Please see my new job ad on the UHH job portal. And if you are interested in joining my lab and tick the boxes, I am looking forward to your application!
Update: please note the position is still open (until Feb 18th)! And don’t be put off by the title (Animal Network Ecology): if you are open to think about plant and animal diversity and species interactions on the community level, chances are high our research interests will meet.
This website has fallen asleep, but under the hood, a lot has happened! Great new papers (congrats to Sylvie for winning the Lieth-award!), exciting thesis projects, perseverance in the IDENT Freiburg long-term data collection, etc….
But for me personally, these achievements are all dwarfed by my big career move: I’ve started a professorship at the University of Hamburg (UHH) and have just started to build up my new lab for Animal Network Ecology. If you’re interested to join to research insect biodiversity change and/or species interaction networks, feel free to contact me!
The new lab is located in the beautiful botanical garden in Klein Flottbek. Lots of opportunities and space to be filled with our research and teaching vibes. I am excited about building up many new collaborations with great colleagues, connecting the different institutes of the Department of Biology and beyond. In teaching, I am particularly involved in the BSc Biology programs, teaching biodiversity of animals, data science and more.
Please note that both this wordpress page and the new page at the UHH are in desperate needs of updates, which will come over the next months…
Last year, I published a paper about interaction rewiring and how to partition network dissimilarity. From looking at the recent literature, it seems that there is still confusion about this topic (partly due to this paper by Tim Poisot).
The key cause of confusion may be that the purpose for calculating the rewiring component (called betaOS in Poisot’s paper and in my paper) is often not made clear enough. I see mostly two purposes: (case A) you want to quantify the degree of rewiring – then the original definition of Poisot et al. is what you need, or (case B) you want to quantify how much rewiring contributes to total network dissimilarity (implied by wording such as “rewiring drives dissimilarity”) – then the definition based on Novotny is for you. In my research, I am often interested in case A, but my above-mentioned paper focused on case B. Like in other areas of diversity partitioning, the core of the discussion is about denominators and the difference between dissimilarity (A) and additive components of dissimilarity (B).
Let me illustrate the denominator issue with a simple example: Imagine you go out for lunch and there are three options on the menu: Penne Arrabiata (vegetarian pasta), Spaghetti Bolognese (meat pasta) and Pizza Margherita (vegetarian pizza). To calculate the proportion of vegetarian options among pasta, you divide 1 by 2 (the denominator is 2): 50% of the pasta options are vegetarian. The percentage of vegetarian pasta among all options is 33% (the denominator is 3). The percentage of vegetarian meals among all options is 66% (the denominator is 3). All three numbers are informative, but they provide different information. However, you cannot calculate the percentage of vegetarian pizza as 66% – 50% = 16%; it is 66% – 33% = 33%. This shows that percentages are only additive if you use a common denominator, i.e. simple additive operations only work if you stick to percentages in the whole menu.
Back to ecological networks: “meat pasta” has to be replaced by “interactions that are shared between networks”, “vegetarian pasta” has to be replaced by “interactions that differ due to rewiring among species shared between networks”, and “vegetarian pizza” has to be replaced by “interactions that differ due to species turnover (in the wide sense)”. “Percentage” has to be replaced by “dissimilarity”, noting that the dissimilarity measures under consideration are just a special type of percentages.
You have to decide if you are interested in the proportion of pasta that is vegetarian (in the ecological network case: betaOS following Poisot; case A) or in the contribution of vegetarian pasta to all options on the menu (in the ecological network case: betaOS based on Novotny; case B). But I have yet to understand what the number 16% should tell me about the importance of vegetarian pizza on the menu (in the ecological network case: betaST following Poisot, which intends to estimate “the importance of species turnover in the overall dissimilarity”). If there is one vegetarian pasta and one vegetarian pizza, both contribute equally to the number of vegetarian options (in the ecological network case, this holds with betaST based on Novotny) – or would you say that the vegetarian options are mostly pasta and much less pizza (50% vs 16%)? Even beautiful maths proving that a denominator of 2 should be used for the pasta-specific question (case A) wouldn’t convince me that this denominator should also be used for the whole-menu question (case B).
Hope this post helps you think more clearly about what you want when estimating rewiring or partitioning network dissimilarity.
Our paper on temporal scale-dependence of network structure led by you, published two years ago in Oikos, is having quite an impact. After being selected as Editors Choice, it became a top downloaded paper and then a top cited paper recently. As of now, it already has 31 citations in the Web of Science – so definitely a booster to Oikos’ Impact Factor 😉 If all papers in Oikos would be cited that much, it would have an Impact Factor of about 20! Congratulations, Benjamin!
I heard there was some kind of pandemic… Have you also heard of it?
I’ve long been looking forward to writing my post-COVID post, but it never really felt like the time. Our university has just phased into the loosest COVID regulations since March 2020 – so maybe that’s the time. Well, over the past two years and a bit, my research certainly hasn’t progressed as planned (with two young kids, I never really had that feeling of an unexpected veeery long writing retreat…). But nevertheless, there have been some great achievements, and I don’t want to leave them unnoticed in this virtual space.
The greatest achievements were certainly those by my two PhD students:
Both have by now graduated and successfully defended their theses. Congratulations! They have published exciting papers, and more are on the way.
Some long-awaited papers have finally come out, including my first single author paper. Some others are still waiting to see the light of a journal… watch for updates here, which I plan to post more frequently again 😉
I’ve had the joy of digital teaching and zoom meetings (we’ve all finally learned how to use technology a bit better, and there are some advantages). But actually, I am longing a lot for real conferences and meeting real people (you?)!
Trees in IDENT are growing, and we (that’s Sylvie, I and a lot of students and hiwis) have never given up recording arthropods and damage on them:
New people have started (hola William!) and new concepts and ideas have developed. Let’s see what time will bring next 🙂
The lab on our retreat in summer 2019 (Jochen, Sylvie, Tobias, Benjamin, Hai-Dong). It happened to be the day when all-time temperature records were broken in Germany, which explains the essential water bottles and the slight hint of dizziness. We still had a productive day with talks, discussion and R tipps, and even found 16 different types of species interactions on our little excursion. And last but not least, we talked about nothing (that is, what different ways of “nothing” you may find in data analysis, and when you have to switch between them).
Just because it is a nice illustration of topics we work on in the lab, I moved this here from the former “lab members” page:
A bipartite network of all current lab members and keywords for their research projects. People doing more similar work tend to be grouped closer together. Made with the bipartite R package, using this code: cols <- rgb(0:6/6, 0.1, 6:0/6, 0.7); plotweb(t(mydata), y.width.low=0.07, y.width.high=0.07, col.interaction=rep(cols,each=7), col.low=cols)
The lab has grown! Just before the beginning of the field season, we got together last week to meet and talk about what everyone is going to study in their (upcoming) research projects. We found out that the different projects have quite a lot in common. We also talked about nothing for a while (that is, about the differences between 0, NA and other types of null); knowing something about nothing is quite important for good science…
Missing on these pictures is Rafael Bohn-Reckziegel, student assistant helping out with his amazing skills in insect sampling, data management and programming.
Welcome new lab members and good luck with your research!
I am looking for a new PhD candidate to work with me on tree-insect networks in the IDENT network of tree diversity experiments. I am looking forward to your applications! See more info here: PhD-position_IDENT_JFruend2017
Update February 2018: the position has been filled.
(update Jan-2017: Position filled)
I have a PhD position (65% contract for 3 years) available in my lab (at the University of Freiburg)!
You will use models and fieldwork to investigate temporal dynamics in insect interaction networks (plant-pollinator, plant-herbivore, host-parasitoid). The main objective is to identify the functional relevance of temporal (daily, seasonal) structure of species interactions. The degree of modeling vs empirical work is somewhat flexible.
Please apply before 5 December 2016.
Here you find the full ad as a pdf.
If you want to read more, this might be a good starting point: Fründ J, Dormann CF, Tscharntke T (2011). Linné’s floral clock is slow without pollinators – flower closure and plant-pollinator interaction webs. Ecology Letters, 14, pp. 896-904.
And somewhat more technical: Fründ J, McCann KS, Williams NM (2016). Sampling bias is a challenge for quantifying specialization and network structure: lessons from a quantitative niche model. Oikos, 125, pp. 502-513.
Another relevant paper with cool ideas and figures on the topic: Rasmussen et al. (2013). Strong impact of temporal resolution on the structure of an ecological network. Plos One
Jochen Fründ 