The dynamics of multi-layer ecological networks

• INT77 • From correlations among multiple trait axes to a structural model of multiplex networks > E. Elisa THÉBAULT
Content : Kayla Sale-Hale (1), Elisa Thébault (2), Fernanda Valdovinos (3)
(1) University of Michigan, USA
(2) iEES Paris, CNRS, France
(3) UC Davis, USA

Previous work on ecological networks has focused on “subnetworks” of a single interaction type, though interconnections between subnetworks are known to affect species’ responses to perturbations with consequences for ecosystem function. A few studies have started to tackle this issue empirically, but models to predict the structure of multiplex networks are still missing.
Species traits have been central for modeling and predicting the structure of subnetworks. For instance, body size predicts food web structure while compatible mouthparts and resource size can accurately predict plant-pollinator and plant-seed-disperser networks. We propose a novel approach to modeling multiplex networks as interlinked subnetworks generated with correlated trait axes. Following previous models, a given interaction depends on the trait “matching” of potential interaction partners, and different sets of traits (hereafter “trait axes”) correspond to different interaction types. Correlations between trait axes set by allometry and evolutionary history then interconnect subnetworks generated from subnetwork models.
Using this model, we assess how correlations between traits affect the structure of multiplex networks. We focus here on particular types of interactions (i.e. plant-herbivore, plant-seed-disperser, plant-pollinator, predator-prey, and parasitoid-host) as these are key to ecosystem function and their corresponding subnetworks are well-known, allowing us to confront theoretical predictions with known patterns. • INT78 • The structure and robustness of tripartite ecological networks > V. Virginia DOMINGUEZ, S. Sonia KEFI
Content : Virginia Domínguez-García (1,2), Sonia Kéfi (1)
(1) ISEM, CNRS, Univ. Montpellier, IRD, EPHE, Montpellier, France
(2) Estación Biológica de Doñana (EBD-CSIC), Sevilla, Spain

Until recently, most ecological network analyses aimed at understanding the effects of species’ declines and extinctions have focused on a single interaction type. In nature, however, diverse interactions co-occur, each of them forming a layer of a ‘multilayer’ network. We gathered 44 tripartite ecological networks from the literature, each composed of two layers of interactions (e.g. herbivory, parasitism, pollination), and investigated their structural features and fragility to species losses. We found that the multi-interaction approach is crucial to know the interdependence between interaction layers, to better gauge the robustness of the community to plant loss, and to correctly determine the importance of the plants at the whole community level. • INT79 • From regional to local scale: biotic interactions shape multilayer food-webs > E. Emilio BERTI, U. Ulrich BROSE, B. Benoit GAUZENS, M. Myriam HIRT, B. Benjamin ROSENBAUM, R. Remo RYSER, S. Stefan SCHEU
Content : Barbara Bauer*,1,2,3, Emilio Berti*,1,2, Remo Ryser*,1,2, Benoit Gauzens1,2, Myriam R. Hirt1,2 , Benjamin Rosenbaum1,2 , Christoph Digel4, David Ott5,6, Stefan Scheu7,8, Ulrich Brose 1,2

1Institute of Ecology, Friedrich Schiller University Jena, Jena, Germany
2German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena- Leipzig, Leipzig, Germany
3Zoological Institute and Museum & Institute for Botany and Landscape Ecology, University of Greifswald, Greifswald, Germany
4Umweltbundesamt, Dessau- Roßlau, Germany
5Institute of Landscape Ecology, University of Münster, Münster, Germany
6Centre for Biodiversity Monitoring, Zoological Research Museum Alexander Koenig, Bonn, Germany
7JFB Institute of Zoology and Anthropology, University of Göttingen, Göttingen, Germany
8Centre of Biodiversity and Sustainable Land Use, University of Göttingen, Göttingen, Germany

* authors shared first authorship

Despite intensive research on species dissimilarity patterns across communities (i.e. β-diversity), we still know little about their implications for variation in food-web structures. Here, we analyzed meta-food web data from 50 lake and 48 forest soil communities and combined this with a food web assembly model to investigate how abiotic and biotic factors influence food web properties of interconnected local patches. In particular, we assessed: the effects of spatial and environmental gradients on species composition of local patches; how such gradients, together with species dissimilarity, influenced food web properties; and which biotic filtering process could best explain observed biodiversity patterns.
We found that species dissimilarity depends on environmental and spatial gradients: local patches have more dissimilar species composition the more dissimilar their environment and the more distant they are located. This suggests that species in local patches are filtered by the environment, but also that the patches are spatially interconnected and influenced by their neighbors. We found, however, that the effects of environmental and spatial gradients are only weakly propagated to the networks. In particular, our results show that network dissimilarity is mostly explained by species dissimilarity, but not by a direct effect of spatial distance.
Moreover, our results show that species and food-web dissimilarities are consistently correlated, but that much of the variation in food-web structure across spatial, environmental, and species gradients remains unexplained. Using the novel food-web assembly models, we found that assembly of the local communities was influenced by biotic filtering processes, namely by availability of resources and limiting similarity in species’ interactions to avoid strong niche overlap and thus competitive exclusion. This reveals a strong signature of biotic filtering processes during local community assembly, which constrains the variability in structural food-web patterns across local communities despite substantial turnover in species composition. • INT80 • Self-organised pattern formation increases functional diversity in metacommunities > C. Christian GUILL, L. Louica PHILIPP
Content : Christian Guill1,*, Janne Hülsemann1, Louica Philipp1, Toni Klauschies1
* guill@uni-potsdam.de
1 Institute of Biochemistry and Biology, University of Potsdam

Ecological communities are naturally distributed in space, leading to the formation of so-called metacommunities in which regional (dispersal) dynamics interact with local (trophic) dynamics. We studied a general ecosystem model where a diverse community of autotroph species consumes an abiotic nutrient and is exploited by a herbivore. The functional diversity of the autotrophs is modelled as the variance of a continuous distribution of a trait that affects both growth of the autotrophs and defence against the herbivore. A network of habitat patches, each hosting such a food web, is interconnected via dispersal, thereby forming a metacommunity on the regional scale. When the spatial dimension is neglected, diversity is always lost over time due to stabilising selection. In contrast, in a metacommunity context, dispersal of the species and diffusion of the abiotic nutrients can destabilise the local communities, which leads to self-organised emergence of complex spatio-temporal patterns in the species’ abundances and the nutrient concentrations. The associated spatial and temporal variation in resource availability and consumption pressure creates biomass-trait feedbacks that enhance the mean local functional diversity of the autotrophs by up to a factor of ten compared to scenarios without self-organised pattern formation. This establishes a novel mechanism for supporting (functional) diversity, which helps to maintain the ability of communities to adapt to potential future changes in biotic or abiotic environmental conditions. • INT81 • Plasmidome multilayer networks reveal potential pathways of gene transmission across microbiomes > S. Shai PILOSOF
Content : Julie Teresa Shapiro1, Alvah Zorea1, Aya Brown Kav1, Itzik Mizrahi1, Shai Pilosof1

1Ben-Gurion University of the Negev, Israel

Plasmids are major agents of microbial evolution, horizontally spreading genes within and between microbes. A hallmark example is genes of antimicrobial resistance - a major threat to public health, many of which are transmitted to humans from cattle. The cow rumen microbiome hosts a diverse community of plasmids (plasmidome). One way to identify potential pathways of gene transmission, inspired by disease ecology, is using plasmidome sequence similarity networks. However, studies of plasmid sequence similarity networks have only used published sequences of plasmids from disparate systems, rendering this approach irrelevant. To investigate potential transmission between cow hosts and genetic exchange between plasmids, we constructed a multilayer network based on pairwise genetic similarity composed of 1344 plasmids (nodes) from 21 cow plasmidomes originating in a single population of dairy cows (layers). The network was dominated by interlayer connectivity, suggesting that gene exchange is more likely between plasmids from different cows than within a cow. By analyzing network modularity compared to shuffled networks we further detect non-random major pathways of transmission. Specifically, we find clusters of cows sharing many transmission pathways -- a signature of super-spreading at the cow level. Plasmid functions influenced network structure: plasmids containing mobility genes were more connected. In addition, plasmids with the same AMR genes, though rare in our data set, formed independent modules. Via analysis of link weights we show that gene exchange between plasmids in major transmission pathways is dominated by plasmid dispersal rather than HGT. Finally, using a dynamical gene transmission model we show that network structure affects gene exchange. Overall, our results provide insights into the mechanisms by which genes can spread across animal hosts, shaping microbiome diversity and spreading antibiotic resistance.