akfbio.bsky.social
Using math + machines to understand nature's complexity | Asst. Professor, Florida Atlantic University
10 posts
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This is the color of my childhood super nintendo
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Yes, the apparent violation of competitive exclusion in nature has guided the search for overlooked niches and other forms of density dependence, that can explain mismatch between theory and data. We talk about all of this in the paper.
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A real step toward understanding how local structure shapes global dynamics! We think this insight will be useful not just for webs, but other networked systems from power grids to epidemics.
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In other words, transient dynamics of foodwebs can be broken down into contributions from building blocks! This is huge. It means measuring reactivity of a single species or a specific interaction can already tell us how much risk of violent perturbations originates from that part of the network.
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We show mathematically why this is the case and why it’s unlikely that undiscovered motifs with similar predictive power exist. But then it gets interesting. We find that reactivity (short-term violent responses to perturbations) is different. Unlike stability, reactivity is rooted in small motifs.
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We ask: when can you predict dynamics of a network just by knowing the dynamics of a small part of it (a motif)? In food webs, the answer is almost never. One famous exception is competitive exclusion: two consumers sharing a single resource can't coexist, precluding stability of the whole web.