Making Food Webs Out Of (Almost) Nothing At All

Food web reconstruction through phylogenetic transfer of low-rank network representation (2022) Strydom and Bouskila et al., Methods in Ecology and Evolution, https://doi.org/10.1111/2041-210X.13835
The Crux
Understanding food webs (and more generally how different species interact) is important in helping us to understand ecological processes, but sampling (observing) interactions in the field is pretty challenging. Observing a parrot? Simple. Observing a possum? No problem. Observing a parrot evicting a possum from a tree-hollow? Rarer.
This means that data on species interactions is sparse. But we do have data for some regions, and things like computers and fancy maths (think machine learning) at our disposal. Which leads to the question: can we learn something from the places for which we do have interaction data and ‘transplant’ this knowledge and create an interaction network for a region with no data at all?
The focus here is to try and use predictive methods to help and at least give us a idea of who might potentially be eating who and use this to construct a metaweb (a full list of potential interactions) for a region that has plenty of species data, but no species interaction data.
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