1 Introduction: Redfish Rocks Marine Reserve Hook and Line Surveys

Hook and line (HnL) sampling targets demersal fishes living on rocky reef habitats using catch and release methods. All fish caught are identified to species level and measured for length. Fish are caught using standardized gear for a fixed amount of time, providing data on effort.

Our HnL sampling began at the Redfish Rocks Site in 2011, one year before harvest restrictions began. Sampling is conducted in the marine reserve and two comparison areas, Humbug and McKenzie Reef (see methods Appendix for additional information about comparison area selection). We sampled at the Redfish Rocks site in 2011 - 2017 and in 2019, providing eight years of data for our analysis and inclusion in the synthesis report.

Table 1: Redfish Rocks Hook and Line Monitoring Efforts. Sample sizes represent the number of cell-days per year at each site

Data from hook and line monitoring efforts can be used to explore questions about fish abundance and size from a method that is similar to local commercial nearshore hook and line fishing efforts. We can also explore these data with questions about diversity and community composition to compare across monitoring tools to understand tool bias or to validate trends seen across tools. This can further help us understand how the fish communities at these sites are similar or different. Data on abundance and size enable us to explore how fish catch, biomass, and size have changed 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.

1.1 Survey Maps

1.1.1 Redfish Rocks Marine Reserve

$Fig. 1: Map of Hook and Line Sampling Cells at the Redfish Rocks Marine Reserve$

Fig. 1: Map of Hook and Line Sampling Cells at the Redfish Rocks Marine Reserve

1.1.2 Humbug Comparison Area

$Fig. 1: Map of Hook and Line Sampling Cells at the Humbug Comparison Area$

Fig. 1: Map of Hook and Line Sampling Cells at the Humbug Comparison Area

1.1.3 Orford Reef Comparison Area

Fig. 1: Map of Hook and Line Sampling Cells at the Orford Reef Comparison Area

1.2 Research Questions

Diversity

Does species diversity vary by site or year?

Community Composition

Does catch composition vary by site or year?
- If yes, what species drive this variation?
- If no, what other factors may explain structure in catch composition?

Aggregate Abundance

Does aggregate catch vary by site or year?
Does aggregate biomass vary by site or year?

Focal Species Abundance

Does focal species catch vary by site or year?
Does focal species biomass vary by site or year?
Does focal species size vary by site or year?

2 Takeaways

Here we present a summary of our Hook and Line monitoring results and our 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.

2.1 Hook and Line Results Summary

Species diversity was similar between the Redfish Rocks Marine Reserves and its associated comparison areas.

The Redfish Rocks Marine Reserve and Humbug and Orford Reef Comparison Areas had similar fish species diversity as evidenced by the results of multiple analyses in the diversity section of this report. They have similar number of observed and estimated species, the number of unique and common species among sites is also similar. There are some slight differences in the Hill diversity numbers (effective number of species), but these are minimal and site specific.

Catch composition was similar between the Redfish Rocks Marine and its comparison areas across sites and years; variation was driven by the three most abundant species.

CPUE of Black Rockfish, Lingcod, and Kelp Greenling drove most of the observed variation in catch composition with hook and line monitoring data, rather than variation by site or year. Black Rockfish CPUE had an inverse relationship with CPUE of Lingcod, and Kelp Greenling, with higher CPUE of Black Rockfish associated with lower CPUE of Kelp Greenling and Lingcod (and vise versa). Season and habitat variables did not explain much model variation in catch composition.

We detected higher aggregate abundance at the Redfish Marine Reserve than the Humbug Comparison Area, but similar yearly trends between Redfish Marine Reserve and Humbug Comparison Area do not suggest a marine reserve effect.

While there was a higher average aggregate CPUE in the Redfish Rocks Marine Reserve than the Humbug Comparison Area, trends at the Redfish Marine Reserve and the Humbug Comparison Area had a similar decreasing trend after 2015. There was no significant yearly trend or difference in aggregate abundance with the Orford Reef Comparison Area.

Species abundances differed between the marine reserve and its comparison areas, mainly with higher average abundance metrics at the marine reserve.

Black Rockfish CPUE and BPUE were greater in the marine reserve compared to Orford Reef CA, and Blue/Deacon Rockfish CPUE and BPUE were greater in the reserve compared to Humbug CA. Lingcod and Kelp Greenling mean sizes were greater in the marine reserve, compared to Humbug and Orford Reef, respectively. There was only one case of the reserve having a lower CPUE than a comparison area (Orford Reef) with Blue/Deacon Rockfish.

Table 2: Snapshots of Mean Abundance Results

We were able to detect natural, interannual variability in CPUE, BPUE, and size for our most abundant species.

Our most abundant species surveyed with hook and line gear include Black Rockfish, Blue/Deacon Rockfish, Lingcod and Kelp Greenling. While yearly trends were inconsistent across species and survey locations, a majority of significant trends in CPUE and BPUE increased until 2015, then decreased between 2015 and 2019. There were not enough observations of China Rockfish, Yelloweye Rockfish, and Cabezon to detect changes between sites or trends by year.

Table 3: Snapshots of Abundance Trend Results

Top quartile sizes among species and sites did not reveal consistent patterns.

The largest top quartile sizes of fish differed among species and sites. Humbug Comparison Area had the largest top quartile sizes of Black Rockfish, where as the largest top quartile sized Lingcod were detected in the marine reserve. Orford Reef Comparison Area had the largest top quartile sizes of Kelp Greenling. Future tracking of this metric is expected to reveal changes in the larger size classes of species that might be obscured by recruitment of smaller fish in the marine reserve.

2.2 Conclusions

The results of this report were similar to those found in baseline monitoring at Redfish Rocks and Humbug Comparison Area, while adding new information about the Orford Reef Comparison Area.

Monitoring results from this report indicate that the Redfish Rocks Marine Reserve is similar to its two comparison areas - Humbug and Orford Reef. This was evident from our initial baseline report with data from the Humbug Comparison Area (ODFW 2014), and is further supported with these analyses, which include the addition of the Orford Reef Comparison Area. From a diversity and community composition perspective the differences among sites are minimal, and variations in the most common species are likely responsible for such differences. New information from this report highlights there are some differences in top quartile sizes among species, and highlights interannual variability in abundances and size of select species. From an abundance perspective, there are some slight differences between the Redfish Rocks Marine Reserve and each comparison area depending on the abundance metric of interest, but together these slight differences are inherent of natural variation in populations and communities than biologically relevant differences among sites.

We had limited ability to analyze data on solitary demersal species with our statistical approach in this report.

For China, Cabezon and Yelloweye, the number of observations per year per site for these species was less than fifteen individuals. This presented challenges in analyzing data from these species for this report. We chose not to do a species-specific modeling approach because with such few observations it was unclear if alternative statistical approaches would have produced fruitful results. Hook and line data gather information on other species (e.g. Copper, Quillback, Vermillion Rockfish), but these solitary demersal fish also had small sample sizes per site per year and similarly would have required an individualized approach for analysis.

Monitoring with hook and line surveys will continue at current levels and intervals.

Current efforts are able to detect interannual trends for the most abundant species although there is limited ability to detect changes of solitary demersal species with current efforts (e.g. China, Copper, Quillback). It is unclear whether increasing effort across all sites would increase our ability to detect change for these species, given that they are found in relatively low densities with this survey tool. Different analytical approaches than those in this report (e.g. presence-absence or other data-poor approaches) may yield relevant results with current data. Without an increase to program budget or staff, hook and line survey efforts will likely continue at current levels and intervals, especially as supplemental longline surveys allow for analysis on these solitary demersal species.

3 Hook & Line Methods

Hook and Line (HnL) sampling is conducted in the Redfish Rocks Marine Reserve, Humbug Comparison Area and Orford Reef Comparison Area. Monitoring began in Redfish and Humbug in 2011 with unequal sampling effort; 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. In 2014 Orford Reef was added in as a comparison area, in part because it is a favorite fishing location of the nearshore hook and line fleet out of Port Orford. Sampling effort targeted 2 days in the reserve, 2 days at Orford Reef and 2 days at Humbug Reef for a total of 6 days, for both spring and fall monitoring. Each day between 5-6 cells (500m x 500 m grids) are targeted, with 3 fifteen-minute fishing drifts occurring in each cell. All catch data collected from drifts are combined for a single cell; the unit of replication for hook and line catch data is at the cell-day level, while all size data is at the individual fish level. All fish caught during each drift are identified to species, measured and released. During each drift we also determined the amount of time not spent fishing, such as when anglers hang up on the bottom, stop to rest, or take a photo with their fish caught. This time is factored into the total time spent fishing, to truly represent fishing effort. We then calculate both a catch and biomass per unit effort for each given cell-day and species. For additional details on data collection, please review documentation in the Methods Appendix.

3.1 Diversity

With hook and line gear, we explored several concepts related to species diversity at a given site:

species richness
unique, common & rare species
diversity indices
diversity through time

3.1.1 Species Richness

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 each site (reserve or comparison area) likely has a species pool larger than can be sampled in any one year. We excluded unidentified species from the summaries as well as species not well targeted by hook and line gear (e.g. Wolf eel).

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 hook and line gear 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.

3.1.2 Unique, Common, and Rare Species

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. These tables exclude the unidentified individuals and species not well targeted by HnL gear. 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 caught in one out of every two cells sampled per day). We also identified species that were unique to each marine reserve and comparison area.

3.1.3 Diversity Indices

To gain additional insight into species diversity, we explored several diversity indices by comparing Hill diversity numbers (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.

3.1.4 Diversity Through Time

Finally we explored how diversity changed through time. First we plotted annual species rarefaction curves to determine if we had sampled appropriately (i.e. reached an asymptote) to compare species diversity from year to year. When our survey effort was not adequate to compare across years, we pooled data from all years to compare average daily diversity using an anova. Average cell diversity provides useful information about the expected number of species per hook and line sample unit, but is not directly related to total expected species richness in a given survey area.

All analyses and graphs were created in R v4.0.2, using the iNEXT and Vegan packages.

3.2 Community Composition

We focused our community composition analysis on the question of whether variation in catch 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 other potential drivers of variation including species-specific differences, habitat and environmental factors.

To explore variation by site and year, we used catch per unit effort (CPUE) data with a dispersion weighting transformation to downweight species that have high variability within each site. This allows us to better deal with highly aggregated schooling species without enhancing importance of rare species (Clarke et al. 2006). CPUE data are considered a rate (catch per angler hour) so a Euclidean distance 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 nested mixed model with site and year as fixed effects factors, and cell, our sampling replicate for hook and line gear, as a random effect, 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 (Anderson and Walsh 2013). Significant factors resulting from PERMANOVA test (Site, Cell, and/or Year) were then analyzed using a PERMDISP. 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 may also be a location effect.

Beyond site and year, we explored several additional factors that could be driving the variation in fish community structure. We extended our data visualization, by performing a vector analysis of fish species in the community, selecting only the species with > 0.5 Pearson correlations (Hinkle et al. 2003). We then generated density plots of the identified species to visualize their relationship to site or year. To better understand how these species contributed to variation in the data, we ran a principal coordinates (PCO) analysis, using a euclidean distance resemblance matrix, which provides information on the percent of variation explained by each axis.

In addition to species specific drivers of variation, we also explored the relationship between community composition and environmental variables. We employed several models incorporating month, proportion of hard bottom (rock) within a sampling cell, and average drift depth (averaged among cell/day combinations) to test if these habitat or environmental variables explained significant variation across sites or years. Due to strict requirements of these variables needing to match with each specific biological sample, only samples that contained estimates of all the above variables were used for analysis. An initial histogram of data revealed non-normal distributions so an overall data transformation (Log(x+1)) was employed. CPUE data are considered a rate (catch per angler hour) so a distance based resemblance matrix was selected, using a euclidean distance with an addition of a dummy variable (=1). With these data a distance-based linear model (DistLM) and a distance-based redundancy analysis (dbRDA) were conducted to determine which variables may explain variation across sites or years (Legendre and Anderson 1999). DistLM is akin to a multivariate multiple regressions model where the relationship between a multivariate data cloud (resemblance matrix) and one or more predictor variables are analyzed and modeled. The dbRDA routine then visualizes the model and fits it into a multi-dimensional space. In the DistLM model AIC values were used as the selection criteria and a Best selection procedure was employed to find the best combination of variables with the lowest AIC value as the best model fit.

All analyses and graphs were made in PRIMERe version 7 with PERMANOVA extension.

3.3 Abundance

We explored changes in aggregate and focal species catch rates (catch per unit effort, CPUE), biomass rates (biomass per unit effort, BPUE), and size (focal species only) by site and year with generalized additive mixed models (GAMM). We modeled raw catch and biomass data with an offset for fishing effort (angler hour) (Maunder and Punt 2004, Zuur 2012); size data were modeled without an offset. A negative binomial distribution was used for the CPUE model and a gaussian distribution on log-transformed biomass for the BPUE model. After exploration of spatial-temporal auto correlation of residuals with focal species data, a gaussian distribution for the size model. GAMMs were chosen to account for non-linear trends in metrics 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. Cell was included as a random effect in the model to account for the nested nature of the sampling design and for random differences in depth and habitat among cells. 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 CPUE across most sites and years, no statistical analyses were conducted as the data violated assumptions of the model framework.

Specifically we analyzed aggregate CPUE and BPUE, and species-specific CPUE, BPUE and size for focal species. Additionally for focal species, we complemented the GAMM modeling results for size with an analysis of variance (ANOVA) exploring changes in the mean top quartile size of fish by site. The mean top quartile size of fish is a measure of how the mean size of the largest quartile of fish changes through time, a technique borrowed from fish longevity studies (Choat and Robertson 2002), whereas the GAMM modeling results evaluate change in mean size of all individuals of a species. The mean size of fish may obscure gains in the larger size classes through time if there has been a strong recruitment of juvenile fishes. When results were significant, a Tukey test was run to determine significant differences among sites.

There are six focal fish species for the OR Marine Reserves Ecological Monitoring Program:

Black Rockfish; Sebastes melanops
Blue/Deacon Rockfish; Sebastes mystinus / S. diaconus
China Rockfish; Sebastes nebulosus
Yellow-eye Rockfish; Sebastes ruberrimus
Cabezon; Scorpaenichthys marmoratus
Lingcod; Ophiodon elongatus

These 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:

CPUE = mgcv::gam(Catch ~ Site + s(Year, by = Site, k = 3) + s(Cell_ID, bs = “re”), offset = log(Effort), family = nb)

BPUE = mgcv::gam(log(Biomass + 1) ~ Site + s(Year, by = Site, k = 3) + s(Cell_ID, bs = “re”), offset = log(Effort), family = gaussian)

Size = mgcv::gam(Length ~ Site + s(Year, by = Site, k = 3) + s(Cell_ID, bs = “re”), family = gaussian)

4 Redfish Rocks Results

Hook and line sampling efforts at Redfish Rocks and its comparison areas resulted in eight years of data collection, where varying sample sizes were collected per year (Fig. 2). The first two years of sampling (2011, 2012) resulted in more sampling effort in the marine reserve than in the Humbug Comparison Area. Sampling efforts at the Orford Reef Comparison Area did not begin until 2014.

Fig. 2: Hook and line monitoring efforts at the Redfish Rocks Marine Reserve and surrounding comparison areas resulted in varied sample sizes over the eight years of data collection. Sample size is represented in cell-days.

Table 4: Redfish Rocks Hook and Line Monitoring Efforts

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4.1 Diversity

4.1.1 Species richness

Species richness is similar across the Redfish Rocks Marine Reserve and its comparison areas

Over the eight years of sampling with hook and line gear a total of 17 species (or species groups) were observed in the Redfish Rocks Marine Reserve (Table 5). The Humbug Comparison Area had slightly fewer species, 15, whereas Orford Reef had the fewest total species observed with 13 (Table 5). These observed numbers of species richness are similar to the estimated numbers of total species richness.

library(kableExtra)

pna <- data.frame(Area = c("Redfish Rocks Marine Reserve", "Humbug Comparison Area", "Orford Reef Comparison Area"), 
                  Observed_Richness = c("17","15","13"), 
                  Estimated_Richness = c("18","15","13"), 
                  LCL = c("17","15","13"), 
                  UCL = c("28", "23","14"))


  kbl(pna, caption = "Table 5: Observed and estimated species richness by site with lower (LCL) and upper (UCL) 95% confidence limits") %>% 
  kableExtra::kable_classic()

Table 5: Observed and estimated species richness by site with lower (LCL) and upper (UCL) 95% confidence limits
Area	Observed_Richness	Estimated_Richness	LCL	UCL
Redfish Rocks Marine Reserve	17	18	17	28
Humbug Comparison Area	15	15	15	23
Orford Reef Comparison Area	13	13	13	14

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Species rarefaction curves highlight that at small samples sizes, such as those for any given year, the species richness among sites is very similar (Fig. 3). As effort across sites increases, more rare species are observed at the Marine Reserve and Humbug Comparison Area than at Orford Reef, resulting in higher estimated species richness for these sites (Fig. 3, Table 5). The Orford Reef rarefaction curve levels off, suggesting saturation in species richness with this tool at this site.

Fig. 3: Species rarefaction curves for the Redfish Rocks Marine Reserve and its two comparison areas. Data are pooled across all years of sampling for each site.

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4.1.2 Unique, common and rare species

Although the number of rare species differ between the marine reserve and the Orford Reef Comparison Area, the number of unique and common species among all sites is similar.

The Redfish Rocks Marine Reserve had two unique species - both singleton observations - the Brown Irish Lord (Hemilepidotus spinosus) and the Gopher Rockfish (S.carnatus). No unique species were found at either the Humbug Comparison Area or Orford Reef Comparison Area. The Redfish Rocks Marine Reserve (n = 3) had similar numbers of common species to both the Humbug Comparison Area (n = 2) and the Orford Reef Comparison Area (n = 4). Across all sites, the two most common species by count and frequency of occurrence were Black Rockfish and Lingcod. The Redfish Rocks Marine Reserve and Humbug Comparison Area had more rare species (both sites n = 6) than the Orford Reef Comparison Area (n = 3). Many of the other species of fisheries interest - China, Quillback, Cabezon, Yelloweye, Copper and Vermilion Rockfish - were not caught frequently resulting in low pooled counts. Not all species were observed each year, for a summary of species counts over the years by site please see tables below.

Pooled species counts across all years and species counts by individual sampling year are included in the following tables:

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4.1.2.1 Redfish Rocks Marine Reserve

Fig. 4: Relative frequency of occurrence of species observed at the Redfish Rocks Marine Reserve and its associated Comparison Areas in hook and line samples. See separate tabs for each site.

4.1.2.2 Humbug Comparison Area

Fig. 4: Relative frequency of species observed at the Redfish Rocks Marine Reserve and the comparison areas in hook and line samples. See separate tabs for each site.

4.1.2.3 Orford Reef Comparison Area

Fig. 4: Relative frequency of species observed at the Redfish Rocks Marine Reserve and the comparison areas in hook and line samples. See separate tabs for each site.

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4.1.3 Diversity Indices

The Redfish Rocks Marine Reserve has more rare species than Orford Reef Comparison Area, and a greater evenness of species than the Humbug Comparison Area

Slight differences in catch composition are observed when comparing the effective number of species across the three sites (Fig. 5). When q = 0, a derivation of species richness, at larger sample sizes, the marine reserve has more rare species than the Orford Reef Comparison Area, but is similar to the Humbug Comparison Area. For Hill numbers 1 and 2, the marine reserve and Orford Reef have similar numbers of effective species, but the Humbug Comparison Area has a lower effective number of species. This indicates that the Redfish Rocks Marine Reserve has greater species evenness than the Humbug Comparison Area (Fig. 5).

Fig. 5: Comparing effective number of species (Hill diversity numbers) across the Redfish Rocks Marine Reserve and its associated Comparison Areas from hook and line samples. 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).

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4.1.4 Diversity through time

We did not get enough samples to evaluate change in species diversity through time at the Redfish Rocks 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. 6-8). When plotting mean species richness by year with 95% confidence intervals, the confidence intervals are quite large suggesting more sampling is needed to detect any meaningful changes.

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For an average day of sampling, Orford Reef Comparison Area has higher species diversity than the Redfish Rocks Marine Reserve.

When comparing mean species richness for an average day of sampling, Orford Reef was the most diverse (Fig. 9). Likely this is because Orford Reef has more common species than either the Redfish Rocks Marine Reserve or the Humbug Comparison Area.

Fig. 9: Mean species richness by area with 95% confidence intervals at the Redfish Rocks Marine Reserve and associated Comparison Areas from hook and line data.

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4.2 Community Composition

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4.2.1 Variation by Site and Year

Catch composition was similar across sites and years at the Redfish Rocks Marine Reserve and its comparison areas with hook and line data.

There was no structuring of catch composition data by site or year at the Redfish Rocks Marine Reserve and its comparison areas (Fig. 10).

While multivariate statistics indicate some differences by site and year, they account for little of the total variation in catch composition.

PERMANOVA results indicate that site, sampling cell, year and the interaction between site and year are significant for catch composition with hook and line data (Table 12). Estimated variation described by each of the variables and variable interactions was very small. Year accounted for the highest variability of all the variables/interactions but only accounted for 6.8% of total variation, where as the residuals describe over 90% of the variation in the results. Therefore, while these factors were significant they are likely not biologically relevant as they explain such a small portion of the variation in the data.

Table 12: PERMANOVA results

Dispersion (PermDISP) tests indicate no difference in dispersion by site (p = 0.251), but differences in dispersion by year (p=0.002). Two years, 2012 and 2016, had smaller mean dispersion than others and were significantly different from others in pairwise comparisons (all p < 0.01) (Table 13, 14). This suggests the significance identified in the PERMANOVA is more likely results of differences in dispersions between years rather than of differences in spatial location among years.

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4.2.1.1 Site

Fig. 10: Results from nMDS plots with CPUE data, demonstrating similarity in catch composition at the Redfish Rocks Marine Reserve and its surrounding comparison areas. See separate tabs for site and year.

4.2.1.2 Year

Fig. 10: Results from nMDS plots for CPUE data, demonstrating similairity in catch composition at the Redfish Rocks Marine Reserve and its surrounding comparison areas. See separate tabs for site and year

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4.2.2 Other drivers of variation

Black Rockfish, Lingcod, and Kelp Greenling catch drive the majority of variation in catch composition regardless of site or year.

We explored species-specific drivers of variation, and found that black rockfish, lingcod and kelp greenling were driving the majority of fish catch composition (Fig. 11). Principal coordinate analysis revealed that ~30% of the variation is explained by CPUE of lingcod and kelp greenling and 23% of variation is described by black rockfish. There is also a trade-off in species composition; at higher CPUE of black rockfish, there are lower CPUE of kelp greenling and lingcod (Fig. 11). Together the CPUE of these three species accounts for over 53% of model variability.

4.2.2.1 PCO Vector Plot

Fig. 11: Results from species correlations and principal coordinate analysis demonstrating that black rockfish, lingcod and kelp greenling drive variaiton in community structure at the Redfish Rocks Marine Reserve and its surrounding comparison areas. Bubble color/size represents species-specific CPUE in each sample (Species CPUE range indicated in legend). See separate tabs for vector and bubble plots.

4.2.2.2 PCO Bubble Plot

Fig. 11: Results from species correlations and principal coordinate analysis demonstrating that black rockfish, lingcod and kelp greenling drive variation in community structure regardless of site at the Redfish Rocks Marine Reserve and its surrounding comparison areas. Bubble color / size represents species-specific CPUE in each sample (Species CPUE range indicated in legend).See specific tabs for vector and bubble plots.

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Including season and habitat variables did not explain much of the total variation in the model.

DISTLM results indicated all four environmental variables (year, month, proportion rock and average drift depth), were significant and the best model included all of these variables (Table 15). Year roughly correlated with the x axis and explained 64% of model variation (not including residuals), but only explained 6.5% of the total variation (residuals included). This indicates that although significant, year alone does not explain very much of the variation in fish communities. Proportion rock roughly correlated with the y axis and explained 21% of the model variation but only explained 2% of the overall variation. Combined, year and hard bottom habitat only accounted for 8.5% of the variability, indicating that while significant, these factors likely do not have a strong role in structuring catch composition.

Table 15: Redfish Rocks DistLM results

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4.3 Aggregate Abundance

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4.3.1 Aggregate CPUE

Significantly higher aggregate CPUE in the Redfish Rocks Marine Reserve than the Humbug Comparison Area.

Redfish Rocks Marine Reserve had statistically higher aggregate CPUE than the Humbug Comparison Area (p < 0.05; Table 16). There was no difference in aggregate CPUE between the marine reserve and the Orford Comparison Area (p > 0.05; Table 16).

Significant yearly trends in aggregate CPUE at both the Redfish Rocks Marine Reserve and Humbug Comparison Area.

There were significant yearly trends in aggregate CPUE at both the Redfish Rocks Marine Reserve and Humbug Comparison Area (p < 0.05; Table 17). At the marine reserve, CPUE increased to a peak around 2015, then declined through 2019. At the Humbug Comparison Area, CPUE remained consistent through the first years of sampling, and then declined from 2015 through 2019. There was no significant trend in aggregate CPUE at the Orford Reef Comparison Area (p > 0.05; Table 17).

The random effect of cell was identified as a significant component of variation (Table 17).

GAMM model results can be found in the links below:

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4.3.1.1 Aggregate CPUE timeseries

Fig. 12: Aggregate catch per unit effort (CPUE) timeseries and modeled GAMM results with 95% confidence intervals, at the Redfish Rocks Marine Reserve and its associated comparison areas. See separate tabs for timeseries and GAMM results.

4.3.1.2 Aggregate CPUE modeled GAMM results

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4.3.2 Aggregate BPUE

No significant difference in aggregate BPUE between the Redfish Rocks Marine Reserve and its comparison areas.

There was no statistical difference in aggregate BPUE between the Redfish Rocks Marine Reserve and either the Humbug or Orford Reef Comparison Areas (p > 0.05, Table 18).

Significant yearly trends in aggregate BPUE at both the Redfish Rocks Marine Reserve and Humbug Comparison Area.

There were significant yearly trends in aggregate BPUE at both the Redfish Rocks Marine Reserve and Humbug Comparison Area (p < 0.05; Table 19). At the marine reserve, BPUE increased to a peak around 2015, then declined through 2019. The Humbug Comparison Area had a very similar trend, with BPUE increasing to a peak in 2015, then declining through 2019. There was no significant trend in aggregate BPUE at the Orford Reef Comparison Area (p > 0.05; Table 19).

The random effect of cell was identified as a significant component of variation (Table 19).

GAMM model results can be found in the links below:

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4.3.2.1 Aggregate BPUE timeseries

Fig. 13: Aggregate biomass per unit effort (BPUE) timeseries and GAMM model results with 95% confidence intervals, at the Redfish Rocks Marine Reserve and its associated comparison areas. See separate tabs for timeseries and GAMM results.

4.3.2.2 Aggregate BPUE modeled GAMM results

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4.4 Focal Species Abundance & Size

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4.4.1 Black Rockfish, S. melanops

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4.4.1.1 CPUE

Significantly higher Black Rockfish CPUE at the Redfish Rocks Marine Reserve than at Orford Reef Comparison Area.

Redfish Rocks Marine Reserve had statistically higher CPUE of Black Rockfish than the Orford Reef Comparison Area (p < 0.05; Table 20). There were no differences in Black Rockfish CPUE between the Redfish Rocks Marine Reserve and the Humbug Comparison Area (p > 0.05; Table 20).

Significant yearly trends in Black Rockfish CPUE at the Redfish Rocks Marine Reserve and Humbug Comparison Area.

There were significant trends by year at both the Redfish Rocks Marine Reserve and Humbug Comparison Area (p < 0.05; Table 21). At the marine reserve, CPUE increased to a peak around 2015, then declined through 2019. The Humbug Comparison Area had a very similar trend, with CPUE increasing to a peak in 2015, then declining through 2019. There was not a statistically significant yearly trend in Black Rockfish CPUE at the Orford Reef Comparison Area (p > 0.05; Table 21).

The random effect of cell was identified as a significant component of variation (Table 21).

GAMM model results can be found in the links below:

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4.4.1.1.1 Black Rockfish CPUE Timeseries

Fig. 14: Black Rockfish catch per unit effort (CPUE) timeseries and GAMM model results with 95% confidence intervals, at the Redfish Rocks Marine Reserve and its associated comparison areas. See separate tabs for timseries and GAMM results.

4.4.1.1.2 Black Rockfish CPUE Modeled GAMM Results

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4.4.1.2 Size

No difference in Black Rockfish mean size between the Redfish Rocks Marine Reserve and its comparison areas.

There were no statistically significant differences in mean size of Black Rockfish among sites (all p > 0.05; Table 22).

Significant yearly trends in Black Rockfish mean size at the Redfish Rocks Marine Reserve and Humbug Comparison Area.

There were significant yearly trends in mean size at both the Redfish Rocks Marine Reserve (p < 0.05) and the Humbug Comparison Area (p < 0.05; Table 23). At the Redfish Rocks Marine Reserve, mean size increased to a peak in 2015/2016 and then declined gradually through 2019. The Humbug Comparison Area had a decline in mean size from 2011 to 2019. Even though the model results reveal statistically significant yearly trends, the mean size time series underscores that mean sizes do not fluctuate more than 1-2 cm per year, per site, and likely represents natural variation as opposed to biological significance through time (Fig. 15).

The random effect of cell was identified as a significant component of variation (Table 23).

GAMM model results can be found in the links below:

$~$

Humbug Comparison Area had the largest quartile of Black Rockfish sizes, followed by Redfish Rocks Marine Reserve, and Orford Reef Comparison Area had the smallest top quartile of sizes

There were differences by site in the top quartile of sizes of Black Rockfish (F. 25.418, p. <0.05). Humbug Comparison Area had the largest fish, followed by the marine reserve, and Orford Reef Comparison Area had the smallest top quartile of Black Rockfish sizes (all adj. p < 0.05).

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4.4.1.2.1 Black Rockfish Mean Size Timeseries

Fig. 15: Black Rockfish mean size timeseries and GAMM model results with 95% confidence intervals at the Redfish Rocks Marine Reserve and its associated comparison areas.See separate tabs for timseries and GAMM results.

4.4.1.2.2 Black Rockfish Size Modeled GAMM Results

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4.4.1.3 BPUE

Statistically higher Black Rockfish BPUE at the Redfish Rocks Marine Reserve than Orford Reef Comparison Area.

Redfish Rocks Marine Reserve had statistically higher BPUE than the Orford Reef Comparison Area (p < 0.05; Table 24). There were no statistical differences in Black Rockfish BPUE between the Redfish Rocks Marine Reserve and the Humbug Comparison Area (p > 0.05; Table 24).

Significant yearly trends in Black Rockfish BPUE at the Redfish Rocks Marine Reserve and its surrounding comparison areas.

There were significant yearly trends at the Redfish Rocks Marine Reserve, Humbug Comparison Area, and Orford Reef Comparison Area with Black Rockfish BPUE (p < 0.05, Table 25). At the Redfish Rocks Marine Reserve, Black Rockfish BPUE increased to a peak around 2015, then declined through 2019. The Humbug Comparison Area had similar trends with BPUE increasing to a peak in 2015, then declining through 2019. The Orford Reef Comparison Area sampling started in 2015 and had a declining trend through 2019.

The random effect of cell was identified as a significant component of variation for BPUE (Table 25).

GAMM model results can be found in the links below:

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4.4.1.3.1 Black Rockfish BPUE Timeseries

Fig. 16: Black Rockfish biomass per unit effort (BPUE) timeseries and GAMM model results with 95% confidence intervals, at the Redfish Rocks Marine Reserve and its associated comparison areas. See separate tabs for timseries and GAMM results.

4.4.1.3.2 Black Rockfish BPUE Modeled GAMM Results

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4.4.2 Blue/Deacon Rockfish, S.mystinus / S.diaconus

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4.4.2.1 CPUE

The Redfish Rocks Marine Reserve had significantly higher Blue/Deacon Rockfish CPUE than the Humbug Comparison Area, but a lower CPUE than the Orford Reef Comparison Area.

Redfish Rocks Marine Reserve had higher CPUE of Blue/Deacon Rockfish than the Humbug Comparison Area (p < 0.05; Table 26). However, the Redfish Rocks Marine Reserve had significantly lower CPUE of Blue/Deacon Rockfish than the Orford Reef Comparison Area (p < 0.05; Table 26).

Significant yearly trends in Blue/Deacon Rockfish CPUE at the Redfish Rocks Marine Reserve and its surrounding comparison areas.

There were significant yearly trends in Blue/Deacon Rockfish CPUE at the Redfish Rocks Marine Reserve and its surrounding comparison areas (all p < 0.05, Table 27). All sites showed a decline in Blue/Deacon Rockfish CPUE through time, with only Orford Reef Comparison Area showing a slight increase in 2019 from a low in 2017.

The random effect of cell was identified as a significant component of variation (Table 27).

GAMM model results can be found in the links below:

$~$ $~$

4.4.2.1.1 Blue/Deacon Rockfish CPUE Timeseries

Fig. 17: Blue/Deacon Rockfish catch per unit effort (CPUE) timeseries and modeled GAMM results with 95% confidence intervals, at the Redfish Rocks Marine Reserve and its associated comparison areas. See separate tabs for timseries and GAMM results.

4.4.2.1.2 Blue/Deacon Rockfish CPUE Modeled GAMM Results

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4.4.2.2 Size

No difference in mean size of Blue/Deacon Rockfish between the Redfish Rocks Marine Reserve and its comparison areas.

There were no significant differences in mean size of Blue/Deacon Rockfish among sites (all p > 0.05, Table 28).

No significant yearly trend in Blue/Deacon Rockfish mean size at the Redfish Rocks Marine Reserve or its surrounding comparison areas.

There were no significant yearly trends in mean size of Blue/Deacon Rockfish at the Redfish Rocks Marine Reserve or its surrounding comparison areas (all p > 0.05, Table 29, Fig. 28).

The random effect of cell was identified as a significant component of variation (Table 29).

GAMM model results can be found in the links below:

$~$

The Redfish Rocks Marine Reserves has larger top quartile sizes of Blue/Deacon Rockfish than the Orford Reef Comparison Area.

There were differences by site in the top quartile of sizes of Blue/Deacon Rockfish (F. 7.111, p. < 0.05). Both the marine reserve and Humbug Comparison Area had larger top quartile size of Blue/Deacon Rockfish than Orford Reef Comparison Area (all adj. p < 0.05), but there was no statistical significance in top quartile sizes between the marine reserve and Humbug Comparison Area (adj. p > 0.05).

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4.4.2.2.1 Blue/Deacon Rockfish Mean Size Timeseries

Fig. 18: Blue/Deacon Rockfish mean size timeseries and GAMM model results with 95% confidence intervals at the Redfish Rocks Marine Reserve and its associated comparison areas. See separate tabs for timseries and GAMM results.

4.4.2.2.2 Blue/Deacon Rockfish Size Modeled GAMM Results

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4.4.2.3 BPUE

Significantly higher Blue/Deacon Rockfish BPUE at the Redfish Rocks Marine Reserve than at Humbug Comparison Area.

Redfish Rocks Marine Reserve had statistically higher BPUE of Blue/Deacon Rockfish than the Humbug Comparison Area (p < 0.05; Table 30). There were no differences in Blue/Deacon Rockfish BPUE between the Redfish Rocks Marine Reserve and the Orford Reef Comparison Area (p > 0.05; Table 30).

Significant yearly trends in Blue/Deacon Rockfish BPUE at the Redfish Rocks Marine Reserve and Orford Reef Comparison Area.

There were significant trends by year at both the Redfish Rocks Marine Reserve and Orford Reef Comparison Area (p < 0.05; Table 31). At the marine reserve, Blue/Deacon Rockfish BPUE slightly increased to a peak around 2015, then declined through 2019. The Orford Reef Comparison Area had a differing trend, with BPUE declining between 2015-2017, then increasing through 2019. There was not a statistically significant yearly trend in Blue/Deacon Rockfish BPUE at the Orford Reef Comparison Area (p > 0.05; Table 31).

The random effect of cell was identified as a significant component of variation (Table 31).

GAMM model results can be found in the links below:

$~$ $~$

4.4.2.3.1 Blue/Deacon Rockfish BPUE Timeseries

Fig. 19: Blue/Deacon Rockfish biomass per unit effort (BPUE) timeseries and modeled GAMM results with 95% confidence intervals, at the Redfish Rocks Marine Reserve and its associated comparison areas. See separate tabs for timseries and GAMM results.

4.4.2.3.2 Blue/Deacon Rockfish BPUE Modeled GAMM Results

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4.4.3 China Rockfish, S. nebulosus

$~$

4.4.3.1 CPUE

Too few observations of China Rockfish to detect differences in CPUE by site or year.

Catch rates of China Rockfish were very low across all sites and years (e.g. 1 fish caught per 10 angler hours fishing; Fig. 20). See Redfish Rocks Longline Appendix for analysis of China Rockfish CPUE with data from a sampling method that better targets this species.

4.4.3.1.1 China Rockfish CPUE by Site

Fig. 20: China Rockfish catch per unit effort (CPUE) by site and yearly timeseries with 95% confidence intervals, at the Redfish Rocks Marine Reserve and its associated comparison areas.

4.4.3.1.2 China Rockfish CPUE Timeseries

Fig. 20: China Rockfish catch per unit effort (CPUE) by site and yearly timeseries with 95% confidence intervals, at the Redfish Rocks Marine Reserve and its associated comparison areas.

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4.4.3.2 Size

Too few observations of China Rockfish to detect differences in size by site or year.

Catch rates of China Rockfish were very low across all sites and years (e.g. 1 fish caught per 10 angler hours fishing;(Fig. 21)). China Rockfish mean size timeseries data are presented below (Fig. 21). See Redfish Rocks Longline Appendix for analysis of China Rockfish mean size data from a sampling method that better targets this species.

4.4.3.2.1 China Rockfish Mean Size Timeseries

Fig. 21: China Rockfish mean size timeseries with 95% confidence intervals at the Redfish Rocks Marine Reserve and its associated comparison areas.

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4.4.3.3 BPUE

Too few observations of China Rockfish to detect differences in BPUE by site or year.

Catch rates of China Rockfish were very low across all sites and years (e.g. 1 fish caught per 10 angler hours fishing; Fig. 22). BPUE timeseries data are presented below (Fig. 22). See Redfish Rocks Longline Appendix for analysis of China Rockfish BPUE with data from a sampling method that better targets this species.

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4.4.3.3.1 China Rockfish BPUE Timeseries

Fig. 22: China Rockfish biomass per unit effort (BPUE) timeseries with 95% confidence intervals at the Redfish Rocks Marine Reserve and its associated comparison areas.

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4.4.4 Yelloweye Rockfish, S.ruberrimus

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4.4.4.1 CPUE

Too few observations of Yelloweye Rockfish to detect differences in CPUE by site or year.

Catch rates of Yelloweye Rockfish were very low across all sites and years (e.g. 1 fish caught per 10 angler hours fishing; Fig. 23), so statistical analyses were not conducted. See Redfish Rocks Longline Appendix for analysis of Yelloweye Rockfish CPUE with data from a sampling method that better targets this species.

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4.4.4.1.1 Yelloweye Rockfish CPUE Timeseries

Fig. 23: Yelloweye Rockfish catch per unit effort (CPUE) timeseries with 95% confidence intervals, at the Redfish Rocks Marine Reserve and its associated comparison areas.

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4.4.4.2 Size

Too few observations of Yelloweye Rockfish to detect differences in size by site or year.

Catch rates of Yelloweye Rockfish were very low across all sites and years (e.g. 1 fish caught per 10 angler hours fishing; Fig. 24), so statistical analyses on size data were not conducted. Yelloweye Rockfish mean size timeseries data are presented below (Fig. 24). See Redfish Rocks Longline Appendix for analysis of Yelloweye Rockfish mean size data from a sampling method that better targets this species.

4.4.4.2.1 Yelloweye Rockfish Mean Size Timeseries

Fig. 24: Mean Yelloweye Rockfish sizes with 95% confidence intervals by site and year, at the Redfish Rocks Marine Reserve and its associated comparison areas.

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4.4.4.3 BPUE

Too few observations of Yelloweye Rockfish to detect differences in BPUE by site or year.

Catch rates of Yelloweye Rockfish were very low across all sites and years (Fig. 25), so statistical analyses on BPUE data were not conducted. BPUE timeseries data are presented below (Fig. 25). See Redfish Rocks Longline Appendix for analysis of Yelloweye Rockfish BPUE with data from a sampling method that better targets this species.

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4.4.4.3.1 Yelloweye Rockfish BPUE Timeseries

Fig. 25: Yelloweye Rockfish biomass per unit effort (BPUE) timeseries with 95% confidence intervals, at the Redfish Rocks Marine Reserve and its associated comparison areas.

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4.4.5 Cabezon, Scorpaenichthys marmoratus

$~$

4.4.5.1 CPUE

Too few observations of Cabezon to detect differences in CPUE by site or year.

Catch rates of Cabezon were low across all sites and years (e.g. 1 fish caught per 10 angler hours fishing; Fig. 26), so statistical analyses on CPUE data were not conducted. See Redfish Rocks Longline Appendix for analysis of Cabezon with data from a sampling method that better targets this species.

4.4.5.1.1 Cabezon CPUE Timeseries

Fig. 26: Cabezon catch per unit effort (CPUE) timeseries with 95% confidence intervals, at the Redfish Rocks Marine Reserve and its associated comparison areas.

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4.4.5.2 Size

Too few observations of Cabezon to detect differences in size by site or year.

Catch rates of Cabezon were very low across all sites and years (e.g. 1 fish caught per 10 angler hours fishing; Fig. 27), so statistical analyses on size data were not conducted. Cabezon mean size timeseries data are presented below (Fig. 27). See Redfish Rocks Longline Appendix for analysis of Cabezon mean size data from a sampling method that better targets this species.

4.4.5.2.1 Cabezon Size Timeseries

Fig. 27: Cabezon mean size timeseries and GAM model results with 95% confidence intervals at the Redfish Rocks Marine Reserve and its associated comparison areas.See separate tabs for timseries and GAM results.

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4.4.5.3 BPUE

Too few observations of Cabezon to detect differences in BPUE by site or year.

Catch rates of Cabezon were very low across all sites and years (e.g. 1 fish caught per 10 angler hours fishing; Fig. 28), so statistical analyses on BPUE data were not conducted. Cabezon BPUE timeseries data are presented below (Fig. 28). See Redfish Rocks Longline Appendix for analysis of Cabezon BPUE with data from a sampling method that better targets this species.

4.4.5.3.1 Cabezon BPUE Timeseries

Fig. 28: Cabezon biomass per unit effort (BPUE) time series with 95% confidence intervals, at the Redfish Rocks Marine Reserve and its associated comparison areas.

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4.4.6 Lingcod, Ophiodon elongatus

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4.4.6.1 CPUE

No significant difference in Lingcod CPUE between the Redfish Rocks Marine Reserve and its comparison areas.

There was no statistical difference in Lingcod CPUE among the Redfish Rocks Marine Reserve and its comparison areas (all p > 0.05; Table 32).

Significant yearly trend at the Redfish Rocks Marine Reserve in Lingcod CPUE but not at its comparison areas.

The only site with significant yearly trends was at the Redfish Rocks Marine Reserve (p < 0.05; Table 33). Lingcod CPUE increased at the Redfish Rocks Marine Reserve to peak around 2015, then declined through 2019.

The random effect of cell was not significant (Table 33).

GAMM model results can be found in the links below:

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4.4.6.1.1 Lingcod CPUE Timeseries

Fig. 29: Lingcod catch per unit effort (CPUE) timeseries and GAMM model results with 95% confidence intervals at the Redfish Rocks Marine Reserve and its associated comparison areas. See separate tabs for timseries and GAMM results.

4.4.6.1.2 Lingcod CPUE Modeled GAMM Results

Fig. 29: Lingcod catch per unit effort (CPUE) timeseries and GAMM model results with 95% confidence intervals, at the Redfish Rocks Marine Reserve and its associated comparison areas. See separate tabs for timseries and GAMM results.

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4.4.6.2 Size

The Redfish Rocks Marine Reserve has significantly larger mean size Lingcod than the Humbug Comparison Area.

The Redfish Rocks Marine Reserve had larger mean size Lingcod than the Humbug Comparison Area(p < 0.05, Table 34, Fig. 30). The mean size of Lingcod at the marine reserve compared to the Orford Reef Comparison Area was on the verge of significance (p = 0.055).

Significant yearly trends in Lingcod size at the Redfish Rocks Marine Reserve and Humbug Comparison Area.

There was a significant yearly trend in Lingcod mean size through time at both the Redfish Rocks Marine Reserve and Humbug Comparison Area (Table 35). At the Redfish Rocks Marine Reserve, there was an increase through time, with an increase in size from 2011 to a peak in 2019 (Fig. 30). At the Humbug Comparison Area the yearly trend was different; mean size of Lingcod increased from 2011 to a peak in 2016, followed by a decline in mean size through 2019 (Fig. 30).

The random effect of cell was identified as a significant component of variation for mean size of Lingcod (Table 35).

GAMM model results can be found in the links below:

$~$

The Redfish Rocks Marine Reserve has larger top quartile sizes of Lingcod than its comparison areas.

There were differences by site in the top quartile of sizes of Lingcod (F.12.108, p.< 0.05). The Redfish Rocks Marine Reserve had larger top quartile sizes of Lingcod than both of its comparison areas (all adj. p < 0.05).

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4.4.6.2.1 Lingcod Mean Size Timeseries

Fig 30: Lingcod mean size timeseries and GAMM model results with 95% confidence intervals at the Redfish Rocks Marine Reserve and its associated comparison areas.See separate tabs for timseries and GAMM results.

4.4.6.2.2 Lingcod Modeled GAMM Results

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4.4.6.3 BPUE

No significant differences in Lingcod BPUE between the Redfish Rocks Marine Reserve and its comparison areas.

There was no statistical difference in Lingcod BPUE between the Redfish Rocks Marine Reserve and its comparison areas (all p > 0.05, Table 36).

Significant yearly trends in Lingcod BPUE at the Redfish Rocks Marine Reserve and Orford Reef Comparison Area.

There was a statistically significant trend by year at the Redfish Rocks Marine Reserve and Orford Reef Comparison Area (p < 0.05; Table 37). At the Redfish Rocks Marine Reserve, Lingcod BPUE increased to a peak in 2015 followed by a decline through 2019 (Fig. 31). BPUE at the Orford Reef Comparison Area followed a similar trend, but with an increase in BPUE to a peak around 2017, followed by a decline through 2019. There was not a statistically significant yearly trend in Lingcod BPUE at the Humbug Comparison Area (p > 0.05; Table 37).

The random effect of cell was not statistically significant (Table 37).

GAMM model results can be found in the links below:

$~$ $~$

4.4.6.3.1 Lingcod BPUE Timeseries

Fig. 31: Lingcod biomass per unit effort (BPUE) timeseries and modeled GAMM results with 95% confidence intervals, at the Redfish Rocks Marine Reserve and its associated comparison areas. See separate tabs for timseries and GAMM results.

4.4.6.3.2 Lingcod BPUE Modeled GAMM Results

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4.5 Additional Species Abundance & Size

4.5.1 Kelp Greenling, Hexagrammos decagrammus

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4.5.1.1 CPUE

No significant difference in Kelp Greenling CPUE across sites or years.

There was no difference in Kelp Greenling CPUE between the Redfish Rocks Marine Reserve and and its comparison areas (all p > 0.05; Table 38). There were also no significant trends by year at any site (all p > 0.05; Table 39).

The random effect of cell was identified as a significant component of variation (Table 39).

GAMM model results can be found in the links below:

$~$ $~$

4.5.1.1.1 Kelp Greenling CPUE Timeseries

Fig. 32: Kelp Greenling catch per unit effort (CPUE) timeseries and modeled GAMM results with 95% confidence intervals, at the Redfish Rocks Marine Reserve and its associated comparison areas. See separate tabs for timseries and GAMM results.

4.5.1.1.2 Kelp Greenling CPUE GAMM Model Results

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4.5.1.2 Size

The Redfish Rocks Marine Reserve has larger Kelp Greenling than the Orford Reef Comparison Area.

The Redfish Rocks Marine Reserve had larger mean size Kelp Greenling than the Orford Reef Comparison Area (p < 0.05, Table 40). There were no significant differences in mean size of Kelp Greenling between the Redfish Rocks Marine Reserve and Humbug Comparison Area (p > 0.05, Table 41).

Significant yearly trends in Kelp Greenling size at the Redfish Rocks Marine Reserve and its comparison areas.

There were significant yearly trends in the average Kelp Greenling size across all sites (all p < 0.05, Table 41, Fig. 33). At the Redfish Rocks Marine Reserve, there was a trend of increasing Kelp Greenling size through time. At the Humbug Comparison Area, there was a trend of Kelp Greenling size increasing to a peak in 2016, followed by a decline through 2019. At the Orford Reef Comparison Area, average size of Kelp Greenling increased from 2014 through 2017, and shows a slight decline through 2019 (Fig. 33).

The random effect of cell was identified as a significant component of variation (Table 41).

GAMM model results can be found in the links below:

$~$

The Redfish Rocks Marine Reserve had smaller top quartile sizes of Kelp Greenling than the Orford Reef Comparison Area.

The top quartile of Kelp Greenling sizes was smaller at marine reserve than the Orford Reef Comparison Area (F = 3.397, p<0.05). No differences in top quartile size were detected between Redfish Rocks Marine Reserve and Humbug Comparison Area (p > 0.05).

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4.5.1.2.1 Kelp Greenling Mean Size Timeseries

Fig. 33: Kelp Greenling mean size timeseries and GAMM model results with 95% confidence intervals at the Redfish Rocks Marine Reserve and its associated comparison areas. See separate tabs for timseries and GAMM results.

4.5.1.2.2 Kelp Greenling Size Modeled GAMM Results

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4.5.1.3 BPUE

No significant difference in Kelp Greenling BPUE across sites or years.

There was no difference in Kelp Greenling BPUE between the Redfish Rocks Marine Reserve and and its comparison areas (all p > 0.05; Table 42). There were also no significant trends by year at any site (all p > 0.05; Table 43).

The random effect of cell was not statistically significant (Table 43).

GAMM model results can be found in the links below:

$~$ $~$

4.5.1.3.1 Kelp Greenling BPUE Timeseries

Fig. 34: Kelp Greenling biomass per unit effort (BPUE) timeseries and modeled GAMM results with 95% confidence intervals, at the Redfish Rocks Marine Reserve and its associated comparison areas. See separate tabs for timseries and GAMM results.

4.5.1.3.2 Kelp Greenling BPUE Modeled GAMM Results

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5 References

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.

Chao A., Gotelli N.J., Hsieh T.C., Sander E.L., Ma K.H., Colwell R.K., Ellison A.M. (2014) Rarefaction and extrapolation with Hill numbers: A framework for sampling and estimation in species diversity studies. Ecol Monogr 84:45–67

Choat, J. H., & Robertson, D. R. (2002). Age-based studies. Coral reef fishes: Dynamics and diversity in a complex ecosystem, 57-80.

Clarke K.R., Chapman M.G., Somerfield P.J., Needham H.R. (2006). Dispersion-based weighting of species counts in assemblage analyses. Mar Ecol Prog Ser 320: 11-27.

Green, R. H., & Young, R. C. (1993). Sampling to detect rare species. Ecological Applications, 3(2), 351-356.

Hill M.O. (1973) Diversity and Evenness : A Unifying Notation and Its Consequences. Ecology 54:427–432.

Hinkle D.E., Wiersma W., Jurs S.G. Applied Statistics for the Behavioral Sciences. 5th ed. Boston: Houghton Mifflin; 2003

Hsieh, T. C., Ma, K. H., & Chao, A. (2016). iNEXT: an R package for rarefaction and extrapolation of species diversity (H ill numbers). Methods in Ecology and Evolution, 7(12), 1451-1456.

Legendre P. and Anderson M.J. 1999. Distance-based redundancy analysis: Testing multispecies responses in multifactorial ecological experiments. Ecological Monographs 69(1): 1-24.

Lester, S. E., Halpern, B. S., Grorud-Colvert, K., Lubchenco, J., Ruttenberg, B. I., Gaines, S. D., … & Warner, R. R. (2009). Biological effects within no-take marine reserves: a global synthesis. Marine Ecology Progress Series, 384, 33-46.

Love, M. S., & Yoklavich, M. M. (2006). Deep rock habitats. In The ecology of marine fishes (pp. 253-266). University of California Press.

Maunder, M. N., & Punt, A. E. (2004). Standardizing catch and effort data: a review of recent approaches. Fisheries research, 70(2-3), 141-159.

ODFW (2014). Oregon Marine Reserve Ecological Monitoring Report 2010-2011. Oregon Department of Fish and Wildlife. Marine Resources Program. Newport Oregon. 1-131.

R Core Team (2020). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL: https://www.R-project.org/.

Starr, R. M., Wendt, D. E., Barnes, C. L., Marks, C. I., Malone, D., Waltz, G., … & Yochum, N. (2015). Variation in responses of fishes across multiple reserves within a network of marine protected areas in temperate waters. PLoS One, 10(3), e0118502.

Venables, W. N., & Dichmont, C. M. (2004). GLMs, GAMs and GLMMs: an overview of theory for applications in fisheries research. Fisheries research, 70(2-3), 319-337.

Zuur, A., Ieno, E. N., Walker, N., Saveliev, A. A., & Smith, G. M. (2009). Mixed effects models and extensions in ecology with R. Springer Science & Business Media.

Zuur, A. F. (2012). A beginner’s guide to generalized additive models with R (pp. 1-206). Newburgh, NY, USA: Highland Statistics Limited.

### This can be a useful function to play a sound at the end of a long script

#beepr::beep()