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30 results for “biofouling”
Data and code to accompany oyster pound biofouling paper
<p>The fouling_for_zenodo folder contains the data and code needed to reproduce the analyses and figures in Krasnow et al. (2025). The other folders contain images of the experimental oysters taken during the measurement process that may be useful in the future.</p> <p>Krasnow, R., Kiffney, T., Coleman, S., Cuddy, R., & Brady, D. (2025). Interacting effects of environment and cultivation method on biofouling of farmed oysters (<em>Crassostrea virginica</em>). <em>Journal of the World Aquaculture Society</em>, <em>56</em>(3), e70012. <a href="https://ruby.science/pubs.html#0">https://doi.org/10.1111/jwas.70012</a></p>
Experimental insights on biofouling growth in marine renewable structures
<p>This is version 2 of the files containing friction forces generated from scraping biofouling samples and the friction forces from subsequential scraping of certain samples. Data for all the samples that had subsequential scrapings has been aded. </p>
Experimental insights on biofouling growth in marine renewable structures
<p>This file contains data pertaining to the paper entitled "Experimental insights on biofouling growth in marine renewable structures". It includes biofouling thickness and the number of taxa, biomass (g Fresh Weight), and density (nbr. individuals) of biofouling organisms.</p>
Figure 5 in Germanium dioxide as agent to control the biofouling diatom Fragilariopsis oceanica for the cultivation of Ulva fenestrata (Chlorophyta)
Figure 5: GeO2-dependent total diatom density present on the surfaces of Plexiglass water tanks after 14 days of large-scale cultivation of Ulva fenestrata. Data are means of three replicates per treatment (n = 3) and error bars represent standard deviations. Lowercase letters above columns indicate statistically significant differences between the treatments (P <0.001, 1-way ANOVA, Tukey-Kramer HSD post-hoc test).
Figure 1 in Germanium dioxide as agent to control the biofouling diatom Fragilariopsis oceanica for the cultivation of Ulva fenestrata (Chlorophyta)
Figure 1: Photographs of the water tanks used for the cultivation of Ulva fenestrata in the laboratory while being (A) moderately and (B) strongly colonised by Fragilariopsis oceanica.
Figure 2 in Germanium dioxide as agent to control the biofouling diatom Fragilariopsis oceanica for the cultivation of Ulva fenestrata (Chlorophyta)
Figure 2: Total diatom biomass at different GeO2 concentrations after 22 days of cultivation at 137 µmol photons m−2 s−1 and 9 °C. Data are means of three replicates per treatment (n = 3) and error bars represent standard deviations. Lowercase letters above columns indicate statistically significant differences between the treatments (P <0.001, 1-way ANOVA, Tukey-Kramer HSD post-hoc test).
Figure 7 in Pilot study: investigating the role of biofouling in transmission of Ostreid herpesvirus 1 (OsHV-1)
Figure 7. Detection of OsHV-1 DNA in serial dilutions prepared with tissue homogenates from various taxa. Data points are the average Ct value for duplicate tissue samples spiked with for each quantity of starting template.
Figure 3 in Pilot study: investigating the role of biofouling in transmission of Ostreid herpesvirus 1 (OsHV-1)
Figure 3. Settlement array structures used for collection of biofouling assemblages. (A) Diagram of the PVC pipe holding the collecting plates; (B, C) Array structures within a mesh basket to reduce predation when fixed to an intertidal oyster tray or deployed in a floating basket.
Figure 5 in Pilot study: investigating the role of biofouling in transmission of Ostreid herpesvirus 1 (OsHV-1)
Figure 5. Frequency of biofouling taxa on settlement plates deployed for the laboratory challenge experiment (n = 44).
Figure 4 in Pilot study: investigating the role of biofouling in transmission of Ostreid herpesvirus 1 (OsHV-1)
Figure 4. Experimental design to test for transmission of OsHV-1 from biofouling organisms recruited from the Georges River when challenged with OsHV-1 by cohabitation with Pacific oysters infected by injection. The number of replicate tanks is indicated along with the number and type of organisms present in each tank for the of acclimation, and two periods of cohabitation.
Figure 1. Scenarios and experimental design for assessing a in Pilot study: investigating the role of biofouling in transmission of Ostreid herpesvirus 1 (OsHV-1)
Figure 1. Scenarios and experimental design for assessing a range of biofouling organisms for the potential to spread OsHV-1. A. Scenario for the OsHV-1 transmission pathway evaluated by field surveillance. B.1 Scenario for the vessel biofouling OsHV-1 transmission pathway. B.2 Adaptation of the vessel biofouling scenario for a laboratory infection trial with Pacific oysters and biofouling organisms evaluated as intermediates for transmission from injected Pacific oysters to naïve Pacific oysters.
Figure 2 in Pilot study: investigating the role of biofouling in transmission of Ostreid herpesvirus 1 (OsHV-1)
Figure 2. Location of the three surveillance and sampling sites (A, B, and C) within Woolooware Bay and the Georges River estuary, NSW, Australia. Site A (Latitude: −34.0339; Longitude: 151.1467); Site B (−34.0260; 151.1413); and Site C (−34.0119; 151.1465).
Biofouling sponges as natural eDNA samplers for marine vertebrate biodiversity monitoring
<p>These are the raw sequencing data and associated analysis codes for the study of "biofouling sponges as natural eDNA samplers for marine <span>vertebrate </span>biodiversity monitoring".</p>
Fig. 1 in Effect of pH on the Early Development of the Biofouling Ascidian .
Fig. 1. Average number of individual Ciona robusta found in 2 mL subsample within each replicate flask (a) varied across pH and time (3–58 hpf). To enable comparison between treatments that had different initial concentration, larval count was normalized against the average of the triplicate flask of the given pH at 3 hpf. In other words, the average between the three replicates at 3 hpf for a given pH = 1. This survivorship estimate (b), indicated by the relative density across four pHs (pH 8.0, pH 7.6, pH 7.2, and pH 6.8) from fertilization to meta-metamorphosis (adhesion period at 21 hpf), did not vary with time or pH (ANCOVA, Table 2). Each dot represents a single replicate flask. The dotted regression lines were not significant but illustrate the general trends (Table 3).
Fig. 3 in Effect of pH on the Early Development of the Biofouling Ascidian .
Fig. 3. The breakpoint pH, represented by the dotted line, varied throughout ontogeny. The breakpoint was identified by piecewise regression. Only five representative time points were presented (see Table 4 for the full regression statistics for all stages). The scale bars of the insets were 100 µm.
Fig. 2 in Effect of pH on the Early Development of the Biofouling Ascidian .
Fig. 2. Ocean acidification led to developmental delay in Ciona robusta. The mean and standard error for the proportion of embryo/larvae at a given stage relative to the total larval count at a particular time point were plotted. Note that 100% represents a different relative larval density for each bar (see Figure 1 for larval density).
Experimental insights on biofouling growth in marine renewable structures
<p>This is version 2 of this file, with the following updates:</p> <ul> <li>The biomass and density of the main biofouling organisms were removed from the file and added to the paper.</li> <li>PERMANOVA results using the biofoulers biomass were added to the file</li> <li>PERMANOVA results using the biofoulers density were added to the file</li> <li>PERMANOVA results using the frictional resstance forces were added to the file</li> </ul>
Biofouling data from underwater surveys of commercial ships in Canada
<p>Ship biofouling is a major vector for the introduction and spread of harmful marine species globally. Comprehensive underwater sampling and video recording of ship hulls was conducted to assess biofouling extent (percent cover, total abundance and species richness) on a subset of ships arriving to Canadian waters. The dataset includes underwater biofouling assessments from 53 commercial ships arriving at Halifax, Nova Scotia (20 international ships), Vancouver, British Columbia (20 international ships) during 2007–2009, and Churchill, Manitoba (11 international and 2 domestic ships) in 2010–2011. Potential explanatory variables in the dataset include ship size, typical sailing speed, port residence time, age of antifouling coating system and travel history (number of biogeographic realms visisted, and average, minimum and maximum port latititude).</p>
Biofouling data from underwater surveys of commercial ships in Canada
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Heting Hong_All Data_Experimental Assessment of Material Resistance to Freshwater Biofouling
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