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BioND Lab

@biondlab.bsky.social

210 followers 460 following 78 posts

Account of the Biodiversity Theory Research Group at HIFMB (Oldenburg, Germany) @hifmb.bsky.social All things Biodiversity, Networks & Data More about us at: biond.org and https://hifmb.de/research/working-groups/biodiversity-theory/

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BioND Lab @biondlab.bsky.social · Dec 3

There is now a starter pack with our group members available: go.bsky.app/4aYCsai

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BioND Lab @biondlab.bsky.social · 21h

Find out more about Juliane and her publications here:
hifmb.de/de/personen/...

www.researchgate.net/scientific-c...

5/5

Juliane Entzian - HIFMB Oldenburg

Vita 2025 – heute Postdoktorandin am HIFMB, Oldenburg 2020 – 2024 PhD im Bereich Angewandte Mathematik mit Schwerpunkt Numerik/ Approximationen, Universität Hamburg 2012 – 2019 Diplom in Mathema...

hifmb.de

BioND Lab @biondlab.bsky.social · 21h

... I’m absolutely grateful for the opportunity to extensively dive into network analysis here, and for finding an application in biodiversity and food web research that contributes to the wide-ranging IMAPP project."

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BioND Lab @biondlab.bsky.social · 21h

... such evidence and facts, I started studying Mathematics in Leipzig with a focus on PDEs, continued giving attention to numerics/approximations during my PhD in Hamburg and finally joined the Biodiversity Theory group at HIFMB as a PostDoc. ...

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BioND Lab @biondlab.bsky.social · 21h

... without having to deal with the (often pretty complicated) implementation? I barely think so.
Still, evidence-based decisions are crucial when it comes to successful implementation. In order to be able to explore, improve, and further develop methods and models that provide ...

2/5

BioND Lab @biondlab.bsky.social · 21h

Time to introduce a new group member: Juliane Entzian
joined us as a new postdoc!

"Don’t we all want to improve the world for at least just a tiny bit? And is there a more comfortable way in doing so than just telling decision-makers what should be done – ...

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BioND Lab @biondlab.bsky.social · Sep 4

Don't miss Tom Clegg's (@cleggtom.bsky.social) poster today at EcoNet 2025 with the title "Cross-feeding networks create tipping points in microbiome diversity" where he tries to answer the question how biodiversity of microbiomes emerges from interactions between populations.

BioND Lab @biondlab.bsky.social · Sep 3

If you’re attending EcoNet 2025, don’t miss Jordan Gault’s (@jagault.bsky.social) poster presentation: “Dissimilarity analysis based on diffusion maps.”
His work highlights how diffusion maps, a manifold learning approach, provide powerful new tools to track community change across space and time.

BioND Lab @biondlab.bsky.social · Sep 1

If you're at CCS 2025 this week:
Tues, Sep 2nd, 12:15 pm, Room 15, Melanie (@mhab.bsky.social) will present her work on functional motifs in foodwebs and networks.
Same day, Room 14, Tim (@timmauch.bsky.social) talks about diffusion-driven pattern formation in an opinion dynamical network model.

BioND Lab @biondlab.bsky.social · Aug 26

Using a master stability function approach, we show conditions where opinions distribute heterogeneously across the network, resulting in communities where the majority of agents hold the minority opinion. These regions can be seen as local hubs where minority views can thrive and develop.

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The figure shows the opinion propagation on a random geometric graph at three different time steps. You can see the same network at time step 0, 283 and 1000. Each network consists of 50 nodes with a distance threshold value of 0.2.
Node colors and radius represent the opinion composition and total abundance per node, respectively, with blue corresponding to opinion X and orange corresponding to opinion Y. The larger the nodes, the higher the abundance. Some nodes are highlighted with a gray shading, indicating where the local majority opinion is switched in favor of the global minority opinion (in this case X attains a higher local abundance than Y).
Over time a pattern forms where Y is the majority opinion but the network is divided into two regions. The lower part of the network at time step 1000 is dominated by nodes with opinion Y with very high abundances (indicated by the larger node size), while the upper part is dominated by those with opinion X with low abundances (smaller nodes). The two parts of the network are only connected by a single link between one node with local majority Y and one with local majority X.

BioND Lab @biondlab.bsky.social · Aug 26

These dynamics lead to bistable conditions where either one of the two opinions can be dominant across all communities. Tipping points can lead to an abrupt switch of the dominant opinion. However, the minority opinion is not doomed totally...

4/5

One parameter bifurcation diagram depending on parameter alpha with a fixed beta and gamma.
The y-axis shows the stable state, marked with a X star and has a range from zero to one with increments of 0.2.
The x-axis shows alpha, also with a range from zero to one, in increments of 0.25. We see a diagram with a graph that is formed like a flipped S. The area is divided into two different zones. In the white areas the system is monostable and the light orange area marks the parameter range where the system is bi-stable. The two regions are separated by two saddle-node bifurcations. One jump from one stable state into the other is marked by a red dot (for the bifurcation point) and a red arrow (indicating the shift from one stable state into the other).
On the bottom of the plot is a beta at 0.55 with two arrows. One arrow points to the right with the text "X inferior" above it. The other arrow points left and is marked with "X superior".

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BioND Lab @biondlab.bsky.social · Aug 26

We build a network model where nodes are communities of interacting agents with two competing opinions, and links represent avenues of migration. Agents can either flip their opinion spontaneously, change their opinion under the influence of others or leave to a more like-minded community.

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Overview of the model mechanisms.
The figure shows three different levels and explains what is going on. The first is the individual level that shows the individual agents. Level two shows a community occupied by multiple agents. These communities form a network in level three, where the individual nodes are connected by diffusion and each node is coloured as a pie diagram that shows the percentage of nodes with one of two opinions the agents (individuals) can have: X or Y. Nodes with opinion X are coloured blue, those with opinion Y are coloured in orange.
The individual agents live in a community. They populate nodes of a complex network and are coupled by diffusion.
Opinion formation on each node is governed by two processes that are further explained in two parts marked with a roman 1 and 2. Roman 1 shows spontaneous flipping of opinions. A node with opinion X can change opinion to Y with a rate of alpha, while the reverse happens with a rate of beta.
Roman 2 shows opinion adjustment through the influence of others. If one node in a group of three is the only one with opinion X, it changes to Y with a rate of gamma.

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BioND Lab @biondlab.bsky.social · Aug 26

Opinions form the basis of how individuals make decisions. We change our opinions through interactions with others along the complex social networks that structure societies. In our paper we ask how these interaction networks shape opinion formation.

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BioND Lab @biondlab.bsky.social · Aug 26

Paper alert! See the new pre-print up on arXiv by Tim Mauch (@timmauch.bsky.social) and Thilo Gross (@thilogross.bsky.social) on opinion formation:
arxiv.org/abs/2508.15377

The paper discusses the very nice results of Tim's master thesis, so let's get into the details, shall we?

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Diffusion-driven pattern formation in an opinion dynamical network model

The spatial organization of individuals and their interactions in communities are important factors known to preserve diversity in many complex systems. Inspired by metapopulation models from ecology,...

arxiv.org

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BioND Lab @biondlab.bsky.social · Jul 1

Great opportunity 👇

HIFMB @hifmb.de · Jul 1

Hallo artist community, this one is for you! Together with @hanse-ias.bsky.social we are looking for an artist in residence in early 2026. Please share!
#artscience #artistinresidence #marinebiodiversity