Francesco Pomati

Last Name

Pomati

First Name

Francesco

ORCID

0000-0002-9746-3735

Organisational unit

01709 - Lehre Umweltsystemwissenschaften

Show all metadata

Search Results

Publications 1 - 10 of 36

A brief guide for the measurement and interpretation of microbial functional diversity
Johnson, David R.; Pomati, Francesco (2020)
Environmental Microbiology
The importance of functional diversity for the functioning and behaviour of microbial communities is clear, yet the widespread incorporation of functional diversity measurements into environmental microbiology study designs remains surprisingly limited. This may, at least to some extent, be a consequence of the unique conceptual and methodological challenges to measuring functional diversity in microbial communities. To facilitate the increased incorporation of functional diversity measurements into environmental microbiology study designs, we review here the process and some key caveats for measuring functional diversity and provide specific examples. We highlight three main decision points and provide guidance to making these decisions based on the underlying mechanisms for how functional diversity relates to an ecosystem process or property of interest. We discuss the selection of an appropriate type of functional trait, selection of the specificity at which functional diversity will be measured, and selection of an appropriate metric for estimating functional diversity from quantitative measures of those traits. We further discuss decisions regarding the use of one- or multi-dimensional measures of functional diversity and how advances in the field of trait-based community ecology could be applied or adapted to address questions in environmental microbiology.
Widespread synchrony in phosphorus concentrations in northern lakes linked to winter temperature and summer precipitation
Isles, Peter D.F.; Creed, Irena F.; Hessen, Dag O.; et al. (2023)
Limnology and Oceanography Letters
In recent years, unexplained declines in lake total phosphorus (TP) concentrations have been observed at northern latitudes (> 42°N latitude) where most of the world's lakes are found. We compiled data from 389 lakes in Fennoscandia and eastern North America to investigate the effects of climate on lake TP concentrations. Synchrony in year-to-year variability is an indicator of climatic influences on lake TP, because other major influences on nutrients (e.g., land use change) are not likely to affect all lakes in the same year. We identified significant synchrony in lake TP both within and among different geographic regions. Using a bootstrapped random forest analysis, we identified winter temperature as the most important factor controlling annual TP, followed by summer precipitation. In Fennoscandia, TP was negatively correlated with the winter East Atlantic Pattern, which is associated with regionally warmer winters. Our results suggest that, in the absence of other overriding factors, lake TP and productivity may decline with continued winter warming in northern lakes.
Quantifying cell densities and biovolumes of phytoplankton communities and functional groups using scanning flow cytometry, machine learning and unsupervised clustering
Thomas, Mridul K.; Fontana, Simone; Reyes, Marta; et al. (2018)
PLoS ONE
Scanning flow cytometry (SFCM) is characterized by the measurement of time-resolved pulses of fluorescence and scattering, enabling the high-throughput quantification of phytoplankton morphology and pigmentation. Quantifying variation at the single cell and colony level improves our ability to understand dynamics in natural communities. Automated high-frequency monitoring of these communities is presently limited by the absence of repeatable, rapid protocols to analyse SFCM datasets, where images of individual particles are not available. Here we demonstrate a repeatable, semi-automated method to (1) rapidly clean SFCM data from a phytoplankton community by removing signals that do not belong to live phytoplankton cells, (2) classify individual cells into trait clusters that correspond to functional groups, and (3) quantify the biovolumes of individual cells, the total biovolume of the whole community and the total biovolumes of the major functional groups. Our method involves the development of training datasets using lab cultures, the use of an unsupervised clustering algorithm to identify trait clusters, and machine learning tools (random forests) to (1) evaluate variable importance, (2) classify data points, and (3) estimate biovolumes of individual cells. We provide example datasets and R code for our analytical approach that can be adapted for analysis of datasets from other flow cytometers or scanning flow cytometers.
Network of Interactions Between Ciliates and Phytoplankton During Spring
Posch, Thomas; Eugster, Bettina; Pomati, Francesco; et al. (2015)
Frontiers in Microbiology
The annually recurrent spring phytoplankton blooms in freshwater lakes initiate pronounced successions of planktonic ciliate species. Although there is considerable knowledge on the taxonomic diversity of these ciliates, their species-specific interactions with other microorganisms are still not well understood. Here we present the succession patterns of 20 morphotypes of ciliates during spring in Lake Zurich, Switzerland, and we relate their abundances to phytoplankton genera, flagellates, heterotrophic bacteria, and abiotic parameters. Interspecific relationships were analyzed by contemporaneous correlations and time-lagged co-occurrence and visualized as association networks. The contemporaneous network pointed to the pivotal role of distinct ciliate species (e.g., Balanion planctonicum, Rimostrombidium humile) as primary consumers of cryptomonads, revealed a clear overclustering of mixotrophic/omnivorous species, and highlighted the role of Halteria/Pelagohalteria as important bacterivores. By contrast, time-lagged statistical approaches (like local similarity analyses, LSA) proved to be inadequate for the evaluation of high-frequency sampling data. LSA led to a conspicuous inflation of significant associations, making it difficult to establish ecologically plausible interactions between ciliates and other microorganisms. Nevertheless, if adequate statistical procedures are selected, association networks can be powerful tools to formulate testable hypotheses about the autecology of only recently described ciliate species.
A global database for metacommunity ecology, integrating species, traits, environment and space
Jeliazkov, Alienor; Mijatovic, Darko; Chantepie, Stéphane; et al. (2020)
Scientific Data
The use of functional information in the form of species traits plays an important role in explaining biodiversity patterns and responses to environmental changes. Although relationships between species composition, their traits, and the environment have been extensively studied on a case-by-case basis, results are variable, and it remains unclear how generalizable these relationships are across ecosystems, taxa and spatial scales. To address this gap, we collated 80 datasets from trait-based studies into a global database for metaCommunity Ecology: Species, Traits, Environment and Space; "CESTES". Each dataset includes four matrices: species community abundances or presences/absences across multiple sites, species trait information, environmental variables and spatial coordinates of the sampling sites. The CESTES database is a live database: it will be maintained and expanded in the future as new datasets become available. By its harmonized structure, and the diversity of ecosystem types, taxonomic groups, and spatial scales it covers, the CESTES database provides an important opportunity for synthetic trait-based research in community ecology.
Phytoplankton and cyanobacteria abundances in mid-21st century lakes depend strongly on future land use and climate projections
Kakouei, Karan; Kraemer, Benjamin M.; Anneville, Orlane; et al. (2021)
Global Change Biology
Land use and climate change are anticipated to affect phytoplankton of lakes worldwide. The effects will depend on the magnitude of projected land use and climate changes and lake sensitivity to these factors. We used random forests fit with long-term (1971-2016) phytoplankton and cyanobacteria abundance time series, climate observations (1971-2016), and upstream catchment land use (global Clumondo models for the year 2000) data from 14 European and 15 North American lakes basins. We projected future phytoplankton and cyanobacteria abundance in the 29 focal lake basins and 1567 lakes across focal regions based on three land use (sustainability, middle of the road, and regional rivalry) and two climate (RCP 2.6 and 8.5) scenarios to mid-21st century. On average, lakes are expected to have higher phytoplankton and cyanobacteria due to increases in both urban land use and temperature, and decreases in forest habitat. However, the relative importance of land use and climate effects varied substantially among regions and lakes. Accounting for land use and climate changes in a combined way based on extensive data allowed us to identify urbanization as the major driver of phytoplankton development in lakes located in urban areas, and climate as major driver in lakes located in remote areas where past and future land use changes were minimal. For approximately one-third of the studied lakes, both drivers were relatively important. The results of this large scale study suggest the best approaches for mitigating the effects of human activity on lake phytoplankton and cyanobacteria will depend strongly on lake sensitivity to long-term change and the magnitude of projected land use and climate changes at a given location. Our quantitative analyses suggest local management measures should focus on retaining nutrients in urban landscapes to prevent nutrient pollution from exacerbating ongoing changes to lake ecosystems from climate change.
Disruption of ecological networks in lakes by climate change and nutrient fluctuations
Merz, Ewa; Saberski, Erik; Gilarranz, Luis J.; et al. (2023)
Nature Climate Change
Climate change interacts with local processes to threaten biodiversity by disrupting the complex network of ecological interactions. While changes in network interactions drastically affect ecosystems, how ecological networks respond to climate change, in particular warming and nutrient supply fluctuations, is largely unknown. Here, using an equation-free modelling approach on monthly plankton community data in ten Swiss lakes, we show that the number and strength of plankton community interactions fluctuate and respond nonlinearly to water temperature and phosphorus. While lakes show system-specific responses, warming generally reduces network interactions, particularly under high phosphate levels. This network reorganization shifts trophic control of food webs, leading to consumers being controlled by resources. Small grazers and cyanobacteria emerge as sensitive indicators of changes in plankton networks. By exposing the outcomes of a complex interplay between environmental drivers, our results provide tools for studying and advancing our understanding of how climate change impacts entire ecological communities.
Underwater dual-magnification imaging for automated lake plankton monitoring
Merz, Ewa; Kozakiewicz, Thea; Reyes, Marta; et al. (2021)
Water Research
The Dual Scripps Plankton Camera (DSPC) is a new approach for automated in-situ monitoring of phyto- and zooplankton communities based on a dual magnification dark-field imaging microscope. Here, we present the DSPC and its associated image processing while evaluating its capabilities in i) detecting and characterizing plankton species of different size and taxonomic categories and ii) measuring their abundance in both laboratory and field applications. In the laboratory, body size and abundance estimates by the DSPC significantly and robustly scaled with measurements derived by microscopy. In the field, a DSPC installed permanently at 3 m depth in Lake Greifensee (Switzerland) delivered images of plankton individuals, colonies, and heterospecific aggregates at hourly timescales without disrupting natural arrangements of interacting organisms, their microenvironment or their behavior. The DSPC was able to track the dynamics of taxa, mostly at the genus level, in the size range between ∼10 μm to ∼ 1 cm, covering many components of the planktonic food web (including parasites and potentially toxic cyanobacteria). Comparing data from the field-deployed DSPC to traditional sampling and microscopy revealed a general overall agreement in estimates of plankton diversity and abundances. The most significant disagreements between traditional methods and the DSPC resided in the measurements of zooplankton community properties. Our data suggest that the DSPC is better equipped to study the dynamics and demography of heterogeneously distributed organisms such as zooplankton, because high temporal resolution and continuous sampling offer more information and less variability in taxa detection and quantification than traditional sampling. Time series collected by the DSPC depicted ecological succession patterns, algal bloom dynamics and diel fluctuations with a temporal frequency and morphological resolution that was never observed by traditional methods. Access to high frequency, reproducible and real-time data of a large spectrum of the planktonic ecosystem expands our understanding of both applied and fundamental plankton ecology. We conclude the DSPC is robust for both research and water quality monitoring and suitable for stable long-term deployments.
Grazing strategies determine the size composition of phytoplankton in eutrophic lakes
To, Sze-Wing; Acevedo-Trejos, Esteban; Chakraborty, Subhendu; et al. (2024)
Limnology and Oceanography
Although the general impacts of zooplankton grazing on phytoplankton communities are clear, we know comparatively less about how specific grazing strategies interact with environmental conditions to shape the size structure of phytoplankton communities. Here, we present a new data-driven, size-based model that describes changes in the size composition of lake phytoplankton under various environmental constraints. The model includes an ecological trade-off emerging from observed allometric relationships between (1) phytoplankton cell size and phytoplankton growth and (2) phytoplankton cell size and zooplankton grazing. In our model, phytoplankton growth is nutrient-dependent and zooplankton grazing varies according to specific grazing strategies, namely, specialists (targeting a narrow range of the size-feeding spectrum) vs. generalists (targeting a wide range of the size-feeding spectrum). Our results indicate that grazing strategies shape the size composition of the phytoplankton community in nutrient-rich conditions, whereas inorganic nutrient concentrations govern phytoplankton biomass. Under oligotrophic regimes, the phytoplankton community is dominated by small cell sizes and the grazers have little to no impact. Under eutrophic regimes, dominating specialist grazers push phytoplankton towards small cells, whereas dominating generalist grazers push phytoplankton towards large cells. Our work highlights that trait-based modeling, based on realistic eco-physiological trade-offs, represents a valuable tool for disentangling the interactive roles played by nutrient regimes and grazing strategies in determining the size compositions of lake phytoplankton. Ultimately, our study offers a quantitative basis for understanding how communities of lake phytoplankton may reorganize in the future in response to changes in nutrient levels and zooplankton grazing strategies.
Potential of lacustrine alkenones as a novel proxy for spring temperatures in mid-latitude European lakes
Schubert, Carsten; Martin, Céline; Richter, Nora; et al. (2022)
EGUsphere
Past temperature records are key tools for inferring climate dynamics and provide empirical data for testing climate models to improve our mechanistic understanding of natural climate variability. Unfortunately, very few quantitative records of pre-historic continental temperatures exist in Europe. Moreover, existing paleothermometers mainly provide mean annual or warm season temperatures, limiting our understanding of climate variability during the transitional seasons and winter. Alkenones are temperature-sensitive lipids produced by Isochrysidales algae, which have been used for decades to reconstruct quantitative changes in sea-surface temperatures. In lakes, they are not ubiquitous, but they have been increasingly reported in both saline and freshwater lakes worldwide, suggesting that there is great potential for alkenone-based paleotemperature reconstructions in lacustrine settings. Lacustrine alkenones have already been successfuly used to reconstruct paleotemperatures in high-latitude lakes. Depending on the timing of ice-out, they record winter/spring or summer temperatures. In our study, we found that a significant number of Swiss lakes contain lacustrine alkenones. Other studies in mid-latitude European lakes suggest that the peak of alkenone production occurs in spring. The monitoring of Lake St Moritz, an alpine lake in the South East of Switzerland, will allow determining the seasonality of alkenone production in mid-latitute high altitude lakes. Combining genetic analyses and the monitoring of physico-chemical parameters will provide more information about the ecology of the alkenone producers. Our first results suggest that we will be able to improve the understanding of alkenone production in freshwater lakes and to develop the first spring lake temperature reconstruction in Switzerland that extends beyond existing historical records.

Publications 1 - 10 of 36

Francesco Pomati

Last Name

First Name

ORCID

Organisational unit

Filters

Search Results