Journal
ECOLOGICAL INDICATORS
Volume 128, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.ecolind.2021.107849
Keywords
Benthic faunal assemblages; Demersal fisheries; Hierarchical clustering; Marine habitat mapping; Marine Spatial Planning; Physiotopes
Categories
Funding
- Centre for Information Technology of the University of Groningen
- NWO grant [016.Veni.181.087]
- Gieskes-Strijbis Fonds, The Netherlands
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Conflicts between economic and conservation interests in coastal seas are increasing, highlighting the need for evidence-based marine spatial planning. This study integrated biological and environmental data to map habitats and assess anthropogenic pressures in the southern North Sea.
Conflicts of interests between economic and nature conservation stakeholders are increasingly common in coastal seas, inducing a growing need for evidence-based marine spatial planning. This requires accurate, highresolution habitat maps showing the spatial distribution of benthic assemblages and enabling intersections of habitats and anthropogenic activities. However, such detailed maps are often not available because relevant biological data are scarce or poorly integrated. Instead, physiotope maps, solely based on abiotic variables, are now often used in marine spatial planning. Here, we investigated how pointwise, relatively sparse biological data can be integrated with gridded, high-resolution environmental data into informative habitat maps, using the intensively used southern North Sea as a case-study. We first conducted hierarchical clustering to identify discrete biological assemblages for three faunal groups: demersal fish, epifauna, and endobenthos. Using Random Forest models with high-resolution abiotic predictors, we then interpolated the distribution of these assemblages to high resolution grids. Finally, we quantified different anthropogenic pressures for each habitat. Habitat maps comprised a different number of habitats between faunal groups (6, 13, and 10 for demersal fish, epifauna, and endobenthos respectively) but showed similar spatial patterns for each group. Several of these 'fauna-inclusive' habitats resembled physiotopes, but substantial differences were also observed, especially when few (6; demersal fish) or most (13; epifauna) physiotopes were delineated. Demersal fishing and offshore wind farms (OWFs) were clearly associated with specific habitats, resulting in unequal anthropogenic pressure between different habitats. Natura-2000 areas were not specifically associated with demersal fishing, but OWFs were situated mostly inside these protected areas. We thus conclude that habitat maps derived from biological datasets that cover relevant faunal groups should be included more in ecology-inclusive marine spatial planning, instead of only using physiotope maps based on abiotic variables. This allows better balancing of nature conservation and socioeconomic interests in continental shelf seas.
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