Prof. Dr. Maite Wilke Berenguer

Prof. Wilke Berenguer erforscht mathematische Modelle von Populationen mit Ruhephasen (Dormanz), insbesondere wie Organismen wie Bakterien oder Pflanzen durch Inaktivität Umweltstress überstehen und genetische Vielfalt bewahren. Sie entwickelt stochastische Differentialgleichungen und Koaleszenz-Theorien, um zu verstehen, wie Ruhepopulationen sich evolutionär verhalten und welche Auswirkungen Dormanz auf Selektion, Mutation und Artbildung hat. Die Ergebnisse ermöglichen es, biologische Systeme mit langen Ruhephasen (Saatbanken, mikrobielle Dormanz) mathematisch präzise vorherzusagen und zu analysieren — relevant für Mikrobiologie, Ökologie, Landwirtschaft und Infektionsbiologie, wo Dormanz eine Rolle bei Resistenz und Persistenz spielt.

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• EXC 2046/1:TP EF4-7 The impact of dormancy on the evolutionary, ecological and pathogenic properties

  Quelle ↗

  Förderer: DFG Exzellenzstrategie Cluster Zeitraum: 04/2021 - 03/2023 Projektleitung: Prof. Dr. Maite Wilke Berenguer

• AA3-18 "Evolution Processes for Populations and Economic Agents"

  Quelle ↗

  Förderer: DFG Exzellenzstrategie Cluster Zeitraum: 04/2024 - 12/2025 Projektleitung: Prof. Dr. Maite Wilke Berenguer

• SFB/TRR 388/1: „Ruhende Populationen in heterogenen Zufallsumgebungen” (TP A09)

  Quelle ↗

  Förderer: DFG Sonderforschungsbereich Zeitraum: 10/2024 - 06/2028 Projektleitung: Prof. Dr. Maite Wilke Berenguer

• Principles of seed banks and the emergence of complexity from dormancy

  2021

  Nature Communications · DOI

  Across the tree of life, populations have evolved the capacity to contend with suboptimal conditions by engaging in dormancy, whereby individuals enter a reversible state of reduced metabolic activity. The resulting seed banks are complex, storing information and imparting memory that gives rise to multi-scale structures and networks spanning collections of cells to entire ecosystems. We outline the fundamental attributes and emergent phenomena associated with dormancy and seed banks, with the vision for a unifying and mathematically based framework that can address problems in the life sciences, ranging from global change to cancer biology.

• A new coalescent for seed-bank models

  2016

  The Annals of Applied Probability · DOI

  We identify a new natural coalescent structure, which we call the seed-bank coalescent, that describes the gene genealogy of populations under the influence of a strong seed-bank effect, where “dormant forms” of individuals (such as seeds or spores) may jump a significant number of generations before joining the “active” population. Mathematically, our seed-bank coalescent appears as scaling limit in a Wright–Fisher model with geometric seed-bank age structure if the average time of seed dormancy scales with the order of the total population size $N$. This extends earlier results of Kaj, Krone and Lascoux [J. Appl. Probab. 38 (2011) 285–300] who show that the genealogy of a Wright–Fisher model in the presence of a “weak” seed-bank effect is given by a suitably time-changed Kingman coalescent. The qualitatively new feature of the seed-bank coalescent is that ancestral lineages are independently blocked at a certain rate from taking part in coalescence events, thus strongly altering the predictions of classical coalescent models. In particular, the seed-bank coalescent “does not come down from infinity,” and the time to the most recent common ancestor of a sample of size $n$ grows like $\log\log n$. This is in line with the empirical observation that seed-banks drastically increase genetic variability in a population and indicates how they may serve as a buffer against other evolutionary forces such as genetic drift and selection.