Across the dry grasslands and sandy steppes of Hungary, one of Europe’s most endearing and imperiled rodents has been quietly telling scientists a story about where it thrives and where it vanishes. The European ground squirrel, Spermophilus citellus, a colonial burrower that spends roughly seven months of each year asleep underground, has undergone a troubling decline across much of its range, and it was upgraded from vulnerable to endangered on the IUCN Red List in 2020. Yet despite decades of monitoring, the proximate drivers of its boom-and-bust population fluctuations have remained frustratingly elusive. A new study, drawing on nearly two decades of national monitoring data, now provides the most comprehensive attempt to date to disentangle the abiotic forces shaping the species’ fortunes in the heart of its range, and its central finding is a surprise: geography itself, more than weather, determines whether colonies flourish or collapse.
The research, published in Frontiers in Zoology, was led by Csongor István Gedeon of the HUN-REN Centre for Agricultural Research and the Herman Ottó Institute, together with Olivér Váczi, Felix Knauer, Mátyás Árvai and Franz Suchentrunk. The team exploited the Hungarian Biodiversity Monitoring System, a national program under which state conservation staff have counted ground squirrel burrows every year since 2000. Because the species is listed in Annexes II and IV of the European Union’s Habitats Directive, member states with populations are obliged to monitor it regularly, and Hungary has done so with a standardized protocol: each spring, in the week around April 22, surveyors count active burrow entrances along five 50-meter transect lines, scanning two meters to either side, and convert the tally into counts per hectare. The method is a proxy rather than a census, but because adults are solitary and burrow-dwelling, and because only overwintered breeding animals are active in April, the number of occupied burrows correlates strongly with real population density, offering a cheap, non-destructive and repeatable index of abundance.
The dataset initially covered 64 colonies monitored annually between 2000 and 2018. Rigorous quality control proved essential. The authors scrutinized the records for inconsistencies, errors and missing values, a process prompted partly by the practical difficulties national park staff faced in following the standardized protocol every year at every site. After filtering, 47 colonies and 57 percent of the complete dataset remained for analysis, yielding 415 site-year data entries. This reduced but carefully vetted matrix formed the empirical backbone of the study, and the authors are candid that their conclusions must be read in light of what was excluded.
To characterize climate at each colony, the researchers downloaded gridded daily temperature and precipitation data from the FORESEE database, an open-access meteorological resource covering Central Europe, for the years 1999 through 2018. From the daily records they calculated sixteen location-specific variables, eight for each half of the ground squirrel’s annual cycle: winter data from September to March, corresponding to the hibernation period, and summer data from April to August, corresponding to the active season. Variables included mean monthly temperature between sunrise and sunset and over the full 24 hours, total monthly precipitation, and the mean temperature and total precipitation of the warmest, coldest and wettest months within each period. Because these variables were strongly collinear, the team compressed them with principal component analysis. For the summer set, the first three components explained roughly 80 percent of the variance, while for winter the first three accounted for about 84 percent. Loadings allowed biological interpretation: the leading winter component tracked mean monthly temperature during hibernation, the second captured precipitation in winter, and the third combined the temperature of the warmest and wettest winter months; the summer components similarly distilled summer warmth, summer rainfall and the temperature of the wettest month.
Because the burrow counts exhibited clearly nonlinear patterns across nineteen years and dozens of sites, with irregular sampling gaps, the authors chose generalized additive models with penalized smoothing splines. GAMs are well suited to such ecological data because they let each predictor exert a flexible, data-driven effect on the response without imposing a predefined functional form, while penalization restrains the model’s wiggliness and guards against overfitting. The response variable, the burrow count, was Box-Cox transformed to stabilize variance and normalize residuals after the initial model violated Gaussian assumptions, an adjustment that improved the generalized cross-validation score and the smoothing parameters. The global model included smoothed terms for year, geographic coordinates in Hungary’s EOV system, the six climate principal components and the categorical airfield status, plus a random-effect spline for colony identity to absorb unobserved site-level heterogeneity. Model selection proceeded along two complementary tracks: a traditional sequential procedure identifying a single best model, and an information-theoretic approach in which 512 candidate models were ranked by conditional AICc, with model averaging and sums of weights used to gauge the importance of individual predictors.
The results were striking in their hierarchy of effects. Geographic location dwarfed everything else: the smoothed interaction of the EOV coordinates was highly significant and alone accounted for the overwhelming majority of the final model’s explanatory power, contributing roughly 83 percent of the explained variance, with an adjusted R-squared of about 0.405 in isolation. Year of observation was also significant, capturing a small but steady downward drift in counts over the study period. Airfield status, climate component C2W representing precipitation during hibernation, and colony identity showed near-significant or modest effects. Among the five top-ranked models from the information-theoretic analysis, predictors for airfield status, the temperature of the wettest summer month, geographic location and year appeared in every candidate, with location and year achieving sums of weights of 1.0. The overall adjusted R-squared of the best model was 0.45.
When the spatial smooth was georeferenced onto a contour map of Hungary, a telling pattern emerged. Densities increased in the Kiskunság and Kisalföld meso-regions, areas with sandy or well-structured soils and favorable water management characteristics, and decreased in the northern and southern parts of the country, where the decline zones overlap strikingly with the floodplains of the River Tisza and other flash-flood-prone areas, including the hilly terrain northwest of Lake Balaton. In these low-lying flood regions, inundation of burrows can be lethal: flooding during the active season has been documented to cause hypothermia and mass mortality, with hundreds of ground squirrels perishing after torrential rains near Budapest in 2007 and in Esztergom in 2010, while flooding of hibernation chambers can drown animals outright. The authors note that historical records show southeastern Hungary and the Transtisza region have supported only small ground squirrel populations for centuries despite seemingly suitable habitat, a pattern consistent with the present-day density map.
Paradoxically, the climate signal that emerged was often positive. In the Kiskunság, Hungary’s driest sand region, intensifying aridification, falling groundwater and more frequent droughts associated with the warming Pannonian ecoregion appeared to benefit the species: the Hungarian ranger service has reported population growth and colonization of new areas there in recent years, and citizen-science records from the Vadonleső program showed a statistically significant doubling of ground squirrel observations in Bács-Kiskun County between 2020 and 2025 relative to the previous five years, using the continuously and abundantly recorded Northern white-breasted hedgehog as a sampling-effort reference and a chi-square test of independence to confirm the effect. The finding echoes evidence from prairie dogs and other rodents that drought-driven expansion can accompany warming in some systems, although the authors caution that the mechanisms, possibly involving reduced flood risk and improved burrow conditions in sandy soils, remain hypothetical.
Equally revealing was what the study failed to find. Visual inspection of the colony time series uncovered no evidence of synchronized cycles across the national network, and the authors deliberately refrained from formal cycle testing, noting that rodent populations cycle over three-to-five-year or, in larger species, nine-to-eleven-year periods, and that nineteen years of patchy data may simply be too short and incomplete to detect such rhythms. The absence of synchrony instead points toward local, stochastic, exogenous drivers, soil characteristics, microtopography, habitat management, isolation and predation pressure, acting independently at each colony. The airfield result underscores this: sites managed as grassy airfields consistently supported higher densities than non-airfield habitats, plausibly because their combination of short grass, restricted public access, low disturbance and reduced raptor predation pressure creates refuges of higher and more stable habitat quality than surrounding landscapes where grassland management has declined.
The practical implications are clear and, in the authors’ view, encouraging. Weather and climate factors, though real, were dwarfed by spatial and local effects, and local factors are far more tractable than global climate. Protecting colonies from flooding, maintaining short-grass swards through mowing or grazing, securing ownership-based protection against persecution, and reinforcing populations through translocation can all be pursued at the site level, and indeed a new EU-funded LIFE Nature project, CitellusLife, is applying precisely this locally targeted conservation philosophy. The study also emphasizes that location-specific factors can override macroecological processes, meaning that nationwide strategies alone will not suffice; each colony’s decline may have its own fingerprint. The authors acknowledge limitations, from the reduced dataset and possible autocorrelation to unmodeled soil variables and climate interactions, and call for longer, continuous series on individual colonies. But the broad message is one of cautious hope: for an endangered hibernator on Europe’s steppe edge, the future may depend less on the weather than on what people do with the ground beneath it.
Subject of Research: Abiotic and spatial drivers of population fluctuations in the endangered European ground squirrel (Spermophilus citellus) in Hungary
Subject of Research: Biology
Article Title: What drives population fluctuations of European ground squirrels in Hungary?
Article References: Gedeon, C. I., Váczi, O., Knauer, F., Árvai, M., & Suchentrunk, F. (2026). What drives population fluctuations of European ground squirrels in Hungary?. Frontiers in Zoology, 23(1), Article 17. https://doi.org/10.1186/s12983-026-00608-3
Image Credits: AI Generated
DOI: 10.1186/s12983-026-00608-3
Keywords: European ground squirrel, Spermophilus citellus, population density, generalized additive models, burrow counts, hibernation, precipitation, flooding, aridification, Hungary, geographic location, climate change
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Margaret Porter. (September 11, 2026). Hungarian study reveals what drives European ground squirrel population swings. Scienmag. https://scienmag.com/hungarian-study-reveals-what-drives-european-ground-squirrel-population-swings/
Margaret Porter. “Hungarian study reveals what drives European ground squirrel population swings.” Scienmag, 11 September 2026, https://scienmag.com/hungarian-study-reveals-what-drives-european-ground-squirrel-population-swings/. Accessed 11 September 2026.
Margaret Porter. “Hungarian study reveals what drives European ground squirrel population swings.” Scienmag. September 11, 2026. https://scienmag.com/hungarian-study-reveals-what-drives-european-ground-squirrel-population-swings/
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Tags: abiotic environmental factors in species fluctuationsconservation challenges for European ground squirrelsdrivers of ground squirrel colony success and declinedrought and weather effects on rodentsecological studies on ground squirrel population dynamicseffects of geography versus weather on species survivalendangered European rodentsendangered rodent species in European grasslandsEuropean ground squirrel population dynamicsEuropean ground squirrel population fluctuationsfactors influencing ground squirrel habitat suitabilityground squirrel conservation strategiesground squirrel ecological studieshabitat and geographic influences on squirrel populationshabitat and geography influencehabitat loss and conservationHungarian biodiversity monitoringHungarian biodiversity monitoring for conservationimpact of abiotic factors on endangered rodentsimpact of dry grasslands and sandy steppesIUCN Red List endangered specieslong-term population monitoringlong-term population monitoring in Hungaryrole of geography in species conservation outcomes
