Work packages

Although global biodiversity loss is well documented, analyses of vegetation-plot time series often show no trend in species richness, highlighting the “biodiversity conservation paradox.” Instead, these time series reveal significant species turnover, indicating that changes in species composition, rather than species loss, are the main component of biodiversity change. Resurveyed vegetation plots offer valuable insights into community structure, habitat quality, ecosystem properties, and nature’s contribution to people. While vegetation-plot resurveys have become important elements in the Swiss monitoring programme for vascular plants, they have yet to be implemented in most EU countries, leaving a huge untapped potential for using vegetation plot resurveys to support European biodiversity monitoring.

WP1 aims to supplement trends from recent national monitoring programs, providing deeper insights into long-term habitat changes. This will fill gaps in current biodiversity monitoring, which often lacks the detailed information that vegetation resurvey data can provide.

The objectives of WP1 are to analyse vegetation changes by habitat, complement plot-level biodiversity metrics with those capturing community structure and ecosystem functions, and link habitat-specific time series to Habitats Directive (HD) reports to enhance biodiversity monitoring. In doing so, we will supplement current monitoring programs with additional insight from long-term time series data.

We recently developed an expert system to automatically classify vegetation plots from the ReSurveyEurope time series (https://euroveg.org/resurvey) to European habitat types (https://eunis.eea.europa.eu/habitats.jsp). Based on this automatic classification, we will be able to provide specific biodiversity trends for a large number of different habitat types. In addition, we will harmonise information on habitat- and status-specific characteristic species groups from national variants of the Interpretation Manual of European Union Habitats (https://eunis.eea.europa.eu/references/2435) to develop universal formulas to define the habitats and their respective conservation status. Assessment of habitat quality will follow the established Article 17 reporting scheme (https://www.eionet.europa.eu/etcs/etc-be/activities/reporting/article-17) but generate standardised habitat designation and quality definitions across Europe.

We will complement taxonomic summary metrics of plot-level biodiversity (e.g., species richness, Shannon diversity and evenness) with metrics that capture changes in community structure (e.g., species’ mean ranks of abundance, turnover and nestedness in temporal beta diversity) as well as trends in functional diversity to derive information on temporal trends in ecosystem properties and functions.

We will link habitat-specific time series information from Task 1.1. to the Habitats Directive Article 17 reports of the EU member states (https://www.eionet.europa.eu/etcs/etc-be/activities/reporting/article-17) and provide details for future reports which cannot be derived from the current reporting schemes. Together with WP5 and WP7, we will expand the Essential Biodiversity Variables (EBVs, https://geobon.org/ebvs/what-are-ebvs) on “Ecosystem distribution of terrestrial EUNIS habitats”.

Accelerating environmental change is driving shifts in species populations and geographic  distribution, leading to a rapid increase in alien plant species across Europe. But not only alien, also native species can expand their ranges to track altered environmental conditions. Yet, little is known about how these trends vary across Europe, how they correlate with the current distribution of species, and to what degree expert assessments of species’ invasive threat are reflected in local-scale trends of abundance, occurrence and range size.

WP2 will assess changes in local plant abundance and regional distribution in Europe since 1950, highlighting hotspots and coldspots of biodiversity change. Using plot-level vegetation time series data from ReSurveyEurope (https://euroveg.org/resurvey), we will 1) assess changes in species abundance and distribution by biogeographic origin, 2) study abundance changes within native ranges, 3) compare trends between threatened and non-threatened species, 4) link those changes to ecological preferences and habitats, 5) correlate these changes with biodiversity drivers from WP4 to 6) explore future biodiversity scenarios under different EU policies. Our results will contribute to the Essential Biodiversity Variables (EBVs, https://geobon.org/ebvs/what-are-ebvs) on species distributions of terrestrial plants and support future predictions of plant species abundance and distribution changes across Europe.

We will assess historic abundance changes and range extensions in native, neonative, alien and invasive species (i.e., the subset of alien species with detrimental impacts on biodiversity). We will focus on the time period from 1950 onwards, i.e. the phase of rapid and accelerating environmental changes in Europe.

We will relate species-specific changes in abundance and range extent to national threat status (e.g., based on national Red Lists of plants) to their degree of specialisation (using Ellenberg Indicator Values, https://vegsciblog.org/2023/01/12/ellenberg-type-indicator-values-for-europe) and affinity to disturbance (using Disturbance Indicator Values, https://onlinelibrary.wiley.com/doi/10.1111/geb.13603). Grouping species according to their phytosociological preferences, we will analyse the species-specific range and abundance changes within different habitat types (e.g. grasslands, forests, arable fields).

Linking species responses to the drivers analysed in WP4, we will compare possible future biodiversity trends until 2050 under business-as-usual vs. scenarios of ambitious EU biodiversity policies based on the goals of the Post 2020-Global Biodiversity Framework (https://iucn.org/resources/issues-brief/post-2020-global-biodiversity-framework).

Subsequently, we will use these fitted models and scenarios of future development to predict how abundance and range of different groups of species (native, neonative, alien; habitat- and conservation status-specific characteristic species) will likely develop until 2050.

Biodiversity changes at species and community levels are partially linked to the disruption of ecosystem functionalities. Although new efforts have focused on evaluating ecosystem properties these efforts have not yet been implemented in habitat-level monitoring systems that combine ground-based and remote-sensing observations. We still need to develop automatized approaches for habitat mapping and monitoring, integrating ground data information on vegetation and COPERNICUS remote-sensing data at high spatial resolution (https://www.copernicus.eu/en) to detect temporal trends across multiple Essential Biodiversity Variables (EBVs, https://geobon.org/ebvs/what-are-ebvs).

WP3 will evaluate spatio-temporal trends of European habitat types at the ecosystem level using COPERNICUS data sets (https://www.copernicus.eu/en) in the areas sampled by ReSurveyEurope (https://euroveg.org/resurvey), focusing on three ecosystem-level EBVs: geographic extent, primary productivity and phenology. Our main objectives are: 1) to quantify changes in the extent of the resurveyed habitats at the landscape scale; 2) to calculate trends in the ecosystem productivity of the resurveyed habitats; and 3) to develop and test a protocol for monitoring phenological changes of habitat types based on time series of remote sensing imagery. In all cases, we will test how the changes observed with remote sensing can be compared with the changes observed at the plot level. The overall results of WP3 are expected to develop tools for monitoring ecosystem based EBVs comprehensively, and to motivate the integration of remote-sensing indicators in the future monitoring systems of European habitats.

Using the Google Earth Engine platform for massive cloud computing (https://earthengine.google.com), we will sample replicates of the same habitat type within different Areas of Interests of 1 km² (AOIs). Using algorithms based on unsupervised classification and multispectral similarities of satellite images (e.g., seeded region growing algorithms), we will map the extent of the resurveyed habitats in the years where actual monitoring took place. Using Natura 2000 habitat maps (https://www.eea.europa.eu/themes/biodiversity/natura-2000/the-natura-2000-protected-areas-network), we will then validate the classification estimated extent of habitats against the vegetation changes measured in the resurveyed plots.

The AOIs defined in task 3.1 will be used to track changes in the productivity of the resurveyed habitats (based on spectral indices such as NDVI and SAVI, as surrogates of vegetation productivity). In addition, we will calculate within-year rates of the same indices to evaluate phenological trends in the focal habitats between the survey(s) and resurveys. We expect most calculations to be based on Landsat 5 (https://www.usgs.gov/landsat-missions/landsat-5), 8OLI and 9OLI (30 m, https://www.usgs.gov/centers/eros/science/usgs-eros-archive-landsat-archives-landsat-8-9-olitirs-collection-2-level-2) for tracking surveys since the mid-1980s.

Using Sentinel 2 data (available since ca. 2017, https://www.esa.int/Applications/Observing_the_Earth/Copernicus/Sentinel-2), we will create inter-annual phenological curves with monthly resolution for each habitat type sampled in the time series data. We will design a comprehensive analytical framework to create representative spectro-phenological signatures and specific functional metrics for each habitat type in the last five years to define a set of EBVs and their relation with known drivers of biodiversity change (e.g. drought, forest fires, or succession) and we will propose a framework for the monitoring of current and future biodiversity trends among EU habitats.

Although the added value of vegetation plot time-series in current biodiversity monitoring schemes is undisputable,  vegetation plot time-series currently only represent spatially punctual observations, whose distribution is rarely representative of the geographic space and environmental conditions of the monitored area. By providing repeated, consistent, and comprehensive representations of the Earth surface, remote sensing has the potential to complement and upscale the biodiversity trends obtained from vegetation plot time-series.

WP4 aims to identify the main global change drivers underlying trends observed in vegetation plot time series, quantify biodiversity loss across Europe, and identify areas of maximum change. Specifically, we will: 1) gather a set of spatially explicit environmental predictors and land use/land cover proxies based on remote sensing, which relate to biodiversity change across Europe; 2) calibrate and validate models of biodiversity change across Europe in a spatially explicit way, 3) create time-resolved large-area maps of plant biodiversity change over the last 35 years, and 4) identify global change drivers behind observed species and habitat changes, as derived from our time-series. As a result, we will provide spatially-explicit, temporally-resolved maps of predicted compositional dissimilarity, to quantify regional biodiversity loss, highlight areas of maximum biodiversity change, and identify the main drivers of the observed biodiversity change.

We will gather and harmonise spatial datasets on current and past environmental and land use conditions, including time-invariant environmental predictors (e.g., soil, topography) and predictors varying over time such as (a) climatic variables, (b) land-cover & land-use data, and (c) anthropogenic pressures using available GIS products (such as SoilGrid, https://soilgrids.org, CHELSA climate data, https://chelsa-climate.org, and EarthEnv, https://www.earthenv.org), but also tracking historical land-use changes for particular time series and particular habitat types using COPERNICUS (https://www.copernicus.eu/en) and LANDSAT programmes (https://landsat.gsfc.nasa.gov).

We will match vegetation-plot time series to our decadal collections of remote sensing imagery to calculate their temporal change in the spectral response since 1984. These spectral change trajectories will then be used to calculate expected temporal turnover in species composition for vegetation plots that time series measurements. Our goal is to develop a three-step model linking compositional turnover to spectral change where time-series are available, predict compositional turnover based on the spectral change and environmental covariates for those additional vegetation plots for which time-series data are not available, and predict species composition and compositional turnover for the remaining pixels in the study area without compositional data.

We will identify the main global change drivers underlying the biodiversity trends observed in our time series across habitats and species by modelling biodiversity changes as a function of the spatio-temporal changes in the data on drivers gathered in Task 4.1. By comparing the performance of generalised linear mixed-effects models with alternative explanatory variables, we will highlight those drivers (e.g., annual evapotranspiration, land use intensity etc.) that have the most important effects on habitat and species temporal trends.

Europe has a more than 100-year-long tradition of plot sampling of vegetation. However, records from plot observations had been scattered in the literature, unpublished reports, field protocols, and multiple regional or national vegetation-plot databases. To make use of these data for international analyses, two of the MOTIVATE partners, in collaboration with dozens of European vegetation scientists, started in 2014 the European Vegetation Archive (EVA, https://euroveg.org), and integrated a database of European vegetation plots. In March 2023, the EVA database contained more than 2 million vegetation-plot records from 106 partner databases. However, data from resurveys were either not included or not tagged consistently in EVA; a gap that was closed by ReSurveyEurope (https://euroveg.org/resurvey). However, this database requires further development as more data from under-represented regions and habitat types have to be added and the development of new online functions is needed to facilitate quick access to the data and analyses.

In WP5, we will 1) analyse the ReSurveyEurope database (https://euroveg.org/resurvey) to highlight gaps in representativeness across regions and time of initial sampling and resampling; 2) extend ReSurveyEurope (https://euroveg.org/resurvey) by including additional literature data, databases and unpublished records, as well as monitoring data from national conservation agencies, and 3) develop an online platform of resurveyed vegetation plots, which will show the plot locations, vegetation or habitat type and survey and resurvey times in an interactive map. The database platform will be co-designed with stakeholders to meet the needs of national conservation agencies and the European Environmental Agency (EEA, https://www.eea.europa.eu/en). As a result, we will develop the largest database of resurveyed vegetation plots in Europe, including all European regions and habitat types. This database will become the most important source of information on vegetation change in Europe, including fine-resolution data from specific locations and detailed information on plant species composition and abundances. This database will then be made available to external users, for research and applications in conservation assessment and monitoring.

The current version of the ReSurveyEurope database (https://euroveg.org/resurvey) will be subject to detailed quality control. Vegetation plot observations will be assigned to EUNIS habitat types at the hierarchical Level 3 (https://eunis.eea.europa.eu/habitats.jsp) using the EUNIS-ESy classification expert system (https://onlinelibrary.wiley.com/doi/full/10.1111/avsc.12519). A gap analysis will then be performed with a focus on geographic coverage, representation of different habitat types, environmental characteristics, and time coverage.

We will use existing international collaborative networks of vegetation scientists to provide additional data from fieldwork, literature or unpublished materials. We will also contact national conservation agencies to negotiate the inclusion of monitoring data in the ReSurveyEurope database. We will use the EVA database to identify historical plots in the areas of the largest data gaps that could be resurveyed in future projects. These plots will be indicated in an online map and collaborators will be invited to resurvey and permanently mark these plots (including options to participate in MOTIVATE’s data analysis and publications).

We will provide public information about the ReSurveyEurope (https://euroveg.org/resurvey) database following the FAIR principles for scientific data management and stewardship (https://www.go-fair.org) while respecting the ownership rules of third-party data contributors according to the approved ReSurveyEurope Data Property and Governance Rules (https://euroveg.org/download/ReSurveyEurope_Rules.pdf). Each new version of ReSurveyEurope (https://euroveg.org/resurvey) and each data selection for research projects will be assigned a DOI to assure the findability and accessibility of the data and repeatability of the study. External programmers will be subcontracted to prepare the database structure together and provide an interactive public  webpage that allows users to filter data from ReSurveyEurope (https://euroveg.org/resurvey) by regions, habitat types and time periods (also in cooperation with national conservation agencies to serve their needs).

The integration of participatory, citizen science approaches that merge natural and social sciences has been highlighted as key to the delivery of both international and EU biodiversity policy targets. Inclusive transdisciplinary research is thus necessary to provide the evidence base for EU policies which aim at achieving effective stakeholder participation in biodiversity conservation. WP6 will develop and operationalise mixed methods from the social sciences that capture qualitative expert knowledge and opinions on the accuracy and value of long-term vegetation surveys in a structured way, allowing for comparisons across sites and spatial scales. These data will help us to improve our understanding of MOTIVATE’s quantitative datasets, enable more complete characterisations of surveyed habitats and associated biodiversity, and enrich the value of the long-term survey data. WP6 will further reflect on how this participatory qualitative knowledge can be used to improve the effectiveness of long-term monitoring schemes and how monitoring data are put into practice by decision-makers within and beyond protected area networks.

In WP6, we will 1) capture personal insights of expert surveyors on the survey process and landscape change and how the vegetation survey process can be improved, 2) identify and support regions where vegetation resurvey capacities could be increased, 3) foster knowledge exchange between vegetation experts and the wider community of local stakeholders. WP6 will thus furnish MOTIVATE with insights to improve long-term monitoring and ensure fuller and more just community participation in biodiversity conservation, making it more efficient, inclusive, and generative. To achieve this, we will provide 1) analyses of questionnaire survey data from vegetation experts who established the long-term vegetation monitoring plots, 2) in-depth analysis of expert opinion on the effectiveness of the vegetation survey methods, future directions to improve the survey process, and ideas to  improve the effectiveness of biodiversity conservation, 3) analysis of how the time series could be improved to reflect changes on the ground, as well as key landscape scale drivers of that change, and 4) raise a sense of broad ownership (via participatory methods) of the final mapping output, as well as key steps towards building a common community vision for biodiversity conservation. To achieve this, we will conduct workshops to gather insides on how vegetation time series and the expert questionnaires could potentially address aspects of the phenomenon of the shifting baseline syndrome, whereby local communities are not aware of how much species richness and abundance has been lost because impoverished landscapes are culturally normalised by successive generations.

Human perceptions of habitat characteristics and attitudes to nature conservation will be collected at scale using questionnaires, provided to the experts who originally established the vegetation plots, as well as to current vegetation resurveyors (n = ~500 studies). This survey will highlight the key aspects of species and habitat change in the surveyors’ study areas from their own viewpoints, key drivers of these changes, whether these changes are accurately represented in the database, as well as reflections on future scenarios and effective management strategies to protect and restore habitats.

Questionnaires from Task 6.1 will be complemented by situated research approaches which explore in depth the various details and nuances of human knowledge at the local scale. We will conduct interviews at the target areas with all available local surveyors along the same transects as used by the vegetation surveyors. This will allow analysis of the relationships between survey data and human insights on the same themes. Walking or ‘go-along’ methods will be used which generate deeper place-based narratives than sedentary research practices as they enable comprehensive documentation of stakeholder experiences and their linked environmental narration. As a qualitative complement to the quantitative vegetation resurvey, we will pair local vegetation surveyors with new research assistants in walking interviews to encourage knowledge exchange and critical capacity building across generations.

We will conduct a series of participatory workshops in four key target locations (pinpointed by the gap analysis in the ReSurveyEurope database, https://euroveg.org/resurvey) to establish a qualitative complement to the new quantitative vegetation survey capacity. Workshop participants will comprise vegetation surveyors and the wider community of stakeholders identified in consultation with local conservation experts. In these workshops, we will share with relevant stakeholders the long-term observations from other WPs together with the expert reflections on change from Task 6.1 and 6.2. They will serve as fieldwork campaigns, to which new potential surveyors will be invited. Lastly, we will capture local feedback and reflections on both the findings from the local area and on some of the broader findings of the MOTIVATE project that can later be integrated in the results from the various WPs to improve the survey process going forward.

The MOTIVATE project is closely linked to the reporting obligations of the Habitats Directive (HD, Council Directive 92/43/EEC, https://environment.ec.europa.eu/topics/nature-and-biodiversity/habitats-directive_en#:~:text=the%20long%2Dterm.-,Law,and%20outside%20Natura%202000%20sites) in Europe. The reports on the conservation status for habitats and species under the HD (Article 17, https://www.eionet.europa.eu/etcs/etc-be/activities/reporting/article-17), suffer from several shortcomings. There is a lack of consistent and reliable raw data on which the conservation status of habitats and species is based. While some member states established a special standardised monitoring programme for Article 11 of the HD, others used data from already existing programmes (e.g. habitat mapping, large-scale forest inventories, landscape monitoring). This can lead to discrepancies, which have been observed when the reports are compared with other assessments.

In WP7, our aim is to support the biodiversity monitoring of the member states. WP7 will be our contact point for contacting and exchanging data with the national conservation agencies. We will provide resurvey data and derived Essential Biodiversity Variables (EBVs, https://geobon.org/ebvs/what-are-ebvs) tailored to the needs and data formats required by the agencies and we will ask the national agencies for additional vegetation-plot time-series data. This process will be co-designed with representatives of the national agencies and vegetation surveyors of the different countries. As a result, WP7 will provide an important component for the future biodiversity monitoring of the EU. Integrating trend information on the majority of habitats monitored under the HD with the regular reports of member states will reinforce the national biodiversity monitoring programmes and facilitate reporting of the member states under the HD. Thus, MOTIVATE will 1) improve the assessment of quality and conservation status of habitats, 2) provide quantitative information on trends of habitats and species in Europe and 3) will serve as a blueprint for the whole process of co-designing pipelines of integrating other data than vegetation plot resurveys into the future European biodiversity monitoring. MOTIVATE will bring in the extremely valuable competences of hundreds of current and future resurveyors of vegetation-plot resurveys into the European monitoring under the HD, in a way that ensures their future engagement into monitoring, at no additional costs for the EU or member states.

We will identify those habitat types that have sufficient coverage in the ReSurveyEurope database (https://euroveg.org/resurvey) and at the same time are not yet well covered in the monitoring under the HD (https://environment.ec.europa.eu/topics/nature-and-biodiversity/habitats-directive_en). We will organise regular stakeholder meetings and regular online workshops with representatives of the national agencies, the EEA (https://www.eea.europa.eu/en), GeoBON (https://geobon.org) and the European Topic Centre for Biological Diversity and Ecosystems (ETC-BE, https://www.eionet.europa.eu/etcs/etc-be) to learn about the agencies’ priorities for improving reporting.

We will develop and report our co-designed pipelines for the éxchange of vegetation resurvey data and the derived EBVs between MOTIVATE and national agencies.By integrating vegetation-plot resurveys into the monitorings, the MOTIVATE project will substantially enhance the quality of reporting the species and habitat conservation status for the entire EU. We will try to expand this approach to cover all habitat types, by combining untapped data with remote sensing, and extrapolation methods.