Ariel Bergamini

Questions: Grassland ecosystems are subject to anthropogenic changes in land use and in climatic and further environmental conditions. In Switzerland, land‐use intensification has led to diversity loss and shifts in the composition of plant communities at low elevations, while higher‐elevation grasslands have been less impacted. However, recent studies have pointed to potential land‐use intensification even at higher elevations, in addition to ongoing changes in temperature, precipitation and nitrogen deposition. Here we investigate how vegetation changed at different elevations in the last 20 years and how this related to environmental and land‐use changes. Location: Switzerland's grasslands. Methods: We analysed monitoring data from Swiss grasslands collected on plots on a grid sampling over the whole country over the last 20 years across an elevation range from 212 to 2724 m a.s.l. We assessed the magnitude and drivers of changes in plant species richness and mean ecological indicator values for nutrients, which relate to changes in land use, and we assessed the shift in winners and loser species, that is, species gained and lost per plot. Results: We found contrasting diversity changes across the elevation range in the last 20 years. Contrary to expectations, both species richness and mean nutrient indicator values were relatively stable at intermediate to high elevations. At low elevations, we even observed increasing species richness, which correlated with decreasing mean nutrient indicator values. However, we could not explain the vegetation changes with changes in environmental conditions. Conclusions: These results point to a positive tendency for habitat conservation at lower elevations, which coincides with federal biodiversity‐promoting measures. However, we also found shifts in community composition indicating increasing thermophilisation and drought tolerance of the vegetation. It is therefore crucial to further enhance biodiversity measures in lowland grasslands, and to develop mitigation strategies for the consequences of vegetation changes driven by drought and higher temperatures across all elevations in Switzerland.

Despite the importance of soil for the distribution of forest organisms, the influence of edaphic properties on species range shifts under climate change remains poorly understood at the regional level. Current biodiversity forecasts frequently rely on climate‐only models, potentially overlooking the edaphic dimension of species niches and overestimating migration potential. Climate‐driven species shifts along elevational and latitudinal gradients may be enhanced or hindered by edaphic properties. Here, we focused on predicting the potential range shifts of 2403 temperate forest species across multiple kingdoms and phyla (grouped as Tracheophytes, Bryophytes, Fungi and Lichens) under rcp 4.5 and 8.5 scenarios, integrating high‐resolution digital soil maps. We employed a hierarchical modelling approach, coupling continental‐scale climate models across Europe with high‐resolution regional models in Switzerland to account for the full climate niche of the species using Nested Species Distribution Models (N‐SDM). Our results demonstrate that edaphic properties are among the most important predictors for regional forest species distributions. The inclusion of soil variables consistently reduced suitable habitat across all taxa. This suggests that soil heterogeneity governs species distributions and range shifts across taxonomic and functional groups in line with their edaphic preferences. These differences may, in turn, lead to divergent migration trajectories. Incorporating soil predictors constrained upslope shifts in tracheophytes and fungi, thereby delaying their migration, while facilitating climate tracking in bryophytes and lichens. Despite divergent migration patterns projected under climate warming, incorporating soil predictors consistently resulted in higher predicted habitat loss, except for tracheophytes under rcp8.5, which showed broadly wide responses. In conclusion, omitting high‐quality soil data from biodiversity forecasts leads to overly optimistic range shift predictions. Integrating soil variables is therefore essential for accurate ecological modelling and for prioritising conservation in areas where soil conditions may hinder climate tracking.

Societal Impact Statement: Cities can harbor greater plant diversity than other ecosystems, yet how city sociocultural factors may determine differences in plant composition across equivalent urban green space types remains understudied. Here, we compare plant communities in five main urban greenspace types across three Swiss cities representing the country's French (Geneva), Italian (Lugano), and German (Zurich) cultural regions. We found that over half of the species recorded occurred in only one of the three cities, whereas less than a quarter were shared across all three. Our study supports the idea that cities' sociocultural contexts can leave a strong imprint on their urban plant life, underscoring the need to consider sociocultural diversity alongside ecological and planning factors when managing and promoting urban biodiversity.

To understand the future of forests, we must have a detailed understanding of past changes due to climate and land use change. And woody encroachment can have important consequences for carbon stocks and mountain biodiversity. The abandonment of agricultural activities results in woody encroachment, converting species rich mosaic habitats like dry meadows, bogs, and fens into expanding forested areas. These habitats, which are particularly important for biodiversity conservation in Switzerland, face imminent threats. Woody vegetation encroachment not only alters habitat structure but also can drive declines in vascular plant species due to associated effects, such as increased shading or altered competition. We quantify cover and height of woody plants in Switzerland during a 40-year period. Our data are based on a high-resolution Vegetation Height Model (VHM) with 1 meter resolution for four time steps between 1979 and 2020. Our research addresses this complex relationship by utilizing 40 years of high-resolution vegetation height data (1 meter) across Switzerland. For plant biodiversity data, we use a comprehensive dataset comprising over 4,000 vegetation surveys from the effectiveness of habitat conservation monitoring (WBS) in Switzerland. We find that although the greatest increases of woody shrub encroachment are occurring along the southern Alps in Ticino and Graubünden, it is also occurring in habitats in the central and northern Alps at a slower pace. We see both infilling with trees in already existing semi-open forest landscapes as well as upward tree and shrub migration at and above treeline. We found this has significant consequences on habitats of conservation concern, where plant species diversity decreases even at the initial stages of encroachment. When plots contained tree species even less than 0.5 m tall, plant species richness was 50% lower than in plots without tree species. By analyzing the drivers and consequences of agricultural abandonment, our project aims to offer scientific insights for mitigating the adverse impacts on biodiversity associated with land use changes.

Functional traits of species are becoming increasingly used in ecological research, providing key insights into organisms-environment interactions, ecosystem functions, and responses to environmental changes. In recent years, substantial initiatives have generated major open-access datasets of species' functional traits. However, these resources typically concentrate on a handful of well-studied biological groups—such as plants, birds, and fishes—and less on specific biogeographic regions limiting their applicability in regional biodiversity assessments and conservation planning. Here, we present TraitCH, a comprehensive dataset of functional traits spanning over 71,874 species (≥ 1 functional trait) across 17 major taxonomic groups: Apocrita (2,278), Arachnida (3,728), Coleoptera (8,565), Ephemeroptera/Plecoptera/Trichoptera (1,349), Lepidoptera (3,757), Odonata (234), Orthoptera (1,283), Bryobiotina (2,285), Fungi (12,469), Lichen (2,435), Mollusca (7,493), Pisces (838), Amphibia (151), Aves (1,356), Mammalia (522), Reptilia (298), and Tracheophyta (22,833). Compiled from 43 published and unpublished sources, TraitCH provides a robust representation of total species richness and composition for Switzerland and Europe. For each species, we compiled their taxonomic hierarchy, existing synonymy, geographic origin, conservation status, micro- and macro-habitat types, global range size and available ecological trait values. TraitCH consists of 17 trait tables (one per major taxonomic group), each available in two formats: (1) original and (2) completed versions with missing trait values imputed using a tree-based modelling method. TraitCH was also embedded within a comprehensive checklist of European species from the same groups (~210,000 taxa), encompassing authoritative Swiss and European checklists, with the exception of Fungi and Lichen, for which only Swiss checklists were available. TraitCH is available on Zenodo: https://doi.org/10.5281/zenodo.15063844 (Chauvier et al., 2025).

Aims: We aimed to determine whether observer expertise (unexperienced, intermediate, experienced) affects the detection of overall bryophyte species richness and of different taxonomic bryophyte groups (e.g., mosses, liverworts, Sphagnum spp.) in vegetation surveys. We further tested if observers with different levels of expertise differ in their estimates of the species richness of various bryophyte size classes (small, medium, large), protection classes (threatened and nonthreatened), and cover classes (Braun‐Blanquet scale). Location: Switzerland. Methods: From 2011 to 2023, we surveyed bryophytes in 10‐m ² plots in a long‐term monitoring program. Plots were situated in raised bogs and fens of national importance, which were distributed across Switzerland. The plots were surveyed by 20 professional botanists with a profound knowledge of the Swiss flora and experience in conducting vegetation surveys, but different levels of expertise in bryophyte surveys. Using 2950 relevés, we fitted linear mixed‐effects models to test if species richness estimates differed among categories of observer expertise. Results: On average, experienced observers detected 76% and 82% more liverwort species per relevé than intermediate and unexperienced observers. In accordance with this, experienced observers detected significantly more small‐sized bryophyte species than intermediate and unexperienced observers. However, total species richness and the richness of other taxonomic groups (mosses, Sphagnum spp.) did not differ significantly between expertise levels. This was due to the low relative richness of liverworts and small species compared to the other taxonomic groups and size classes. Conclusions: Our findings demonstrate the importance of ecological and morphological knowledge of bryophytes for bryophyte surveys in monitoring programs. However, as the total species numbers did not differ significantly between observers with different experience levels, it seems that teams composed of differently experienced observers can also collect reliable data. We recommend continuous training to keep observer errors consistently low and to statistically correct for observer differences.

Aims: The accurate classification of habitats is essential for effective biodiversity conservation. The goal of this study was to harness the potential of deep learning to advance habitat identification in Europe. We aimed to develop and evaluate models capable of assigning vegetation‐plot records to the habitats of the European Nature Information System (EUNIS), a widely used reference framework for European habitat types.Location: The framework was designed for use in Europe and adjacent areas (e.g., Anatolia, Caucasus).Methods: We leveraged deep‐learning techniques, such as transformers (i.e., models with attention components able to learn contextual relations between categorical and numerical features) that we trained using spatial k‐fold cross‐validation (CV) on vegetation plots sourced from the European Vegetation Archive (EVA), to show that they have great potential for classifying vegetation‐plot records. We tested different network architectures, feature encodings, hyperparameter tuning and noise addition strategies to identify the optimal model. We used an independent test set from the National Plant Monitoring Scheme (NPMS) to evaluate its performance and compare its results against the traditional expert systems.Results: Exploration of the use of deep learning applied to species composition and plot‐location criteria for habitat classification led to the development of a framework containing a wide range of models. Our selected algorithm, applied to European habitat types, significantly improved habitat classification accuracy, achieving a more than twofold improvement compared to the previous state‐of‐the‐art (SOTA) method on an external data set, clearly outperforming expert systems. The framework is shared and maintained through a GitHub repository.Conclusions: Our results demonstrate the potential benefits of the adoption of deep learning for improving the accuracy of vegetation classification. They highlight the importance of incorporating advanced technologies into habitat monitoring. These algorithms have shown to be better suited for habitat type prediction than expert systems. They push the accuracy score on a database containing hundreds of thousands of standardized presence/absence European surveys to 88.74%, as assessed by expert judgment. Finally, our results showcase that species dominance is a strong marker of ecosystems and that the exact cover abundance of the flora is not required to train neural networks with predictive performances. The framework we developed can be used by researchers and practitioners to accurately classify habitats.

The success of ponds constructed to restore ecological infrastructure for pond‐breeding amphibians and benefit aquatic biodiversity depends on where and how they are built. We studied effects of pond and landscape characteristics, including connectivity, on metapopulation dynamics of 12 amphibian species in Switzerland. To understand the determinants of long‐term occupancy (here summarized as incidence), environmental effects on both colonization and persistence should be considered. We fitted dynamic occupancy models to 20 years of monitoring data on a pond construction program to quantify effects of pond and landscape characteristics and different connectivity metrics on colonization and persistence probabilities in constructed ponds. Connectivity to existing populations explained dynamics better than structural connectivity metrics, and simple metrics (distance to the nearest neighbor population, population density) were useful surrogates for dispersal kernel‐weighted metrics commonly used in metapopulation theory. Population connectivity mediated the persistence of conservation target species in new ponds, suggesting source–sink dynamics in newly established populations. Population density captured this effect well and could be used by practitioners for site selection. Ponds created where there were 2–4 occupied ponds within a radius of ∼0.5 km had >3.5 times higher incidence of target species (median) than isolated ponds. Species had individual preferences regarding pond characteristics, but breeding sites with larger (≥100 m ² ) total water surface area, that temporarily dried, and that were in surroundings with maximally 50% forest benefitted multiple target species. Pond diversity will foster amphibian diversity at the landscape scale.

Aims: We introduce ReSurveyEurope — a new data source of resurveyed vegetation plots in Europe, compiled by a collaborative network of vegetation scientists. We describe the scope of this initiative, provide an overview of currently available data, governance, data contribution rules, and accessibility. In addition, we outline further steps, including potential research questions.Results: ReSurveyEurope includes resurveyed vegetation plots from all habitats. Version 1.0 of ReSurveyEurope contains 283,135 observations (i.e., individual surveys of each plot) from 79,190 plots sampled in 449 independent resurvey projects. Of these, 62,139 (78%) are permanent plots, that is, marked in situ, or located with GPS, which allow for high spatial accuracy in resurvey. The remaining 17,051 (22%) plots are from studies in which plots from the initial survey could not be exactly relocated. Four data sets, which together account for 28,470 (36%) plots, provide only presence/absence information on plant species, while the remaining 50,720 (64%) plots contain abundance information (e.g., percentage cover or cover–abundance classes such as variants of the Braun‐Blanquet scale). The oldest plots were sampled in 1911 in the Swiss Alps, while most plots were sampled between 1950 and 2020.Conclusions: ReSurveyEurope is a new resource to address a wide range of research questions on fine‐scale changes in European vegetation. The initiative is devoted to an inclusive and transparent governance and data usage approach, based on slightly adapted rules of the well‐established European Vegetation Archive (EVA). ReSurveyEurope data are ready for use, and proposals for analyses of the data set can be submitted at any time to the coordinators. Still, further data contributions are highly welcome.