Settele J., Aracil A., Arnberg H., Åström S., Bacon J., Balalaikins M., Báldi A., Bane M., Barda M., Barea-Azcón J.M., Beckert J., Berlengée F., Bevk D., Biesmeijer J.C., Bonelli S., Bosch J., Botham M., Bourn N., Bozua M., Brosens D., Burguillos A., Breeze T.D., Buchner D., Cabiddu L., Cancela J.P., Cantú-Salazar L., Carbone D., Caritg R., Carvell C., Castro S., Collins S., Dauber J., De Flores M., de Groot M., Dapporto L., Demeter I., Dennis E.B., Dieker P., Dopagne C., Dorchin A., Dvořák T., Ellis S., Escobés R., Eykelboom J., Fric Z.F., Fernández-García J.M., Flaminio S., Fontaine C., Frenzel M., Gecchele L., Gelaude E., Ghisbain G., Glogovčan P., Gracianteparaluceta A., Grescho V., Haase P., Harpke A., Harrower C., Haubrock P.J., Heliölä J., Herrera-Mesías F., Hlaváček A., Honchar H., Houard X., Høye T.T., Isaac N.J.B., Ješovnik A., Jocqué M., Johnson K., Judge M., Karlis G., Kablar D., Kazlauskis K., Knapp M., Koderman B., Kolev Z., Komac B., Kovács-Hostyánszki A., Kühn E., Kuussaari M., Lang A., Le Divelec R., Leese F., Loureiro J., Lutovinovas E., Lysaght L., Maebe K., Maes D., Mandery K., McGowan D., Mestdagh X., Menger J.S., Michez D., Middlebrook I., Milotic T., Monasterio Y., Monteiro E., López Munguira M., Musche M., Neukermans A., Nogueira Tavares C., Östrand F., Oteman B., Ozden O., Pavlíčko A., Pérez-Bañón C., Perrard A., Petanidou T., Pettersson L.B., Pladevall C., Pocock M.J.O., Pollet M., Potts S.G., Quaranta M., Ranalli R., Rákosy L., Rasmont P., Reverté Saiz S., Reyserhove L., Roberts S.P.M., Rodrigo A., Rojo S., Rosa P., Roth T., Rüdisser J., Šašić M., Scalercio S., Schamp K., Schmidt V., Schmucki R., Schönwälder M., Schweiger O., Sevilleja C.G., Sielezniew I., Sielezniew M., Simoens N., Sinclair J.S., Slabbert E., Sobczyk-Moran G., Soors J., Ståhls G., Stavrianakis G., Stavrinides M., Stefanescu C., Štrobl M., Šturm R., Švitra G., Szabadfalvi A., Szigeti V., Teunissen L., Tiitsaar A., Titeux N., Tscheulin T., Tzirkalli E., Ubach A., van Breda A., van Breda J., Van Deijk J., van de Meutter F., van den Heuvel Y., Vanden Houten J., Vander Mijnsbrugge K., van Gompel W., Vanhaverbeke K., van Nieuwstadt M., van Swaay C.A.M., Varnava A., Vereecken N.J., Verkaik I., Verovnik R., Vilks K., Vizauer T.C., Vray S., Vujić A., Warren M.S., Weigand A., Wever R., Whitfield A., Wood T.J., Wynhoff I., Zavatta L., Roy D.B.
SPRING - Strengthening Pollinator Recovery through Indicators and monitoring.: Final Report.
Publications Office of the European Union, Luxembourg. 2025, 122 S.
The SPRING project supports the development of an EU Pollinator Monitoring Scheme. It comprises tasks on evaluating the potential of pollinator Citizen Science, development of butterfly
monitoring schemes across the EU, piloting pan traps and transects methods for sampling pollinating insects in the field, evaluating the potential of malaise traps and light traps for sampling
wider insect biodiversity and moths respectively.
A provisional network of Butterfly Monitoring Schemes across the EU was completed during this project. This includes support for schemes in Lithuania, Greece, Romania, Latvia, Denmark and
Slovakia - mainly on the basis of trained volunteer observers, provision of identification guides and support for coordinators in each Member State. An update to the European Grassland
Butterfly indicator was completed and shows a linear decline of 32% in the EU-27 and 36% in Europe from 1990-2020. All Butterfly Monitoring Schemes in Europe were supported by this
project through provision of guidance and promotional material, including workshops to share experience and best practices between schemes. Technical tools to support butterfly monitoring
communities (website and the ButterflyCount mobile application) were enhanced in response to user feedback, e.g. updates to species lists, improved reports and data downloads and
translations. The tools support 36 Butterfly Monitoring Schemes in 30 countries - including 27 EU Member States - and has resulted in 9122 active butterfly transects (i.e. walked in the last two
years) for the European continent. In total, around 10,000 volunteers have participated in the eBMS network, providing valuable butterfly monitoring data during all the monitoring years. We
updated the Grassland Butterfly Index which was published by as an EEA SEBI 027 indicator, as well as in the EU Biodiversity Strategy Dashboard on the Knowledge Centre for Biodiversity
website and Eurostat's 2024 SDG report.
We undertook an audit of methods for pollinator monitoring with Citizen Science. We assessed numerous pollinator Citizen Science projects (from searches of websites and academic papers,
and public elicitation) and assessed variation in their methodologies using multivariate statistics. Overall, 75% of pollinator Citizen Science projects focussed on recording pollinators (e.g. butterfly
monitoring), 20% focussed on interactions (e.g. focal flower counts like FIT Counts) and 5% focussed on pollination (e.g. level of seed set for insect pollinated plants). We developed a public
survey gaining 321 responses from experts in pollinators and/or Citizen Science in 35 European countries about factors and barriers supporting Citizen Science. We found that the support for
Citizen Science (based on assessment of the overall rating of pollinator Citizen Science, factors supporting Citizen Science, and barriers) was strongly related to affluence (as measured by Gross
National Income). Based on our analysis and experience during the SPRING project we recommend regionally specific ways to support pollinator Citizen Science in different countries.
We developed training materials through a didactical framework, in support of capacity building for pollinator species identification and field sampling. We ran 27 courses during 2022 and 2023,
covering all regions of the EU, aimed at participants with a basic or intermediate level of expertise. Courses were adapted to local conditions by translating materials as required. Over 250
participants attended, and the courses received high marks (>90%) through formal evaluation. In collaboration with leading taxonomic experts in bee and hoverfly identification, and in
collaboration with the ORBIT and TAXOFLY projects, we ran 17 courses in advanced identification skills for pollinating insects. Over 120 people attended the courses. We developed
a large body of material to support capacity building for an EU Pollinator Monitoring Scheme and designed an approach to the development of knowledge and capacity towards a pollinator
monitoring scheme for the EU. A Pollinator Academy website was developed to consolidate all training and capacity building material developed during this project.
We piloted pollinator monitoring methods to inform the design of an EU Pollinator Monitoring Scheme. Based on recommendations of the STING expert group (Potts et al. 2021) we tested
pan trap and transect sampling across the EU, surveying 231 sites in 15 countries and over 1100 separate days in the field. Over all surveys we collected data on 527 bee, 224 butterfly and 197
hoverfly taxa. At the level of individual field sampling occasion, there was considerable variability in the diversity and abundance of pollinating insects. This represents variability between sites,
differences over time (across the season and between years) and differences between bioclimatic regions of the EU. For bees and hoverflies from pan traps, the overall average diversity was 7 to
10 species and 2 to 3 species respectively. The average number of individual insects was 30 bees and 8 hoverflies. Guidance was made available to support surveys and included
specifications for building and spraying pan traps, survey protocols for all methods (pan traps, transects, flower and habitat assessments), field recording forms and guidance of entering data
via an online data entry system. Data from field surveys was made available to the STING project and experts.
To evaluate the potential of pan traps for pollinator monitoring, we reviewed the impact of floral resources on sampling efficiency. We developed a conceptual framework for the relationship
between pollinator abundance and local floral resource, and how this could affect the abundance of sampled insects in scenarios of competition between flowering plants and pan traps. We
collated available data to model these relationships, including 14 studies across Europe. After filtering we analysed 11 datasets for pan traps (covering Spain, Greece, UK and The Netherlands)
and 4 for transects (covering Romania, The Netherlands, Serbia and the UK). For both pan traps and transects, wild bee abundance initially increased with increasing flower density, peaked and
then decreased. The relationship between flower density and abundance of wild bees from transects peaked at high flower densities (e.g. for mass flowing crops), whereas for pan traps the
peak was at markedly lower flower densities. This suggests a strong dilution effect for pan traps due to competition between pan traps and flowers. We therefore recommend that the EU
Pollinator Monitoring Scheme should focus on transects as the primary sampling method.
We piloted additional sampling methods for pollinating insects: light trapping for moths and malaise trapping for wider insect biodiversity. Moth sampling was tested at 253 locations in five
countries (Germany, Hungary, Netherlands, Spain, Sweden) using a cost-effective and portable light trap. A manual and field protocol were produced to support the wider adoption of this
sampling method. The ButterflyCount mobile application was extended to capture data from moth traps, including the use of AI image classifiers to support species identification by non-experts.
Results from the pilot were encouraging for the abundance and diversity of moths sampled and the practical feasibility of applying the sampling approach across EU Member States.
We developed standardised guidance for the use of Malaise traps and metabarcoding to support pollinator monitoring, and tested Malaise traps in 20 locations (13, 5 and 2 sites in Germany,
Hungary and Greece respectively) alongside pan traps. Total insect richness was an order of magnitude lower in pan traps compared to Malaise traps, with ~10-20 taxa and ~400-600 average
richness respectively. However, for pollinator richness the two methods were similar, although some species were unique to one or other sampling method. Malaise traps have potential to wider
the taxonomic scope of insect sampling within a monitoring scheme, and are recommended as a method to complement but not replace pan traps or transects.
The results of the SPRING project have been communicated to a range of audiences through in person and online events, including a final conference held in January 2024. Project outputs such
as field sampling protocols, training materials, datasets and recommendations have been shared with the Science and Technology for Pollinating Insects (STING) expert group.
The Nature Restoration Regulation requires capacity building and methodological piloting to enable Member States to implement effective monitoring schemes for pollinating insects. The
SPRING project has made a major contribution to developing Citizen Science best practice (for butterflies and other pollinators), building capacity through extensive training materials, piloting
a range of field methods such as transects, pan traps, light traps and malaise traps that sample all the main groups of pollinating insects (bees, butterflies, hoverflies, moths). The results of the
SPRING project have been communicated widely to Member State stakeholders and have contributed directly to the work of the STING expert group reports.