Author
Listed:
- Miettunen, Elina
- Forsblom, Louise
- Virtanen, Elina A.
Abstract
In response to new conservation targets, countries are expanding their marine protected areas (MPAs) to increase protection of species and habitats. A critical aspect in the design of MPAs is ecological connectivity, which can be challenging to account for in areas with fragmented habitats and variable current patterns. We evaluated connectivity in a highly dynamic archipelago in the northern Baltic Sea using a Lagrangian particle tracking model driven by high-resolution, three-dimensional current velocity data, and species distribution models informed by extensive biological surveys. Simulations for the summer season showed low potential connectivity in general, due to variable surface layer currents. With a pelagic larval duration of 30 days, median for potential connectivity between sites 1.5–5 km apart was 11.5% (maximum 43.6%), but declined to 1.3% at distances of 15–25 km and to only 0.02% beyond 50 km. Potential connectivity was higher from north to south than vice versa, indicating that habitats in the northern parts of the study area have a key role in sustaining habitats further south. Therefore, it is essential to maintain these northern habitats in good ecological condition. In contrast, several habitats in heavily eutrophicated inner archipelago areas were effectively isolated, with limited connections to other habitats in the study area. Species recovery in these inner areas may be difficult even with substantial eutrophication mitigation measures, given their poor ecological connectivity. Our findings highlight the importance of high-resolution modelling approaches to capture variable connectivity patterns that are the cornerstone of effective MPA design.
Suggested Citation
Miettunen, Elina & Forsblom, Louise & Virtanen, Elina A., 2026.
"Evaluating ecological connectivity of key benthic habitats in a dynamic, complex archipelago,"
Ecological Modelling, Elsevier, vol. 511(C).
Handle:
RePEc:eee:ecomod:v:511:y:2026:i:c:s0304380025003710
DOI: 10.1016/j.ecolmodel.2025.111385
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