Replication Data for: Beyond connecting the dots: A multi-scale, multi-resolution approach to marine habitat mapping

This dataset consists of five zipped folders: Final_habitatmaps_physiotopes.zip: This folder contains the raster (tif) files in ETRS89 UTM31 projection of the final habitat and physiotope maps as presented in the paper. Final_accuracy_plots.zip: This folder contains the raster (tif) files in ETRS89 UTM31 projection of the final habitat accuracy maps as presented in the paper. Input_abiotic_factors.zip: All the abiotic factor data used to determine the relevant environmental gradients in the study area are included as raster data (tif) in ETRS89 UTM31 projection (supplementary figures B1-22). Most datasets were obtained elsewhere, but all datasets were processed by Karin van der Reijden in R and ArcGIS to have a similar projection, resolution and extent. In addition, the shapefiles (in ETRS89 UTM31 projection) of offshore wind farms, Natura2000-areas and national waters are included. Data-description: An overview of all folders, and of all files included in the abiotic factors folder. Input_environmental_gradients.zip: This folder contains the raster (tif) files in ETRS89 UTM31 projection of the environmental gradients used in the study as input to the Random Forest models and physiotope-delineation. Each gradient is a PCA-component (1-7) summarizing the abiotic factors. Gradients including (FE) and excluding (NF) demersal fishing intensity as abiotic factor are available. Input_biological_cluster_data.zip: This folder contains datafiles (.Rdata and .CSV files) for the three biological datasets (demersal fish, epifauna, endobenthos), that give locations and corresponding biological cluster, as used in the Random Forest habitat maps. The biological datasets used for the determination of biological clusters are not included in this repository. For demersal fish and endobenthos, these datasets can freely be downloaded at the DATRAS-portal on the ICES website (demersal fish) and the EMODnet Biology portal (endobenthos). Link to demersal fish data: https://datras.ices.dk/Data_products/Download/Download_Data_public.aspx Link to endobenthos data: https://www.emodnet-biology.eu/data-catalog?module=dataset=67 Epifauna_data_CONFIDENTIAL.zip: The dataset for epifauna was confidentially shared with the first author and is therefore not made publicly accessible. Upon (reasonable) request contact details with the corresponding person could be shared

Beyond connecting the dots: A multi-scale, multi-resolution approach to marine habitat mapping

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, high-resolution 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 socio-economic interests in continental shelf seas.Aircraft Noise and Climate Effect

Survival Strategies of Yeast and Filamentous Fungi against the Antifungal Protein AFP*

The activities of signaling pathways are critical for fungi to survive antifungal attack and to maintain cell integrity. However, little is known about how fungi respond to antifungals, particularly if these interact with multiple cellular targets. The antifungal protein AFP is a very potent inhibitor of chitin synthesis and membrane integrity in filamentous fungi and has so far not been reported to interfere with the viability of yeast strains. With the hypothesis that the susceptibility of fungi toward AFP is not merely dependent on the presence of an AFP-specific target at the cell surface but relies also on the cell's capacity to counteract AFP, we used a genetic approach to decipher defense strategies of the naturally AFP-resistant strain Saccharomyces cerevisiae. The screening of selected strains from the yeast genomic deletion collection for AFP-sensitive phenotypes revealed that a concerted action of calcium signaling, TOR signaling, cAMP-protein kinase A signaling, and cell wall integrity signaling is likely to safeguard S. cerevisiae against AFP. Our studies uncovered that the yeast cell wall gets fortified with chitin to defend against AFP and that this response is largely dependent on calcium/Crz1p signaling. Most importantly, we observed that stimulation of chitin synthesis is characteristic for AFP-resistant fungi but not for AFP-sensitive fungi, suggesting that this response is a successful strategy to protect against AFP. We finally propose the adoption of the damage-response framework of microbial pathogenesis for the interactions of antimicrobial proteins and microorganisms in order to comprehensively understand the outcome of an antifungal attack