Higher-Order Interactions and Indirect Effects: A Resolution Using Laboratory Drosophila Communities

Worthen, Wade B.; Moore, Jennifer L.

doi:10.1086/285271

Cited by 49 publications

(44 citation statements)

References 29 publications

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“…

\frac{d S_{2}}{d t} = r_{20} S_{2} + \frac{r_{S_{2} C} S_{1}}{ς + ω S_{1} + ψ S_{2}} S_{2}

) embodying both the saturable form and the alternative form can serve as a general-purpose model at least for pairwise interactions via a single mediator. In fact, even the effects of indirect interactions may be quantified and included in the model by incorporating higher-order interaction terms (Case and Bender, 1981; Worthen and Moore, 1991), although with many challenges (Wootton, 2002). In the end, although these strategies may lead to a sufficiently accurate phenomenological model especially within the training window, they may fail to predict future dynamics.…”

Section: Discussionmentioning

confidence: 99%

Lotka-Volterra pairwise modeling fails to capture diverse pairwise microbial interactions

Momeni

Xie

Shou

2017

eLife

236

262

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Pairwise models are commonly used to describe many-species communities. In these models, an individual receives additive fitness effects from pairwise interactions with each species in the community ('additivity assumption'). All pairwise interactions are typically represented by a single equation where parameters reflect signs and strengths of fitness effects ('universality assumption'). Here, we show that a single equation fails to qualitatively capture diverse pairwise microbial interactions. We build mechanistic reference models for two microbial species engaging in commonly-found chemical-mediated interactions, and attempt to derive pairwise models. Different equations are appropriate depending on whether a mediator is consumable or reusable, whether an interaction is mediated by one or more mediators, and sometimes even on quantitative details of the community (e.g. relative fitness of the two species, initial conditions). Our results, combined with potential violation of the additivity assumption in many-species communities, suggest that pairwise modeling will often fail to predict microbial dynamics.DOI: http://dx.doi.org/10.7554/eLife.25051.001

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“…

\frac{d S_{2}}{d t} = r_{20} S_{2} + \frac{r_{S_{2} C} S_{1}}{ς + ω S_{1} + ψ S_{2}} S_{2}

Section: Discussionmentioning

confidence: 99%

Lotka-Volterra pairwise modeling fails to capture diverse pairwise microbial interactions

Momeni

Xie

Shou

2017

eLife

236

262

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“…The approach also ignores possible indirect eects. Given that competition among these insects is probably largely exploitative, we ®nd it dicult to envisage strong indirect eects, but see Worthen & Moore (1991). How the superspecies approach is aected precisely by these assumptions remains to be investigated theoretically and empirically.…”

Section: The Superspecies Approachmentioning

confidence: 99%

Species diversity in a mycophagous insect community: the case of spatial aggregation vs. resource partitioning

Wertheim

Sevenster

Eijs

et al. 2000

Journal of Animal Ecology

102

105

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Summary1. Previous work has suggested that species diversity in resource-limited insect communities on patchy resources is maintained by spatial aggregation, not by resource partitioning. The most comprehensive test of this claim to date was by Shorrocks & Sevenster (1995), but some of their datasets included only a few resource types, which reduces the likelihood of ®nding a strong eect of resource partitioning. Also, methods of analysis have since been re®ned, e.g. to account for patch size. 2. We collected 733 mushroom samples belonging to 66 taxa in a Dutch woodland area. From these mushrooms, 38,891 insects were reared, belonging to 60 taxa of Diptera and Hymenoptera. Drosophilid species and their parasitoids were identi®ed to the species level; other taxa to the family level. We argue that the community is resource limited. 3. Generally, the insects have fairly narrow diets, including only a few of the available mushroom species. The degree of niche overlap varies widely in this community. 4. Within single resource types, co-existence can be explained by intra-speci®c aggregation over patches alone, in accordance with previous studies. 5. This conclusion remains unchanged for the mycophagous community as a whole: intra-speci®c aggregation of competitors is a sucient and necessary mechanism for co-existence in this diverse community, while resource partitioning does not contribute detectably to species diversity. This is the ®rst time that this pattern has been demonstrated in a dataset involving such a large number of resource types. 6. Our conclusions are strongly supported by data manipulations in which we removed or intensi®ed the eect of resource partitioning and spatial aggregation. 7. We argue that this community may be close to saturation, but we emphasize that saturation is a gradual phenomenon in patchy systems. 8. Since dierential use of resource types does not reduce competitive interactions among the insects, it seems unlikely that inter-speci®c competition constitutes the selective pressure favouring specialization.

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“…However, simply documenting the presence of trait-mediated interactions is no longer the challenge; the existence of trait-mediated interactions is now rarely debated. The challenge is to determine how different environments change an individual's traits, how altered traits change individual performance, and how changes in individual performance translate into changes in interspecific interactions (Worthen and Moore 1991;Wootton 1992;Schmitz 1998;Peacor and Werner 2000).…”

Section: Introductionmentioning

confidence: 99%

Predicting community outcomes from pairwise interactions: integrating density- and trait-mediated effects

Relyea

Yurewicz

2002

Oecologia

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Understanding how species interactions shape the structure of ecological communities based on pairwise comparisons has been a difficult undertaking for ecologists because effects in reassembled communities can be different than simple density-mediated interactions would suggest. Part of this complexity occurs because many species change their behavior and morphology with different predators and competitors and, thus, change their per-capita interaction rates (i.e. trait-mediated interactions). Our objective was to use a simple experimental community of two predators (larval dragonflies, Anax longipes, and larval salamanders, Ambystoma tigrinum), two prey (larval green frogs, Rana clamitans, and larval bullfrogs, R. catesbeiana), and a shared prey resource to determine whether we can predict interactions in a reassembled community by combining our knowledge of density- and trait-mediated interactions,. We combined pairwise laboratory experiments on predation rates and predator-induced behaviors with a mesocosm experiment to examine density- and trait-mediated effects. We used a factorial combination of no predators, caged Anax (to induce anti-predator traits without changing prey density), and lethal Anax crossed with no predators, caged Ambystoma, and lethal Ambystoma. The species interactions in the reassembled community were qualitatively predictable based on the pairwise experiments. Lethal Anax preyed upon Ambystoma and green frogs while lethal Ambystoma only preyed upon green frogs. Anax also reduced the activity of the green frogs; this caused a decrease in salamander predation on green frogs, a decrease in green frog acquisition of resources, and an increase in bullfrog acquisition of resources. Ambystoma had no effect on green frog activity, no effect on resource acquisition by green frogs, and no effect on resource acquisition by bullfrogs. These results suggest that we can better understand how species interact in natural communities if we have a more detailed understanding of trait-mediated mechanisms. However, if predicting the structure of large communities requires identifying how each species alters its traits in the presence of all other species along with altering density, improving our predictive ability may be a prohibitively large undertaking.

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Higher-Order Interactions and Indirect Effects: A Resolution Using Laboratory Drosophila Communities

Cited by 49 publications

References 29 publications

Lotka-Volterra pairwise modeling fails to capture diverse pairwise microbial interactions

Lotka-Volterra pairwise modeling fails to capture diverse pairwise microbial interactions

Species diversity in a mycophagous insect community: the case of spatial aggregation vs. resource partitioning

Predicting community outcomes from pairwise interactions: integrating density- and trait-mediated effects

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