Advancing Ecosystem-Based Practices in Transboundary Contexts: Systematic Comparative Analysis of European MSP Plans
Bibliographic record
Abstract
Sustainable and equitable management practices are critical to achieve protection and restoration of marine and coastal ecosystems. This urgency is reflected in the ambitious targets set for 2030 by the Kunming-Montreal Global Biodiversity Framework (GBF) and Sustainable Development Goals (SDGs). Maritime Spatial Planning (MSP) is a central tool in integrating economic, social, and environmental priorities in marine environments. However, its effectiveness relies on cooperation and harmonization across national boundaries ensuring cohesive management of transboundary marine ecosystems. The aim of this study is to assess the coherence of ecosystem-based approaches at the European (EU) and cross-border levels, evaluating the extent to which these strategies are integrated across regions. This analysis seeks to identify gaps and propose solutions to enhance alignment and effectiveness in marine management in EU countries. This research adopts an evidence-based approach to systematically analyze EU MSP plans provided by the European Marine Observation and Data Network (EMODnet) portal, leveraging on their harmonized data scheme. By designing and applying a specific methodology, we compare sea use classifications and spatial patterns within MSP plans from various EU Member States. This includes the reconstruction of geospatial topological relationships, both at the national level and, more specifically, in border areas. The methodology integrates visual solutions to effectively explore and communicate multi-use patterns (e.g., with UpSet plots), and comparative analysis at the sea basin level or within specific case studies. Complementing this analysis, interviews with MSP experts provide qualitative insights into factors that enabled transboundary coherence of these plans, as well as criticalities, with a particular focus on ecosystem-based perspectives and environmental protection. The approach conceptualization and reusable tool is developed within the EU funded ReMAP project. The findings provide an initial understanding of how diverse policy contexts and planning methodologies impact the transboundary harmonization process. By emphasizing the importance of partnerships and cross-border cooperation, as highlighted in SDG 17, the analysis reveals both common practices that promote effective transboundary collaboration and critical discrepancies that may hinder the achievement of an integrated MSP framework and marine governance. These insights can guide MSP planners and policymakers towards more effective strategies for achieving ecosystem-based solutions, sustainable blue economy and safeguarding marine ecosystems through enhanced collaboration.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.032 | 0.049 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.013 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".