European Nature Information System Research Articles

Habitat Diversity, Environmental Conditions, and Distribution of Endangered Fungus Sarcosoma globosum (Ascomycota) in Lithuania.

Sarcosoma globosum (Pezizales, Ascomycota) is a rare and endangered fungus, and it is believed to be extinct in most central European countries. Known records of S. globosum in Lithuania reveal that it is situated on the south-western edge of a shrinking geographical distribution range in Europe. An assessment of the species' current habitat conditions and threats could enhance and provide new knowledge and guidelines to facilitate the efficient conservation of this threatened fungus and its habitats. The main aim of this study was to analyse the habitats and environmental conditions of S. globosum in Lithuania. We examined the diversity of habitats, various soil and tree stand characteristics, forest management activities, and natural disturbances in all 28 known fungus localities. S. globosum habitats in Lithuania are restricted to coniferous forests with the presence of Picea abies; the species was observed in boreo-nemoral bilberry western spruce taiga (the European Nature Information System habitat type T3F14), continental tall-herb western spruce taiga (T3F44), and native fir, spruce, larch, and cedar plantations (T3N1). An analysis of forest stand age structures in Lithuanian S. globosum localities revealed a rather large proportion of young Norway spruce stands of cultural origin (25.6% of study plots were assigned to age classes from 21 to 50 years); nevertheless, the majority of fungus growth sites were situated in older forests. Various natural and anthropogenic disturbances that threaten S. globosum habitats were assessed.

Mobilising Long-Term Natural Environment and Biodiversity Data and Exposing it for Federated, Semantic Queries

Biodiversity and ecosystems cannot be studied without assessing the impacts of changing environmental conditions. Since the 1980s, the U.S. National Science Foundation's Long Term Ecological Research (LTER) Network has been a major force in the field of ecology to better understand ecosystems. In Europe, the LTER developments are led by the the Integrated European Long-Term Ecosystem, critical zone and socio-ecological system Research Infrastructure (eLTER RI), a currently project-based infrastructure initiative with the aim to facilitate high impact research and catalyse new insights about the compounded impacts of climate change, biodiversity loss, soil degradation, pollution, and unsustainable resource use on a range of European ecosystems and socio-ecological systems. The European LTER network, which forms the basis for the up-coming eLTER RI, is active in 26 countries and has 500 registered sites that provide legacy data e.g., historical time-series data about the environment (not only biodiversity). Its site information and dataset metadata with the measured variables are available to be searched at the Dynamic Ecological Information Management System - Site and dataset registry (DEIMS-SDR, Wohner et al. 2019). While DEIMS-SDR data models utilize parts of the Ecological Metadata Language (EML) schema 2.0.0, location information follows the European INSPIRE specification. The future eLTER data is planned to consist of site-based, long-term time-series of ecological data. The eLTER projects have defined eLTER Standard Observations (SO), which will include the minimum set of variables as well as the associated method protocols that can characterise adequately the state and future trends of the Earth's systems. (Masó et al. 2020, Reyers et al. 2017). The current eLTER network consists of sites that differ in terms of infrastructure maturity or environment type and may focus on one or several of the future SOs or they are not yet executing any holistic monitoring scheme. The main objective is to convert the eLTER site network into a distributed research infrastructure that incorporates a clearly outlined mandatory monitoring program. Essential to this effort are the suggested variables for eLTER SOs and the corresponding methods and protocols for relevant habitat types according to the European Nature Information System (EUNIS) in each domain. eLTER variables are described by using the eLTER thesaurus "EnvThes". These descriptions are currently enhanced by the use of the InteroperAble Descriptions of Observable Property Terminology (I-ADOPT, Magagna et al. 2022) framework to provide the necessary level of detail required for seamless data discovery and integration. Variables and their associated methods and protocols will be formalised to enable automatic site classifications, by building on existing observation representations such as the Extensible Observation Ontology (OBOE), Open Geospatial Consortium's Observation and Measurement, and the future eLTER Standard Observation ontology. DEIMS-SDR will continue to be used as a core service with an RDF representation of its assets (sites, sensors, activities, people) currently being implemented. This action is synced with the Biodiversity Digital Twin (BioDT) project to ensure maximum findability, accessibility, interoperability and re-usability (FAIRness; Wilkinson et al. 2016) of data through FAIR Digital Objects (FDO). Other (digital) assets such as datasets, models and analytical workflows will be documented in the Digital Asset Register (DAR) alongside semantic mapping and crosswalk techniques, to provide machine-actionable metadata (Schultes and Wittenburg 2019, Schwardmann 2020). The Biodiversity Digital Twin (BioDT) project is bringing together biodiversity and natural environment data from seven thematic use cases for modeling. BioDT prototypes rely on openly available data that comes from multiple heterogeneous sources using a multitude of standards and formats. In the pilot phase, merging data requires "hand picking" from selected sources, and automation of workflows would still require many additional steps. There are ongoing efforts in both the BioDT and eLTER projects to find best ways and practices to bring the raw data together by using suitable standards but also to harmonise the other environment variables by referring to vocabularies and possibly express the data as FDOs. Currently both the EML schema and Darwin Core standard (Darwin Core Task Group 2009; with registered extensions) allow referring to external schemas and vocabularies, which give flexibility but may still prove to be too narrow for the multitude of data types and formats the natural environment data requires. We welcome discussion about how to create good practices for enriching and harmonising natural environment data and species occurrence data in a meaningful way. GBIF's new data model and enriching the raw data with semantic artefacts may prove to be the way to provide thematic data products that combine data from multiple sources.

Habitat mapping of Portugal’s north-western continental shelf and its application to implement the European Marine Strategy Framework Directive

Seafloor habitat maps allow to integrate various data layers and compare areas, being valuable tools for assessing environmental quality. Although the European Nature Information System (EUNIS) was created to catalogue habitats throughout Europe, its use in ecological assessment is relatively uncommon. This work proposes a EUNIS, level 5, benthic habitats map for the Portuguese continental shelf North of Nazaré canyon. Seven EUNIS level 5 habitats were identified, of which six were new to EUNIS, as this catalogue is less complete for southern Europe. Hereafter this map was used to assess the environmental status (ES) within the Marine Strategy Framework Directive (MSFD), which was developed to help European Union countries achieve a good environmental status (GES) in their marine ecosystems. In this sense, eleven quality descriptors (and respective criteria) were set to assess the environmental status (ES), which can be performed using diverse indicators. In this study, the ES status was assessed for two of such descriptors, namely D1, Biodiversity, which was assessed using the Marine Biological Value (MBV); and D6, Seafloor Integrity, which was assessed through the AZTI Marine Biotic Index (AMBI) and Multivariate-AMBI (M-AMBI). For both descriptors, an overall GES (or higher) was determined for this study area. These results set a baseline for future ES assessments within the MSFD, while the use of the EUNIS habitat maps can be expanded to assess the ES of other descriptors, namely D2, non-indigenous species, D3, commercially exploited fish and shellfish and D4, food webs.

Modeling approach for coastal dune habitat detection on coastal ecosystems combining very high‐resolution UAV imagery and field survey

AbstractEarth observation (EO) data, derived from remote sensing and unmanned aerial vehicle (UAV), have been recently demonstrated to be essential tools for the ecosystem monitoring and habitat mapping, combining high technological and methodological procedures for applied ecology. However, research based on EO data analyses often tend to focus on image processing techniques, neglecting the development of a detailed sampling design scheme needed for an exhaustive habitat detection. This paper shows the results of a novel approach for mapping coastal dune habitats at a fine scale, using a supervised machine learning model, through the combination of vegetation plot sampling scheme, synergic use of multi‐sensor spectral imagery (UAV‐VHR) and environmental predictors (e.g., LiDAR), object‐based image analysis, and landscape metrics analysis. Proposed approach was tested in a protected area, established to preserve notable habitats along the Italian Tyrrhenian coast. A detailed sampling scheme was designed and carried out during spring and summer of 2019, combining simultaneously UAV flight acquisition and field vegetation survey data, collected at high precision positioning. The calibrated classification model achieved an overall accuracy of 78.6% (standard error 4.33), allowing us to accurately classify and map five coastal habitats, according to EUNIS (European Nature Information System) classification, which were further verified through a fully independent validation field survey. Results demonstrate that VHR imageries, combined with specific field survey schemes, can be exploited to train classification models used for the detection of plant communities (i.e., meso‐habitat) and plant species at local scale. Our findings demonstrate that UAV‐VHR data is a valid tool to produce high spatial resolution information in sand beach ecosystems, giving ecology research a new way for responsive, timely, and cost‐effective ecosystem monitoring.

ReSurveyGermany: Vegetation-plot time-series over the past hundred years in Germany

Vegetation-plot resurvey data are a main source of information on terrestrial biodiversity change, with records reaching back more than one century. Although more and more data from re-sampled plots have been published, there is not yet a comprehensive open-access dataset available for analysis. Here, we compiled and harmonised vegetation-plot resurvey data from Germany covering almost 100 years. We show the distribution of the plot data in space, time and across habitat types of the European Nature Information System (EUNIS). In addition, we include metadata on geographic location, plot size and vegetation structure. The data allow temporal biodiversity change to be assessed at the community scale, reaching back further into the past than most comparable data yet available. They also enable tracking changes in the incidence and distribution of individual species across Germany. In summary, the data come at a level of detail that holds promise for broadening our understanding of the mechanisms and drivers behind plant diversity change over the last century.

Marine priority habitat mapping in a Mediterranean conservation area (Gyaros, South Aegean) through multi-platform marine remote sensing techniques

The aim of this study is to present the results of the first complete marine habitat mapping through marine remote sensing techniques in Gyaros Island, a remote island in the Cyclades archipelago with a great historical and ecological value. Gyaros Island is of great biological importance and, for this reason, since 2011, is part of the NATURA 2000 network and, by 2019, is characterised as a marine protected area (MPA). More than 80 km2 of seafloor area were inspected through a multi-platform marine remote sensing technique survey through two individual expeditions in 2014 and 2017. The remote sensing survey was conducted utilising side scan sonar, sub bottom profiler and multi- and single-beam echosounders. In addition to the remote sensing survey, an extensive ground truth network was established utilising a underwater towed camera and VanVeen sediment grabber. These resulted in the area being fully covered with high-quality data. Through these, a classification of the area was performed based on three distinct seafloor habitat mapping schemes (Expert, European Nature Information System and NATURA HD). The survey and the classification revealed that over 50% of the seafloor is covered by Posidonia oceanica meadows and coralligenous and other calcareous bio-concretion priority habitats. Based on the results of this work, Gyaros MPA was also established and different protections and conservation zones were set.

A Multidisciplinary Approach for A Better Knowledge of the Benthic Habitat and Community Distribution in the Central and Western English Channel

About 80% of the seabed of the English Channel (EC) is covered by coarse sediment, from coarse sand to pebbles. Quantitative data on the benthic macrofauna in these types of sediment remains are rare due to the difficulty of using grab corers in such hard substrates. The deepest central part of the EC (45–101 m depth) was prospected during two VIDEOCHARM surveys in June 2010 and June 2011 to increase knowledge of such sublittoral coarse sediment benthic habitats. Sampling focussed on a longitudinal transect in the deepest part of the EC (13 boxes), extending from the western approach to the Greenwich meridian. Both indirect (side scan sonar, Remote Operated Vehicule) and direct (grab sampling with benthos determination, and grain-size analyses) approaches were used and combined, permitting description of the benthic habitats and communities using seven methods. Five benthic EUNIS habitats (European Nature Information System) were reported: MC3215, MD3211, MC4, MC3212 and MC4215, of which two extended main habitats (MC3211 and M23212) corresponded to an eastern/western gradient from sandy gravel to sandy gravel and pebbles sediment. Three other spatially discrete habitats were associated with poor coarse sand and gravel habitats as well as sandy gravel and pebbles with the presence of the brittle star Ophiothrix fragilis. Taxonomic richness of both extended habitats was on the same order of magnitude as the coarse sand habitat reported elsewhere in the EC, whilst the abundances were among the lowest in deeper areas with low nutrient input and low primary production. The epifauna appeared relatively homogenous in this type of sediment at the scale of the sampling area and was not determined to assign a EUNIS habitat/class. ROV footage illustrated the presence of large epifauna and provided valuable information to ground truth in other sampling methods such as side scan sonar mosaic. Grab photos showing surface sediment was relevant to determine the sediment type, whilst granulometric analyses gave additional information on fine particles content (typically very low).

Reading the heterogeneity and spatial structuring of benthic habitats in macrophyte wracks

In coastal socio-ecosystems, the European Commission has proposed a set of indicators that could meet the objectives of the Marine Strategy Framework Directive. Most of them refer to the state of benthic habitats, a marine biodiversity compartment under major threat. However, biodiversity monitoring in the marine environment is logistically, technologically, and economically challenging. One possibility may be the monitoring of marine biodiversity “ex situ”, i.e. thanks to the material transported naturally along the sea to land continuum, but the relationship between benthic donor habitats and beach-casted macrophytes remains unclear. Only few studies have previously explored this relationship and they raised two questions: Could some wrack macrophyte species inform on the composition of proximate marine habitats? What is the contribution of local donor habitats in the composition of macrophyte wrack communities from one site to another? Here we provide answers to these questions from the sampling of macrophyte wracks on 131 beaches and the use of benthic habitat maps from the European Nature Information System. From linear regressions, we first show that the α-diversity of non-floating beach casted macrophytes reflects the heterogeneity of benthic habitats lying in straight marine buffers. Second, using non-linear modelling we show that this correlation peaks at 500 m offshore and maintains up to 1000 m far, which corresponds to the infralittoral seabed along our study coastline. Finally, regressions on distance matrices reveal that dissimilarities in wrack communities of non-floating macrophytes are more the result of differences in proximate benthic habitats rather than geographic patterns. While macrophyte wracks are already considered relevant indicators of geomorphological and ecological processes on coastal socio-ecosystem, this study advocates for their further consideration as ex situ indicators of benthic ecosystems.

Central European forest floor bryophytes: Richness, species composition, coexistence and diagnostic significance across environmental gradients of forest habitats

Bryophytes are good indicators of habitat conditions and show associations with different types of forests. In this study we assessed the diversity and distribution of forest floor bryophytes across a wide gradient of Central European forests using vegetation records from the Polish Vegetation Database (PVD). We identified forest types using the Habitat Classification of the European Nature Information System (EUNIS) – the main comprehensive pan-European hierarchical classification of habitats. Based on 9258 plots containing bryophyte species and representing 20 forest types, we assessed the species number and cover, species composition of the bryophyte layer, species tendency for coexistence, and bryophyte diagnostic value for forest types. We explained the observed trends by environmental variables and bryophyte species traits to understand how bryophytes function in forest habitats.Bryophyte species number and cover were high in forest types on moist sites, both with deciduous and coniferous tree stands. The richness and abundance of bryophyte species, as well as the species composition of the bryophyte layer depended mainly on substrate moisture, fertility and pH, as well as on the percentage cover of coniferous and deciduous tree species in the stand. Species traits which responded to environmental factors were, first of all, requirements for substrate moisture, fertility and pH. Bryophytes of closed forests and short-lived shuttle species preferred deciduous stands, while bryophytes occurring in forests as well as on open land and perennial species were associated with coniferous stands.Bryophyte species showed a clear preference for forest types, but their fidelity was usually not high. Based on the fidelity of species, we also identified 10 groups of coexisting species which were also indicators of forest types and were dependent on environmental variables.Forest floor bryophytes respond to environmental gradients by species number, cover and composition, and they play a diagnostic role in forest types. Our research shows the importance of databases in learning about bryophyte ecology. However, the use of vegetation data has some limitations.

An ignored habitat in Türkiye: Sandy steppes

The steppes habitat in Türkiye took bedrock formed of soil as the basis, and was classified by separating into groups, such as calcareous, with gypsum, volcanic, and serpentine. However, a classification was not made that took the soil texture as the basis. In this study, the stable sand dunes’ soil texture observed in Karapınar, Konya, Turkiye erosion region, was evaluated for flora and syntaxonomy. Within the scope of the study, observations were conducted in the sandy habitats found to the south-southwest of the Karapınar county center, the plant species that preferred the habitat were determined, and the data obtained was compared with the steppes’ habitat in the close environs and with the studies made previously. Furthermore, it emphasized the necessity of analyzing syntaxonomically the sandy steppes in Türkiye, which are evaluated within the “E1.A5 - Irano-Anatolian inland dunes” habitat type according to the European Nature Information System (EUNIS).

Mapping the macrofauna communities of Portugal's continental shelf north of Nazaré Canyon using Community Distribution Modelling (CDM)

The conservation and sustainable use of marine ecosystems is a worldwide concern, and to achieve it, managers and decision-makers require detailed environmental and biological information, namely supplied as maps of the seafloor. This work was conducted on Portugal's continental shelf located north of Nazaré Canyon. Sediment data was obtained in 226 grab samples, of which 169 were used to study the macroinvertebrate benthic communities. Acoustic transects were run for more than 2500 Km to obtain depth and maps of environmental variables were produced through spatial interpolation of the point data. A multivariate analysis of the biological data identified seven benthic communities, characterized by different species and environmental conditions (i.e., sediment type and depth). The spatial distribution of each biological community was modelled as the response to environmental variables using generalized linear models with a binomial distribution. Depth was the variable more often significantly related to the distribution of the benthic communities, selected in 5 of the 7 Community Distribution Models (CDM). Using the CDM expressions and maps of the environmental variables, probability maps were produced for the distribution of each community. Their combination allowed to obtain a final map of the most probable benthic communities throughout the study area, showing a high agreement (81%) between the observed and the predicted distributions. The maps produced in this study are valuable tools for the decision-making process involved in the management of the marine environment and their resources, for instance to classify these habitats according to the European nature information system (EUNIS) and in the scope of the Marine Strategy Framework Directive.

Large-Scale Distribution of the European Seahorses (Hippocampus Rafinesque, 1810): A Systematic Review.

Simple SummaryPopulations of many marine species are threatened by a number of interacting factors, including anthropogenic activities, climate change, and biodiversity loss. The assessment of the conservation status of such populations relies heavily on several types of data, such as large-scale geographical and ecological distribution. Seahorses are charismatic fish sensitive to environmental pressures, and according to the IUCN directive 95/2020, they should be considered a model for environmental quality assessment. As in many other areas, the data on seahorse ecological distribution in Europe are scattered, patchy, and mainly focused on small-scale studies. Therefore, we undertook a systematic review using the PRISMA protocol to identify the current knowledge status, detect gaps, and propose future research priorities. We analyzed 32 years of published studies and described the distribution of Hippocampus guttulatus and H. hippocampus across 176 sites in the Atlantic Ocean, Mediterranean Sea, and Black Sea as a function of habitat, depth, and degree of confinement. The applied method evidenced the overall lack of a detailed habitat description in published studies. Seahorse conservation would benefit from an analytical description of habitats, such as data on the depth, nature of the substrate, and associated biological communities, as well as the use of a standardized habitat classification system, such as formally recognized EUNIS habitat codes.Human pressures on marine ecosystems have caused extensive degradation of marine habitats and several local extinctions. Overexploitation and destructive fishing practices are responsible for biodiversity loss in many coastal ecosystems. The definition of conservation programs in marine fish requires comprehensive knowledge on large-scale geographical distribution, while considering distribution/abundance patterns in relation to key environmental variables. Due to their life-cycle traits, the two European seahorses (Hippocampus guttulatus and H. hippocampus), as with other congeneric species, are particularly sensitive to the effects of anthropogenic activities and habitat changes. However, information on the ecological distribution of these two species is scattered, patchy, and mainly focused on small-scale studies. In this paper, we followed an international standard protocol for systematic reviews (the PRISMA protocol) to provide a detailed assessment of the two species’ geographical distribution in relation to the environmental characteristics. According to the 134 analyzed studies, Hippocampus guttulatus is more common in confined areas, while H. hippocampus is found in marine shelf waters. With several interspecific differences, seagrasses were the most used holdfasts of both species. The EUNIS codes (European nature information system) referring to a specific and unique habitat were discussed as a potential tool for defining the ecological distribution of the two species. The obtained results and their future implementation could help plan conservation actions.

Habitat Classification of Cilo Glaciers and Their Surroundings

This study was carried out in 2018-2019 for the purpose of habitat classification of the Cilo glaciers and their surroundings, which have significant biodiversity within the borders of the National park of Hakkari Province and have been under serious threat especially due to global climate change in recent years. As a result of the studies, 11 habitat types were determined on the area according to habitat types of The European Nature Information System (EUNIS) and observations about these habitats were given. In addition, 4 types of vegetation are determined according to the plant density with satellite images of the area. This research reveals the importance of habitat type determination studies for important nature areas

Two different new Tamarix smyrnensis Bunge associations on the Yeşilırmak Delta Plain (Samsun/Türkiye)

The aim of this paper is to deal with syntaxonomical and ecological characteristics of Tamarix smyrnensis communities developed on both salt marsh and riparian habitats of the Yeşilırmak Delta Plains. The floristic composition of the communities was analysed by Braun-Blanquet method and the effect of edaphic parameters on the communities were determined using ordination techniques (CCA). The habitat types were identified according to the European Nature Information System (EUNIS) habitat coding list. Junco acuti-Tamaricetum smyrnensis ass. nov. developed on salt marshes and belonging to the alliance of Tamaricion tetragynae, and Tamaricetum tetrandrae-smyrnensis ass. nov. developed on meander banks/river island (eyot) and belonging to the alliance of Rubo sancti—Nerion oleandri distributed under influence of electrical conductivity (EC) of soil. Additionally, it was observed that both associations belonged to subunits of Mediterraneo-Macaronesian tamarisk thickets according to EUNIS.

Syntaxonomy of steppe depression vegetation of Ukraine

Aims: To revise the syntaxonomy of the vegetation of steppe depressions (pody), in particular (1) to identify the associations and to reveal their environmental, structural and compositional peculiarities; (2) to assign the associations to higher syntaxa; and (3) to correct nomenclatural aspects according to the ICPN.Study area: Steppe zone of Ukraine, Left-Bank of the Lower Dnieper basin.Methods: 641 relevés were included in the final analysis in the PCOrd program integrated into Juice software. Two expert systems (EVC and EUNIS-ESy) were used to assign relevés to vegetation classes and to EUNIS units.Results: The analysis resulted in nine clusters, which were interpreted asFestuco-Brometea(two units),Molinio-Arrhenatheretea(three units),Isoёto-Nanojuncetea(three units) and one derivate community of theFestuco-Puccinellietea. Detailed characteristics of the species composition, structure, distribution, and environmental conditions are provided for each unit. According to the DCA ordination, the leading factors of the syntaxa differentiation are soil moisture and fluctuating water level.Conclusions: We could clarify the placement of steppe depression vegetation in the system of syntaxonomic units of Europe. The previously described syntaxa of the rank of alliance (Myosuro-Beckmannion eruciformis), suballiance (Galio ruthenici-Caricenion praecocis), and six associations are validated. Two associations and two subassociations are described as a new to science.Taxonomic references: Euro+Med PlantBase (https://www.emplantbase.org), except Mosyakin and Fedoronchuk (1999) forPhlomis scythicaKlokov & Des.-Shost. andTulipa scythicaKlokov & Zoz.Syntaxonomic references: Mucina et al. (2016) for syntaxa from alliance to class level; Dubyna et al. (2019) for associations.Abbreviations: DCA = Detrended Correspondence Analysis; DES = Didukh Ecological Scales; EUNIS = European Nature Information System; EVC = EuroVegChecklist; GIVD = Global Index of Vegetation-Plot Databases; ICPN = International Code of Phytosociological Nomenclature.

Shrubland habitats in Dragoman municipality: a case study from western Bulgaria

The current research focuses on the investigation of shrubland vegetation in Dragoman municipality. The study is motivated by the willingness of the authors to check the shrubland habitats’ territorial extent and their importance to ecosystem processes, following the increased degree of succession over the last three decades. On the other hand, governmental subsidizing has been common for the last decade, leading to a clearance of lands with shrubs. Shrublands were studied through the application of the Braun-Blanquet approach and were defined by the European Nature Information System (EUNIS) classification. One main habitat type with three subtypes have been defined. Those are the Subcontinental and continental deciduous thickets (F3.24) that covers the largest area, Peri-Pannonic dwarf almond scrub (F3.24122), Moesian oriental hornbeam thickets (F3.2431), Moesian lilac thickets (F3.2432), covering a total area of 52.32 km2. Secondary succession has to be considered among the main reasons for shrubland distribution. The lower number of grazing animals and forest clearings act as boosters for this ecological process. Large areas in Dragoman municipality are characterized also by shallow soils that are unable to sustain forest vegetation, thus giving way to shrubs.

Combined use of environmental and spectral variables with vegetation archives for large-scale modeling of grassland habitats

Grassland habitats provide many ecosystem services but are threatened by agricultural intensification and urbanization. While the lack of accurate and comprehensive inventories at the national scale makes them difficult to manage, advances in spatial modeling using open remote sensing data and open-source software, as well as the increasing use of ecological archives, provide new perspectives for mapping natural habitats. In this context, this study evaluated the contribution of spectral and environmental variables to discriminate and then map grassland habitats throughout France. To this end, 92 spectral variables derived from moderate-resolution imaging spectroradiometer data, 19 bioclimatic variables derived from WorldClim data, 4 topographic variables derived from the European Union Digital Elevation Model (DEM), and 8 soil variables derived from SoilGrids data were combined at a spatial resolution of 250 m. Reference plots that characterized 6 and 21 grassland ecosystems at European Nature Information System (EUNIS) levels 2 (broad habitats) and 3 (habitats), respectively, were collected from vegetation archives. We first performed descriptive analysis that included habitat description, ordination, and pairwise separability. We then performed predictive analysis of grassland habitats using a cross-validated random forest model that included a spatial constraint. While environmental and spectral variables characterized most grassland habitats well and consistently, some confusion occurred between habitats with similar abiotic conditions. The main grassland habitat types were correctly mapped at EUNIS level 2 ( F1 score = 0.68), but not at EUNIS level 3 ( F1 score = 0.52). In addition, the two variables that contributed most to the model were the near-infrared spectral band in spring and the minimum temperature of the coldest month. The model’s prediction at EUNIS level 2 for mainland France provides the map of grassland habitats at a new spatial scale.

Earth Observation and Biodiversity Big Data for Forest Habitat Types Classification and Mapping

In the light of the “Biological Diversity” concept, habitats are cardinal pieces for biodiversity quantitative estimation at a local and global scale. In Europe EUNIS (European Nature Information System) is a system tool for habitat identification and assessment. Earth Observation (EO) data, which are acquired by satellite sensors, offer new opportunities for environmental sciences and they are revolutionizing the methodologies applied. These are providing unprecedented insights for habitat monitoring and for evaluating the Sustainable Development Goals (SDGs) indicators. This paper shows the results of a novel approach for a spatially explicit habitat mapping in Italy at a national scale, using a supervised machine learning model (SMLM), through the combination of vegetation plot database (as response variable), and both spectral and environmental predictors. The procedure integrates forest habitat data in Italy from the European Vegetation Archive (EVA), with Sentinel-2 imagery processing (vegetation indices time series, spectral indices, and single bands spectral signals) and environmental data variables (i.e., climatic and topographic), to parameterize a Random Forests (RF) classifier. The obtained results classify 24 forest habitats according to the EUNIS III level: 12 broadleaved deciduous (T1), 4 broadleaved evergreen (T2) and eight needleleaved forest habitats (T3), and achieved an overall accuracy of 87% at the EUNIS II level classes (T1, T2, T3), and an overall accuracy of 76.14% at the EUNIS III level. The highest overall accuracy value was obtained for the broadleaved evergreen forest equal to 91%, followed by 76% and 68% for needleleaved and broadleaved deciduous habitat forests, respectively. The results of the proposed methodology open the way to increase the EUNIS habitat categories to be mapped together with their geographical extent, and to test different semi-supervised machine learning algorithms and ensemble modelling methods.

Monitoring and Recording Changes in Natural Landscapes: A Case Study from Two Coastal Wetlands in SE Italy

This study analyzed and evaluated the changes that occurred in two coastal wetlands, characterized by complex and fragmented landscape patterns, in Southern Italy, which were monitored over a period of seven years from 2007 to 2014. Furthermore, the performances of two Land Cover (LC) and habitat taxonomies, compared for their suitability in mapping the identified changes, were assessed. A post-mapping method was adopted to detect the habitat/LC changes that occurred in the study period. Various changes were identified, both inter-class changes (class conversions) and intra-class changes (class modifications), and quantified by means of transition matrices. Conversions were easily mapped, while the modification mapping depended on the taxonomy adopted: the Land Cover Classification System (LCCS) allowed the detection of morpho-structural changes in woody vegetation, but the European Nature Information System (EUNIS) showed a higher thematic resolution for the salt marsh types. The detected changes were related to specific impacts, pressures and underlying factors. Landscape indices highlighted different trends in landscape richness and complexity in the two sites. Changes are occurring very quickly in the observed coastal sites and the ongoing dynamics are strictly related to their small size and complexity. For effective monitoring and detection of change in these environments, the coupling of EUNIS and LCCS is suggested.

Predicting Plant Communities in the Vicinity of Wheat Crops and Vineyards in Europe using Participatory Modeling

The risk assessment of pesticide use on non-target terrestrial plants is currently based on standardized greenhouse tests with a limited number of mostly crop plant species. Higher tier tests or assessments of any kind (e.g., field, semi-field, landscape studies) are not standardized. In this study we explored an approach to inform such a higher level by collecting datasets and information at European scale to characterize the vegetation communities that are likely to grow in the off-field areas of wheat and vine crops. The EUNIS (European Nature Information System) habitat classification was used to identify eight man-made habitats considered characteristic of the off-field areas in the European agricultural landscape. These habitats are spatially identified on the bases of a modelling process where vegetation plots, taken from the European Vegetation Archive, were used as observations and climate, soil, topographic, population density parameters and Remote Sensed Essential Biodiversity Variables as predictors. This modelling results in habitat suitability maps. The habitats are also described in terms of species frequencies and abundances, and to plant traits underlying possible vulnerability to pesticide exposure requested from the TRY plant trait database. Wheat and vine crop spatial data were derived from EUROSTAT and the QUICKScan methodology was used to combine all these data. We conclude that this method is helpful in reaching the objective as described in this paper. Its potential is that it can be extended probabilistically or linked to plant effect models.