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Gebietseigenes Saatgut für Begrünungen und Renaturierungen in der freien Landschaft wird in Deutschland nach Regeln des Regiosaatgutkonzepts in 22 Ursprungsgebieten (UG) produziert. Das Projekt RegioDiv untersuchte die genetische Diversität von über 30 Pflanzenarten des Grünlands deutschlandweit, um zu überprüfen, wie gut die beobachtete räumliche Verteilung der genetischen Strukturen dem geographischen Zuschnitt der UG entspricht. Jede Art zeigte ein artspezifisches innerartliches räumlich-genetisches Diversitätsmuster, aber fast alle Arten zeigten das Muster von "Isolation-durch-Distanz", also zunehmende genetische Distanz mit zunehmender räumlicher Entfernung. Bei einigen Arten mit mehreren Ploidiestufen, d. h. innerartlichen Taxa mit verschiedenen Anzahlen an Chromosomensätzen, die eigenständige biologische Arten darstellen können, konnten auf Basis ihrer Verbreitungsgebiete spezifische Regeln entwickelt werden. Die Synthese der Verbreitungsmuster der innerartlichen Gruppen über alle Arten hinweg identifizierte Schwächen des aktuellen UG-Systems. Im vorliegenden Beitrag werden wichtige Einzelergebnisse vorgestellt und Empfehlungen für die Praxis gegeben. Unter anderem werden Vorschläge für alternative Zuschnitte der UG, die die genetische Vielfalt besser repräsentieren, vorgestellt. Diese bilden die Grundlage für mögliche Änderungen am UG-System, die in naher Zukunft mit den relevanten Akteuren erarbeitet werden müssen.

In Deutschland ist für die Ausbringung von Pflanzen in der freien Natur nach § 40 BNatschGgebietseigenes Saat- und Pflanzgut zu verwenden. Für die praktische Umsetzung dieser Vor-gabe werden im Regiosaatgutsystem 22 Ursprungsgebiete (UG) unterschieden. Der Zuschnittder UG beruht im Wesentlichen auf naturräumlichen Einteilungen. Dies kann kritisch betrach-tet werden, da keine spezifischen, empirischen Informationen über diejenigen Pflanzenarteneingingen, für welche das System geschaffen wurde. Da die UG generell für alle Arten in glei-cher Weise gelten, muss eine große Zahl an Arten untersucht werden, um die Plausibilität derUG zu prüfen. Das Projekt RegioDiv hatte das Ziel, eine breite empirische Datenbasis der ge-netischen Vielfaltsmuster von Wiesenpflanzen zu erarbeiten, um auf dieser Basis Empfehlun-gen für das Regiosaatgutsystem ableiten zu können.Insgesamt sammelten 160 SammlerInnen an über 2.500 Grünlandflächen Pflanzenproben von28 Arten. Wir charakterisierten den individuellen Genotyp (SNP-Marker, single nucleotide po-lymorphism) von ca. 12.000 Proben. Die Datenanalyse für jede Art umfasste unter anderemHauptkomponenten- und Clusteranalysen. Außerdem analysierten wir den Zusammenhangder genetischen und der geographischen Distanz zwischen UG-Paaren, die jeweils als Popula-tionen interpretiert wurden.

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

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 prev

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).

Butterfly monitoring enjoys a growing popularity in Europe, mainly supported by Butterfly Conservation Europe (BCE) and its partners. While Butterfly Monitoring Schemes are present in a growing number of countries and new ones are being initiated in many places, long time-series are currently only available for a limited number of countries. For the indicators in this report, we used data from 22 countries (Figure 1): Andorra, Austria, Belgium, Czech Republic, Estonia, Finland, France, Germany, Hungary, Ireland, Jersey, Latvia, Lithuania, Luxembourg, Norway, Romania, Slovenia, Spain, Sweden, Switzerland, The Netherlands and the United Kingdom.The indicators use field data up to and including the 2020 field season. The method for calculating indicators has been greatly improved and enhanced. During 2020, more than 2,500 standardised butterfly transects distributed across 22 monitoring schemes were used to inform the EU27 Grassland Butterfly Indicator and almost 5,000 from 25 schemes for the European Grassland Butterfly Indicator (Figure 2). Since 1990 over 6,350 and 11,500 separate transects have contributed to the EU27 and Europe indicators, respectively.

EinführungDie Möglichkeiten der Finanzierung von Biodiversitätsforschung einschließlich entomologischer Forschung sind begrenzt, wenn es um längere Zeiträume und größere Areale geht. Wollte man in Deutschland beispielsweise 50 Expertinnen und Experten beschädigen, um auf 500 standardisierten Strecken, sogenannten Transekten,die Tagfalter über einen Zeitraum von zehn Jahren nach Standard-Methoden zu erfassen, so würde das je nach Berechnungsbasis zwischen 5 und 20 Millionen Euro kosten. Daten zur Entwicklung zum Beispiel der Insekten-Biodiversität auf nationaler Skala liegen daher bislang nur lückenhaft und unsystematisch vor, sollen nun aberfür Deutschland über das nationale Monitoringzentrum in Leipzig gebündelt, standardisiert und einer systematischen Auswertung zugeführt werden.Viele Mitbürger und Naturfreunde – hier und im Folgenden verwenden wir aus Platzgründen teilweise das generische Maskulinum, es sind aber immer beide Geschlechter gemeint – engagieren sich gerne ehrenamtlich. Zudem empfinden sie den Grad der Unwissenheit über den Zustand der Natur als beschämend für Länder wie Deutschland. Folglich haben beispielsweise der Dachverband Deutscher Avifaunisten (DDA) oder das Helmholtz-Zentrum für Umweltforschung (UFZ) in Kooperation mit der Gesellschaft für Schmetterlingsschutz (GfS) schonvor längerer Zeit eigene Wege gewählt, um entsprechende Rahmenbedingungen zum Sammeln von Informationen zur Verbreitung und Häufigkeit von als Indikatoren besonders geeigneten Tiergruppen zu schaffen. Im Vogelmonitoring des DDA und im Tagfalter-Monitoring Deutschland (TMD) von UFZ/GfS sind es vorallem Ehrenamtliche, die die regelmäßigen Beobachtungen vornehmen. Diese leisten einen immensen Beitrag.

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

The Citizen Science-project “Butterfly Monitoring Germany - TMD” is running for 16 years,now. The basis of the TMD are volunteer transect walkers who count butterflies along adefined route. The scheme’s success depends on the number of the participating volunteersand the effort they take by spending their free time collecting butterfly data all over Germany.While the benefits of such projects for science and public and private stakeholders are wellunderstood, relatively little is known about the benefits participants get from these projectsas well as their personal backgrounds and motivations. Furthermore, very little is known abouttheir expectations. In this talk, we present the results of a questionnaire sent out to allparticipants of the TMD in 2019.

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.

There is mounting evidence of widespread declines in the diversity and abundance of insects from across the globe (Sánchez-Bayo and Wyckhuys 2019, Seibold et al. 2019, van Klink et al. 2020, Wagner 2020). This gives a stark warning for the perilous state of biodiversity (Díaz et al. 2019), and demonstrates that addressing the gap in knowledge of the status of insects is vital (Cardoso et al. 2020, Samways et al. 2020). Insects are estimated to comprise more than half of all described species and are a dominant component of biodiversity in most ecosystems (Bar-On et al. 2018). Insects also provide a crucial role in the functioning of ecosystems. They are not only related to the supply of many ecosystem services such as pollination, biological control, soil fertility regulation and diverse cultural ecosystem services but also to disservices such as damage to crops and spread of diseases to livestock and humans (Gutierrez-Arellano and Mulligan 2018, Noriega et al. 2018). There is a pressing need to assess the status of insects to set and evaluate conservation targets. At the Convention on Biological Diversity (CBD) meeting in Nagoya (Japan), the Strategic Plan for Biodiversity 2011–2020 was adopted. It proposed five goals and 20 “Aichi” biodiversity targets. In line with this plan, a new EU biodiversity strategy was adopted by the European Commission in May 2011. This strategy provided a framework for the EU to meet its biodiversity targets and global commitments as a party to the CBD. The Headline Target in the existing EU Biodiversity Strategy 2020 is to halt the loss of biodiversity and the degradation of ecosystem services in the EU by 2020, and restore them, in so far as feasible, while stepping up the EU contribution to averting global biodiversity loss. Under Target 3A the EU is committed to increasing the contribution of agriculture to biodiversity recovery. Further, the EU Biodiversity Strategy 2030 includes the development of a coherent framework for monitori

Wer Schmetterlinge schützen will, muss wissen, wo sie vorkommen. Die Fundmeldungen aus bestehenden Monitoringprogrammen lagen bislang jedoch nur regional vor. Erstmals führt der Atlas die Verbreitungsdaten aller 184 heimischen Tagfalter- und der 24 Widderchenarten zu einem schlüssigen Bild ihrer Gesamtverbreitung zusammen und liefert so ein wirkungsvolles Instrument zu ihrem Schutz. Eine Einleitung beschreibt die Lebensweisen der Schmetterlinge und ihren Wert für Ökosysteme und Naturschutz und gibt Einblicke in das Monitoring. Ausführliche Porträts und lebendige Bilder stellen die Arten samt Schutz- und Gefährdungsstatus vor und zeigen ihre Verbreitung in meist ganzseitigen Karten.

Im vorliegenden Beitrag identifizieren wir Möglichkeiten und Grenzen einer Aufarbeitung bisher noch ungenutzter Datenquellen für raum-zeitliche Biodiversitätsanalysen in Deutschland. Im Rahmen des Syntheseprojekts sMon (https://www.idiv.de/smon) des Deutschen Zentrums für integrative Biodiversitätsforschung (iDiv) Halle-Jena-Leipzig erprobt eine Arbeitsgemeinschaft aus Bundes- und Landesbehörden gemeinsam mit Fachgesellschaften, Verbänden und wissenschaftlichen Einrichtungen Methoden, wie heterogene Daten der letzten Jahrzehnte für retrospektive Trendanalysen genutzt werden können. Darauf aufbauend schlagen wir gangbare Wege zur Zukunft des deutschen Biodiversitätsmonitorings vor und illustrieren, wie Daten aus der Vergangenheit helfen können, Monitoring künftig zu gestalten. In this article, we identify possibilities and limits of processing as yet unused data sources for spatio-temporal biodiversity trend analyses inGermany. The sMon synthesis project (https://www.idiv.de/smon) of the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzigis a joint working group of federal and state authorities cooperating with natural history societies, nature protection organisations and scientific institutions. In this group, we develop and evaluate methods for using heterogeneous data for retrospective trend analyses over the last decades. Building on this, we propose viable approaches for the future of German biodiversity monitoring and illustrate how data from the past can help to shape monitoring in the future.

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.