Ecological Network Metrics: Opportunities for Synthesis

Lau, Matthew K.; Borrett, Stuart R.; Baiser, Benjamin; Gotelli, Nicholas J.; Ellison, Aaron M.

doi:10.1101/125781

Cited by 17 publications

(22 citation statements)

References 154 publications

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“…By keeping the ecosystem description structured in patches, it offers the possibility to bring together studies centred on ecosystem cores and research on ecotones, two approaches that have often been treated separately, despite their relation to understand landscapes as dynamic and networked entities [67,68]. Recognising that patches can grade into each other aligns with more recent ecological theories, such as network theory [69] and complexity theory [67], that recognise that exchanges, links and continuity between entities are crucial for the description and functioning of ecosystems. Moreover, several quantitative metrics can be extracted from the shape of the fuzzy clusters, such as the extent and strength of the mixing area (here measured as widths and rate of change).…”

Section: Methods Considerations Suitability and Efficiencymentioning

confidence: 99%

Reducing the arbitrary: fuzzy detection of microbial ecotones and ecosystems – focus on the pelagic environment

Bagnaro

Baltar

Brownstein

et al. 2020

Environmental Microbiome

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Background: One of the central objectives of microbial ecology is to study the distribution of microbial communities and their association with their environments. Biogeographical studies have partitioned the oceans into provinces and regions, but the identification of their boundaries remains challenging, hindering our ability to study transition zones (i.e. ecotones) and microbial ecosystem heterogeneity. Fuzzy clustering is a promising method to do so, as it creates overlapping sets of clusters. The outputs of these analyses thus appear both structured (into clusters) and gradual (due to the overlaps), which aligns with the inherent continuity of the pelagic environment, and solves the issue of defining ecosystem boundaries. Results: We show the suitability of applying fuzzy clustering to address the patchiness of microbial ecosystems, integrating environmental (Sea Surface Temperature, Salinity) and bacterioplankton data (Operational Taxonomic Units (OTUs) based on 16S rRNA gene) collected during six cruises over 1.5 years from the subtropical frontal zone off New Zealand. The technique was able to precisely identify ecological heterogeneity, distinguishing both the patches and the transitions between them. In particular we show that the subtropical front is a distinct, albeit transient, microbial ecosystem. Each water mass harboured a specific microbial community, and the characteristics of their ecotones matched the characteristics of the environmental transitions, highlighting that environmental mixing lead to community mixing. Further explorations into the OTU community compositions revealed that, although only a small proportion of the OTUs explained community variance, their associations with given water mass were consistent through time. Conclusion: We demonstrate recurrent associations between microbial communities and dynamic oceanic features. Fuzzy clusters can be applied to any ecosystem (terrestrial, human, marine, etc) to solve uncertainties regarding the position of microbial ecological boundaries and to refine the relation between the distribution of microorganisms and their environment.

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Section: Methods Considerations Suitability and Efficiencymentioning

confidence: 99%

Reducing the arbitrary: fuzzy detection of microbial ecotones and ecosystems – focus on the pelagic environment

Bagnaro

Baltar

Brownstein

et al. 2020

Environmental Microbiome

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“…, Lau et al. ). We constructed SDNs for the HVMC using Spearman's rank correlation coefficient ( ρ ) computed between pairs of species‐specific species dominance indices D s (Eq.…”

Section: Dominance Network Analysismentioning

confidence: 99%

“…Network analysis is one of the most powerful approaches for dealing with complex, high‐dimensional data because the basic network structure still holds and can be computed when the dimensions of the data far exceed the number of data points (Lau et al. ).…”

Section: Dominance Network Analysismentioning

confidence: 99%

Dominance network analysis provides a new framework for studying the diversity–stability relationship

Ellison

2019

Ecological Monographs

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The diversity–stability relationship is a long‐standing, central focus of community ecology. Two major challenges have impeded studies of the diversity–stability relationship (DSR): the difficulty in obtaining high‐quality longitudinal data sets; and the lack of a general theoretical framework that can encompass the enormous complexity inherent in “diversity,” “stability,” and their many interactions. Metagenomic “Big Data” now provide high quality longitudinal data sets, and the human microbiome project (HMP) offers an unprecedented opportunity to reinvigorate investigations of DSRs. We introduce a new framework for exploring DSRs that has three parts: (1) a cross‐scale measure of dominance with a simple mathematical form that can be applied simultaneously to individual species and entire communities and can be used to construct species dominance networks (SDNs); (2) analysis of SDNs based on special trio motifs, core‐periphery, rich‐club, and nested structures, and high salience skeletons; and (3) a synthesis of coarse‐scale core/periphery/community‐level stability modeling with fine‐scale analysis of SDNs that further reveals the stability properties of the community structures. We apply this new approach to data from the human vaginal microbiome of the HMP, simultaneously illustrating its utility in developing and testing theories of diversity and stability while providing new insights into the underlying ecology and etiology of a human microbiome‐associated disease.

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“…In recent years, network theory has been used increasingly by ecologists to investigate community assembly processes, resilience of communities to perturbations, and the importance of species in ecosystem functioning (Kaiser‐Bunbury & Blüthgen, ; Lau, Borrett, Baiser, Gotelli, & Ellison, ). Ecological networks can be constructed based on the co‐occurrence of species, with species (nodes) being connected via their measure of co‐occurrence (edges) (Lau et al, ). Metrics used to describe ecological networks include modularity at the community level and centrality at the species level (Lau et al, ).…”

Section: Introductionmentioning

confidence: 99%

“…Ecological networks can be constructed based on the co‐occurrence of species, with species (nodes) being connected via their measure of co‐occurrence (edges) (Lau et al, ). Metrics used to describe ecological networks include modularity at the community level and centrality at the species level (Lau et al, ). Modularity is a measure of the extent of compartmentalization of the ecological network, with modules being subsets of highly interacting species that have few interactions with species outside the module (Borthagaray, Arim, & Marquet, ).…”

Section: Introductionmentioning

confidence: 99%

Evolutionary histories impart structure into marine fish heterospecific co‐occurrence networks

Ford

Roberts

2019

Global Ecol Biogeogr

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Aim Understanding the role of interspecific interactions in maintaining diversity, ecosystem function and evolutionary processes is a major challenge in ecology. Historically, antagonistic heterospecific interactions were the focus of many studies, but the importance of facilitative interactions has become increasingly apparent over recent decades. Ecological networks can provide insights into potential interactions among co‐occurring heterospecifics. We compared the structures of temperate and tropical marine fish co‐occurrence networks to estimate their resilience and/or robustness to perturbations. Location Western Australia. Time period Present. Major taxa studied Marine fishes. Methods We compared the structure of temperate and tropical marine fish communities through interspecific co‐occurrences using joint species distribution modelling. Network analyses identified modules of co‐occurring species and those which play a strong role in the organization of communities. Results In all study locations, most interspecific co‐occurrences did not differ significantly from random, with positive co‐occurrences being more prevalent than negative non‐random co‐occurrences. The modularity of networks created from interspecific co‐occurrences tended to decrease poleward, with the opposite for species centrality. An increase in functional diversity among co‐occurring species with latitude was detected. Species centrality was greatest among the temperate endemic species, with a positive association between species centrality and intrinsic vulnerability scores. Main conclusions The differences in community structure between tropical and temperate Western Australian marine fish communities might be attributable, in part, to differing evolutionary histories. The temperate endemic species have co‐evolved in a relatively homogeneous abiotic and biotic environment, whereas the Indo‐Pacific ichthyofauna have evolved in a diverse range of environments. The temperate communities are characterized by: (a) low functional redundancy among co‐occurring species, with endemic species playing keystone roles in community structure; (b) attributes associated with increased vulnerability to perturbations; with (c) many of the species identified as potential keystone species having high intrinsic vulnerability scores and being targeted by fishers.

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Ecological Network Metrics: Opportunities for Synthesis

Cited by 17 publications

References 154 publications

Reducing the arbitrary: fuzzy detection of microbial ecotones and ecosystems – focus on the pelagic environment

Reducing the arbitrary: fuzzy detection of microbial ecotones and ecosystems – focus on the pelagic environment

Dominance network analysis provides a new framework for studying the diversity–stability relationship

Evolutionary histories impart structure into marine fish heterospecific co‐occurrence networks

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