SCUBA habitat and cover sampling characterizes benthic habitat and cover and associated reef attributes (substrate type, relief) following PISCO protocols for uniform point count (UPC) surveys. These surveys provide insight into the structure and function of nearshore rocky reef communities in Oregon’s state waters. Divers record three types of information every meter along a 30m transect: substrate type, physical relief and identity of the organism attached to the reef. The percent-cover of space-occupying organisms is estimated for species that are directly attached to the primary substrate and includes non-motile benthic invertebrates and algae. Two depths are targeted for these surveys 12.5 and 20 meters. Write-ins are allowed, for species not included on PISCO data-sheets.
Our SCUBA UPC sampling at Otter Rock began in 2010, two years before harvest restrictions began. Sampling is conducted in the marine reserve and one comparison area, Cape Foulweather (see methods Appendix for additional information about comparison area selection). We conducted five years of sampling at the marine reserve and efforts resulted in three years of sampling at the comparison area. Data across all five years is included in our analysis and synthesis report.
Data from SCUBA habitat and cover monitoring efforts can be used to explore questions about benthic habitat diversity, community composition and percent cover of various species groups. Questions about diversity and community composition can be used to help us understand how the benthic communities at these sites are similar or different. Data on percent cover can enable us to explore changes over time; and whether these changes are similar both inside the reserve and outside in comparison areas. For all data our main focus is exploring trends by site and year.
Substrate
Relief
Benthic Cover
*Does the diversity of benthic cover vary by site or year?
Does community composition of benthic cover vary by site or year? If yes, what species drive this variation?
Focal Species Benthic Cover
Here we present a summary of our SCUBA habitat and cover monitoring results and conclusions. Our conclusions are written with an evaluation of our sampling design, knowledge from prior marine reserves monitoring reports, and future directions of marine reserves monitoring in mind.
The surveyed substrate and relief categories were very similar between the reserve and comparison area.
Substrate types encountered in transects at the Otter Rock Marine Reserve and Cape Foulweather Comparison Area were mostly similar. Slightly more sand/gravel substrate was sampled in the Otter Rock Marine Reserve than the comparison area, but this category did not dominate the substrate encountered on transects in either location. There were minimal differences in relief across sites and years from SCUBA surveys. Means across the different relief categories were not significantly different.
Benthic cover diversity was similar between Otter Rock Marine Reserve and Cape Foulweather Comparison Area.
There were similar number of observed and estimated cover categories between the marine reserve and its comparison area. Both sites also had similar diversity indices (effective number of cover categories), and there were minimal differences in unique, common, and rare categories.
Benthic cover community composition is similar between sites, but has some slight structuring by year.
Benthic cover transects were similar between the Otter Rock Marine Reserve and Cape Foulweather Comparison Area. However, the early years of sampling (2010/2011) were slightly different from the later years (2015, 2017, 2019). There were two species groups driving the majority of transect variation in benthic cover community composition - crustose coralline algae (CCA) and lacy red algae - with higher percent cover of lacy red algae in early survey years (2010/2011) and higher percent cover of CCA in later survey years (2015-2019).
Four taxonomic groups dominate aggregate percent cover analyses: bryozoans, coralline algae, red algae and sponges.
There were four dominant taxonomic groups for aggregate percent cover - bryozoans, coralline algae, red algae and sponges. There were minimal apparent differences in mean percent cover of taxonomic groups by site, however there were more tunicates and inanimate cover (e.g. bare sand/cobble) at the Otter Rock Marine Reserve than the Cape Foulweather Comparison Area. Densities of coralline algae were significantly greater at the comparison area than the Otter Rock Marine Reserve. As we look across taxonomic groups through time we see variable trends at the reserve and comparison area.
We detected trends by year in percent cover of articulated coralline algae, crustose coralline algae, and lacy red algae at the Otter Rock Marine Reserve and Cape Foulweather Comparison Area.
There were no significant differences in percent cover between sites with articulated coralline algae, crustose coralline algae, and lacy red algae. However, declines in articulated coralline algae and lacy red algae percent cover were detected through time at both the marine reserve and Cape Foulweather Comparison Area. Conversely, increases in percent cover of crustose coralline algae were detected at both sites.
Results of this report consistent with the initial Ecological Monitoring Report od 2010-2011.
In the first Ecological Monitoring Report of 2010-2011, the SCUBA summary for Otter Rock concluded that the Otter Rock Marine Reserve is characterized by a moderate diversity of taxa that occur at even abundances. This report documents the abundance of red algae has decreased through time while crustose coralline algae percent cover has increased. As a result, community composition appears to be more evenly distributed relative to the 2010/2011 report, though still dominated by four main species groups. Differences in taxa-specific percent cover by site are likely driven by subtle differences in sampled habitat. Relative proportions of habitat sampled are consistent with this earlier report and provide additional evidence that the reference areas were appropriately chosen.
The Cape Foulweather Comparison Area is an appropriate reference site to understand changes at the Otter Rock Marine Reserve.
The conclusions of this report support previous monitoring report results (ODFW 2014) that the Cape Foulweather Comparison Area is an appropriate reference site to understand change at the marine reserve. We detected similar trends through time at both sites with focal species and there were similar measures of diversity and community composition between both sites.
SCUBA cover data provides valuable information about red algae not gathered in other monitoring tools.
We documented higher cover of red algae relative to brown and green algae at both sites. This is not surprising given the depths targeted by SCUBA surveys at the Otter Rock Marine Reserve and Cape Foulweather Comparison Area. Red algae are the most diverse group of seaweeds in the Northeast Pacific, and many are used by humans for a variety of purposes including food, medical research or in cosmetics. The SCUBA benthic cover data provides useful information about the relative cover and change over time of red algae, not gathered in other monitoring tools, and Lacy Red Algae was found to be an important driver of benthic cover community composition. Algal-dominated communities, when examined at the functional group level, can be more temporally stable and predictable than when examined at the species level (Steneck and Dethier 1994), suggesting the algal functional group data of the SCUBA habitat and cover surveys will be useful in evaluating community stability through time.
A move toward permanent sites or transects is needed to confidently detect future trends in benthic habitat and cover with SCUBA surveys.
The 2010 ODFW Monitoring Report suggested 10 transects per site are needed to characterize the benthic habitat and cover community, in most years we did not achieve that sample size at either site. Limited sample sizes were a result of challenging logistics related to a small boat based survey method in Oregon’s nearshore environment; reducing required sample sizes needed to detect change such as moving to permanent transects, would be beneficial because of these challenges. While we were able to detect several species’ yearly trends at either one site or both despite limited sample sizes, the magnitude of these changes was quite large (1.45-6 fold increases). In order for our program to confidently detect future changes in benthic habitat and cover at smaller magnitudes of change than those detected in this report, increased sampling effort or a move to permanent sites or transects is needed. Increased sampling effort would likely require an increase to the research budget. With a better understanding of the sea states, visibility and communities of nearshore reefs, we can now select the appropriate permanent locations to focus monitoring efforts, maximizing efficiency in data collection and power to detect change over time.
SCUBA habitat and cover surveys provide valuable context to ecological patterns detected in other SCUBA surveys.
The SCUBA habitat and cover surveys at Otter Rock Marine Reserve and Cape Foulweather Comparison Area allowed us to collect valuable information on benthic cover species and cover groups. This tool collects reliable, fine-scale data on habitat cover that provides important context to ecological patterns detected, such as with changes to coralline algae, sea urchin, and sea star populations. SCUBA habitat and cover surveys are conducted simultaneously with SCUBA invertebrate surveys, and when water clarity allows, SCUBA fish transects are subsequently conducted along the same transect. While beyond the capacity for formal inclusion in this report, conducting community analyses that explore change through time and by site with multiple components of the ecosystem is feasible with the suite of SCUBA surveys conducted at this site.
SCUBA habitat and cover sampling is conducted in the Otter Rock Marine Reserve and Cape Foulweather Comparison Area following PISCO uniform point count (UPC) protocols, modified for diving safety in Oregon. Monitoring began in the Otter Rock Marine Reserve in 2010, successful sampling of Cape Foulweather occurred in 2011; in the initial years there was a strong focus to place more sampling effort in the reserve to ensure adequate characterization of baseline conditions prior to closure. Since then, sampling effort targeted 2 days for both spring and fall monitoring, splitting effort between the marine reserve and Cape Foulweather Comparison Area based on ocean conditions.
The purpose of UPC sampling is to characterize benthic cover and associated reef attributes (substrate type, relief). Divers record three types of information beneath 30 points (one per meter mark), along a 30 meter transect: substrate type, physical relief and identity of the organism attached to the reef. The percent-cover of space-occupying organisms is estimated for species that are directly attached to the primary substrate and includes non-motile benthic invertebrates and algae. Two depths are targeted for these surveys 5 and 12.5 m. The Otter Rock Marine Reserve is the shallowest of all marine reserve, and there are no 20 m sites to survey here.
In 2010/2011, scientific divers from Partnership for Interdisciplinary Studies of Coastal Oceans (PISCO) selected survey locations with the intent that these sites would be permanent. Selected locations were representative of available rocky reef habitat with kelp, within targeted depth ranges. As monitoring continued, the challenges and safety constraints of diving in Oregon’s nearshore (see Methods Appendix for more details) led to the inevitable need to select alternate locations. Due to unpredictable weather and visibility conditions, sites were selected from randomly generated points based on available rocky reef habitat within targeted depth ranges. These changes resulted in greater spatial coverage of the reef and is more reflective of a stratified random sampling design, rather than one with permanent sites.
The unit of replication at the transect level. Only fully completed, independent transects were included in analysis. Targeted 5 meter transects from early years of sampling (2010-2011) were included in analysis because of the shallow nature of this site, and several transects from later years occurred at similar depths. For additional details on data collection, please review documentation in the Methods Appendix.
Substrate type is recorded as one of four categories: sand/gravel (<2cm), cobble (2-10cm diameter), small boulder (10cm-1m diameter), large boulder (1-4m), or bedrock (> 4m diameter).
We focused our analysis on the question of whether variation in substrate surveyed was driven by spatial (site) or temporal (year) factors. We did this through data visualizations with non-multidimensional scaling (nMDS) and an anova of mean percent cover of substrate class by site.
To explore variation by site and year, we used substrate data collected on SCUBA UPC transects; data were not exceedingly skewed so no transformation was used (Clarke et al. 2006).Percent cover of substrate types were calculated from SCUBA UPC count data (# points/ transect) so a similarity-based resemblance matrix was selected. A dummy variable (=1) was added prior to creating the resemblance matrix due to the high prevalence of zeros in the dataset. To visualize the data, we generated nMDS plots by site and year.
All analyses and graphs were made in PRIMERe version 7 with PERMANOVA extension.
To explore variation in substrate type category by site we ran a Kruskal-Wallis comparison, and plotted mean substrate category by site with 95% confidence intervals.
Relief is recorded as one of four categories: 0 < 10 cm, 10 cm < 1m, 1 <2 m, and > 2m.
We focused our analysis on the question of whether variation in relief surveyed was driven by spatial (site) or temporal (year) factors. We did this through data visualizations with non-multidimensional scaling (nMDS) and an anova of mean percent cover of relief category by site.
To explore variation by site and year, we used substrate data collected on SCUBA UPC transects; data were not exceedingly skewed so no transformation was used (Clarke et al. 2006).Percent cover of substrate types were calculated from SCUBA UPC count data (# points/ transect) so a similarity-based resemblance matrix was selected. A dummy variable (=1) was added prior to creating the resemblance matrix due to the high prevalence of zeros in the dataset. To visualize the data, we generated nMDS plots by site and year.
All analyses and graphs were made in PRIMERe version 7 with PERMANOVA extension.
To explore variation in Relief category by site we ran a Kruskal-Wallis comparison, and plotted mean substrate category by site with 95% confidence intervals.
We explored three concepts related to benthic cover - diversity, community composition and changes in abundance (percent cover).
Note: SCUBA UPC transects survey both biotic and abiotic habitat cover categories. We’ve used the term ‘species’ below to mean the combination of these cover categories.
With SCUBA benthic surveys, we explored several concepts related to species diversity at a given site:
To explore species richness at a given site, we reported total observed species richness and also calculated total estimated species richness.
To report total observed species richness at a given site we used incidence data across all sampling years because species turnover at each site (reserve or comparison area) likely occurs on timescales greater than one year.
To calculate estimated species richness, we used a rarefaction and extrapolation technique as described in Hsieh et al 2016, to calculate the effective number of species at each given site. This is the equivalent of calculating Hill diversity = 0. Hill numbers represent a unified standardization method for quantifying and comparing species diversity across multiple sites (Hill 1973), and they represent an intuitive and statistically rigorous alternative to other diversity indices (Chao et al 2014).
We used the same sampling based incidence data as used to document total observed species richness, using the iNext package in R to estimate the asymptote of the species accumulation curve, or the estimated total number of species observable by SCUBA UPC surveys at a given site. We also calculated confidence intervals associated with these rarefaction and extrapolation curves and can therefore compare across sites to explore similarity of total estimated species richness for a given sampling effort.
Richness alone does not sufficiently describe species biodiversity; additionally uniqueness, rarity and common species also shape and define concepts of biodiversity.
As a first step to exploring unique, rare and common species we generated species count tables. The species count tables include a total count for each species summed for all years by site, and for each year-site combination, as well as mean frequency of occurrence across all samples. This information can tell us both about how frequently the species is observed, as well as its relative abundance.
From the species count tables we identified rare species, as those with a frequency of occurrence of 10% or less (Green and Young 1993), and common species as those with a frequency of occurrence greater than 50% (in other words, the species is observed on one of every two transects). We also identified species that were unique to each marine reserve and comparison area.
To gain additional insight into species diversity, we explored several diversity indices by comparing Hill diversity numbers, also known as effective number of species, across sites using the iNEXT diversity package in R (Hsieh et al 2016). Hill numbers are parameterized by a diversity order q, which determines the measures’ sensitivity to species relative abundances (Hsieh et al 2016). Hill numbers include the three most widely used species diversity measures; species richness (q = 0), Shannon diversity (q=1) and Simpson diversity (q=2) (Hsieh et al 2016). We used sampling based incidence data with the iNext package in R, to plot rarefaction and extrapolation curves for each Hill number, and compare results across sites. We also calculated 95% confidence intervals associated with these rarefaction & extrapolation curves.
Finally we explored how diversity changed through time. First we plotted each species yearly rarefaction curve against the total cumulative rarefaction curve for all years combined to determine if we had sampled appropriately to compare species diversity from year to year. When our sampling effort was not adequate to compare across years, we pooled data from all years to compare average transect diversity using an analysis of variance (ANOVA). This would provide useful information about site diversity for an average sampling transect.
All analyses and graphs were created in R v4.0.2, using the iNEXT and Vegan packages.
We focused our community composition analysis on the question of whether variation in benthic cover community composition was driven by spatial (site) or temporal (year) factors. We did this through both data visualizations with non-multidimensional scaling (nMDS) plots and with statistical tests such as principal coordinates analyses (PCO),multivariate ANOVA tests (PERMANOVA), and dispersion tests (PERMDISP). In addition to site and year, we also explored several cover category-specific drivers of variation.
To explore variation by site and year, we used percent cover data collected on SCUBA UPC transects with no transformation (Clarke et al. 2006). Percent cover was calculated from SCUBA UPC count data (# points/ transect) so a similarity-based resemblance matrix was selected. A dummy variable (=1) was added prior to creating the resemblance matrix due to the high prevalence of zeros in the dataset. To visualize the data, we ran a cluster analysis and generated nMDS plots by site and year.
To test the statistical significance in our data of variation by site and year we ran a permutational analysis of variance (PERMANOVA), using a mixed model with site and year as fixed effects factors. Initial explorations of the first two years of data resulted in no apparent trends by depth between the two target depths, therefore depth was considered a random effect, and nested under site. To explore if any significant results of the PERMANOVA were related to true differences in location or differences in dispersion of samples (either by site or year to year), we ran a PERMDISP, a distance based test for homogeneity of multivariate dispersions for any factors that were significant in the PERMANOVA (Anderson and Walsh 2013). If a factor was significant in the PERMANOVA but not the PERMDISP, then it can be inferred that the significance is related to a location effect, but not a dispersion effect. If the factor is also significant in the PERMDISP, then significance in the PERMANOVA is related to dispersion, but there may also be a location effect.
Beyond site and year, we explored cover category-specific drivers in the variation of benthic community structure. We extended our data visualization, by performing a vector analysis of benthic cover categories in the community, selecting only the categories with > 0.5 Pearson correlations (Hinkle et al. 2003). If more than four categories were identified, we only reported on categories with high ( > 0.7) Pearson correlations. We then generated percent cover plots of the identified categories to visualize their relationship to site or year. To better understand how these categories contributed to variation in the data, we ran a principal coordinates (PCO) analysis, using a Bray-Curtis resemblance matrix, which provides information on the percent of variation explained by each axis.
All analyses and graphs were made in PRIMERe version 7 with PERMANOVA extension.
We explored changes in aggregate and focal species percent cover by site and year. For aggregate percent cover we summarized data across benthic cove taxonomic groups (similar to Lester et al. 2009) to identify broad scale differences in benthic cover by site and year. Based on the cover categories observed, we had 16 broad taxonomic groupings (Table 2). A list of which categories are included in each taxonomic groupings is provided in Table 3.
Table 2: Otter Rock SCUBA Cover Aggregate Percent Cover Broad Taxonomic Groupings
Table 3: Otter Rock SCUBA Cover Categories List and Their Broad Taxonomic Groupings
To determine which taxonomic groups (aggregate) were the most dominant, we summarized means and 95% confidence intervals grouped by site and as a timeseries. For focal species, we analyzed changes in percent cover by site and time with generalized additive mixed models (GAMMs). We modeled percent cover by using percent cover data with a quasi-binomial distribution to account for the metric (counts with an upper limit) and overdispersion (Zuur et al 2009). GAMMs were chosen to account for non-linear trends in percent cover by year detected in preliminary data exploration (Veneables and Dichmont 2004, Zuur et al. 2009). GAMMs were fitted using the mgcv package in R. Site was treated as a fixed categorical variable, while Year was continuous and smoothed with the thin-plate smoother ‘s()’ (Zuur et al 2009; Zuur 2012), grouped by Site, and k was restricted to 3 knots to prevent over-fitting. Depth-Bin was included as a random effect in the model to account for the sampling design targeting three fixed depths. We limited our modeling exercise to focus on Site and Year as these are two of the primary questions of interest. For species with very low percent cover across most sites and years, no statistical analyses were conducted as the data violated assumptions of the model framework.
There are two focal algae species groups for the OR Marine Reserves Ecological Monitoring Program recorded on benthic cover surveys:
SCUBA UPC surveys record data on two types of coralline algae - articulated coralline algae and crustose coralline algae. We report on coralline algae as an aggregate group, but also report on these two functional groupings of coralline algae as focal species.
Focal species were chosen based on their ecological, economic or management importance. For more information please refer to the methods Appendix detailing focal species selection. Additional species beyond focal species were included for analysis when they were identified in community analysis as being an important driver of variation.
All analyses and data plots were created in R v4.0.2, using the mgcv (version 1.8-36), mgcViz and gratia packages. Models were structured in R as follows:
Percent Cover = mgcv::gam(Percent_Cover ~ Site + s(Year, by = Site, k = 3) + s(Depth_bin, bs = “re”), family = quasibinomial)
SCUBA habitat and cover sampling efforts at Otter Rock and its comparison area resulted in five years of data collection, where varying sample sizes were collected per year (Fig. 2). With the exception of 2019, sampling efforts resulted in more transects completed in the marine reserve than in the Cape Foulweather Comparison Area. Sampling did not result in data from Cape Foulweather Comparison Area in 2010 or 2015.
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No apparent differences in substrate by site or year at the Otter Rock Marine Reserve and Cape Foulweather Comparison Area.
There was no structuring of substrate by site or year at the Otter Rock Marine Reserve and its comparison area. (Fig. 4).
More sand/gravel habitat surveyed in the Otter Rock Marine Reserve than Cape Foulweather Comparison Area
The only significant difference in substrate type by site was in the sand/gravel category, where the marine reserve had greater percent cover than the comparison area; for all other subtrate types there was no difference in mean percent cover of substrate type by site (Fig. 3, Table 5).
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No apparent differences in relief by site at the Otter Rock Marine Reserve and Cape Foulweather Comparison Area.
There was no structuring of relief by site at the Otter Rock Marine Reserve and its comparison area. (Fig. 6).
Overall relief was not substantially different among years, with the exception of 2019.
Relief was not substantially different among years, with the exception of 2019 where relief estimates were both more variable within-year and slightly different than all other sampling years (Fig. 6).
No difference in mean percent cover of relief between the Otter Rock Marine Reserve and Cape Foulweather Comparison Area
There was also no difference in mean percent cover of relief categories by site (Fig 5, Table 6).
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Benthic cover species richness is similar across the Otter Rock Marine Reserve and Cape Foulweather Comparison Area
Over the five years of sampling with SCUBA habitat and cover surveys, a total of 26 species (or species groups) were observed in the Otter Rock Marine Reserve (Table 7). The Cape Foulweather Comparison Area had similar total number of observed species (n=23). These observed numbers of species richness are similar to the estimated numbers of total species richness.
library(kableExtra)
<- data.frame(Area = c("Otter Rock Marine Reserve",
pna "Cape Foulweather Comparison Area"),
Observed_Richness = c("26","23"),
Estimated_Richness = c("32","26"),
LCL = c("26","23"),
UCL = c("64", "41"))
kbl(pna, caption = "Table 7: Observed and estimated benthic cover species richness by site with lower (LCL) and upper (UCL) 95% confidence limits") %>%
::kable_classic() kableExtra
Area | Observed_Richness | Estimated_Richness | LCL | UCL |
---|---|---|---|---|
Otter Rock Marine Reserve | 26 | 32 | 26 | 64 |
Cape Foulweather Comparison Area | 23 | 26 | 23 | 41 |
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Species rarefaction curves highlight that for any samples size, including those for any given year, the species richness among sites is very similar (Fig. 7). Both rarefaction curves appear to level off, suggesting saturation in species richness with this tool at these sites.
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Minimal differences in unique, common and rare species between the Otter Rock Marine Reserve and Cape Foulweather Comparison Area.
The Otter Rock Marine Reserve had more unique species (n = 7) than the Cape Foulweather Comparison Area (n = 4) (Table 8). The Otter Rock Marine Reserve (n = 4) had similar common species than the Cape Foulweather Comparison Area (n = 5). Two of the four common species in the marine reserve were also found to be common in the Cape Foulweather Comparison Area (Table 8). The Otter Rock Marine Reserve had more rare species (n = 8) than its comparison area (n = 5).
Many of the other benthic species were not observed frequently resulting in low frequency of occurrence. Not all species were observed each year, for a summary of species frequency of occurrence over the years by site please see tables below.
Unique species, pooled species counts across all years and species counts by individual sampling year are included in the following tables:
Table 9: Otter Rock Marine Reserve Pooled Species Frequency of Occurrence
Table 12: Cape Foulweather Comparison Area Pooled Species Frequency of Occurrence
Table 13: Cape Foulweather Comparison Area Species Counts by Year
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The Otter Rock Marine Reserve and Cape Foulweather Comparison Area have similar diversity indices for benthic cover species
The effective number of species is similar across all three diversity indices for the SCUBA benthic cover community at the marine reserve and Cape Foulweather Comparison Area (Fig. 9).
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We did not get enough samples to evaluate change in species diversity through time at the Otter Rock Marine Reserve and its comparison areas.
Species rarefaction curves by year for each site indicated that we did not sample enough on a yearly basis to compare changes in mean species richness through time (Fig. 10-11).
Fig. 10: Otter Rock Marine Reserves species rarefaction curves by year from SCUBA transects.
Fig. 11: Cape Foulweather Comparison Area species rarefaction curves by year from SCUBA transects.
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For an average day of sampling, benthic cover species diversity does not differ between the Otter Rock Marine Reserve and Cape Foulweather Comparison Area.
When comparing mean species richness for an average day of sampling, there was no difference between the marine reserve and Cape Foulweather Comparison Area (F.0.187, p>0.05) (Fig. 12).
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Benthic communities were similar at the Otter Rock Marine Reserve and Cape Foulweather Comparison Area.
There was no structuring of benthic cover community composition data at the Otter Rock Marine Reserve and Cape Foulweather Comparison Area. (Fig. 13).
Slight structuring by year with benthic community composition data at the Otter Rock Marine Reserve and its comparison area.
There was slight structuring by year with benthic community composition data at the Otter Rock Marine Reserve and the Cape Foulweather Comparison Area. Early survey years (2010-2011) appear slightly distinct from the later survey years (2015, 2017, 2019) (Fig. 13). This is likely because of a methodological change between 2011 and 2015, where sampling shifted away from kelp beds due to safety concerns (see methods section).
While multivariate statistics indicate some differences by site and depth, they account for little of the total variation in benthic community data
The main factors of site and depth, but not year or any of the interactions, significantly explained variation in benthic community composition with SCUBA data (Table 14). Site accounted for 9% of the variability in the model, while depth accounted for 6%. Combined, site and depth accounted for 15% of model variability, far below the variability explained by residuals (59%). Dispersion tests for site and depth reveal no significant dispersions between sites or depths sampled, indicating that significance of these two factors are related to location and not dispersion effects. While non-significant dispersion tests indicate a location effect for both site and depth, the amount of variance these two factors explain in the model is quite low.
Table 15: PERMDISP mean dispersions and standard errors by Site
Table 17: PERMDISP mean dispersions and standard errors by Depth
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Two benthic cover categories drive the majority of variation in community composition data, related to yearly changes
We explored category-specific drivers of variation, and found that Crustose Coralline Algae, (CCA) and Lacy Red Algae were driving the majority of variation in the benthic cover data (Fig. 14). Principal coordinate analysis revealed that ~28% of the variation along the x axis is explained by the trade-offs between Crustose Coralline Algae (CCA) and Lacy Red Algae, with higher percent cover of Lacy Red Algae in early survey years (2010/2011) and higher percent cover of CCA in later survey years (2015-2019). The y-axis accounts for ~14% of the variability.
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Four main taxonomic groups dominate the relative abundance at both the Otter Rock Marine Reserve and Cape Foulweather Comparison Area.
Four main taxonomic groups dominate the relative abundance among taxonomic groups - bryozoans, coralline algae, red algae and sponges - at the Otter Rock Marine Reserve and its comparison area. (Fig. 15).
Some differences by site in mean percent cover of benthic cover species.
The Otter Rock Marine Reserve had higher percent cover for tunicates and inanimate (e.g. bare sand/cobble, shell debris) groups (Fig. 15). For many other broad taxonomic groups differences in percent cover were not apparent.
Variable trends through time across broad taxonomic groups.
There were variable trends through time across broad taxonomic benthic cover groups (Fig. 15). The majority of taxonomic groups show no clear trends over time (e.g. anemones, bivalves, sponges). For a few groups, there are declines through time at one or both sites, such as with brown algae or sea grass.
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No significant difference in articulated coralline algae percent cover between the Otter Rock Marine Reserve and Cape Foulweather Comparison Area.
There was no difference in articulated coralline algae percent cover between the marine reserve and Cape Foulweather Comparison Area (p>0.05, Table 19).
Significant yearly trends in articulated coralline algae percent cover at the Otter Rock Marine Reserve and Cape Foulweather Comparison Area
There were significant trends by year in articulated coralline algae at the Otter Rock Marine Reserve and the Cape Foulweather Comparison Area (p < 0.05; Table 20). At the marine reserve percent cover decreased linearly through time, whereas at the Cape Foulweather Comparison Area there was a non-linear decrease through time, with most of the decrease occurring between the 2011 and 2017 sampling (Fig 16).
The random effect of depth was not identified as a significant component of variation (Table 20).
GAMM model results can be found in the links below:
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No significant difference in crustose coralline algae percent cover between the Otter Rock Marine Reserve and Cape Foulweather Comparison Area.
There was no difference in crustose coralline algae percent cover between the marine reserve and Cape Foulweather Comparison Area (p > 0.05; Table 21).
Significant yearly trends in crustose coralline algae at the Otter Rock Marine Reserve and Cape Foulweather Comparison Area.
There were significant trends by year in crustose coralline algae at the Otter Rock Marine Reserve and the Cape Foulweather Comparison Area (p < 0.05; Table 22). At the marine reserve, percent cover increased linearly through time, whereas at the Cape Foulweather Comparison Area there was a non-linear increase through time (Fig. 17).
The random effect of depth was not identified as a significant component of variation (Table 22).
GAMM model results can be found in the links below:
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No significant difference in lacy red algae percent cover between the the Otter Rock Marine Reserve than the Cape Foulweather Comparison Area.
There was no difference in percent cover of lacy red algae between the marine reserve then Cape Foulweather Comparison Area (p > 0.05; Table 23).
Significant yearly trends in lacy red algae percent cover at the Otter Rock Marine Reserve and the Cape Foulweather Comparison Area.
There were significant trends by year in lacy red algae at the Otter Rock Marine Reserve and Cape Foulweather Comparison Area (p < 0.05; Table 24). At both sites percent cover of lacy red algae declined through time (Fig 18).
The random effect of depth was identified as a significant component of variation (Table 24).
GAMM model results can be found in the links below:
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Anderson M.J., Walsh D.C.I. 2013. PERMANOVA, ANOSIM, and the Mantel test in the face of heterogeneous dispersions: What null hypothesis are you testing? Ecological Monographs 83(4): 557-574.
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### This can be a useful function to play a sound at the end of a long script
#beepr::beep()