Inferring the trophic attributes and consequences of co-occurring lake invaders using an allometric niche model
2022
Vagnon, Chloé | Cattanéo, Franck | Guillard, Jean | Frossard, Victor
Identifying the trophic attributes of co-occurring invaders is a prerequisite to anticipate and mitigate their simultaneous impacts. We used an allometric niche model (aNM) to infer the trophic attributes of a mysid (Hemimysis anomala) and a catfish (Silurus glanis) that recently colonized the largest natural lake in France (Lake Bourget) and we raised the potential consequences of this multispecies invasion on this ecosystem following changes in trophic links in the invaded food web. H. anomala was predicted to mainly rely on primary producers, while S. glanis was expected to experience an ontogenetic change in its trophic attributes (i.e., a diet shift from invertebrate to fish at ~ 90 cm and no more predators at ~ 60 cm). At the whole-lake scale, both invaders would have additive impacts, by competing for resources (diet overlap) with a set of resident species and increasing the trophic vulnerability of fish, invertebrates and primary producers. The trophic link changes caused by the current S. glanis population (i.e., mainly composed of 40–60 cm individuals) and a “future” population (i.e., higher proportion of > 100 cm individuals) suggested an increasing predation pressure on resident fish. In both scenarios, both invaders were also highlighted to be putative prey for resident species, especially H. anomala. The aNM represents a flexible tool for biological invasion management, taking advantage of widely available monitoring data, to identify vulnerable resident species and implement early management actions (e.g. size-based functional controls) when empirical data on invaders are sparse, particularly in the early phases of their colonization.
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