Sunday, November 15, 2026

Survival in a patchwork landscape: City life leaves subtle genetic traces in Berlin squirrels

Leibniz Institute for Zoo and Wildlife Research (IZW)

image:
Eurasian red squirrel (Sciurus vulgaris) in Berlin (photo by Stephanie Kramer-Schadt/Leibniz-IZW)
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Credit: photo by Stephanie Kramer-Schadt/Leibniz-IZW

Roads, buildings and other infrastructure can restrict the movements of wildlife in cities. As a result, urban wildlife from different areas encounter one another less frequently, potentially resulting in reduced genetic diversity. Scientists from the Leibniz Institute for Zoo and Wildlife Research (Leibniz-IZW) and the Technische Universität Berlin (TUB) investigated whether these effects are also evident in squirrels in Berlin. While genetic differences between the populations studied were generally small, subtle differences between locations were already evident. These suggest that the exchange of genetic variations (alleles) within the city may be limited. However, this does not yet have a significant impact on survival probability. The study has been published in the journal Ecology and Evolution.

Eurasian red squirrels (Sciurus vulgaris) are well adapted to life in cities. They adjust their diurnal activities very flexibly to humans, pets and wildlife in the city, actively avoiding predators such as cats, martens and dogs. They readily make use of human food sources and generally thrive in gardens and parks. Nevertheless, frequent sightings should not obscure the fact that their habitats are small and fragmented, and thus are more reminiscent of a patchwork quilt. A new study by the Leibniz-IZW has now investigated whether this habitat fragmentation is already detectable in the genomes of red squirrels from different locations in Berlin, and whether these differences have an impact on the animals’ probability of survival.

141 squirrels, three locations, two genetic groups

To this end, the team studied squirrels at three locations in Berlin from autumn 2021 to spring 2025: an inner-city cemetery, a large city park and a woodland area on the outskirts of the city. The areas differ significantly in terms of development, infrastructure and human activity. The three sites were specifically selected because, despite generally providing suitable habitats for squirrels, they represent varying degrees of urbanisation and different levels of integration into the urban landscape: ranging from a contiguous woodland area to a city park heavily surrounded by urban infrastructure. A total of 141 squirrels were captured and individually marked. For the genetic analyses, 135 individual genetic profiles were generated. This enabled the scientists to investigate how genetically diverse the populations are and to what extent they differ from one another. In a well-connected urban landscape, it is to be expected that populations are more genetically intermixed and therefore differ less from one another.

“Genetic diversity was high at all three sites. If one considered only the geographical location, one would have expected the populations in the city park and the cemetery – which are just a few kilometres apart – to be genetically similar, whilst the forest population, which is significantly further away, would stand out more,” explains lead author Sinah Drenske from the Leibniz-IZW. However, the genetic analyses revealed a different pattern: Whilst the squirrels from the woodland and the cemetery were predominantly assigned to a single genetic group, the animals from the city park differed more markedly from the other two. “We do not see any highly isolated populations,” says Drenske. “But we are already detecting subtle genetic differences that suggest that squirrels cannot move completely freely through the city.”

Subtle genetic differences, but no clear differences in survival

The team also investigated whether these genetic differences were already having an impact on the animals, using catch-recapture data collected over several years. The estimated probability of survival over a six-month period was similar across the three sites. Although it was slightly lower in the heavily urbanised city park, the statistical uncertainty was too great to conclude that urbanisation had a clear negative effect.

Stephanie Kramer-Schadt from the Leibniz Institute for Zoo and Wildlife Research (IZW) and the Technische Universität Berlin (TUB) explains: “The results show that Berlin’s squirrels exhibit a high level of genetic diversity and that there is currently no evidence of significant inbreeding or advanced isolation. Should connectivity between urban habitats continue to decline in future, this could also lead to a further reduction in genetic exchange.” For squirrels and other species that depend on tree-rich habitats, green spaces and tree-lined corridors could therefore play an important role in maintaining exchange between populations. Wildlife-friendly urban planning should take this into account.

Journal

Ecology and Evolution

DOI

10.1002/ece3.74273

Method of Research

Data/statistical analysis

Subject of Research

Animals

Article Title

Urbanisation Leaves a Genetic Signature but No Detectable Demographic Effects in a Small Mammal Population

Eurasian red squirrel (Sciurus vulgaris) in Berlin

(photo by Stephanie Kramer-Schadt/Leibniz-IZW)

Eurasian red squirrel (Sciurus vulgaris) in Berlin (photo by Stephanie Kramer-Schadt/Leibniz-IZW)

ERC Synergy Grant of €10 million awarded to Hebrew University and international partners to study judges’ role in defending democracy

The Hebrew University of Jerusalem

Prof. Keren Weinshall joins researchers from the University of Copenhagen, Washington University in St. Louis and the University of Oslo in a six-year collaboration examining 48 supreme and constitutional courts.

The Hebrew University of Jerusalem proudly announces that Prof. Keren Weinshall of its Faculty of Law, together with three international research partners, has been selected to receive a European Research Council (ERC) Synergy Grant, one of the Council’s most prestigious and competitive funding awards. With a success rate of approximately 5%, the grant will support an ambitious six-year project with a total budget of approximately €10 million.

The research project, JUSTGOV, is jointly led by Prof. Weinshall; Prof. Urška Šadl of the University of Copenhagen; Prof. Lee Epstein of Washington University in St. Louis; and Prof. Daniel Naurin of the University of Oslo.

JUSTGOV seeks to transform how scholars understand the role of courts in safeguarding democracy. Rather than treating supreme courts as single, unified institutions and assessing their decisions solely by whether they favor or oppose those in power, the project places individual judges at the center of the analysis. It will examine judges as actors operating within complex social, institutional, and political environments.

The international research team will undertake an unprecedented comparative study of 48 supreme and constitutional courts in OECD countries and candidate countries, including Israel. The researchers aim to map how judges act as agents of democracy during periods of democratic stability, under threats to democratic governance, and throughout processes of institutional recovery.

At a time when democracies around the world face mounting institutional challenges, the project will offer a new comparative perspective on the choices judges make and the conditions that shape their capacity to defend democratic institutions.

“Understanding what enables democratic institutions to withstand pressure is a vital challenge for research today,” said Prof. Tamir Sheafer, President of the Hebrew University of Jerusalem. “Prof. Keren Weinshall and her international partners are bringing exceptional expertise to a question that matters deeply across societies: how individual judges help sustain democracy when its institutions are tested. This ERC Synergy Grant recognizes both their scholarly ambition and the power of international collaboration to advance knowledge on questions of shared public importance. We are proud of Prof. Weinshall and the Hebrew University’s role in this important undertaking.”

ERC Synergy Grants support ambitious research projects that bring together leading investigators whose complementary expertise can address complex scientific questions. The award recognizes both the promise of the JUSTGOV collaboration and the Hebrew University’s contribution to internationally significant research on law, courts, and democracy.

New research could lead to faster, trustworthy AI models for climate prediction

MIT scientists developed a training method to generate models that simulate the effects of human activities on climate much more quickly than other approaches.

Massachusetts Institute of Technology

Accurate, up-to-date climate projections are essential for planning decisions that enhance the resilience of power grids, protect public health, maximize agricultural yields, and more.

Now, MIT researchers have developed a technique that streamlines the production of fast, trustworthy, and adaptable artificial intelligence models for climate prediction.

These specialized AI models, known as climate emulators, can rapidly simulate the effects of human activities onto a future climate, predicting impacts on temperatures or sea level, for example.

Because emulators run in a matter of seconds, scientists use them to efficiently test thousands of varied climate scenarios. This provides more reliable estimates and can identify unexpected outcomes of regional interventions.

The MIT researchers developed a training technique that boosts the performance and adaptability of a climate emulator while using only a fraction of the data typically required. This significantly cuts production time for these practical scientific tools.

They show that an emulator trained with a much smaller amount of carefully selected synthetic data accurately predicts outcomes of scenarios it did not see during training, while traditional emulators failed to adapt to new situations.

“Climate emulators are especially well-suited for modeling policy-relevant scenarios. By using our method to generate optimized training data for an emulator, we can speed up the production of much more reliable emulators, so we can better trust their outputs for making policy decisions,” says Christoher Womack PhD ’26, who is now a postdoc at ETH Zurich and lead author of a paper on this technique.

He is joined on the paper by Shahine Bouabid, a postdoc in the MIT Department of Earth, Atmospheric and Planetary Sciences (EAPS); Andrei Sokolov, a research scientist in MIT’s Center for Sustainability Science and Strategy (CS3); Popat Salunke, a postdoc in CS3; Glenn Flierl, a professor of oceanography in EAPS; Sebastian D. Eastham, an associate professor at Imperial College London; and senior author Noelle E. Selin, a professor in the MIT Institute for Data, Systems, and Society (IDSS) and EAPS, and director of CS3. The research appears this week in the Proceedings of the National Academy of Sciences.

Speedier surrogates

Climate scientists typically use earth system models (ESMs) to make long-term projections about how global temperature or precipitation could change in response to varying greenhouse gas emissions.

These enormous, physics-based models capture the major components and interactions of the earth’s climate in extreme detail. While powerful, ESMs can take months to run on a cluster of supercomputers — and that’s only to project one possible future climate scenario.

Selin and her collaborators design climate emulators, which are fast AI surrogate models that mimic the behavior of full-scale ESMs. Emulators help scientists test many scenarios, make more accurate forecasts, and explore specific pollutants and regional effects.

“Climate emulators can run in just a few seconds, so it really expands what we can do in terms of exploring these future climate scenarios,” Womack says.

When scientists design a climate emulator, they often train the AI model using a set of six to eight future scenarios based on realistic future trajectories of emissions. They must run each scenario through a full-scale ESM, making these datasets costly and time-consuming to generate.

The MIT researchers recently found that using realistic future scenarios as training data can lead to underperforming emulators that fail to predict unfamiliar or novel scenarios.

In this work, they developed an algorithm that generates a synthetic dataset of optimized climate scenarios tailored to boost one emulator’s predictive performance.

“Our algorithm might generate some weird scenarios which look nothing like a realistic future, but we don’t care so much if the training scenarios are realistic. We are just trying to make the best possible dataset to train an emulator,” Womack says.

Importantly, rather than needing to run a full ESM six or eight times to generate training data, a user would only need to run that model once.

Tuning the training data

The researchers begin by generating an arbitrary climate scenario using a fast and simple climate model. They test how well their emulator can reproduce the results of that ESM, which gives them a measure of error.

Because of the programming technique they used to build the training pipeline, they can iteratively update the training data to increase the emulator’s predictive skill. For instance, the algorithm could increase CO2 emissions dramatically in the year 2050 or rapidly decrease methane emissions in 2037.

Then the optimization updates the training data until the emulator’s error level reaches a certain threshold.

In the end, rather than resembling realistic scenarios in which emissions follow smooth trajectories, the synthetic data contain rapid variations.

“By introducing these high-frequency wiggles and oscillations, our data enable the emulator to extract a lot more information about the overall system,” Womack explains.

Their training algorithm outputs these emissions scenarios, which they can use to train an emulator that is more accurate and adaptable.

“In the future, we are definitely going to see climates and scenarios we haven’t seen before. If we can simulate these different scenarios more robustly, we can provide more reliable information to the stakeholders who need it,” Selin says.

For instance, an emulator trained with their technique can capture the effects of local pollutant control policies that reduce one pollutant while other emissions continue rising. The traditional emulators they evaluated failed this test.

In the long run, Womack hopes this work improves the usefulness of fast and adaptable climate emulators for policy formulation.

“This is such an important piece of the pipeline when it comes to creating useful tools that speak to stakeholder needs. Because the process of training an emulator can takes months or even years, the emulators we have are usually out-of-date. By cutting down that production time, I think this technique will be a game-changer in terms of getting updated tools into the hands of researchers and practitioners,” Selin adds.

In the future, the researchers want to test their technique using an emissions scenario generated by a full ESM. They also want to apply it to other types of climate models and explore its effectiveness in broader machine learning and computer vision applications.

This research was part of the Bringing Computation to the Climate Challenge (BC3) project and supported by Schmidt Sciences through the MIT Grand Challenges.

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Written by Adam Zewe, MIT News

Paper: "Optimal scenario design for climate emulation"