The aim of the study was to compare in situ and remote sensing data, in order to assess the applicability of satellite images in water quality monitoring of floodplain lakes. Two indicators of trophic status were compared: chlorophyll a and total suspended matter. Two lakes on Lower Danube floodplain were selected: Srebarna and Malak Preslavets. Data were obtained in July and August 2018. Sentinel 2 MSI L1c images were analyzed in SeNtinel Application Platform (SNAP), (v. 6.0). According to in situ data, Srebarna Lake indicated status of eutrophication, while Malak Preslavets experienced hypertrophic conditions. Satellite data indicated eutrophic conditions for both lakes. Comparing the results from in situ and satellite data, chlorophyll a showed higher correlation (r = 0.66) and comparable results. On the other hand, significantly overestimation of suspended matter according to satellite data were found, as well weaker correlation (r = 0.57) between both methods. Remote sensing i.e. Sentinel products are emerging as a powerful tool in environmental observation. Although weather conditions could have significant impact on environmental dynamic especially in floodplain lakes, combining and comparing of different methods could improve the preciseness of the methodology as well as assessment reliability.

The rainbow trout Oncorhynchus mykiss is non-indigenous species for Europe, with numerous records for occurrence, spawning and self-sustaining populations across the continent. The species has been found in surface water bodies in Bulgaria but naturally-reproducing have not been yet detected. In 2020, 2021 and 2022, we observed spawning behaviour of mature fish in the Ogosta River, downstream of Ogosta Reservoir, north-western Bulgaria. In order to verify whether the rainbow trout reproduces naturally in Bulgaria, complete process of spawning was tracked. Through the winter-spring period of 2022, fish material was sampled from the trout redds and identified via DNA analysis. The results showed that rainbow trout reproduce successfully in the sampled river stretch. Vital specimens at stages of egg and fry development were found through the whole period, from February to April. The registered water temperature and recent flow management occurred as beneficial for the periods of rainbow trout spawning, egg development as well as fry emergence.

One of the most evident consequences of eutrophication of waters is the progressive spreading of persistent cyanobacterial blooms. They are often accompanied by the production of cyanotoxins in concentrations, which are hazardous for human health. In this research, we analysed phytoplankton communities in four lowland water bodies, for the presence of cyanobacterial blooms and toxin production. The cyanobacterial biovolumes we found, determine three of the lowland water bodies: Onogur Reservoir (OR), Asparuhov Val Reservoir (AVR), and Srebarna Lake (SL) as “Alert Level 1” of potentially hazardous levels of cyanotoxins. Cyanobacterial biovolume exceeds the threshold value of 8 mm3 L-1 (recreational waters) in AVR and SL at the end of the summer period. In OR, we registered sustainable bloom of Microcystis spp. during the whole summer season, and extremely high average seasonal value of the total biovolume (146.5 mm3 L-1). Micro-cystins were reported in all four analysed water bodies, with the highest concentration in OR (6 µg L-1). Cylindrospermopsin was detected in AVR and OR, while saxitoxins were in AVR and SL. The concentrations of cyanotoxins do not exceed the guideline values in recreational waters. However, the increased biovolumes of cyanobacteria are a signal that in three of the analysed water bodies, monitoring is recommended at the levels of cyanotoxins during the summer period.

Hydrological alteration is among the principal drivers of ecological change in floodplain wetlands, affecting ecosystem functioning, biodiversity, nutrient cycling and the provision of ecosystem services. Distinguishing natural variability from long-term environmental change requires sustained observations based on harmonised monitoring protocols. As part of the Bulgarian Long-Term Ecosystem Research Network (LTER-BG) and the Integrated European Long-Term Ecosystem, Critical Zone and Socio-Ecological Research Infrastructure (eLTER), Lake Srebarna Biosphere Reserve provides a unique natural laboratory for studying ecosystem responses to hydrological modification, ecological restoration and climate variability in one of Europe’s most valuable floodplain wetlands. The hydrology and ecological functioning of Lake Srebarna have been closely linked to its connection with the Danube River. The interruption of this connection following the construction of the protective embankment in 1949 fundamentally changed the lake’s hydrological regime. In 1978, restoration activities were limited to partial dyke removal, while the construction of the Eastern (1994) and Western (2023) Channel—have aimed to improve the water exchange and recover natural ecosystem processes. These successive alterations make Srebarna an exceptional model system for evaluating ecological responses to both hydrological degradation and restoration efforts under increasing climatic variability. The study presents recent observations (2023-2026) generated as part of the long-term environmental monitoring at Lake Srebarna eLTER Site. Approximately 250 monthly samples collected from seven representative monitoring stations were analysed, encompassing open-water areas, channels, groundwater springs, and the Danube River. The monitoring network was designed to capture the principal hydrological gradients and environmental heterogeneity of the ecosystem. Standardised field observations and laboratory analyses were used to characterise the hydrological, physicochemical and hydrochemical conditions, the nutrient dynamics and the indicators of ecosystem functioning, providing one of the most comprehensive up-to-date datasets describing the overall current status of the wetland. The obtained data revealed pronounced seasonal variability together with considerable spatial heterogeneity in the studied abiotic variables. The period was characterised by lack of sufficient flooding events and persistently low water levels, resulting in the desiccation of vast areas of peripheral pools, reduced or absent lateral connectivity within the lake and increased physicochemical differentiation among the sampling sites. These hydrological conditions influence the nutrient dynamics and physicochemical processes, and ultimately affect the overall ecosystem functioning. The spatial differences among monitoring stations further demonstrate the combined effects of natural environmental gradients and anthropogenic hydromorphological modifications, highlighting the importance of maintaining an integrated long-term monitoring network capable of detecting ecological responses to ongoing environmental changes. The observed shifts in the hydrological connectivity and physicochemical conditions indicate changes in the habitat quality and ecosystem processes, revealing the role of the water regime as the principal driver of ecological functioning in the wetland. The generated dataset establishes a baseline for distinguishing natural seasonal variability from long-term changes associated with hydrological alteration and provides a valuable basis for evaluating the effectiveness of recent restoration measures aimed at improving the hydrological connectivity between the wetland and the Danube. Beyond documenting environmental conditions, the data demonstrates the value of long-term ecological observations for translating scientific evidence into informed adaptive management. By contributing harmonised long-term observations to the eLTER research infrastructures, the study supports ecosystem restoration, biodiversity conservation and climate-change adaptation while reinforcing the role of long-term ecosystem research in the sustainable management of protected floodplain wetlands.

Background When working with stakeholders, context and presentation are of utmost importance since users seldom have the knowledge and motivation to comprehend and critically analyse data. This is especially so for ecologists whose knowledge is not immediately related to many of the stakeholders' daily life or economic activities and hence is often beyond - or in some cases in direct conflict with - their everyday activities. Reliance on the scientist's interpretation based on scientific analysis and its subsequent visualisation in the form of graphs, tables etc. has a number of limitations: Data is only one form of knowledge for characterising socio-ecological systems. Non-data knowledge includes both important persistent descriptive characteristics of an ecosystem ("Srebarna is a hyper-eutrophic lake"), and shared socio-cultural context implicitly acknowledged by both sides ("Bai Ganyo is an exporter of essential oil from Rosa damascena in the classic 19th century satiric fiction by Aleko Konstantinov, a part of Bulgaria's literary heritage.") Discrepancies in implicit knowledge: common scientific knowledge not explicitly mentioned in research papers whose omission deprives non-specialist readers of important context. This can cause numerous biases in verbal and written communication (Kellerman 2007, Ahlert et al. 2016). Specialisation limits the knowledge of individual scientists so their work does not contain all information about the model ecosystem that the stakeholders need for informed decision-making; larger scientific teams, on the other hand, require careful wording for clarity and brevity when communicating their finding about complex ecosystem processes. Data is only one form of knowledge for characterising socio-ecological systems. Non-data knowledge includes both important persistent descriptive characteristics of an ecosystem ("Srebarna is a hyper-eutrophic lake"), and shared socio-cultural context implicitly acknowledged by both sides ("Bai Ganyo is an exporter of essential oil from Rosa damascena in the classic 19th century satiric fiction by Aleko Konstantinov, a part of Bulgaria's literary heritage.") Discrepancies in implicit knowledge: common scientific knowledge not explicitly mentioned in research papers whose omission deprives non-specialist readers of important context. This can cause numerous biases in verbal and written communication (Kellerman 2007, Ahlert et al. 2016). Specialisation limits the knowledge of individual scientists so their work does not contain all information about the model ecosystem that the stakeholders need for informed decision-making; larger scientific teams, on the other hand, require careful wording for clarity and brevity when communicating their finding about complex ecosystem processes. Ontology-based approach to communication In this work, we present the use of machine-readable formalised ontologies that contain known and inferred facts about relations within the ecosystem in the form Subject-Predicate-Object. This form of presenting relations is significantly more expressive than the fuzzy knowledge graphs used in socio-ecological research. For example, "Pelecanus crispus had X nesting pairs in year Y" is a relationship that cannot be denoted as positive or negative in the typical fuzzy cognitive network out of the context of a dataset with Pelecanus population trends. Furthermore, ontologies allow for different relations between the same objects such as food competition between two species and expressing their taxonomic relation, annotating hierarchies such as the taxonomic relationships or the elements of a standard observation, authorship and sources, etc. in a machine readable and unambiguous manner. Our ontology production workflow uses an AI-in-the-loop extraction of information from publications, its linking to historical data and standard observation datasets (including the ones published in the eLTER data repository as open datasets), and reasoning across these sources of heterogeneous information to create a flexible representation of the ecosystem complexities. We use the Ontotext graph tools dataset - GraphDB and OntoRefine. A sufficiently comprehensive ontology can contain tens of thousands of factual and inferred relationships and by itself is not a suitable tool for stakeholder communication. However, querying the complex ontology to retrieve a subset of the knowledge therein (referred to as ontoset), allows for extracting the information pertinent to a given communication topic and its reuse for simplified but factual communication with one or more target groups. We present two cases of stakeholder communication basing on ontologies about two model ecosystems - the lake ecosystem of biosphere reserve Srebarna and the agroecosystems of the Valley of Roses. For both model ecosystems, we create ontologies from heterogeneous sources. We then proceed to extract thematic ontosets for the target audience and use the ontoset for specific communication purposes (Fig. 1). In the case of lake Srebarna, we present a set of games developed for the Science day (September, 2026) basing on a subset of the ontology about Srebarna that includes trophic and habitat interactions, historic and fun facts about Srebarna from Michev and Iliev (1982) and the experience of the Srebarna research team, as well as information about the method and significance of standard observations performed in the site. The games are intended to support system thinking and engage the most interested citizen scientists (school and university students and interested adults - teachers, parents). They can be given opportunity for job shadowing the researchers during actual fieldwork and performing simple observations. In the case of the future socio-ecological platform Valley of Roses, we present the transition from an earlier knowledge graph to an ontology containing information about the characteristic crops in the region - essential oils from Rosa damascena and Lavandula angustifolia. The ontology links the ecosystem data collected in an ongoing seed funding project to create the platform, existing data from research and other projects, as well as ecosystem information extracted from textual publications, with social and economic data derived from interviews and a survey. We present the way businesses - farmers, distilleries, traders, local tourism and attractions, can interact with rose oil ontoset, including the yield parameters for rose oil, the influence of specific pests, and links to national and international legislation, market and customer requirements and the rose as an iconic tourist attraction. The presented work demonstates a workflow for processing and semantically linking heterogeneous information from transdisciplinary research teams with AI-in-the-loop. We use a structured approach to present facts free of hallucination and context deviations - the main shortcomings of current AI models. This approach supports the formalisation and reproducibility of socio-ecologic research and stakeholder involvement using the new tools for extracting actionable insights from big data that became available in the last years.