Higher-order interactions in ecology can be hidden in plain sight
Violeta Calleja-Solanas, Santiago Lamata-Otín, Carlos Gómez-Ambrosi, Jesús Gómez-Gardeñes, Sandro Meloni
TLDR
This paper shows that higher-order ecological interactions are often indistinguishable from pairwise models using only time-series data, leading to misinterpretations.
Key contributions
- Higher-order ecological interactions can be accurately mimicked by simpler pairwise models.
- Time-series data alone is insufficient to reliably infer the presence of higher-order interactions.
- Introduces "mechanistic identifiability" problem where different mechanisms produce similar dynamics.
- Stresses the need for complementary ecological data to accurately infer interaction structures.
Why it matters
This paper reveals a critical limitation in inferring ecological interactions from time-series data, showing that complex higher-order interactions can be indistinguishable from simpler pairwise models. It introduces the concept of mechanistic identifiability, urging ecologists to integrate diverse data sources for more accurate understanding of ecosystem dynamics.
Original Abstract
Higher-order interactions are increasingly recognized as a key component of ecological dynamics. However, we show that higher-order Lotka-Volterra dynamics can, in some scenarios, be accurately reproduced by effective pairwise models fitted to the same abundance time series. Consequently, higher-order interactions cannot, in general, be inferred from time-series data alone. We further identify a fundamental problem of mechanistic identifiability, whereby distinct interaction mechanisms generate nearly indistinguishable dynamics, potentially leading to accurate yet misleading ecological interpretations. Our results highlight the need to complement time-series data with additional ecological information to infer interaction structure reliably.
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