Department Aquatic Ecology

Aquatic Ecology

Eawag’s Department of Aquatic Ecology is currently home for eight research groups that cover the broad disciplines of ecology and evolution from the individual to the community and ecosystem level, utilizing a wide range of tools and techniques from microscopes to molecular genetics. Read more

News

Quagga mussel: prognosis for affected lakes

Quagga mussels in Lake Geneva: the biomass per square metre is likely to increase by a factor of nine to 20 over the next 22 years (Photo: Eawag, Linda Haltiner).
November 16, 2023 –

A comparison of three Swiss lakes with the Great Lakes of North America show that the quagga mussel is spreading with a similar dynamic.

A comparison of three Swiss lakes with the Great Lakes of North America show that the quagga mussel is spreading with a similar dynamic.
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Aquascope

Real-time underwater imaging for lake phytoplankton and zooplankton monitoring

Publications

Adde, A., Rey, P. L., Brun, P., Külling, N., Fopp, F., Altermatt, F., … Guisan, A. (2023). N-SDM: a high-performance computing pipeline for Nested Species Distribution Modelling. Ecography, 2023(6), e06540 (11 pp.). doi:10.1111/ecog.06540, Institutional Repository

Predicting contemporary and future species distributions is relevant for science and decision making, yet the development of high-resolution spatial predictions for numerous taxonomic groups and regions is limited by the scalability of available modelling tools. Uniting species distribution modelling (SDM) techniques into one high-performance computing (HPC) pipeline, we developed N-SDM, an SDM platform aimed at delivering reproducible outputs for standard biodiversity assessments. N-SDM was built around a spatially-nested framework, intended at facilitating the combined use of species occurrence data retrieved from multiple sources and at various spatial scales. N-SDM allows combining two models fitted with species and covariate data retrieved from global to regional scales, which is useful for addressing the issue of spatial niche truncation. The set of state-of-the-art SDM features embodied in N-SDM includes a newly devised covariate selection procedure, five modelling algorithms, an algorithm-specific hyperparameter grid search, and the ensemble of small-models approach. N-SDM is designed to be run on HPC environments, allowing the parallel processing of thousands of species at the same time. All the information required for installing and running N-SDM is openly available on the GitHub repository https://github.com/N-SDM/N-SDM.
Adde, A., Rey, P. L., Fopp, F., Petitpierre, B., Schweiger, A. K., Broennimann, O., … Guisan, A. (2023). Too many candidates: embedded covariate selection procedure for species distribution modelling with the covsel R package. Ecological Informatics, 75, 102080 (8 pp.). doi:10.1016/j.ecoinf.2023.102080, Institutional Repository

1. Selecting the best subset of covariates out of a panel of many candidates is a key and highly influential stage of the species distribution modelling process. Yet, there is currently no commonly accepted and widely adopted standard approach by which to perform this selection.
2. We introduce a two-step "embedded" covariate selection procedure aimed at optimizing the predictive ability and parsimony of species distribution models fitted in a context of high-dimensional candidate covariate space. The procedure combines a collinearity-filtering algorithm (Step A) with three model-specific embedded regularization techniques (Step B), including generalized linear model with elastic net regularization, generalized additive model with null-space penalization, and guided regularized random forest.
3. We evaluated the embedded covariate selection procedure through an example application aimed at modelling the habitat suitability of 50 species in Switzerland from a suite of 123 candidate covariates. We demonstrated the ability of the embedded covariate selection procedure to provide significantly more accurate species distribution models as compared to models obtained with alternative procedures. Model performance was independent of the characteristics of the species data, such as the number of occurrence records or their spatial distribution across the study area.
4. We implemented and streamlined our embedded covariate selection procedure in the covsel R package, paving the way for a ready-to-use, automated, covariate selection tool that was missing in the field of species distribution modelling. All the information required for installing and running the covsel R package is openly available on the GitHub repository https://github.com/N-SDM/covsel.
Alexander, J., Spaak, P., Möst, M., Straile, D., & Hetzenauer, H. (2023). Ökosystemforschung am Bodensee. Abschluss des Forschungsprojekts "Seewandel: Leben im Bodensee - gestern, heute und morgen". Aqua & Gas, 103(6), 54-59. , Institutional Repository

Während fünfeinhalb Jahren untersuchten Forschende aus den drei Bodenseeländern den Einfluss und die Wechselwirkung verschiedener Stressfaktoren wie Nährstoffänderungen, invasive Arten und Klimawandel auf das Ökosystem des Sees. Der aktuelle Wandel ist tiefgreifend und mit voraussichtlich weitreichenden Folgen für das komplexe Ökosystemgefüge und die Gewässernutzenden. Am 13. und 14. Juni 2023 schliesst das Projekt mit einem wissenschaftlichen Symposium und einer Informationsveranstaltung für die Praxis ab.

SNSF Starting Grants/Ambizione Fellowships

Information for potential candidates

Eco Seminars

06.12.​2023,
18. - 19.01.​2024,
14.02.​2024,
9.00 am
Eawag Dübendorf
Wirkungskontrolle Revitalisierung – Makrozoobenthos

PEAK-Vertiefungskurs V57/24

Research Projects

A project for the development of a quagga mussel monitoring concept mussel monitoring concept and the support of preventative and protective measures in Switzerland.

Development of a quagga mussel monitoring concept and the support of preventative and protective measures
Functional characterization of isopod-microbe symbiosis

Defensive Actinobacteria in freshwater- and terrestrial Isopods
The architecture of community structure, functional traits and trophic networks across blue-green ecosystems

Architecture of blue-green communities
New tools to monitor changes in ecosystem conditions and to quantify genetic changes of populations in (semi-)natural environments to predict how human mediated environmental change will influence stability and resilience of ecosystems.

Stability and the eco-evolutionary dynamics of ecosystems

More current Research Projects