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arXiv · 2607.27496

Identifying common backbones of interactions underlying food webs via non-deterministic alignments

Yifan Xu·Carlos Taveras·Lydia Beaudrot·César A. Uribe
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Abstract

Climate change reshapes food webs by altering species distributions and interactions, making it essential to identify structural backbones of interactions that persist across ecosystems. Deterministic alignment methods are computationally slow and restricted to one-to-one correspondences. We introduce a scalable, non-deterministic alignment framework inspired by optimal transport that captures overlapping species roles via many-to-many mappings. Framed via motif-role profiles as a Gromov-Wasserstein transport problem, our method is both efficient and interpretable. We apply the proposed method to a large continental-scale data set of 129 mammal food webs in Sub-Saharan Africa. Pairwise alignments are identified, and we uncover robust backbones with greater connectivity and transitivity than those expected under null models. The proposed approach provides a formal, reproducible tool for forecasting ecosystem reorganization and conservation efforts.

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Yifan Xu, Carlos Taveras, Lydia Beaudrot, César A. Uribe. 2026-07-29. Identifying common backbones of interactions underlying food webs via non-deterministic alignments. https://doi.org/10.1109/icassp55912.2026.11462837

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