Search Results (9)

This research presents a comprehensive analysis of the spatial extent and temporal change in benthic habitats within the Puck Lagoon in the southern Baltic Sea, utilizing integrated machine learning classification and multi-sourced remote sensing. Object-based image analysis was integrated with Random Forest, Support Vector Machine, and K-Nearest Neighbors algorithms for benthic habitat classification based on airborne bathymetric LiDAR (ALB), multibeam echosounder (MBES), satellite bathymetry, and high-resolution aerial photography. Ground-truth data collected by 2023 field surveys were supplemented with long temporal datasets (2010–2023) for seagrass meadow analysis. Boruta feature selection showed that geomorphometric variables (aspect, slope, and terrain ruggedness index) and optical features (ALB intensity and spectral bands) were the most significant discriminators in each classification case. Binary classification models were more effective (93.3% accuracy in the presence/absence of Zostera marina) compared to advanced multi-class models (43.3% for EUNIS Level 4/5), which identified the inherent equilibrium between ecological complexity and map validity. Change detection between contemporary and 1957 habitat data revealed extensive Zostera marina loss, with 84.1–99.0% cover reduction across modeling frameworks. Seagrass coverage declined from 61.15% of the study area to just 9.70% or 0.63%, depending on the model. Seasonal mismatch may inflate loss estimates by 5–15%, but even adjusted values (70–94%) indicate severe ecosystem degradation. Spatial exchange components exhibited patterns of habitat change, whereas net losses in total were many orders of magnitude larger than any redistribution in space. These findings recorded the most severe seagrass habitat destruction ever described within Baltic Sea ecosystems and emphasize the imperative for conservation action at the landscape level. The methodology framework provides a reproducible model for analogous change detection analysis in shallow nearshore habitats, creating critical baselines to inform restoration planning and biodiversity conservation activities. It also demonstrated both the capabilities and limitations of automatic techniques for habitat monitoring. Full article

Floristic and biodiversity knowledge play a crucial role in ecosystem conservation and sustainable land management, particularly in urban-rural contexts that can serve as biodiversity reservoirs, hosting species of high biogeographic value. Focusing on the new municipality of Misiliscemi, established in 2021 in Sicily and now facing the challenge of developing new management strategies, this study provides fundamental knowledge on the plant biodiversity of the area and explores how the integration of floristic and environmental data can guide territorial planning strategies aimed at preserving natural capital and ecosystem services. The research, based on field surveys conducted over many years, taxonomic identification of species, analysis of biological forms and chorological data, evaluation of ecological indicators, and GIS-based habitat mapping according to the EUNIS classification, has made it possible to obtain a comprehensive dataset. The results of this work led to the identification of 623 taxa, recording new findings for the Sicilian flora, including both native and alien species, which represent primary biodiversity data crucial for plant resource management. In addition, 42 habitat types were mapped, highlighting that approximately 80% of the territory is occupied by vegetated man-made habitats. Despite anthropogenic pressures and landscape modifications, Misiliscemi retains significant plant biodiversity, including habitats and species of conservation interest, that represent a vital resource for natural capital and ecosystem services. This knowledge base, in addition to constituting the scientific foundation upon which this young municipality can develop an urban planning strategy aimed at achieving sustainable local development, also represents a methodological approach that highlights how basic knowledge of urban biodiversity should be considered a crucial aspect of sustainable urban planning worldwide. Full article

On a global scale, wetlands are suffering from a steady decline in surface area and environmental quality. Protecting them is essential and requires a careful spatialisation of their natural habitats. Traditionally, in our study area, species discrimination for floristic mapping has been achieved through on-site field inventories, but this approach is very time-consuming in these difficult-to-access environments. Usually, the resulting maps are also not spatially exhaustive and are not frequently updated. In this paper, we propose to establish a complete map of the study area using remote sensors and set up a long-term and regular observatory of environmental changes to monitor the evolution of a major French wetland. This methodology combines three dataset acquisition technologies, airborne hyperspectral and WorldView-3 multispectral images, supplemented by LiDAR images, which we compared to evaluate the difference in performances. To do so, we applied the Random Forest supervised classification methods using ground reference areas and compared the out-of-bag score (OOB score) as well as the matrix of confusion resulting from each dataset. Thirteen habitats were discriminated at level 4 of the European Nature Information System (EUNIS) typology, at a spatial resolution of around 1.2 m. We first show that a multispectral image with 19 variables produces results which are almost as good as those produced by a hyperspectral image with 58 variables. The experiment with different features also demonstrates that the use of four bands derived from LiDAR datasets can improve the quality of the classification. Invasive alien species Ludwigia grandiflora and Crassula helmsii were also detected without error which is very interesting when applied to these endangered environments. Therefore, since WV-3 images provide very good results and are easier to acquire than airborne hyperspectral data, we propose to use them going forward for the regular observation of the Brière marshes habitat we initiated. Full article

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). Full article

Due to global climate change and increased forest transformation by humans, accounting for the dynamics of forest ecosystems is becoming a central problem in forestry. We reviewed the success of considering vegetation dynamics in the most influential ecological forest classifications in Russia, the European Union, and North America. Out of the variety of approaches to forest classification, only those that are widely used in forestry and forest inventory were selected. It was found that the system of diagnostic signs developed by genetic forest typology based on the time-stable characteristics of habitats as well as the developed concept of dynamic series of cenosis formation allows us to successfully take into account the dynamics of vegetation. While forest dynamics in European classifications is assessed at a theoretical level, it is also possible to assess forest dynamics in practice due to information obtained from EUNIS habitat classification. In ecological classifications in North America, the problem of vegetation dynamics is most fully solved with ecological site description (ESD), which includes potential vegetation and disturbance factors in the classification features. In habitat type classification (HTC) and biogeoclimatic ecosystem classification (BEC), vegetation dynamics is accounted based on testing the diagnostic species and other signs of potential vegetation for resistance to natural and anthropogenic disturbances. Understanding of vegetation–environment associations is fundamental in forming proper forest management methods and improving existing classification structures. We believe that this topic is relevant as part of the ongoing search for new solutions within all significant forest ecological classifications. Full article

In climbing plants, fruits can be formed at different heights, depending on the height of external support. However, the effect of height on fruit and seed traits in invasive vines of Cucurbitaceae has not been intensively studied so far. In Europe, Echinocystis lobata, a North American member of Cucurbitaceae, is considered one of the most abundant invasive alien plants spreading in natural riparian forests, thickets, and tall herbs, whereas it is a rare species in urban woodlands. In this study, we tested the variability of selected fruit and seed traits of E. lobata in connection with habitat origin (natural, semi-natural, and anthropogenic), habitat type (using the EUNIS habitat classification), height (the distance between the fruit and the ground), and geographical position. The study was conducted in 2018 in 65 sites located in Latvia, Lithuania, Poland, and Slovakia. In each study site, a random sample of 10 fresh mature fruits of E. lobata was collected from subsequent 0.50 m intervals of height. The length, the width, and the weight of the fresh fruits, as well as the total number of seeds and number of undeveloped seeds per fruit, were examined. Moreover, the well-developed seeds from selected study sites were weighed. The statistical analysis showed the significant effect of habitat origin, habitat type, and height on most of the studied fruit and seed traits. The largest range of height (from 0.00 to 4.00 m) was observed in two types of habitats (F—heathland, scrub, and tundra; and G—woodland, forest, and other wooded land). The total number of seeds per fruit was positively correlated with the length, width, and weight of the fresh fruits. The fruits were a little heavier and bigger in natural habitats located in the northeast of the study area. The distribution of fruits at different heights may contribute to better dispersal of seeds by animals and wind, and may also better protect the seeds from being eaten by granivorous animals. The defence against seed-eating animals is expected to be stronger in semi-natural habitats, as well as on banks and shores of inland surface waters, where the seed production is the highest. The influence of seed traits on seed germination and seedling survival in various habitats and their importance in the invasiveness of E. lobata require further study. Full article

The present study aims to discriminate four semi-arid grassland habitats in a Mediterranean Natura 2000 site, Southern Italy, involving 6210/E1.263, 62A0/E1.55, 6220/E1.434 and X/E1.61-E1.C2-E1.C4 (according to Annex I of the European Habitat Directive/EUropean Nature Information System (EUNIS) taxonomies). For this purpose, an intra-annual time-series of 30 Sentinel-2 images, embedding phenology information, were investigated for 2018. The methodology adopted was based on a two-stage workflow employing a Support Vector Machine classifier. In the first stage only four Sentinel-2 multi-season images were analyzed, to provide an updated land cover map from where the grassland layer was extracted. The layer obtained was then used for masking the input features to the second stage. The latter stage discriminated the four grassland habitats by analyzing several input features configurations. These included multiple spectral indices selected from the time-series and the Digital Terrain Model. The results obtained from the different input configurations selected were compared to evaluate if the phenology information from time-series could improve grassland habitats discrimination. The highest F1 values (95.25% and 80.27%) were achieved for 6210/E1.263 and 6220/E1.434, respectively, whereas the results remained stable (97,33%) for 62A0/E1.55 and quite low (75,97%) for X/E1.61-E1.C2-E1.C4. However, since for all the four habitats analyzed no single configuration resulted effective, a Majority Vote algorithm was applied to achieve a reduction in classification uncertainty. Full article

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. Full article

Biotic homogenization is an expected effect of biological invasions. Invasive alien species typically show great adaptability to a wide range of environmental conditions and may expand into different habitats, thus reducing the dissimilarity among the recipient communities. We tested this assumption by analyzing a comprehensive database (78 species × 229 samples) collected between 2012 and 2017 in the marine protected area of Portofino (NW Italy), where Caulerpa cylindracea, one of the worst invaders in the Mediterranean Sea, exhibits high substratum cover at depths between 1 m and 45 m in 14 different communities (identified according to the European Nature Information System EUNIS for habitat classification). Five samples for each of the eight depth zones (i.e., 5 m, 10 m, 15 m, 20 m, 25 m, 30 m, 35 m, and 40 m) were randomly re-sampled from the comprehensive database to produce a dataset of 67 species × 40 samples. Then, a second dataset of 66 species × 40 samples was simulated by excluding Caulerpa cylindracea. Both re-sampled datasets underwent multivariate analysis. In the presence of C. cylindracea, the overall similarity among samples was higher, thus indicating homogenization of the rocky reef communities of Portofino Marine Protected Area. Continued monitoring activity is needed to understand and assess the pattern and extent of C. cylindracea’s inclusion in the recipient ecosystems. Full article