Coupling ecological network analysis with high-throughput sequencing-based surveys: Lessons from the next-generation biomonitoring project

Dubart, Maxime; Alonso, Pascal; Barroso-Bergadà, Didac; Becker, Norbert; Bethune, Kévin; Bohan, David; Boury, Christophe; Cambon, Marine; Canard, Elsa; Chancerel, Émilie; Chiquet, Julien; David, Patrice; Manincor, Natasha de; Donnet, Sophie; Duputié, Anne; Facon, Benoît; Guichoux, Erwan; Minh, Tâm Le; Ortiz-Martínez, Sebastián A.; Piouceau, Lucie; Preville, A Sacco-Martret de; Plantegenest, Manuel; Poux, Céline; Ravigné, Virginie; Robin, Stéphane; Trillat, Marine; Vacher, Corinne; Vernière, Christian; Massol, François

doi:10.1016/bs.aecr.2021.10.007

Cited by 7 publications

(4 citation statements)

References 170 publications

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“…By combining different primers, soil eDNA can be used to detect species across taxonomic kingdoms from the same soil sample (Zinger et al 2016; Donald et al 2021) and could be used to monitor recovery across a range of organisms for a more holistic measure of restoration success. Indeed, eDNA studies are increasingly being used to capture species interactions and modifications to trophic web structures using machine learning techniques (Cordier et al 2019; Dubart et al 2022).…”

Section: Discussionmentioning

confidence: 99%

Soil environmental DNA metabarcoding can quantify local plant diversity for biomonitoring across varied environments

Duley

Iribar

Bisson

et al. 2022

Restoration Ecology

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Biomonitoring of plant communities is essential when evaluating outcomes of ecological restoration, but morphology‐based inventories can impede consistency across spatial and temporal scales. The Eden Project botanic garden (Cornwall, UK) offers an opportunity to test whether soil environmental DNA (eDNA) reflects plant species richness, community composition, and diversity. Furthermore, it enables the exploration of whether community complexity, environmental conditions, or sampling scale influence the similarity of soil eDNA‐derived results compared with those derived from classic botanical inventories. Survey plots were established encompassing a mixture of high‐ and low‐complexity plant assemblages, under either hot and humid or cool and dry conditions. Botanical inventories were conducted in quadrats up to 7 m around a soil eDNA sample plot. Soil samples were processed by metabarcoding of trnL p6 loop to determine plant eDNA identity and relative abundance. Differences in diversity and community composition were calculated before determining whether (1) inventory scale; (2) plant assembly complexity; (3) ambient conditions; (4) soil chemistry; (5) bulk root biomass and (6) soil respiration influenced the similarity of soil eDNA and botanical inventory methods. Inventory scale significantly determined the dissimilarity in both diversity and composition, with soil respiration, phosphorus, and C:N ratio also accounting for variation across sites. Our results demonstrate that soil eDNA metabarcoding is an effective approach for quantifying relative diversity in plant communities across broad habitat types and could be integrated into restoration monitoring strategies, but that its application requires an appropriate a priori knowledge of survey sites to best tailor soil eDNA survey implementation.

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Section: Discussionmentioning

confidence: 99%

Soil environmental DNA metabarcoding can quantify local plant diversity for biomonitoring across varied environments

Duley

Iribar

Bisson

et al. 2022

Restoration Ecology

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“…Using molecular tools to understand ecological interactions is an established but rapidly evolving area of research (Cuff et al, 2022; Derocles et al, 2018; Dubart et al, 2021). The methods have primarily been described for terrestrial ecosystems (Evans et al, 2016), yet they have been applied in aquatic systems (Compson et al, 2019) and new techniques (e.g.…”

Section: Filling the Gaps In Freshwater Ecological Networkmentioning

confidence: 99%

Expanding network ecology in freshwater ecosystems

Windsor

2023

Journal of Animal Ecology

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Research in freshwater ecosystems has always had a strong focus on ecological interactions. The vast majority of studies, however, have investigated trophic interactions and food webs, overlooking a wider suite of non‐trophic interactions (e.g. facilitation, competition, symbiosis and parasitism) and the ecological networks they form. Without a complete understanding of all potential interactions, ranging from mutualistic through to antagonistic, we may be missing important ecological processes with consequences for ecosystem assembly, structure and function. Ecological networks can be constructed at different scales, from genes to ecosystems, but also local to global, and as such there is significant opportunity to put them to work in freshwater research. To expand beyond food webs, we need to leverage technological and methodological advances and look to recent research in marine and terrestrial systems—which are far more advanced in terms of detecting, measuring and contextualising ecological interactions. Future studies should look to emerging technologies to aid in merging the wide range of ecological interactions in freshwater ecosystems into networks to advance our understanding and ultimately increase the efficacy of conservation, management, restoration and other applications.

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“…Therefore, understanding how species' biomass changes over time is necessary for basic ecological research as well as applied management and conservation. The recent development of sequencing for food webs (Novotny et al in press) and biomonitoring Dubart et al (2021) offers new possibilities to compare model predictions with empirical observations to test ecological mechanisms and their associated parameter values formalised by ATN models. From a modelling perspective, the generation of time series datasets is achieved using theoretical models that implement ordinary differential equations (ODEs) describing the rate of change in species' densities depending on their interactions with the other species in the community (Boit et al, 2012; Hudson & Reuman, 2013; Sauve & Barraquand, 2020; Volterra, 1927).…”

Section: Introductionmentioning

confidence: 99%

ATNr: Allometric Trophic Network models in R

Gauzens,

Brose,

Delmas

et al. 2023

Methods Ecol Evol

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Understanding and predicting how densities of interacting species change over time has been one of the main goals of community ecology, which has become a pressing challenge in the context of global change. We present the R package ATNr, which provides an implementation of different versions of Allometric Trophic Network models that simulate the biomass dynamics of trophically interacting species. Relying on C++ routines, the ATNr proposes an efficient and standardised implementation of the different ATNs models. By proposing a set of built in functions ready to use in a language widely used in the community of ecologists, the ATNr package offers an easy access to ATN models focusing on trophic interactions.

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Coupling ecological network analysis with high-throughput sequencing-based surveys: Lessons from the next-generation biomonitoring project

Cited by 7 publications

References 170 publications

Soil environmental DNA metabarcoding can quantify local plant diversity for biomonitoring across varied environments

Soil environmental DNA metabarcoding can quantify local plant diversity for biomonitoring across varied environments

Expanding network ecology in freshwater ecosystems

ATNr: Allometric Trophic Network models in R

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