Pierre, Eloi, Nathan Olivier

Pierre, Eloi, Nathan Olivier
Åbo Akademi University · Department of Biosciences

MSc in Environmental Sciences; Oceanography and Marine Environments


How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
Pierre, Eloi, Nathan Olivier currently works at the Department of Biology, Åbo Akademi University. Pierre, does research in Community ecology with a main focus on Food web and BEF. Their current project is 'MARmaED - Marine Management and Ecosystem Dynamics under Climate Change..'
Additional affiliations
March 2016 - present
Åbo Akademi University
  • PhD Student in Marine Biology, Ecology
March 2016 - February 2019
Åbo Akademi University
  • PhD Student
September 2013 - June 2015
Sorbonne Université
  • MSc in Environmental Sciences; Oceanography and Marine Environments


Publications (4)
Full-text available
Studying how food web structure and function varies through time represents an opportunity to better comprehend and anticipate ecosystem changes. Yet, temporal studies of highly resolved food web structure are scarce. With few exceptions, most temporal food web studies are either too simplified, preventing a detailed assessment of structural proper...
Full-text available
Ecological communities are constantly being reshaped in the face of environmental change and anthropogenic pressures. Yet, how food webs change over time remains poorly understood. Food web science is characterized by a trade-off between complexity (in terms of the number of species and feeding links) and dynamics. Topological analysis can use comp...
Full-text available
A food web topology describes the diversity of species and their trophic interactions, i.e. who eats whom, and structural analysis of food web topologies can provide insight into ecosystem structure and function. It appears simple, at first sight, to list all species and their trophic interactions. However, the very large number of species at low t...


Questions (9)
I am analyzing my data and I plan to use the result of my analysis to build a network of interactions. I calculate correlations using the fourth-corner method and I would like to use the p-values as a measurement for strength of the interactions. The author of the method suggested to adjust p-values for multi-comparison testing using the FDR method.
If I would use the unadjusted p-values, I would simply do
1 - pvalue
to get the smallest pvalues to be the highest strengths.
Does that still hold after adjustment? Can I range the adjusted pvalues the same way?
A colleague told me one can't consider them the same way and I should then put the values between 0.5 and 1. I am not sure why.
Any clue on what to do?
I am doing a fourth-corner (co-inertia on 3 matrices to evaluate relationships between two matrices) and the analysis is known to increase the occurrence of false positives (multiple comparison). It is advised to adjust the p-values with the False Discovery Rate method.
However, I wonder how to evaluate whether to use non-adjusted vs. adjusted p-values.
A colleague and the literature mentioned that there is no strong basis whether or not to adjust p-values but that it mainly depends on the results.
What are the results supposed to look like so that you know if you should adjust the p-values or not?
I would like more opinions on this. :)
I plan to use the p-values further in my analysis as an indicator for relationships between my variables and will change the range so that it represents strong and weak relationships (X - pvalue).
As non-adjusted pvalues range between 0-1, I would do 1- non-adjusted pvalues.
However, my colleague mentioned (if I understood) that for adjusted pvalues, the range should go from 0.5-1 from the significant p-values. I am not sure why though and not sure I grasp how my non-adjusted pvalues relate to the adjusted counterparts.
Any lights on this?
Thanks in advance,
Since I started doing regular science communication on my website OceanFact and on the related social medias, I have observed a large increase in my reach and the reads for my scientific publications.
Who does regular science communication (more than going to conferences and talking to your peers)? Did you observe a similar increase?
I love reaching out to a lay audience. It is so nice to get feedbacks and comments through the mailing list. :)
Since I started the facebook group for the project, the interactions with other biologists and science communicators have brought so many good ideas and projects. Science communications ideas and research ideas. 🎉
What do you do to communicate your science?
I am a marine biologist and I personally blog about marine science/environmental science on my website with contributions from other scientists and reach out to readers and other people on social medias.
I am running my own audience-based collaborative science communication website in marine biology and part of the public outreach of our ITN project. I realized that so few researchers are doing scicomm, or only to their peers (e.g. conferences, workshops...) and not a lay audience.
Nowadays it takes me 30 min to write a popular summary of my own articles or on my own topic because I know the topic and I already did and constantly update my literature review.
As my audience and referencing is growing more and more people find and read my research. It seems it can only be beneficial to maintain an online presence.
Thus, I am curious to know what is stopping you? Lack of time? Imposter syndrome? You don't know where or how to do it? Fear of what your colleagues might think? Would you do it more often if someone would handle all the technical parts like publishing?
We will write an opinion piece on scicomm and I am interested to know :
- if you are already doing scicomm at your own scale (is it going well? how often do you publish? where? what are/were your struggles?),
- and if not what stops you from starting. :)
Thanks a lot in advance,
Is there an easy way to trace the origin of a concept better than back tracking cited literature?
For instance, when was first used a term in the literature? Could be a theory, or you just want to access the oldest report on anything.
With google scholar, you can't really sort by date.
Web of Science doesn't go that far back.
I recently heard of Google Ngrams but you can't have access to the documents behind the stats I am afraid?
Going further, how would you trace the evolution of a concept? The different milestones behind a concept. For instance, I could use the concept of "ecological niche" as I am aware of what I should get as a result.
Hi food web colleagues, diet experts...etc
Our last project started from the crazy idea to build a comprehensive benthic topology food web for the whole North Sea. It quickly seemed impractical for only a few human-beings as we lack data for most non-commercial species. It took almost two years to focus on 152 species, project that got reduced to 50 or so species for practicality.
We still want to go for it but I think we need to find the right people who might have the diet data we need or know where to find them (in situ, lab feeding experiments, published or unpublished data, or inference from other species).
Do you have diet information on species in the North Sea? Know someone who does? We could start from there.
With colleagues, we started this conversation over a cup of coffee where we realized most of the work on food webs (our field) focuses on links. In food webs, we focuses on fluxes for instance. It seemed no metrics incorporate information at the node-level.
We did the exercise of incorporating abundance information at the node level and it gives complementary information on the structure of the network.
So my question is, has anybody else tried this or thought of this, if not why has nobody else tried this?
It made me a little insecure to find no information on this in the literature.
I wanted to collect your opinions on this.
Best regards,
I am moving from analyzing food web network to bipartite network and I was wondering if anyone knew where to start? What books/articles I must read?
I am especially interested in the metrics I could use (modularity among others). Have an overview of those metrics...etc
I screened through the 'bipartite' package in R.
Thanks in advance,
An idea of planting some Malus sieversii has come to mind to build a preservation orchard in the city of La Chapelle in France but it is very difficult to get seeds from Kazakhstan where it grows easily. There is already the same kind of project in the USA and England but this idea is poorly established in France.
I could put you in contact with the manager of the project.


Cited By


Project (1)
The MARine MAnagement and Ecosystem Dynamics under Climate Change (MARmaED) project is a Marie Sklodowska-Curie European Training Network under Horizon 2020 (grant agreement no. 675997) that started on 1 October 2015 and will run for 4 years. It hired 15 PhD students to explore and investigate marine ecosystem change in careful detail from physical and biological effects to economic management implications and is unique in the way it will integrate effect studies with economic perspectives. www.marmaed.eu