Abstract
Most of earth’s biodiversity is comprised of interactions among species, yet it is unclear what causes variation in interaction diversity across space and time. We define interaction diversity as the richness and relative abundance of interactions linking species together at scales from localized, measurable webs to entire ecosystems. Large-scale patterns suggest that two basic components of interaction diversity differ substantially and predictably between different ecosystems: overall taxonomic diversity and host specificity of consumers. Understanding how these factors influence interaction diversity, and quantifying the causes and effects of variation in interaction diversity are important goals for community ecology. While previous studies have examined the effects of sampling bias and consumer specialization on determining patterns of ecological networks, these studies were restricted to two trophic levels and did not incorporate realistic variation in species diversity and consumer diet breadth. Here, we developed a food web model to generate tri-trophic ecological networks, and evaluated specific hypotheses about how the diversity of trophic interactions and species diversity are related under different scenarios of species richness, taxonomic abundance, and consumer diet breadth. We investigated the accumulation of species and interactions and found that interactions accumulate more quickly; thus, the accumulation of novel interactions may require less sampling effort than sampling species in order to get reliable estimates of either type of diversity. Mean consumer diet breadth influenced the correlation between species and interaction diversity significantly more than variation in both species richness and taxonomic abundance. However, this effect of diet breadth on interaction diversity is conditional on the number of observed interactions included in the models. The results presented here will help develop realistic predictions of the relationships between consumer diet breadth, interaction diversity, and species diversity within multi-trophic communities, which is critical for the conservation of biodiversity in this period of accelerated global change.
Highlights
The devaluation of natural history and taxonomy has added to the failure of ecologists to document biodiversity and subsequently to understand the magnitude and consequences of the growing extinctions caused by global change [1]
Identifying the effects of consumer specialization on interaction diversity may be difficult given the nonlinear relationship with the sample size or changes in scale. While this model will be useful for developing basic hypotheses concerning the drivers of trophic interaction diversity, there are details in our model that merit further work
A great deal of progress has been made towards understanding species diversity, but we lack even a rudimentary understanding of the determinants and spatial or temporal dynamics of interaction diversity
Summary
The devaluation of natural history and taxonomy has added to the failure of ecologists to document biodiversity and subsequently to understand the magnitude and consequences of the growing extinctions caused by global change [1]. We define interaction diversity as a measure that combines the relative abundance and richness of interactions linking species together into dynamic biotic communities at multiple scales [3,10,11,12,13] For this metric of diversity, the calculation of richness, diversity indices, and rarefaction diversity is based on experimentally established links between interacting individuals rather than species alone, or alternatively, lists of observations of species found in the same area to determine network nodes and edges. Trophic interactions, such as enemy-herbivoreplant interactions, have large effects on all ecosystem attributes and are well studied [3,14,15], tri-trophic webs are suitable systems for examining networks and interaction diversity. We focus on this interaction diversity across multiple trophic levels
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