck and just a handful of marble trout survived. The main goal is to understand the recovery process after the flood, who reproduced and whether certain traits were related with higher chances of post-flood reproduction. Then, I'd like to test whether my predictions on post-flood recovery (younger age at reproduction due to the relaxation of density-dependent processes after an episode of massive mortality) were right. If it is true, we should expect the 2011 cohort to have reproduced (at least some individuals) in 2013, thus anticipating one year reproduction (at age 3 or 4 under normal conditions).

- Phylogeny of marble trout living in Western Slovenia. We are sequencing right now additional fish from the populations of Idirijca, Svenica, and Studenc. For Idirijca, the sequencing of additional individuals was motivated by the lack of a sufficient number of SNPs for pedigree reconstruction (96 SNPs recommended, ~80 should be enough). Fish from Svenica and Studenc have never been sequenced. In order to save some money, we tried to sequence fish from some of the populations part of the cluster identified by Fumagalli et al. 2002 (14 microsatellite loci were used). However, since almost none of the SNPs found in the populations of Trebuscica and Idrijca were found to be variable also in Svenica and Studenc, we now have the suspicion that Svenica and Studenc are not as genetically close to Trebuscica and Idrijca as reported by Fumgalli et al. After this sequencing run, we should have all the elements for studying the phylogeny of marble trout, inbreeding, loci under selection etc.

- Writing a technical paper on SNP discovery for marble trout. While we are still discovering and characterizing SNPs for the populations of Idirjca, Svenica and Studens, I am confident we will discover the population-specific panel of SNPs soon. The only real problem is the population of Huda, for which we found very little to almost non-existent polymorphism. Given money, we might try to sequence some fish from Huda using an Hi-seq machine (we are currently using a Mi-seq with size selection at 500 base pairs).

- Differences in life-histories (growth, survival, morphology) in marble trout, including density-dependent patterns, with the main focus on the relationship between growth and survival as possibly mediated by cannibalism. Most of the analysis have been done.

Career of Marie Curie Fellows

The European Commission just published an interesting document on the long-term career development of Marie Curie researchers: Marie Curie researchers and their long-term career
development: A comparative study". You can find it here (executive summary).

in general, it seems that Marie Curie programs have a positive effects on multiple indicators of career quality (although not speed). This part was particularly interesting:

"No particular effects on career ‘speed’ were registered. MC fellows achieve  professorship titles more frequently than other fellows, but this seemingly requires  more time than for researchers with smaller mobility experience, i.e. those that  tend to stay in the same institution throughout their entire career. Here, an ‘affiliation effect’ can be observed which rewards non-mobile researchers within certain academic environments and penalises somewhat mobile ones."

This is very likely to be ascribed to the typical recruitment of European Universities (Spain and Italy for example), in which the "internal" researchers is heavily supported by the local hiring committee. Thus, staying in the same place for (almost) all the career may be a wise decision. Sad thing.

 

 

One-page application to "Science and the City" event

Euraxess Links North America is putting together a terrific event in New York City on the 28th of March. The event aims to present exciting EU-funded research as well as to offer and share tips and experience with potential applicants to EU research actions.

I sent my one-page application including Title, Abstract, and Motivation, you can read it here below (formatting somewhat lost).

Science and the City, NYC March 28th, 2014

Title: Shaken, burned, drowned, but still there: how species survive catastrophic events in an increasingly extreme world.

Abstract: The world is becoming more extreme. Increasingly frequent catastrophic events, such as fires, floods, extreme high or low temperatures, rain and snowstorms, deep freezes, and droughts often result in crashes or extinction of populations or species, loss of genetic diversity, and dramatic changes in ecosystems. Surprisingly, even after almost complete collapses, in some species populations are able to bounce back to safe abundances from a handful of surviving individuals. How does it happen? Why and how do certain species possess traits that allow them to persist when on the verge of extinction? And, will those species and populations be able to survive an increased frequency and intensity of extreme events associated with global climate change?

I study the resilience of population to extreme events using marble trout, a freshwater fish currently found only in Slovenia, as model species. Since 1993, my colleagues and I have extensively collected and analyzed marble trout demographic and genetic data. The last relict populations of this species are routinely affected by catastrophic flash floods and debris flow driving them just a few individuals away from extinction. We have observed multiple occasions when just a handful of fish surviving a flood rescued the population! However, the future is not bright for marble trout: rainfall and stream discharge data collected since the 1960s show a recent increased frequency, intensification, and altered seasonality of catastrophic floods. Will marble trout be able to persist? Will we observe bigger or smaller fish, more juveniles or older fish? Will population collapses lead to more deformities caused by inbreeding, dangerous loss of genetic diversity, and/or altered life cycles? Will we be able to save the species through science‑driven conservation actions? To answer these questions, an interdisciplinary research approach combining cutting‑edge molecular genetics, demographic modeling, natural history and meteorology is needed. The complexity of project along with its intrinsic interdisciplinary nature motivated me to present an application for a Marie Curie International Outgoing Fellowship, which I won in 2011.

Motivation: EU funding schemes are a terrific opportunity for early-career scientists. I would be delighted to take the opportunity offered by “Science and the City” to present my EU‑funded research, as well as offering my vision and tips for a successful application to EU funding schemes. Extreme events are having a massive impact on ecosystem and species, including humans (e.g. the recent California drought, the deep freeze in NE US, floods in central Europe and China), and it is my desire to raise awareness on the interdisciplinary research required for predicting their occurrence, understand their consequences, and mitigate their impact.

Since winning my Marie Curie IOF in late 2011 I have been helping several scientists preparing their applications to EU 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 MC IOF application, free for the public and fellow scientists. Due to my blog, word of mouth, and Twitter activity (@svincenzi) I routinely receive emails from applicants and winners of EU research actions asking for help or advice regarding research, how to prepare the application package, and more practical things such as how to pay taxes in the US, what solutions I recommend for health insurance, and how to prepare reports. Looking forward, in my future capacity as a senior scientist I have the ambition to develop a structured program that supports the applications of young and promising scientists to EU funding schemes.

 

Simone Vincenzi, Marie Curie IOF Fellow

              UCSC (USA) and Polytechnic of Milan (Italy)