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Dynamic Macroecology

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The dynamic macroecology group studies different aspects of ecology on large spatial and temporal scales, from the Pleistocene to the Anthropocene, related to the question

“How do species and their traits change in space and time, particularly with global change?”

We explore

the current and past distributions of species or functional groups and their traits and niches

the effect of climate and other factors on biodiversity
the spatio-temporal dynamics of plant (particularly tree) species and their ranges interacting with the environment, ecophysiology, population dynamics, species migration and climate and land-use change

the evolution in time and geographical space of species niches and traits and biological communities and assemblages

Main methods we develop and work with

climate (change) data scaling and provision

dynamic ecological models
model scaling
statistical methods in ecology, e.g., species distribution models, phylogenetic comparative methods, trait analyses

FURTHER INFORMATION

Projects

ClimEx

Climatic extremes such as droughts, heat waves, and late frost events, are predicted to increase with ongoing climate change and are therefore of primary concern for environmental research. We will develop such data on extreme climatic events on a global scale from 1950-2100.

FutureWeb

FutureWeb will integrate predictive biogeography, geography, biostatistics and trophic web ecology to derive an ensemble of scenarios of the impact of global change on multi-trophic vertebrate biodiversity, ecosystem functioning and the provision of ecosystem services in Europe.

Simulating dynamics and spread of vegetation and interacting species

The spatio-temporal DGVM LPJ-GM is extended with modules for dynamics and spread of interacting species and tested in case studies with different interactors

FORClimateS

The project aims to aggregate and synthesize existing information on different spatial and temporal scales to provide decision-makers with relevant and robust information on short- and long-term risks for forests and forest functions and on adaptation strategies under different climate futures

Ecology of Interactions

Hummingbird-plant interactions across elevation gradients in Central and South America

Joint models in biodiversity modeling

This project aims to evaluate advantages and potential pitfalls of JSDMs in biodiversity modeling

Automatisierte Erfassung invasiver Neophyten an Autobahnen

Autobahnen sind bedeutende Ausbreitungskorridore für invasive Arten. Im Projekt wird eine bildgestützte, automatisierte Erfassung invasiver Neophyten an Autobahnen im Schweizer Mittelland entwickelt und angewendet. Dabei kommen neue Ansätze der künstlichen Intelligenz (Deep Learning) zum Einsatz.

Photoperiod and ciracian clocks - effects on adaptation and acclimation

Do evolutionary constraints on photoperiod and circadian clocks hinder adaptation and acclimation of plants to climate change? With this project, we will provide the mechanistic basis and a conceptual framework to understand how climatic and daylight/photoperiod cues jointly affects tree functioning.

Can all agriculture in Europe changed to organic production?

What happens when all agriculture in Europe is changed to organic production? This project investigates how the transition to organic production can be made and at a truly European scale combining 11 universities and 15- multi actors from 9 EU countries and 3 associated countries.

SpeedMind

The SpeedMind project will focuses on floristic data from Switzerland as a pilot system to set up and study the benefits of data-mining and machine learning techniques for facilitating biodiversity assessments.

DEForScen

Current plastic response of plants to climate change may be reflected by tree health. We investigate tree health data collected on ca. 6000 plots across Europe since the 1980s to figure out whether changes and trends in defoliation permit to identify species-specific response to climate change.

Tree species migration in DGVMs

Combining very efficient methods for simulation of seed dispersal and for local vegetation dynamics allows for large scale spatiotemporal vegetation dynamics simulations in DGVMs

Shiny Server

The R package "Shiny" offers a simple web application framework for R. Within this internal project we use a dedicated Shiny server to evaluate the capability of web-based Shiny applications for existing work processes and projects at WSL.

ClimSens - Climate Sensitivity of plants and animals in Switzerland

This project assesses the sensitivity of (mostly) plant and animal species to expected climatic changes.

STACCATO

STACCATO is a BiodivERsA project carried out in collaboration with 10 European Institutions and investigates direct effects of climate and land-use change on biodiversity, as well as indirect effects on ecosystem services.

FORHYCS

A hydrological model is coupled to a forest model to better assess the influence of changing drivers to forests and the hydrological cycle

Forest dynamics in Switzerland - pattern, driving forces and ecological implications

Aim of the project is the reconstruction of forest changes in Switzerland (since 1840) and Canton of Zurich (since 1667) to study forest dynamics and search for transition processes.

FORECOM Forest cover changes in mountainous regions

In the Polish-Swiss joint research project Forecom we will analyze historical forest cover changes and their drivers in the Carpatians and Alps. We will develop scenarios of potential future forest cover changes and assess the impact of past and future changes on key ecosystem services.

Biodiversität und Raumentwicklung

Das Projekt «Biodiversität und Raumentwicklung» untersucht Zusammenhänge zwischen Biodiversität und Raumentwicklung auf Landschaftsebene. Die Resultate sind kartographisch dargestellt und können zur Visualisierung von Szenarien der Landschaftsentwicklung eingesetzt werden.

Revision of the Red List of fern and vascular plants

The accessory study of the revision of the red list of fern and vascular plants aims to evaluate the practicability of using statistical methods as a tool for revisions and quality control of red lists.

The need for high resolution

The goal of this project is to provide current and scenario climate grids of resolutions adequate for ecological studies and applications.

Genetic Variation

Die Klimerwärmung dürfte den Wald auf vielen Standorten unter Stress setzen. Wir untersuchen, ob die genetische Variation der Waldbäume es ihnen erlaubt, sich an den Klimawandel anzupassen. Wir fokussieren dabei auf die drei häufigsten Baumarten in Schweizer Wäldern, die Fichte, die Tanne und die Buche.

Bark Beetle Modeling

The most important forest insect in Europe, i.e. the bark beetle Ips typographus, is likely to become even more important with climate change. In this project, we evaluate the driving factors of recent bark beetle infestations by means of statistical modeling and develop bark beetle population and tree susceptibility models for infestation risk analysis.

Waldausdehnung

Ziel des Projektes ist es, zu verbesserten Grundlagen für die politische Lenkung der Waldflächenzunahme im Schweizer Berggebiet beizutragen.

TreeMig

A spatio-temporal forest modelled has been developed to simulate forest dynamics and species migration under a changing climate.

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Publications

Alsos, I.G.; Lavergne, S.; Merkel, M.K.F.; Boleda, M.; Lammers, Y.; Alberti, A.; Pouchon, C.; Denoeud, F.; Pitelkova, I.; Pușcaș, M.; Roquet, C.; Hurdu, B.; Thuiller, W.; Zimmermann, N.E.; Hollingsworth, P.M.; Coissac, E., 2020: The treasure vault can be opened: large-scale genome skimming works well using herbarium and silica gel dried material. Plants, 9, 4: 432 (18 pp.). doi: 10.3390/plants9040432

Ringelberg, J.J.; Zimmermann, N.E.; Weeks, A.; Lavin, M.; Hughes, C.E., 2020: Biomes as evolutionary arenas: convergence and conservatism in the trans-continental succulent biome. Global Ecology and Biogeography, doi: 10.1111/geb.13089

Karger, D.N.; Wüest, R.O.; König, C.; Cabral, J.S.; Weigelt, P.; Zimmermann, N.E.; Linder, H.P., 2020: Disentangling the drivers of local species richness using probabilistic species pools. Journal of Biogeography, 47, 4: 879-889. doi: 10.1111/jbi.13763

Zurell, D.; Zimmermann, N.E.; Gross, H.; Baltensweiler, A.; Sattler, T.; Wüest, R.O., 2020: Testing species assemblage predictions from stacked and joint species distribution models. Journal of Biogeography, 47, 1: 101-113. doi: 10.1111/jbi.13608

Wüest, R.O.; Zimmermann, N.E.; Zurell, D.; Alexander, J.M.; Fritz, S.A.; Hof, C.; Kreft, H.; Normand, S.; Cabral, J.S.; Szekely, E.; Thuiller, W.; Wikelski, M.; Karger, D.N., 2020: Macroecology in the age of Big Data - where to go from here?. Journal of Biogeography, 47, 1: 1-12. doi: 10.1111/jbi.13633

Csilléry, K.; Ovaskainen, O.; Sperisen, C.; Buchmann, N.; Widmer, A.; Gugerli, F., 2020: Adaptation to local climate in multi-trait space: evidence from silver fir (Abies alba Mill.) populations across a heterogeneous environment. Heredity, 124: 77-92. doi: 10.1038/s41437-019-0240-0

Wohlgemuth, T.; Del Fabbro, C.; Keel, A.; Nobis, M. (eds), 2020: Flora des Kantons Zürich. Zürcherische Botanische Gesellschaft. 1127 p.

Liao, Z.; Zhang, L.; Nobis, M.P.; Wu, X.; Pan, K.; Wang, K.; Dakhil, M.A.; Du, M.; Xiong, Q.; Pandey, B.; Tian, X., 2020: Climate change jointly with migration ability affect future range shifts of dominant fir species in Southwest China. Diversity and Distributions, 26, 3: 352-367. doi: 10.1111/ddi.13018

Speich, M.J.R.; Zappa, M.; Scherstjanoi, M.; Lischke, H., 2020: FORests and HYdrology under Climate Change in Switzerland v1.0: a spatially distributed model combining hydrology and forest dynamics. Geoscientific Model Development, 13, 2: 537-564. doi: 10.5194/gmd-13-537-2020

Salazar-Tortosa, D.; Castro, J.; Saladin, B.; Zimmermann, N.E.; Rubio De Casas, R., 2020: Arid environments select for larger seeds in pines (Pinus spp.). Evolutionary Ecology, 34: 11-26. doi: 10.1007/s10682-019-10016-1

Thuiller, W.; Gravel, D.; Ficetola, G.F.; Lavergne, S.; Münkemüller, T.; Pollock, L.J.; Zimmermann, N.E.; Mazel, F., 2020: Productivity begets less phylogenetic diversity but higher uniqueness than expected. Journal of Biogeography, 47, 1: 44-58. doi: 10.1111/jbi.13630

Granda, E.; Baumgarten, F.; Gessler, A.; Gil-Pelegrin, E.; Peguero-Pina, J.J.; Sancho-Knapik, D.; Zimmerman, N.E.; Resco de Dios, V., 2020: Day length regulates seasonal patterns of stomatal conductance in Quercus species. Plant, Cell and Environment, 43, 1: 28-39. doi: 10.1111/pce.13665

Descombes, P.; Kergunteuil, A.; Glauser, G.; Rasmann, S.; Pellissier, L., 2019: Plant physical and chemical traits associated with herbivory in situ and under a warming treatment. Journal of Ecology, 108, 2: 733-744. doi: 10.1111/1365-2745.13286

Kambach, S.; Lenoir, J.; Decocq, G.; Welk, E.; Seidler, G.; Dullinger, S.; Gégout, J.; Guisan, A.; Pauli, H.; Svenning, J.; Vittoz, P.; Wohlgemuth, T.; Zimmermann, N.E.; Bruelheide, H., 2019: Of niches and distributions: range size increases with niche breadth both globally and regionally but regional estimates poorly relate to global estimates. Ecography, 42, 3: 467-477. doi: 10.1111/ecog.03495

Araújo, M.B.; Anderson, R.P.; Barbosa, A.M.; Beale, C.M.; Dormann, C.F.; Early, R.; Garcia, R.A.; Guisan, A.; Maiorano, L.; Naimi, B.; O’Hara, R.B.; Zimmermann, N.E.; Rahbek, C., 2019: Standards for distribution models in biodiversity assessments. Science Advances, 5, 1: eaat4858 (10 pp.). doi: 10.1126/sciadv.aat4858

Abdi, A.M.; Boke-Olén, N.; Jin, H.; Eklundh, L.; Tagesson, T.; Lehsten, V.; Ardö, J., 2019: First assessment of the plant phenology index (PPI) for estimating gross primary productivity in African semi-arid ecosystems. International Journal of Applied Earth Observation and Geoinformation, 78: 249-260. doi: 10.1016/j.jag.2019.01.018

Taleshi, H.; Jalali, S.G.; Alavi, S.J.; Hosseini, S.M.; Naimi, B.; Zimmermann, N.E., 2019: Climate change impacts on the distribution and diversity of major tree species in the temperate forests of Northern Iran. Regional Environmental Change, 19, 8: 2711-2728. doi: 10.1007/s10113-019-01578-5

Peters, R.L.; Speich, M.; Pappas, C.; Kahmen, A.; Von Arx, G.; Graf Pannatier, E.; Steppe, K.; Treydte, K.; Stritih, A.; Fonti, P., 2019: Contrasting stomatal sensitivity to temperature and soil drought in mature alpine conifers. Plant, Cell and Environment, 42: 1674-1689. doi: 10.1111/pce.13500

Brun, P.; Zimmermann, N.E.; Graham, C.H.; Lavergne, S.; Pellissier, L.; Münkemüller, T.; Thuiller, W., 2019: The productivity-biodiversity relationship varies across diversity dimensions. Nature Communications, 10: 5691 (11 pp.). doi: 10.1038/s41467-019-13678-1

Brun, P.; Thuiller, W.; Chauvier, Y.; Pellissier, L.; Wüest, R.O.; Wang, Z.; Zimmermann, N.E., 2019: Model complexity affects species distribution projections under climate change. Journal of Biogeography, doi: 10.1111/jbi.13734

20 from 440 publications

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Staff

Dynamic macroecology

Dr. Heike Lischke	teamleader, senior scientist
David Böhm	civil service employee
Dr. Philipp Brun	Postdoc
Yohann Chauvier	PhD student
Dr. Katalin Csillery	Postdoc
Patrice Descombes	Postdoc
Dr. Dörte Lehsten	visiting scientist
Prof. Veiko Lehsten	scientific staff member
Yi Liu	PhD student guest
Christoph Mayer	scientific assistant
Christine Moos	visiting scientist
Dr. Michael Nobis	scientific staff member
Prof. Signe Normand	visiting scientist
Blaise Petitpierre	visiting scientist
Prof. Dr. David Roberts	fellow
Dr. Bianca Saladin	PhD student guest
Dr. Dirk Schmatz	scientific staff member
Matthias Speich	visiting scientist
PD Dr. Wilfried Thuiller	visiting scientist
Deborah Zani	PhD student
Dr. Zhen Zhang	visiting scientist
Prof. Dr. Niklaus Zimmermann	senior scientist, member of directors board
Dr. Damaris Zurell	scientific staff member