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\title{Forecasting in the face of ecological complexity: number and strength of
species interactions determines forecast skill in ecological communities}



\author[1]{Uriah Daugaard}%
\author[2]{Stephan Munch}%
\author[1]{David Inauen}%
\author[1]{Frank Pennekamp}%
\author[1]{Owen Petchey}%
\affil[1]{University of Zurich}%
\affil[2]{University of California Santa Cruz}%


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  \date{May 18, 2024}


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\begin{abstract}
The potential for forecasting the dynamics of ecological systems is
currently unclear, with contrasting opinions regarding its feasibility
due to ecological complexity. To investigate forecast skill within and
across system complexity, we monitored a microbial system exposed to
either constant or fluctuating temperatures in a five months long
laboratory experiment. We tested how forecasting of species abundances
depends on number and strength of interactions and on model size (number
of predictors). We also tested how greater system complexity (i.e. the
fluctuating temperatures) impacted these relations. We found that the
more a species interacted, the weaker these interactions were and the
better its abundance was predicted. Forecast skill increased with model
size. Greater system complexity decreased forecast skill for three out
of eight species. These insights into how abundance prediction depends
on the embedding of the species within the system and on overall system
complexity could improve species forecasting and monitoring.%
\end{abstract}%



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