Planktonic Trophic Transitions in the Black Sea: Functional Perspectives and Ecosystem Policy Relevance

Abstract

Phytoplankton–mesozooplankton interactions play a central role in shaping Black Sea food web dynamics, yet their trophic coupling has been insufficiently investigated in policy-relevant frameworks. This systematic review of 86 peer-reviewed studies (1987–2025) synthesizes research trends, limitations, and knowledge gaps in the field. The analysis reveals a clear dominance of work on plankton community structure (81%), whereas topics such as modeling and scenario analysis (7%), ecosystem assessment (7%), and bloom dynamics and seasonality (5%) remain comparatively underrepresented. Post-2020 publications indicate a promising shift toward scenario-based frameworks, gelatinous zooplankton impacts, and trait-based indicators, although functional integration remains fragmented. Keyword co-occurrence and network analyses revealed a concentration on nutrient–phytoplankton–zooplankton pathways, while other themes—such as bioluminescence and redoxcline dynamics—appeared only marginally represented in the literature we analyzed. To support ecosystem-based management under the Marine Strategy Framework Directive (MSFD), we highlight three priorities: improving NPZD-type models, using trophic efficiency metrics, and standardizing plankton indicators across the region. Strengthening the mechanistic understanding of planktonic trophic linkages is critical for improving food web assessments and adaptive marine governance in the Black Sea.

1. Introduction

Phytoplankton communities form the base of marine pelagic food webs and are key drivers of elemental cycling in oceanic systems through their role in primary production, carbon sequestration, and nutrient regeneration [1,2,3]. Phytoplankton strongly influence higher trophic levels by shaping zooplankton communities, which transfer energy from primary producers to fish and other consumers [4,5,6,7]. Their importance lies not only in biomass but also in traits such as size, motility, and nutrient use, which affect grazing, energy transfer, and food web connectivity [8,9,10,11,12]. Shifts in phytoplankton communities—for example, from diatoms to picoplankton or toxin-producing species—can reduce grazing efficiency and block energy transfer in the food web [2,13,14,15,16,17]. Such shifts often trigger cascading responses in mesozooplankton assemblages, manifesting as altered species dominance, recruitment failure, or shifts in life-history traits [1,5,18,19,20]. These processes are particularly consequential in mesotrophic and semi-enclosed systems, where the buffering capacity of the ecosystem is limited, and anthropogenic perturbations can lead to rapid trophic destabilization [14,21,22,23].

The Black Sea is a classic example of a marginal, strongly stratified marine basin exhibiting hypersensitivity to both climatic and anthropogenic drivers [24,25,26,27,28]. Characterized by a persistent halocline, a sharp redoxcline separating the oxic surface waters from anoxic deep layers, and steep nutrient gradients, the Black Sea functions as a transitional system with reduced vertical exchange and high retention of allochthonous inputs [29,30,31]. Since the onset of intense eutrophication in the 1970s—primarily due to nitrogen and phosphorus enrichment from the Danube and Dniester catchments—the region has undergone a series of profound ecological regime shifts [26,27,29,32,33,34]. These include the proliferation of opportunistic and bloom-forming phytoplankton taxa, the expansion of hypoxic zones, collapse of benthic macrofauna, and a shift in the trophic structure of the pelagic realm [27,35,36,37,38,39].

A particularly disruptive episode was the introduction and explosive spread of the invasive ctenophore Mnemiopsis leidyi, which severely depleted native mesozooplankton biomass through direct predation and competitive exclusion [4,32,40,41,42,43]. This event precipitated a collapse of the classical diatom–copepod–fish trophic pathway and facilitated the emergence of gelatinous-dominated food webs characterized by inefficient energy transfer, microbial loop dominance, and altered nutrient recycling dynamics [44,45,46,47]. Although the subsequent establishment of Beroe ovata partially mitigated the Mnemiopsis outbreak, the mesozooplankton community has not returned to pre-invasion structure or function, remaining dominated by omnivorous and opportunistic taxa [44,45,48].

Despite decades of research on phytoplankton and zooplankton communities in the Black Sea, most empirical investigations have treated these groups in isolation, resulting in a paucity of studies addressing their direct trophic coupling. This approach has limited progress in understanding how bottom-up and top-down processes interact, how mismatches between trophic levels occur, and how functional traits influence energy transfer under multiple stressors. Moreover, the limited temporal resolution and spatial extent of mesozooplankton datasets constrain our ability to validate ecosystem models, assess regime transitions, or develop robust ecological indicators [49,50].

These limitations carry important implications for the implementation of ecosystem-based management frameworks. Within the European Union’s Marine Strategy Framework Directive (MSFD), achieving a holistic assessment of Good Environmental Status (GES) requires an integrated understanding of food web dynamics, ecosystem functioning, and the responses of plankton communities to environmental pressures [4,51,52,53,54,55]. However, existing monitoring strategies remain disproportionately focused on phytoplankton biomass proxies (e.g., chlorophyll-a concentration) and taxonomic composition, with minimal consideration of phytoplankton quality, zooplankton functional diversity, or producer–consumer interactions. The operationalization of functionally relevant plankton indicators remains largely absent, particularly in the context of spatially coordinated, long-term ecological assessments [6,56,57].

In this context, the present study conducts a comprehensive systematic review of the peer-reviewed literature published between 1987 and 2025 that explicitly examines phytoplankton–zooplankton interactions in the Black Sea. The aims of this review are to:

• Synthesize existing knowledge on the temporal and spatial dynamics of phytoplankton–zooplankton trophic coupling, including responses to eutrophication, climate variability, and invasive species.
• Identify dominant thematic trends, methodological approaches, and functional knowledge gaps within the literature.
• Evaluate the degree to which phytoplankton–mesozooplankton interactions are incorporated into ecosystem-based monitoring frameworks and marine policy implementation, with particular emphasis on functional indicators and model-based assessments relevant to MSFD descriptors.

By adopting an integrative, trait-based, and ecosystem-oriented perspective, this review contributes to advancing the mechanistic understanding of trophic transfer processes in semi-enclosed marine systems. Our synthesis also offers a conceptual basis for strengthening plankton indicators and supporting adaptive management under pressures such as climate change, eutrophication, and biodiversity loss in the Black Sea and other semi-enclosed basins.

2. Materials and Methods

2.1. Literature Search Strategy

To capture the breadth of empirical and conceptual research on phytoplankton–zooplankton interactions in the Black Sea, a systematic literature search was conducted in the Web of Science Core Collection, covering the time span from 1987 to 2025. The search string was developed through an iterative process using key terms associated with plankton. The final query string included: (“Black Sea”) AND (“phytoplankton”) AND (“zooplankton”), yielding a total of 131 articles.

2.2. Inclusion and Exclusion Criteria

Studies were included in the review if they focused on phytoplankton and/or ooplankton within the Black Sea and incorporated data or conceptual analyses relevant to trophic interactions, bloom dynamics, or energy transfer. Eligible articles were original research papers published in peer-reviewed journals and contained sufficient metadata (e.g., abstract, keywords, institutional affiliation) to allow for thematic analysis.

Conversely, studies were excluded if they focused on regions outside the marine Black Sea basin, such as the Caspian Sea, the Sea of Azov, or freshwater systems. Additionally, purely methodological or remote sensing studies that lacked ecological interpretation were not considered. Articles that dealt exclusively with the description of a single taxon without contextual ecological relevance were also excluded.

The screening process resulted in a final, curated dataset of 86 articles deemed suitable for detailed analysis (

Table 1. The screening process used to identify relevant peer-reviewed papers on phytoplankton–zooplankton interactions in the Black Sea.

Step	Description	Count
Records Identified	Web of Science search results	133 papers
Records Excluded	Other basins/non-marine systems	47 papers
Studies Included	Black Sea marine-focused studies	86 papers

and Table S1).

2.3. Metadata Extraction and Standardization

Bibliographic metadata was extracted into Microsoft Excel for structured organization. Fields included the author(s), year, journal, study location, research topic, keywords, abstract, institutional affiliation, and methodological approach. To ensure terminological consistency across studies, the manual harmonization of keywords was conducted. Ambiguous or irrelevant keywords (e.g., “coastal pollution” without biological data) were excluded. Institutional affiliations were parsed to identify national contributions and regional coverage.

2.4. Chronological Analysis of Publication Output

To assess long-term patterns in research activity, the publication year of each included article was recorded and analyzed. Annual publication counts were used to generate a temporal distribution covering the period from 1987 to 2025. Temporal trends were visualized using line plots to highlight years of increased publication activity and to reveal broader decadal patterns. Emphasis was placed on detecting peaks in output and linking them to potential drivers such as regional collaboration efforts, emerging environmental concerns, and shifts in governance frameworks. This analysis was complemented by interpretative cross-referencing with thematic focus and keyword trends to understand how research priorities evolved across time.

2.5. Thematic Classification

To bring structure to the diversity of findings, each publication was assigned to a dominant thematic category. This was done through a close reading of abstracts and keywords. If the focus was unclear, the full text was reviewed for clarity.

Four key themes emerged as central to the body of literature:

• Plankton Community Structure: studies analyzing species composition, biomass, abundance, or ecological roles.
• Bloom Dynamics and Seasonality: investigations into bloom events, phenology, and seasonal patterns.
• Modeling and Scenario Analysis: works employing simulations, projections, or conceptual models.
• Ecosystem Assessment: research contributing to ecosystem health indicators, ecological status, or environmental policy frameworks.

When studies spanned multiple themes, classification was based on the primary research objective and methodological emphasis. Cross-cutting studies were tagged for secondary classification during the keyword clustering stage to acknowledge their integrative nature and ensure thematic consistency.

2.6. Keyword Co-Occurrence and Cluster Analysis

A keyword co-occurrence matrix was constructed to identify patterns of conceptual association between taxa, processes, and stressors. Co-occurrence frequency was calculated based on shared keyword appearances across studies. The resulting matrix was visualized using cluster heatmaps and conceptual network diagrams. To reduce dimensionality and highlight dominant trends, a filtered subset of the top 20 most frequent keywords was also analyzed separately.

2.7. Temporal Trend Analysis

To evaluate temporal dynamics in scientific focus, keyword usage was aggregated by year of publication. The top 10 most frequent keywords per year were tracked to identify emergent research priorities, particularly after major policy or ecological events (e.g., MSFD adoption in 2008, Mnemiopsis outbreaks). Publication trends were visualized through time-series plots and bar graphs, indicating peaks in thematic interest and evolving research directions.

2.8. Analytical Framework and Method Typology

To examine methodological patterns and conceptual shifts in the reviewed literature, each article was evaluated for the presence of three analytical dimensions: (i) functional process quantification (e.g., grazing rates, trophic transfer efficiency), (ii) coupled phytoplankton–zooplankton modeling frameworks (e.g., simulate the interactions of the four variables nutrients (N), phytoplankton (P), zooplankton (Z), and detritus (D) NPZD-type models), and (iii) analyses of environmental or anthropogenic drivers (e.g., eutrophication, hypoxia, climate variability). NPZD models simulate core trophic processes and nutrient cycling in marine ecosystems. In the reviewed literature, their use in the Black Sea remains limited and often uncoupled from empirical validation. Strengthening their application—especially when linked with functional traits—could enhance predictive assessments under MSFD Descriptor 4—Food Webs.

Studies were classified based on which of these components they incorporated. Descriptive statistics were used to determine the prevalence of single-method and multi-method studies. In addition, keyword co-occurrence networks were constructed using author-defined terms to map the conceptual relationships between plankton groups, stressors, and methodological tools.

A subset analysis focused on recent publications (2020–2025) to identify emerging research priorities. These studies were manually coded according to four predefined themes: (1) jellyfish blooms and trophic decoupling, (2) hypoxia-driven phytoplankton shifts, (3) fuzzy cognitive modeling and scenario tools, and (4) trait-based zooplankton indicators. Keyword co-occurrence matrices and modularity analyses were used to explore thematic clustering and conceptual integration across publications.

This approach allowed for both quantitative and qualitative insights into how Black Sea plankton research has evolved methodologically and thematically over the past four decades.

2.9. Data Analysis

To investigate structural similarities among the reviewed studies based on keyword composition, a multivariate exploratory analysis was conducted using the Shade Plot function in PRIMER v7 software [58]. Keyword frequency data were initially extracted and curated in Microsoft Excel, where synonymous terms were harmonized to reduce redundancy and improve comparability across studies. The cleaned matrix was then standardized and imported into PRIMER for analysis. Shade plots were generated to visualize the relative abundance and co-occurrence patterns of keywords across all publications. This ordination approach enabled the detection of conceptual clusters and thematic gradients within the dataset, revealing groups of studies that shared common focal points, such as eutrophication, hypoxia, invasive species, or modeling frameworks.

This analysis supported the identification of research gaps, thematic compartmentalization, and emergent areas of conceptual integration, offering a qualitative dimension to complement the quantitative assessment of publication trends and methodological typologies.

To explore emerging conceptual linkages, a co-occurrence analysis was performed on studies published between 2020 and 2025. Keyword pairs were extracted from abstracts and author keywords, and a co-occurrence matrix was constructed to capture ecological and methodological associations. Pairs with at least one co-occurrence were retained to highlight both dominant and emerging themes. The data were visualized using SankeyMATIC (https://sankeymatic.com, accessed on 10 July 2025), where flow width reflects the strength of co-occurrence between terms. This enabled the identification of core clusters—such as nutrient–phytoplankton–zooplankton interactions—as well as niche research areas including gelatinous zooplankton, bioluminescence, and redox dynamics.

3. Results

3.1. Temporal Trends in Research Output

The temporal distribution of the reviewed studies revealed an increasing trend in scientific interest regarding phytoplankton–zooplankton dynamics in the Black Sea (Figure 1). Research output remained low through the late 1980s and early 1990s, likely reflecting the post-Soviet transition period and reduced regional collaboration. A modest increase occurred between 1997 and 1999, concurrent with heightened ecological concern following the M. leidyi invasion. A second wave of studies emerged in the mid-2000s, aligning with the development of ecosystem modeling frameworks and the early discourse on ecosystem-based management. Publication frequency peaked in 2014 and again in 2024, corresponding to broader policy attention under the MSFD and rising interest in food web resilience under climate change. Despite these peaks, publication activity remained uneven over time (Figure 1).

3.2. Thematic Distribution of Studies

Analysis of the thematic distribution (Figure 2) reveals a strong dominance of studies focused on Plankton Community Structure, which accounted for 81% of the total. These publications primarily addressed species composition, abundance, and biomass trends, reflecting the foundational stage of research in Black Sea plankton ecology. In contrast, more process-oriented or integrative themes were substantially less represented. Only 7% of studies examined Modeling and Scenario Analysis, applying NPZD or trait-based models to simulate trophic interactions under environmental change. An additional 7% focused on Ecosystem Assessment, often linked to policy frameworks like MSFD. The least represented theme, Bloom Dynamics and Seasonality, appeared in just 5% of the studies, despite the ecological importance of phytoplankton bloom timing and its effects on mesozooplankton. This skewed thematic landscape underscores the limited attention to predictive, scenario-based, or management-relevant research, highlighting the need for broader methodological diversification and policy-oriented focus in future studies.

3.3. Keyword Co-Occurrence Patterns

The keyword co-occurrence heatmap (Figure 3) highlighted dominant conceptual linkages in the reviewed literature. Core ecological terms such as “Black Sea,” “zooplankton,” and “phytoplankton” co-occurred with high frequency, reflecting their central role in the research focus. These were strongly associated with “nutrients,” “chlorophyll,” and “eutrophication,” indicating sustained attention to bottom-up drivers and primary production processes. Taxon-specific terms like “calanus euxinus” and “noctiluca scintillans” appeared less frequently but formed distinct clusters, suggesting targeted studies on species-specific roles. In contrast, environmental stressors such as “river runoff,” “hydropower impact,” and “dam” showed weak co-occurrence with biological terms, implying limited integration of hydrological pressures into trophic-level studies.

Overall, the heatmap revealed a research landscape centered on nutrient-driven phytoplankton–zooplankton dynamics, with fragmented attention to other stressors and limited cross-taxa or cross-compartment linkages. This supports the broader finding that trophic coupling remains underexplored in a multi-stressor context.

Figure 4 presents a co-occurrence heatmap illustrating the frequency with which major plankton functional groups were associated with key environmental stressors in the reviewed literature. The matrix reveals distinct patterns of ecological alignment, reflective of both organismal traits and evolving environmental conditions in the Black Sea.

Diatoms and copepods exhibited the highest co-occurrence values with nutrient enrichment and eutrophication, consistent with their foundational role in classical phytoplankton–herbivore trophic pathways [59,60]. These groups have historically dominated nutrient-rich, early successional phases of the pelagic production cycle, particularly under spring mixing regimes that favor large, fast-growing diatom species and their efficient transfer to calanoid copepods [61]. Their co-association underscores a legacy focus on bottom-up processes and secondary production in mesotrophic conditions.

Conversely, cyanobacteria and flagellates were more frequently linked to climate change and hypoxia, reflecting a growing body of literature that documents their expansion under thermally stratified, oxygen-depleted, and nutrient-imbalanced conditions [62,63,64,65,66,67]. These groups exhibit traits such as buoyancy regulation, mixotrophy, and resistance to grazing, enabling them to outcompete classical phytoplankton under stressor-amplified regimes. Their proliferation signals a shift toward lower food quality and reduced trophic transfer efficiency [64,66,68,69,70,71,72].

Gelatinous zooplankton, notably M. leidyi and B. ovata, demonstrated strong associations with biological invasion and climatic forcing, indicating their dual role as both consequences and drivers of ecosystem disruption [43,73]. Their dominance has been linked to the suppression of mesozooplankton populations, collapse of herbivorous grazing control, and redirection of carbon flow through the microbial loop rather than classical trophic channels. These associations reflect increased attention to top-down destabilization and altered food web topology in the recent literature [4,8,74,75].

3.4. Methodological Integration and Gaps in Research Design

Figure 5 illustrates the methodological composition of the peer-reviewed studies examined, based on the presence of three distinct analytical components: (i) functional process quantification (e.g., grazing rates, trophic transfer efficiency), (ii) coupled phytoplankton–zooplankton modeling frameworks (e.g., NPZD-type models), and (iii) environmental or anthropogenic driver analyses (e.g., eutrophication, hypoxia, climate variability).

Most studies (39.5%, n = 34) were categorized as environmental-only, focusing primarily on bottom-up controls such as nutrient loading, temperature, and oxygen dynamics without integrating direct trophic linkages. A smaller fraction (5.8%, n = 5) addressed functional processes in isolation, typically through localized measurements of zooplankton feeding or production rates. Only 2.3% (n = 2) employed coupled producer–consumer models without contextualizing environmental forcing.

Notably, just 18.6% (n = 16) of the reviewed studies incorporated multiple methodological dimensions, reflecting a limited but emerging effort toward integrative ecosystem modeling. In contrast, 33.7% (n = 29) of studies did not report the use of any of the three assessed methodological approaches—underscoring a substantial gap in the empirical evaluation of trophic coupling, energy flow, and functional plankton dynamics.

This distribution highlights the methodological fragmentation that persists in Black Sea plankton research. While advances in numerical modeling and trait-based frameworks have occurred in recent years, their implementation remains sporadic and often decoupled from empirical validation. The lack of functional integration limits the predictive capacity of existing ecosystem models and constrains the development of robust, mechanistically informed indicators necessary for ecosystem-based assessments and MSFD-aligned marine governance.

3.5. Advancements in Plankton Research Methodologies

A focused analysis of recent publications (2020–2025) revealed a discernible shift toward novel analytical approaches in Black Sea plankton ecology, reflecting growing interest in mechanistic, functional, and scenario-based frameworks. Out of the 20 post-2020 studies, 13 (65%) addressed at least one of four key emerging themes (Figure 6).

The most frequently encountered topic was Jellyfish Blooms and Trophic Decoupling (n = 6), with studies emphasizing the disruptive ecological effects of gelatinous zooplankton—particularly M. leidyi—on mesozooplankton assemblages and classical energy transfer pathways. These works framed jellyfish proliferation as both a symptom and driver of ecosystem instability, often linked to overfishing, eutrophication, and warming-induced stratification.

The second most prevalent theme was Hypoxia-Driven Phytoplankton Shifts (n = 4), which captured the increasing dominance of mixotrophic flagellates and cyanobacteria under low-oxygen and nutrient-altered regimes. These studies used pigment analysis and bloom tracking to characterize transitions from large diatoms to smaller, less-palatable taxa.

Fuzzy Cognitive Modeling and Scenario Tools (n = 2) represented a growing effort to integrate expert knowledge and simulate ecosystem trajectories under uncertainty. These models helped visualize causal feedback among stressors and trophic groups, offering qualitative diagnostics in data-limited settings.

Finally, Trait-Based Zooplankton Indicators (n = 1) emerged as a promising but underutilized approach. The single identified study applied fatty acid profiling to assess mesozooplankton food quality, signaling a potential direction for linking biochemical traits to ecosystem health metrics under Descriptor 4 of the MSFD.

Collectively, these trends indicate a nascent but expanding effort to move beyond taxonomic inventories toward integrative, function-oriented analyses capable of capturing ecological complexity and supporting ecosystem-based management.

To elucidate the conceptual architecture of recent advancements in Black Sea plankton research, a keyword co-occurrence network was constructed (Figure 7).

The Sankey diagram illustrates the co-occurrence structure of key ecological and methodological terms across the reviewed literature, revealing distinct thematic clusters and interaction strengths. Three primary clusters emerge. The first, centered on marine reporting units, modeling tools, and phytoplankton proliferation, reflects a methodological emphasis on observational frameworks and correlation analysis. A second cluster highlights the intersection of bioluminescence, ctenophores, redoxcline, and video observations, capturing the niche but growing research on gelatinous zooplankton behavior and hypoxia dynamics. The most prominent cluster anchors around phytoplankton and zooplankton, with strong inflows from nutrients, abiotic factors, and macrozoobenthos, suggesting continued focus on bottom-up controls and trophic connectivity.

Zooplankton (n = 7) and phytoplankton (n = 5) emerged as the most interconnected nodes, serving as conceptual hubs in studies exploring energy transfer and ecological responses to environmental drivers. Additionally, biodiversity and mesozooplankton appear in weaker but targeted connections, reflecting their role in functional assessments. Overall, the diagram underscores both the centrality of nutrient–phytoplankton–zooplankton pathways and the fragmentation of peripheral research strands. This co-occurrence structure highlights the balance between traditional ecosystem process studies and emerging niche topics in Black Sea plankton ecology.

4. Discussion

4.1. Reconstructing Planktonic Trophic Coupling in the Black Sea for MSFD-Relevant Ecosystem Assessment

The accelerating pace of ecological change in the Black Sea, driven by eutrophication, climate forcing, invasive species, and hypoxia, has placed increasing pressure on the region’s planktonic food webs [28,29,31,33]. Despite decades of observation and research, critical uncertainties persist regarding the trophic relationships that structure pelagic ecosystems and sustain higher trophic levels. This review was therefore conceived to address a pressing need: to systematically synthesize and evaluate empirical knowledge on phytoplankton–mesozooplankton interactions, with a focus on functional traits, trophic coupling, and ecosystem-based diagnostic potential.

While numerous studies have explored either phytoplankton or zooplankton independently, few have explicitly examined their dynamic interplay across environmental gradients or under stressor regimes. This siloed approach obscures emergent properties of the food web—such as energy transfer efficiency, selective grazing, trophic mismatch, and the disruption of classical diatom–copepod pathways—which are central to understanding ecosystem functioning and resilience. Our review responds to this gap by integrating long-term ecological data, methodological trends, and emerging functional perspectives to reconstruct how the Black Sea’s lower trophic structure has evolved and why it matters for marine management.

One of the key findings of this review is the chronic decoupling of classical phytoplankton–zooplankton linkages, a process initiated by the massive eutrophication events of the 1970s–1990s and exacerbated by subsequent environmental stressors. As nitrogen and phosphorus inputs surged—primarily via the Danube—phytoplankton communities shifted toward dominance by fast-growing, small-sized, and often non-edible taxa, including cyanobacteria and bloom-forming flagellates [76,77,78,79,80]. These changes reduced food quality and grazing efficiency for mesozooplankton, particularly calanoid copepods, ultimately impairing energy transfer to planktivorous fish and compromising secondary production [81,82].

The situation was further compounded by the invasion and proliferation of gelatinous zooplankton species, notably M. leidyi and B. ovata, which outcompeted native mesozooplankton and destabilized traditional energy pathways [43,45,83]. These trophic disruptions were not only ecologically significant but structurally transformative—altering community composition, biogeochemical fluxes, and seasonal succession patterns in the pelagic zone. Our synthesis of co-occurrence patterns confirms this restructuring, showing that diatoms and copepods remain linked to eutrophication, while cyanobacteria, flagellates, and gelatinous taxa are increasingly associated with climate change, stratification, and hypoxia.

Critically, we found that only a limited subset of studies—less than 20%—adopted integrative methodological frameworks capable of capturing trophic coupling, functional metrics, and environmental drivers simultaneously. This points to a fundamental bottleneck in current Black Sea research: while taxonomic resolution has improved, the empirical quantification of functional processes such as grazing rates, trophic transfer efficiency, or nutrient flux remains rare. Moreover, the underutilization of coupled NPZD-type models and trait-based assessments has constrained the region’s capacity to generate predictive diagnostics aligned with Descriptor 4 (food webs) of the Marine Strategy Framework Directive (MSFD).

Emerging research from the post-2020 period suggests a potential inflection point. We identified a diversification of methodologies, including fuzzy cognitive mapping (FCM), scenario modeling, fatty acid profiling, and remote-sensing-enhanced phytoplankton analysis. These innovations reflect a growing recognition that understanding food web structure requires not only improved observation but also the capacity to simulate system behavior under uncertainty [5,25,84]. Nevertheless, the adoption of these approaches remains fragmented and disconnected from long-term monitoring frameworks, limiting their translational impact on marine policy.

The keyword co-occurrence network constructed in this review highlights this thematic shift. Overall, the co-occurrence structure reflects a conceptual transition in the literature—from a nutrient-dominated, tightly coupled diatom–copepod paradigm to more complex, stressor-mediated assemblages characterized by functional reorganization, trophic decoupling, and ecological inefficiency. Central terms such as modeling tools and phytoplankton proliferation underscore a transition toward process-oriented, functional approaches, while peripheral concepts such as trait-based indicators and macrozoobenthos reveal promising but underdeveloped research frontiers. The partial integration of ecological, biogeochemical, and policy-relevant dimensions suggests a field in transition—moving toward, but not yet achieving, the kind of synthetic, multi-scalar understanding required for effective ecosystem-based management.

Thus, this review provides not only a synthesis of past knowledge but also a roadmap for future inquiry. We argue for a redefinition of monitoring priorities to include functional traits, predator–prey coupling, and energy transfer metrics; the integration of empirical and model-based approaches; and greater cross-border collaboration to harmonize data collection across the Black Sea basin. In doing so, this review advances the field toward an operational understanding of food web dynamics that is both scientifically robust and policy relevant.

This review has direct implications for marine environmental policy in the Black Sea, particularly in the context of the European Union’s Marine Strategy Framework Directive (MSFD). Although Descriptor 4 (Food Webs) is most explicitly related to trophic coupling, our findings intersect with several other descriptors—including Descriptor 1 (Biodiversity), Descriptor 5 (Eutrophication), Descriptor 6 (Seafloor Integrity), and Descriptor 8 (Contaminants and their effects)—highlighting the interconnected nature of ecosystem health indicators.

First, the documented shift in phytoplankton community structure—from diatom-dominated to flagellate- and cyanobacteria-rich assemblages—not only affects food web energy transfer (D4), but also alters the biodiversity landscape (D1), contributes to eutrophication feedback (D5), and, through hypoxia-induced mortality, impacts benthic habitat quality (D6). Similarly, the proliferation of gelatinous zooplankton, such as M. leidyi, signifies both a trophic imbalance and a disruption of biodiversity, with cascading consequences for fish recruitment and benthic–pelagic coupling.

Second, the current reliance on isolated, taxonomic, or biomass-based indicators within national monitoring programs restricts the implementation of an integrated ecosystem-based management approach. Our results show that less than 20% of the reviewed studies incorporate functional metrics, trophic linkages, and environmental drivers concurrently, limiting their utility for robust MSFD assessment and adaptive policy development.

Third, several emerging tools and approaches—such as trait-based indicators, fuzzy cognitive mapping (FCM), and coupled ecological modeling—have the potential to inform multiple descriptors simultaneously. For example, trait-based mesozooplankton indicators can signal food quality (D4), trophic efficiency (D1), and system sensitivity to nutrient inputs (D5), while FCMs can support qualitative scenario testing.

To strengthen the policy relevance of plankton-based assessments and foster cross-descriptor integration under the Marine Strategy Framework Directive (MSFD), we recommend the following actions:

• Adopt cross-cutting ecological indicators that integrate multiple MSFD descriptors by linking plankton community structure and function with biodiversity status (Descriptor 1), food web integrity (Descriptor 4), eutrophication processes (Descriptor 5), and benthic habitat condition (Descriptor 6). Such integrative metrics can offer holistic insights into ecosystem dynamics and anthropogenic pressures.
• Incorporate functional plankton traits—including grazing efficiency, trophic redundancy, size structure, and community-level metabolic activity—into regional monitoring frameworks and national MSFD reporting. These indicators can improve the detection of subtle ecosystem shifts and resilience thresholds.
• Broaden the application of predictive and exploratory tools, such as nutrient–phytoplankton–zooplankton–detritus (NPZD) models, fuzzy cognitive mapping (FCM), and satellite-derived plankton proxies, to simulate ecosystem responses under various environmental and management scenarios. These tools can aid in evaluating the effectiveness of policy measures and anticipating cumulative impacts across descriptors.
• Foster regional standardization and data interoperability by aligning plankton monitoring protocols and sharing practices through established governance mechanisms, including the Black Sea Commission (BSC), the EMBLAS initiative, and Horizon Europe missions.

Such harmonization efforts are essential for ensuring transboundary comparability, improving cumulative impact assessments, and supporting evidence-based marine spatial planning. In sum, this review provides a science-based foundation to evolve current monitoring systems toward a multi-descriptor, functionally integrated framework, capable of capturing ecosystem complexity and informing adaptive marine policy under accelerating environmental change.

4.2. Advancing Plankton-Based Assessments Through Cross-Regional Comparisons and Functional Integration

The Black Sea, with its distinctive vertical stratification, expansive anoxic zone, and long history of anthropogenic pressures [26,28,33,85,86], remains underdeveloped in terms of integrated plankton monitoring. However, key functional attributes such as phytoplankton community structure, zooplankton size spectra, grazing rates, or trophic efficiency are rarely quantified or reported systematically. Zooplankton monitoring is particularly sparse and lacks harmonization, undermining the development of food web indicators aligned with Descriptor 4.

In contrast, the Baltic Sea has achieved a relatively high level of integration and regional coordination, facilitated by the HELCOM framework. Functional plankton indicators, including cyanobacterial bloom indices and zooplankton-based metrics (mean size, total abundance), are applied in coordinated assessments under Descriptors 4 and 5 [87,88,89,90]. These metrics have been validated as early warning indicators of trophic shifts and ecosystem degradation [91]. The availability of long-term, high-resolution data further supports the identification of regime shifts and the evaluation of eutrophication trends [92,93].

The North Sea presents a particularly advanced model, grounded in extensive datasets such as those from the Continuous Plankton Recorder (CPR) program. Indicators such as community mean trophic level (mTL), size-based indices, and functional group transitions are used to track ecosystem dynamics influenced by both top-down (e.g., fishing) and bottom-up processes [94,95,96,97]. These data feed into ecosystem models that simulate multi-descriptor responses to policy scenarios, providing valuable input for adaptive marine management [98].

The Mediterranean Sea, while more fragmented institutionally, has developed region-wide guidance under the UNEP/MAP Integrated Monitoring and Assessment Programme (IMAP). Although implementation varies by subregion, there is increasing uptake of functional plankton metrics such as bloom timing, taxonomic diversity, and trophic composition [99,100,101,102,103,104]. High-frequency time-series and modeling efforts (e.g., in the Adriatic and Western Med) are beginning to inform cumulative impact assessments and climate adaptation strategies [105,106].

By comparison, the Black Sea still faces substantial gaps in transboundary integration, functional indicator uptake, and predictive capacity (

Table 2. Comparative overview of plankton monitoring and functional integration in regional seas.

Region	Governance Platform	Plankton Indicators Used	Descriptors Addressed	Functional Approaches	Modeling/Tools
Black Sea	BSC, EMBLAS	Chlorophyll-a (satellite, in situ); basic biomass estimates	D1 (limited), D5	Minimal, functional metrics are rarely applied	Limited; some NPZD/FCM pilot studies
Baltic Sea	HELCOM	Chl-a, cyanobacteria index, zooplankton abundance & size	D1, D4, D5	Size-based, life-history traits, bloom metrics	Regional NPZD models, scenario simulations
North Sea	OSPAR, CPR program	Size spectra, biomass trends, trophic level changes	D1, D4, D5, D6	Trait-based indicators; mTL, energy flow metrics	CPR data-based ecosystem modeling
Mediterranean	UNEP/MAP (IMAP)	Functional phytoplankton traits, bloom phenology	D1, D4, D5 (varies by subregion)	Emerging: diversity indices, trophic coupling	Satellite + local model coupling, climate risk

). Despite progress made through regional projects such as MISIS, ANEMONE, EMBLAS, and initiatives under the Black Sea Commission (BSC) and Horizon Europe, functional plankton indicators remain limited. Few countries apply size spectra, grazing efficiency, or trophic redundancy metrics, and there is limited coupling between pelagic and benthic assessments [51]. Similarly, modeling tools—such as NPZD frameworks, end-to-end trophic models, and fuzzy cognitive mapping (FCM)—are rarely used to inform marine policy in the region [75].

Despite the proven value of indicators such as mean Trophic Level (mTL) and Continuous Plankton Recorder (CPR) datasets in the North Sea for detecting trophic shifts and informing policy, similar approaches have not yet been adopted in the Black Sea. This is largely due to institutional fragmentation, limited long-term and high-frequency biological datasets, and the absence of standardized, basin-wide monitoring protocols. Furthermore, gaps in transboundary coordination and funding constraints have hindered the development of consistent plankton time-series and the integration of functional indicators into national MSFD reporting. Bridging these barriers is essential to unlock the predictive and diagnostic potential of North Sea-style assessment frameworks in the Black Sea region.

To close these gaps and align the Black Sea with the MSFD’s ecosystem-based approach, several priorities are evident:

• Standardization of monitoring protocols and taxonomic resolution, especially for zooplankton and microplankton groups.
• Routine inclusion of functional traits and trophic indicators—such as grazing rates, metabolic balance, and size-based metrics—to capture ecosystem functioning beyond biomass.
• Adoption of integrative modeling tools, combining physical, chemical, and biological processes to assess ecosystem responses under different management and climate scenarios.
• Expansion of transboundary collaboration and data sharing, leveraging platforms such as the BSC, EMBLAS, and SeaDataNet for regional harmonization and open science.
• Capacity-building for emerging methodologies, including molecular (eDNA), remote sensing, and artificial intelligence tools to extract ecological signals from complex data streams.

In summary, the experience of other regional seas highlights a clear trajectory toward the integration of functional, cross-descriptor plankton indicators into marine environmental assessments. The Black Sea, despite its geopolitical complexity and ecological specificity, has a strategic opportunity to adopt and adapt these approaches. Doing so would not only improve compliance with EU directives and international agreements but also provide the scientific basis for adaptive, ecosystem-based marine governance in the face of accelerating environmental change.

This review, while comprehensive, is subject to several limitations. First, the analysis was intentionally restricted to Web of Science-indexed, peer-reviewed publications to ensure standardized bibliometric metadata and methodological consistency for network and keyword analyses. While this approach provides robustness, it is not exhaustive, and excludes relevant works published in other databases, regional journals.

Second, this restriction introduced a degree of geographic imbalance. The dataset is weighted toward studies from the western and northwestern Black Sea, particularly Romania and Bulgaria, followed by Ukraine and parts of Turkey. By contrast, research from the eastern basin (Georgia, Russia, eastern Turkey) is largely absent, not due to a lack of scientific activity, but because much of this work is published in national journals or languages not indexed by WoS. This structural bias of the database skews representation, creating the impression of national dominance in certain areas of research.

Conceptually, our synthesis is also constrained by the traditional NPZD-type paradigm, in which phytoplankton and zooplankton are treated as strictly autotrophic and heterotrophic compartments. This framework does not fully capture the ecological role of mixoplankton, which integrate both nutritional strategies and are increasingly recognized as key players in food web dynamics. Future reviews and modeling efforts in the Black Sea should explicitly incorporate mixoplankton to provide a more accurate representation of trophic coupling.

Although the review identifies emerging tools such as trait-based indicators and cognitive mapping, these remain in early application stages and are rarely integrated into long-term monitoring or policy frameworks. Additionally, the focus on planktonic components excludes benthic and nektonic interactions, which are integral to full food web assessments.

Despite these constraints, the review offers a critical foundation for functional food web research and identifies clear directions for advancing trophic indicators and integrative assessments in the Black Sea.

5. Conclusions

This review represents a synthesis of phytoplankton–zooplankton interactions in the Black Sea through a functional and trophodynamic lens. By examining over three decades of peer-reviewed literature, it highlights a critical shift in both ecological structure and research approaches—from classical, taxonomic monitoring toward emerging methodologies that integrate environmental stressors, functional traits, and ecosystem modeling.

Our findings reveal that trophic coupling between phytoplankton and zooplankton in the Black Sea has been progressively weakened by eutrophication, climate-induced stratification, and biological invasions. These pressures have led to community transitions characterized by smaller, less palatable phytoplankton and gelatinous-dominated zooplankton assemblages, undermining energy transfer efficiency and pelagic food web stability.

Despite the increasing ecological complexity, most studies remain limited in scope, with only a minority employing integrated frameworks that couple functional indicators with environmental drivers or predictive models. This fragmentation impairs the ability of scientific outputs to inform marine policy, especially under the MSFD, and restricts the development of holistic, cross-descriptor ecosystem assessments. Yet, the review also identifies a nascent methodological shift, with the post-2020 literature embracing tools such as fuzzy cognitive mapping, trait-based metrics, and scenario-based modeling. These approaches offer promising pathways to bridge current empirical gaps and to support adaptive, policy-relevant marine governance.

We conclude that unlocking the full potential of plankton-based assessments in the Black Sea requires a strategic pivot: from descriptive inventories to functionally grounded, cross-trophic, and transdisciplinary frameworks. Strengthening regional cooperation, integrating empirical and modeling efforts, and embedding functional indicators into long-term monitoring will be essential for capturing the true dynamics of this ecologically sensitive and rapidly changing marine basin.