In response to increasing human pressures on biodiversity, conservation targets have been set to reduce these pressures and halt biodiversity decline. However, consequences of these objectives on common species are rarely studied. We analyse the effect of a range of drivers related to climate, land use and land-use intensity on 265 common bird and 144 common butterfly species from more than 20,000 sites between 2000 and 2021 across 27 European countries. We use land use and land-use intensity scenarios produced previously using the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) Nature Futures Framework and climate change scenarios to project biodiversity drivers in Europe up to 2050. We translate these driver changes into abundance variations for common bird and butterfly species and for multi-species indicators used to monitor common biodiversity status in Europe. The projected trends relatively improve, while still declining for birds, notably farmland species, under the scenarios meeting conservation objectives, with few effects on butterflies. No scenario shows a stop or a reversal in the average decline in abundance of bird and butterfly species. Our results therefore question the common biodiversity future under current conservation policies and highlight the need for other anticipatory frameworks not implicitly based on a growing need for natural resources.

Agricultural landscapes feature marked seasonal changes in the quality and quantity of habitats and floral resources supporting pollinating insects. Seasonal dynamics can affect the structure of plant-pollinator interactions, yet the relative importance of both landscape elements with spatio-temporal dynamics and those elements that are more static in space and time remains largely unknown. Such an understanding is needed to identify resource-mediated modifications of plant-pollinator network structures and their functional and management implications. To understand the spatio-temporal effects of landscape heterogeneity on the structure of plant-pollinator networks, we sampled plant-pollinator (Apiformes-except Apis mellifera; Syrphidae) communities over three seasonal periods in 12 landscapes in central Germany. The landscapes comprised spatial gradients in the proportion of semi-natural habitat cover and edge density. To assess temporal changes, we evaluated the cover of mass-flowering crops in bloom, floral diversity and honey bee density at each plant-pollinator sampling event. Spatio-temporally dynamic characteristics, particularly the cover of mass-flowering crops, were more important than static characteristics in explaining variation in plant-pollinator network structure across the three seasonal periods. The richness of plants and pollinators was generally lower when the proportion of mass-flowering crops was high. Under such conditions, networks were more connected, with greater niche overlap among pollinators, and decreased network specialization (H2 '). Richness was higher in landscapes with high edge density, with an increasing effect on network connectance up to a certain threshold. The proportion of semi-natural habitat cover and floral diversity had differential effects on the richness of plants and pollinators, with strong effects on the dietary niche overlap of the pollinators, potentially indicating a decrease in competition when semi-natural habitat cover and flower diversity are high. Synthesis and application. To better support plant-pollinator communities in agricultural-dominated landscapes, we suggest incentivizing the planting of complementary floral resources and preserving or restoring semi-natural habitat areas. Especially in intensively used agroecosystems, the negative effects of mass-flowering crops can be mitigated by maintaining flower-rich edge habitats and relatively small field sizes, which help support plant and pollinator communities, avoid potential negative effects of exploitative competition, and ensure the sustainability of pollination services via increased functional redundancy.

Aim: Biodiversity is increasingly threatened by human impacts. While abiotic conditions are well known to shape species richness, the role of human activities remains less clear. We examined how abiotic and human factors influence terrestrial and limnic species richness in a densely populated region with a long land-use history. Location: Germany. Time Period: 1900-2023 (varies by taxonomic group). Major Taxa Studied: Mammals, breeding birds, fishes, amphibians, reptiles, butterflies, dragonflies, fungi, vascular plants. Methods: Species richness data were aggregated in 11 & times; 11 km grid cells and related to abiotic (climate, soil) and human drivers (land use, protection status). We applied a two-step approach: (1) Boosted Regression Trees (BRTs) to select relevant predictor variables and (2) Generalised Additive Models (GAMs) to test their effects, accounting for spatial autocorrelation. Results: Land-use and climate were similarly important for species richness (26% vs. 21% in BRTs), while protection status and soil contributed less (8% and 9%). GAMs showed positive effects of temperature across many groups. Among land-use factors, human footprint, urban open spaces and water bodies consistently enhanced richness. Protected areas were positively related to richness, whereas soil variables had mixed effects. Main Conclusions: In Germany, species richness peaks not only in semi-natural, protected areas but also along water bodies and within settlement open spaces. These results suggest that conservation strategies should integrate both traditional protected areas and human-modified habitats that sustain high biodiversity.

Aim To examine how butterfly population trends respond to climate change and urbanisation at a continental scale, and whether responses differ between urban and rural environments. Location 869 sites across 12 European countries, spanning six bioclimatic zones. Time Period 1976-2021. Major Taxa Studied Butterflies (Lepidoptera). Methods We analysed long-term monitoring data from > 8400 populations of 145 species representing a wide range of ecological and life-history traits. Population trends were modelled in relation to climate variables (temperature, precipitation and aridity), urbanisation (built-up surface), and their interactions with urban context (urban vs. rural) and species traits (trophic specialisation, body size, reproductive rate and thermal adaptation). Results Climate warming and aridification were consistently linked to population declines in both rural and urban contexts, while precipitation effects varied by location and species. Urbanisation alone did not predict trends, but the urban-rural context strongly modulated species' responses to warming, indicating potential synergies between climate change and urbanisation. The stronger impact of warming in urban populations likely reflects elevated baseline temperatures and reduced habitat suitability and connectivity in urban landscapes, limiting thermal buffering. Species with colder thermal niches and lower reproductive rates were most vulnerable to warming, as warming exceeds the thermal optima of cold-adapted species and lower reproductive rates limit their capacity to buffer climate-driven population declines. Under aridification, which can reduce host-plant availability, trophic specialists declined more in urban areas, whereas generalists unexpectedly declined more in rural sites, suggesting context-dependent constraints under increasing water limitation. Main Conclusions Our findings highlight the complex interplay between climate change, urban context, and species traits in driving population dynamics. Importantly, our results suggest that urbanisation generally amplifies the negative impact of climate change on insect population trends.

In 2024, the European Union implemented its Nature Restoration Regulation (NRR) to restore degraded ecosystems and to reverse the loss of biodiversity. One of the objectives is to increase biodiversity in agricultural systems. To measure progress towards this goal, Member States need to report two out of three indicators, one of which is the Grassland Butterfly Index (GBI). The GBI represents a composite index which combines the trends of 17 butterfly species, some widespread and some more specialised, considered as typical for grassland habitats across Europe. The aim of the present study was to calculate a first version of the GBI for Germany using data collected within the German butterfly monitoring scheme from 2006 to 2023. For this purpose, two methodological approaches were applied: (1) the approach prescribed by the NRR (EU 2024) and (2) an alternative approach which includes other frequently applied methods to analyse time series from biodiversity monitoring schemes. Depending on the methodological approach, the GBI showed a stable development (approach 1) or a moderate decline (approach 2) over the entire study period. Both approaches, however, showed a significant decline over the last 10 years, which mainly seems to be a result of low butterfly abundances in recent years. A closer examination of the underlying species trends indicated that habitat specialists tended to suffer most from declines. These results largely correspond to patterns found in other regions and at the European scale and suggest that butterflies inhabiting agricultural systems are under threat. However, the reasons for the negative trends require further research. There is also a clear need to improve the representativity and robustness of the indicator at the national scale. Several options for expanding monitoring and widening the data basis are discussed.

Species populations naturally fluctuate, yet long-term trend analysis can reveal patterns of success, decline, or stability under global change pressures. While responses to climate change are well-documented, its synergy with another major global driver, urbanization, remains understudied. Here, we analyzed long-term monitoring data from over 8,400 populations of 145 butterfly species across Europe, representing a high diversity of species traits, to assess population trends in response to climate change and urbanization. We examined how population responses vary between urban and rural contexts, providing insights into the influence of site-specific conditions. Climate warming was associated with population declines, which were more pronounced in urban areas. The effect of precipitation varied between environments: increases in precipitation generally benefited populations in rural areas but had detrimental effects in urban ones. Aridity consistently drove population declines across environments, with slightly stronger effects in urban areas. Species with colder climatic niches declined the most in response to warming, increased aridity, and reduced precipitation, while trophic specialists were particularly vulnerable to aridity and precipitation changes in urban environments. Although increasing urbanization did not explain overall population trends, its effects became evident when considering species traits, with certain traits being more vulnerable to urbanization. Specifically, species with narrow climatic niches declined the most in response to urbanization in rural areas, while those and larger body sizes decline the most in urban environments. Our findings highlight the complex interplay between environmental change, landscape context, and species traits in shaping biodiversity outcomes. Importantly, our results suggest that urbanization generally amplifies the impact of climate change on insect population trends. ### Competing Interest Statement The authors have declared no competing interest.

In response to increasing threats to biodiversity, conservation objectives have been set to halt biodiversity decline by reducing direct anthropogenic drivers. However, the potential effects of these objectives on common species remain rarely studied. We analyse the effect of a range of drivers related to climate, land use and land use intensity, on 265 common bird and 144 common butterfly species from more than 20,000 sites between 2000 and 2021 across 26 European countries. We use land-use and land-use intensity scenarios produced previously using the IPBES Nature Futures Framework, and climate change scenarios in order to project biodiversity drivers in Europe up to 2050. We translate these driver changes into abundance variations for common bird and butterfly species, and for multi-species indicators used to monitor common biodiversity status in Europe. The projected trends relatively improve, while still declining for birds, notably farmland species, under the scenarios meeting conservation objectives, with few effects on butterflies. No scenario shows a stop or a reversal in the average decline in abundance of bird and butterfly species. Our results therefore question the common biodiversity future under current conservation policies and highlight the need for other anticipatory frameworks, not implicitly based on a growing need for natural resources.

Agricultural intensification in grasslands, characterized by increased livestock density, frequent mowing, and landscape homogenization, has driven significant declines in insect populations. Butterflies, key indicators of habitat quality, are sensitive to intensification and often used for monitoring. As they are influenced by the landscape context, understanding the landscapes surrounding monitoring transects is crucial for the evaluation of the status of butterflies and the effectiveness of conservation strategies. Using data from the German Butterfly Monitoring Scheme (DEBMS), we applied a nested clustering approach to group landscapes surrounding survey transects by dominant land cover, land-use intensity, and landscape structure. We then related these landscape contexts to butterfly diversity and community composition. Grassland- and forest-dominated clusters had highest species richness, abundance, number of specialists, and endangered species, while urban clusters had the lowest. Most species occurred independently of dominant land-cover types, highlighting the importance of even small proportions of habitats to support populations. We found no statistically significant differences in butterfly communities within crop- and grassland-dominated clusters when comparing different land-use intensity and landscape structure characteristics. However, data indicated higher richness, abundance, and more endangered species on less intensively managed grasslands. Our findings underscore the value of citizen science monitoring schemes in capturing broad-scale patterns in land use and landscape structure. Although clusters did not strongly differentiate distinct butterfly communities, they suggest that maintaining less intensively managed grasslands and expanding semi-natural habitats in agricultural landscapes can enhance butterfly diversity. We highlight the importance of accounting for landscape contexts when interpreting biodiversity patterns and informing conservation strategies.

Floral nectar sugar composition is assumed to reflect the nutritional demands and foraging behaviour of pollinators, but the relative contributions of evolutionary and abiotic factors to nectar sugar composition remain largely unknown across the angiosperms. We compiled a comprehensive dataset on nectar sugar composition for 414 insect-pollinated plant species across central Europe, along with phylogeny, paleoclimate, flower morphology, and pollinator dietary demands, to disentangle their relative effects. We found that phylogeny was strongly related with nectar sucrose content, which increased with the phylogenetic age of plant families, but even more strongly with historic global surface temperature. Nectar sugar composition was also defined by floral morphology, though it was not related to our functional measure of pollinator dietary demands. However, specialist pollinators of current plant-pollinator networks predominantly visited plant species with sucrose-rich nectar. Our results suggest that both physiological mechanisms related to plant water balance and evolutionary effects related to paleoclimatic changes have shaped floral nectar sugar composition during the radiation and specialisation of plants and pollinators. As a consequence, the high velocity of current climate change may affect plant-pollinator interaction networks due to a conflicting combination of immediate physiological responses and phylogenetic conservatism.

Halting and reversing the ongoing insect decline requires in-depth knowledge on key drivers. Due to their sensitivity to habitat quality, butterflies are valuable indicators for grassland management intensity, including mowing. However, most studies examining mowing regime impacts on butterflies are limited to small spatial extents. Here, we tested the potential of citizen science butterfly monitoring data for assessing landscape-level effects of mowing regimes (number of mowing events and timing of the first event) and edge density (density of boundaries between different land-cover types) on butterfly richness, abundance, and community composition. We used generalised linear mixed-effects models to relate nationwide data from the German Butterfly Monitoring Scheme (DEBMS) to high-resolution satellite imagery on mowing events in permanent grasslands (grasslands excluded from crop rotation). As butterfly transects may not consistently be located within grasslands, we ran our models for different thresholds from 0 to 50%, representing increasing shares of the transect route situated within permanent grasslands (10% intervals). We did not find significant associations between mowing regimes and butterflies when focussing on species richness and abundance of all species inhabiting open land. However, we found strong positive associations of delayed mowing with the abundance of grassland specialists with increasing grassland shares per transect. Further, we found negative associations of delayed mowing with the annual number of generations and of more frequent mowing with the abundance of specialists, depending on the share of grassland per transect. Edge density had a positive association with species richness and abundance of species inhabiting open land, as well as abundance of grassland indicator species and grassland specialists in landscapes with a low grassland share per transect. Our findings underscore the importance of low-intensity managed permanent grasslands at the landscape scale for specialised butterflies. Additionally, we highlight the importance of a high density of boundaries for open-land and specialised butterflies, particularly in landscapes with highly fragmented permanent grasslands. To improve future analyses of grassland management impacts, we recommend expanding DEBMS monitoring sites to cover a larger grassland management intensity gradient and to place more transects within grasslands.

1. The importance of genetic diversity has been recognised by the Convention on Biological Diversity but attempts at monitoring or improving the genetic diversity of populations have been minimal. 2. Here, we investigate changes over time in the genetic diversity of a wild insect species, Maniola jurtina (Lepidoptera: Nymphalidae) and present a large-scale investigation into contemporary spatial genetic diversity. 3. Using microsatellite markers, we calculate multiple measures of genetic diversity and divergence for M. jurtina populations over 8 years in the UK and compare these findings with long-term abundance trends. 4. We also conduct a large-scale spatial analysis into the genetic diversity and population structuring of M. jurtina across Europe. 5. All UK populations sampled have high levels of gene flow and genetic diversity, with genetic diversity stable over time. 6. Across Europe, we find some population structuring between populations in the UK and the European mainland, suggesting restricted geneflow between the two regions. 7. The monitoring of a wild species' genetic diversity is an achievable aim, and one that could be carried out for many species, particularly Lepidoptera. Future approaches may aim to develop higher resolution genetic markers and cover a wider range of species. 8. The use of abundance data offers additional insight, and we find that concurrent, dedicated genetic monitoring can provide effective tracking of biodiversity trends.

The goal of this task was to identify and characterise novel methods for biodiversity monitoring, and to assess their suitability for large scale deployment across Europe. To address this goal we combined extensive literature searches with expert consultation, namely using a survey and through an online workshop. The outcome of our searches is summarised in a metadatabase, which includes 282 methods or method components, which have been classified according to EBV classes addressed, target taxa, and broad method type the method relates to. We then consulted experts within the EuropaBON network and beyond, on the advantages and challenges associated with each of these novel methods, as well as their technology readiness level. In combination, our approaches revealed a wealth of novel methods and a highly active research field, with extensive emerging innovation on several fronts. However, it also revealed high variability in technology readiness, with lack of validation being a prevalent hurdle yet to be overcome for many applications of these methods (i.e. for some taxa and in some environments). Moreover, the opportunities for expansion in observations created by these novel approaches open new challenges associated to the standardisation, integration and storage of biodiversity monitoring data. Finally, the expansion of observations should take a designed approach, in order to deliver on its potential to improve representation and resolution of biodiversity monitoring, and should aim to complement rather than replace human observations.

EuropaBON harnesses the power of modelling Essential Biodiversity Variables (EBVs) to integrate different reporting streams, data sources, and monitoring schemes, and measure biodiversity change across multiple dimensions in space and time. Therefore, EBVs are at the core of the project and form the basis for several of the tasks feeding into the co-design of a biodiversity monitoring system for Europe. In this document, we describe the stepwise process of identifying and specifying the EBVs in the EBV list presented in this deliverable. We further provide a summary of the characteristics of the EBVs identified for EuropaBON, in terms of their desired spatial- and temporal resolutions, as well as the taxonomic/ ecosystem scope to be measured.

Extensively managed grasslands are globally recognized for their high biodiversity value. Over the past century, a continuous loss and degradation of grassland habitats has been observed across Europe that is mainly attributable to agricultural intensification and land abandonment. Particularly insects have suffered from the loss of grassland habitats due to land-use change and the decrease in habitat quality, either due to an increase in livestock density, higher mowing frequency, and an increase in nitrogen fertilization, or by abandonment. However, only a few studies have used nationwide datasets to analyse the effects of land cover and land-use intensity on insects. It further remains largely unexplored how these effects are modulated by species traits, i.e. habitat specialisation and mobility. Using nationwide butterfly data originating from the German Butterfly Monitoring Scheme, we investigated the effect of three indicators related to land cover and agricultural land-use intensity on species richness as well as trait composition of butterfly communities. Based on agricultural census data at the municipality scale, we calculated the share of permanent grasslands (measure of habitat availability), the total livestock density (proxy for organic fertilization) and the livestock density of domestic herbivores (proxy for management intensity in grasslands) within a 2 km buffer surrounding each butterfly transect. To analyse the relationships between butterflies and indicators of land cover and land-use intensity, we applied generalised linear mixed effect models. We found a negative relationship between butterfly species richness and the livestock density of domestic herbivores. Further, the ratio of butterfly generalist to specialist species shifted towards generalists and the size of butterflies increased with higher herbivore livestock density, indicating a shift in communities towards mobile habitat generalists. Our results are in accordance with previous studies carried out across smaller geographic extents, highlighting the importance of low herbivore livestock densities to halt the loss of pollinating insects and safeguard biodiversity and associated ecosystem services in agricultural landscapes. We here demonstrate that indicators based on livestock distribution data at the municipality scale can provide insights into processes and spatial diversity patterns of butterflies at the national level. Further, we highlight potentials and limitations of using agricultural census data to quantify and assess effects of land cover and land-use intensity on butterflies, and make recommendations for further research needs.

Observations are key to understand the drivers of biodiversity loss, and the impacts on ecosystem services and ultimately on people. Many EU policies and initiatives demand unbiased, integrated and regularly updated biodiversity and ecosystem service data. However, efforts to monitor biodiversity are spatially and temporally fragmented, taxonomically biased, and lack integration in Europe. EuropaBON aims to bridge this gap by designing an EU-wide framework for monitoring biodiversity and ecosystem services. EuropaBON harnesses the power of modelling essential variables to integrate different reporting streams, data sources, and monitoring schemes. These essential variables provide consistent knowledge about multiple dimensions of biodiversity change across space and time. They can then be analyzed and synthesized to support decision-making at different spatial scales, from the sub-national to the European scale, through the production of indicators and scenarios. To develop essential biodiversity and ecosystem variables workflows that are policy relevant, EuropaBON is built around stakeholder engagement and knowledge exchange (WP2). EuropaBON will work with stakeholders to identify user and policy needs for biodiversity monitoring and investigate the feasibility of setting up a center to coordinate monitoring activities across Europe (WP2). Together with stakeholders, EuropaBON will assess current monitoring efforts to identify gaps, data and workflow bottlenecks, and analyse cost-effectiveness of different schemes (WP3). This will be used to co-design improved monitoring schemes using novel technologies to become more representative temporally, spatially and taxonomically, delivering multiple benefits to users and society (WP4). Finally, EuropaBON will demonstrate in a set of showcases how workflows tailored to the Birds Directive, Habitats Directive, Water Framework Directive, Climate and Restoration Policy, and the Bioeconomy Strategy, can be implemented (WP5).

Citizen science (CS) projects, being popular across many fields of science, have recently also become a popular tool to collect biodiversity data. Although the benefits of such projects for science and policy making are well understood, relatively little is known about the benefits participants get from these projects as well as their personal backgrounds and motivations. Furthermore, very little is known about their expectations. We here examine these aspects, with the citizen science project "German Butterfly Monitoring" as an example. A questionnaire was sent to all participants of the project and the responses to the questionnaire indicated the following: • Most transect walkers do not have a professional background in this field, though they do have a high educational level, and are close to retirement, with a high number of females; • An important motivation to join the project is to preserve the natural environment and to contribute to scientific knowledge; • Participants benefit by enhancing their knowledge about butterflies and especially their ability to identify different species (taxonomic knowledge); • Participants do not have specific expectations regarding the project beyond proper management and coordination, but have an intrinsic sense of working for a greater good. The willingness to join a project is higher if the project contributes to the solution of a problem discussed in the media (here, insect decline). Based on our findings from the analysis of the questionnaire we can derive a set of recommendations for establishing a successful CS project. These include the importance of good communication, e.g., by explaining what the (scientific) purpose of the project is and what problems are to be solved with the help of the data collected in the project. The motivation to join a CS project is mostly intrinsic and CS is a good tool to engage people during difficult times such as the COVID-19 pandemic, giving participants the feeling of doing something useful.

In order to synthesize changes in pollinating insect communities across space and time, it is necessary to understand whether, and how, sampling methods influence assessments of community patterns. We compared how two common sampling methods—yellow combined flight traps and net sampling—influence our understanding of the species richness, abundance and composition of wild bees and hoverflies, and addressed whether these patterns resulted from potentially biased sampling of individuals or species with different types of functional traits. We sampled bee and hoverfly communities in six sites over three seasons in Saxony-Anhalt, Germany. We captured more species and individuals of bees with traps and more species and individuals of hoverflies with net sampling. However, rarefied richness results were less dramatic between the sampling methods for bees and were not different between the sampling methods for hoverflies. Thus, differences in species richness across sampling methods were mostly due to differences in the number of individuals captured in the different methods. We captured more small-sized bees and hoverflies with traps. We tested if the different methods collected individuals and species with different functional traits, such as nesting preferences, sociality and flower specialization for bees and floral preference, migratory status and habitat preference for hoverflies. For most traits, we collected more individuals but not more species with a certain trait in the different methods. This was mainly due to a high abundance of one species being collected in the different methods. These results suggest that the best methodology depends on the aim of the survey, and that the methods cannot be easily combined into synthesis research. Our results have implications for the development of monitoring schemes for pollinators and for synthesis of trends that can identify threats to pollinators and inform research of pollinator conservation strategies.

Trait-based analyses explaining the different responses of species and communities to environmental changes are increasing in frequency. European butterflies are an indicator group that responds rapidly to environmental changes with extensive citizen science contributions to documenting changes of abundance and distribution. Species traits have been used to explain long- and short-term responses to climate, land-use and vegetation changes. Studies are often characterised by limited trait sets being used, with risks that the relative roles of different traits are not fully explored. Butterfly trait information is dispersed amongst various sources and descriptions sometimes differ between sources. We have therefore drawn together multiple information sets to provide a comprehensive trait database covering 542 taxa and 25 traits described by 217 variables and sub-states of the butterflies of Europe and Maghreb (northwest Africa) which should serve for improved trait-based ecological, conservation-related, phylogeographic and evolutionary studies of this group of insects. We provide this data in two forms; the basic data and as processed continuous and multinomial data, to enhance its potential usage.