Hook and line (HnL) sampling target 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.
Hook and Line surveys (HnL) began at the Cape Falcon Marine Reserve and two comparison areas (Low Fishing Pressure, and Moderate Fishing Pressure) in 2014, before implementation of the marine reserve in 2016. The High Fishing Pressure Comparison Area was added in 2015. Sampling is conducted in the marine reserve and its three comparison areas (see methods Appendix for additional information about comparison area selection). Monitoring efforts resulted in four years of data for analysis and inclusion in the synthesis report.
Data from hook and line surveys can be used to explore questions about fish abundance and size from a survey tool 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 if these trends are similar inside and outside the reserve, in areas with varied fishing pressure. Our expectation is that similar trends exist at the Cape Falcon and the Low Fishing Pressure Comparison Area, located at Cape Meares. This is because there was historically low fishing pressure in the marine reserve prior to closure. The Moderate and High Fishing Pressure Comparison Areas will likely have trends that differ from the marine reserve and Low Fishing Pressure Comparison Area. For all data our main focus is exploring trends by site and year.
Diversity
Community Composition
Aggregate Abundance
Focal Species Abundance
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.
Species diversity differed between the Cape Falcon Marine Reserve and its comparison areas.
From a species diversity perspective there was a lack of similarity between the Cape Falcon Marine Reserve and its associated comparison areas. The Moderate Fishing Pressure Comparison Area had higher total and observed species richness, more unique species and the highest effective number of species across the three diversity indices than all other sites. The Cape Falcon Marine Reserve and Low Fishing Pressure Comparison Area had similar numbers of observed species, and had the lowest effective number of species for two of three diversity indices than the other two sites. However, they different in the number of unique, common and rare species. The High Fishing Pressure Comparison Area had different unique, common and rare species than the marine reserve and had the highest species richness for an average day of sampling than all other sites. It also had surprisingly higher effective number of species for the relatively lower sample sizes compared to the Cape Falcon Marine Reserve. There were no common species observed at the Cape Falcon Marine Reserve, but four species (Black Rockfish, Cabezon, Lingcod and Kelp Greenling) were considered common across two of three comparison areas.
Although there was high variation within the Cape Falcon Marine Reserve and its associated comparison areas, catch composition was similar across sites and years
Despite high variation within sites there was no apparent clustering by sites or years at the Cape Falcon Marine Reserve and its associated comparison areas. Multivariate statistics indicate that our unit of replication, cell, was significant as were interactions with cell, site, and year, supporting that there is higher variation across replicates within a site than between sites or years.
Lower aggregate CPUE and BPUE in the Cape Falcon Marine Reserve than the Moderate and High Fishing Pressure Comparison Areas, was likely driven by higher Black Rockfish and Lingcod abundances at these sites.
There was lower aggregate abundance with both CPUE and BPUE in the Cape Falcon Marine Reserve than two of three comparison areas. This lower aggregate abundance was likely driven by lower Black Rockfish and Lingcod CPUE and BPUE in the marine reserve as compared to the Moderate and High Fishing Pressure Comparison Areas.
High variability in aggregate CPUE and BPUE through time prevented detection of yearly trends at three of four sites including the Cape Falcon Marine Reserve
No significant yearly trends in aggregate CPUE or BPUE were detected at the Cape Falcon Marine Reserve, or Moderate or High Fishing Pressure Comparison Areas. High variability within sites and between years prevented us from detecting change through time. There were significant yearly trends detected at the Low Fishing Pressure Comparison Area for aggregate CPUE and BPUE, with declines through time in both metrics.
We were able to detect natural, interannual variability in CPUE, BPUE, and size for a limited number of species.
Out of six focal species, we only had enough data to statistically analyze Black Rockfish and Lingcod to explore differences by site or trends by year. Kelp Greenling, another abundant species across the majority of sites and an important species from our community composition analysis, also had enough data to statistically analyze. While yearly trends were inconsistent across species and survey locations, a majority of significant yearly trends were in the comparison areas and not in the Cape Falcon Marine Reserve. There were not enough observations of China Rockfish, Yelloweye Rockfish, and Cabezon to detect changes between sites or trends by year.
This is the first report of Hook and Line monitoring efforts at the Cape Falcon Marine Reserve and its comparison areas
The Cape Falcon Marine Reserve is Oregon’s youngest marine reserve, with implementation starting in 2016 and to date there has been no monitoring report that includes data from the Cape Falcon Marine Reserve. The information on species diversity, community composition, aggregate and species level abundances in this report are the first of its kind evaluating similarities and differences from the Cape Falcon Marine Reserve and its associated comparison areas.
Differences between sites match our expectations based on known habitat differences in the Cape Falcon Marine Reserve and its comparison areas.
Lower abundances of aggregate fish, Black Rockfish, and Lingcod were found in the Cape Falcon Marine Reserve than the comparison areas with greater fishing pressure (Moderate and High). There is more rocky hard bottom habitat in these two comparison areas, and we would expect higher levels of abundance in these areas. These results also support local fishermen knowledge that minimal habitat in the Cape Falcon Marine Reserve is associated with lower catch rates than at other fishing locations.
Cape Falcon provides a case study on evaluating yearly change across a gradient of fishing pressure
We detected little to no change over time at Cape Falcon in aggregate or species level abundances with four years of hook and line monitoring data. We did observe more change over time in the comparison areas but with no clear patterns. This somewhat matches our expectations that Cape Falcon would show little change over time while some of the more heavily fished areas would be expected to display changes over time. However the most change over time in aggregate and species level CPUE and BPUE analyses was detected at the Low Fishing Pressure Comparison Area, where both species and aggregate level trends showed declines through time. The reason for this decline is unclear, but additional monitoring will increase our understanding if this is truly a decline or natural variability of a dominant schooling species at this site.
An increase in monitoring effort with hook and line surveys is needed because of the high variability within the Cape Falcon Marine Reserve and its associated comparison areas.
Monitoring with hook and line surveys at the Cape Falcon Marine Reserve and its three associated comparison areas will continue, but increasing effort at all sites would be beneficial because of high variability within cells (replicates) across sites. Current efforts are able to detect interannual trends for the most abundant species but 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. Future analytical efforts may explore different techniques than the ones in this report, which may be more appropriate for data-poor species (e.g. occupancy modeling), or exploring species-habitat relationships. We did observe high variability around abundance estimates, and community composition analyses suggest most of the variability is found within our level of replication (cell) at each site. We may look further into variability at the cell level to determine if we can minimize variability to better detect differences between sites and trends by year. As we re-evaluate budget priorities, increasing monitoring efforts at this site, is one of our priorities. Without an increase to program budget or staff, hook and line survey efforts will continue at current levels and intervals.
Hook and Line (HnL) surveys were conducted in the Cape Falcon Marine Reserve, and its three comparison areas representing different fishing pressures - low (Cape Meares), moderate (Nehalem, Manzanita, Dinner Plate, and Adjacent Reefs), and high (Three Arch Rocks). Surveys began in 2014 with unequal survey effort. In the initial years there was a strong focus to place more survey effort in the reserve to ensure adequate characterization of baseline conditions prior to closure. Survey effort targeted 2 days in the reserve and Moderate Fishing Pressure Comparison Area, and 2 days at the Low and High Fishing Pressure Comparison Areas for both spring and fall surveys.
Each day between five to six 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 during these surveys. 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.
With hook and line gear, 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 survey years because each site (reserve or comparison area) likely has a species pool larger than can be surveyed 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 & extrapolation curves & can therefore compare across sites to explore similarity of total estimated species richness for a given survey effort.
Richness alone does not comprise all aspects of species biodiversity - 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 species and species not well targeted by hook and line gear. The species count tables include a total count for each species summed for all years by area, and for each year-area 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.
Frequency of occurrence was defined as the proportion of cells surveyed that a species was observed. 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%. The 50% threshold for common species represents that a species is caught in one out of every two cells surveyed. We also identified species that were unique to each marine reserve and comparison area.
To gain additional insight into species diversity, we compared the 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, also referred to as the effective number of species, 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 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.
We focused our community composition analysis around understanding if the variation in fish community structure 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 area 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 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 area, and year. Because of the known differences between the Cape Perpetua Marine Reserve and the Postage Stamp Comparison Area, we also explored data visualizations by area using cell as centroids.
To test the statistical significance in our data of variation by site and year we ran a permutational ANOVA, using a nested mixed model with site and year as fixed, and cell, our sampling replicate for hook and line gear, as a random nested factor 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 area or year to year), we ran a PERMDISP, a distance based test for homogeneity of multivariate dispersions for any factors 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 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 area 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 variable. We employed a multivariate model 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 yielded 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 (Dist-LM) 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 extesnsion.
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 catch rate and biomass, and species-specific catch rate, biomass 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:
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 Model = gam(Catch ~ Site + s(Year, by = Site, k = 3) + s(Cell_ID, bs = “re”), offset = log(Effort), family = nb)
BPUE Model = gam(log(Biomass + 1) ~ Site + s(Year, by = Site, k = 3) + s(Cell_ID, bs = “re”), offset = log(Effort), family = gaussian)
Size Model = gam(Length ~ Site + s(Year, by = Site, k = 3) + s(Cell_ID, bs = “re”), family = gaussian)
Hook and line survey efforts at Cape Falcon and its comparison areas resulted in four years of data collection, where varying sample sizes were collected per year (Fig. 2). Sampling efforts resulted in more survey effort in the Marine Reserve than in any one comparison area for three of the four survey years. Survey efforts at the High Fishing Pressure Comparison Area did not begin until 2015.
Species richness is similar at the Cape Falcon Marine Reserve and two of its comparison areas, the Moderate Fishing Pressure Comparison Area has the highest species richness of all sites
Over the five years of sampling with hook and line gear a total of 10 species were observed in the Cape Falcon Marine Reserve (Table 5). The Low Fishing Pressure Comparison Area had fewer observed species, 8, whereas the Moderate Fishing Pressure Comparison Area had more observed species (15) and the High Fishing Pressure Comparison Area had lower numbers of observed species (9) (Table 5). Even though the observed richness for the marine reserve, the Low Fishing Pressure, and High Fishing Pressure Comparison Areas are similar, the Cape Falcon Marine Reserve has a higher estimated total species richness. The Moderate Fishing Pressure Comparison Area had the most observed and estimated total species richness among all sites (Table 5).
library(kableExtra)
<- data.frame(Area = c("Cape Falcon Marine Reserve",
pna "Low Fishing Pressure Comparison Area",
"Moderate Fishing Pressure Comparison Area",
"High Fishing Pressure Comparison Area"),
Observed_Richness = c("10","8","15","9"),
Estimated_Richness = c("14","8","18","9"),
LCL = c("10","8","15","9"),
UCL = c("50","16","40","10"))
kbl(pna, caption = "Table 5: Observed and estimated species richness by site with lower (LCL) and upper (UCL) 95% confidence limits") %>%
::kable_classic() kableExtra
Area | Observed_Richness | Estimated_Richness | LCL | UCL |
---|---|---|---|---|
Cape Falcon Marine Reserve | 10 | 14 | 10 | 50 |
Low Fishing Pressure Comparison Area | 8 | 8 | 8 | 16 |
Moderate Fishing Pressure Comparison Area | 15 | 18 | 15 | 40 |
High Fishing Pressure Comparison Area | 9 | 9 | 9 | 10 |
\(~\) \(~\) \(~\) \(~\)
The Cape Falcon Marine Reserve has a different composition of unique, common and rare species, than its comparison areas.
We observed one unique species to the Cape Falcon Marine Reserve, a Shiner Perch, Cymatogaster aggregata. Across the three comparison areas there were seven unique species - meaning these species were only found in the comparison areas. Of those seven, five were observed only in the Moderate Fishing Pressure Comparison Area (Yelloweye Rockfish, Canary Rockfish,S.pinniger, Quillback Rockfish,S.maliger, Tiger Rockfish,S. nigrocinctus, and the Brown Irish Lord, Hemilepidotus spinosus) (Fig 3). The two remaining species, Blue/Deacon Rockfish and China Rockfish were observed at more than one comparison area site but not at the Cape Falcon Marine Reserve.
The Cape Falcon Marine Reserve had no common species (n=0). The Low Fishing Pressure and High Fishing Pressure Comparison Areas had four common species, whereas the Moderate Fishing Pressure Comparison Area only had two. Black Rockfish, Cabezon, Lingcod and Kelp Greenling were identified as common at more than one comparison area site (Tables 6, 7). The Cape Falcon Marine Reserve had five rare species as did the Moderate Fishing Pressure Comparison Area. The Low Fishing Pressure and High Fishing Pressure Comparison Areas had fewer rare species (n = 1 and 0, respectively). Many of the other species of fisheries interest - China, Quillback, Yelloweye, Copper and Vermillion Rockfish - were not caught frequently resulting in low pooled counts. Not all species were observed each year, for a summary of species counts and frequency observed over the years by site please see tables below (Tables 6-13).
Pooled species counts across all years and species counts by individual survey year are included in the following tables:
Table 8: Low Fishing Pressure Comparison Area Pooled Species Counts
Table 9: Low Fishing Pressure Comparison Area Species Counts by Year
Table 10: Moderate Fishing Pressure Comparison Area Pooled Species Counts
Table 11: Moderate Fishing Pressure Comparison Area Species Counts by Year
Table 12: High Fishing Pressure Comparison Area Pooled Species Counts
Table 13: High Fishing Pressure Comparison Area Species Counts by Year
\(~\) \(~\) \(~\) \(~\)
The Cape Falcon and Low Fishing Pressure Comparison Area have lower effective numbers of species for all three diversity indices than the Moderate and High Fishing Pressure Comparison Areas.
At low sample sizes, the Cape Falcon Marine Reserve and Low Fishing Pressure Comparison Area have the lowest effective number of species for all three Hill numbers (Fig. 4). The Moderate Fishing Pressure Comparison Area consistently has the highest effective number of species for all three Hill numbers. When Hill = 0, the High Fishing Pressure and Low Fishing Pressure Comparison Areas, appear to level off, suggesting saturation has been reached at these sites with this sampling tool. However at larger samples sizes, more rare species are found in the marine reserve and Moderate Fishing Pressure Comparison Area, suggesting saturation has not been reached at either of these two locations.
Differences in Hill numbers among the marine reserve and the Moderate Fishing Pressure Comparison Area and High Fishing Pressure Comparison Areas are not surprising given the differences in habitat at these sites (e.g. depth, reef size).
\(~\) \(~\) \(~\) \(~\)
We did not get enough samples to evaluate change in species diversity through time at the Cape Falcon Marine Reserve or 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. 5-8). When plotting annual species rarefaction curves 95% confidence intervals, there is high overlap among the years suggesting that additional sampling is needed detect temporal patterns in species richness.
Fig. 5: Cape Falcon Marine Reserves species rarefaction curves by year
Fig. 6: Low Fishing Pressure Comparison Area species rarefaction curves by year
Fig. 7: Moderate Fishing Pressure Comparison Area species rarefaction curves by year
Fig. 8: High Fishing Pressure Comparison Area species rarefaction curves by year
\(~\) \(~\)
For an average day of sampling, the Cape Falcon Marine Reserve has the lowest species richness than all other sites.
When comparing mean species richness for an average day of sampling, there were statistically significant differences among sites (F = 17.554, p = 0.000). Tukey HSD tests reveal that the Cape Falcon Marine Reserve has statistically fewer species observed in a day of sampling than any of its comparison areas (all adj. p < 0.05, Fig. 9). The High Fishing Pressure Comparison Area has statistically more species observed in a day of sampling out of all the comparison areas (all adj. p < 0.05).
\(~\) \(~\)
\(~\) \(~\)
\(~\) \(~\)
Catch composition was similar across sites and years at the Cape Falcon Marine Reserve and its comparison areas.
There was no structuring of catch composition data across sites and years at the Cape Falcon Rocks Marine Reserve and its comparison areas (Fig. 9). Some samples appear to be unique both at the Cape Falcon Marine Reserve and in two of the comparison areas.
Multivariate statistics indicate differences by cell, and the interactions site by year and cell by year, but they account for little total variation in the data
PERMANOVA results indicate that cell and the interactions between site and year, and cell and year were significant for catch composition, while there were no significant differences between sites or years (Table 14). Cell accounted for the highest variability of all the variables/interactions (17%). The residuals explained approximately 56% of the variability in the data.
PERMDISP results by cell indicate that dispersion was variable amongst cells in areas (Table 15). Results indicate that those cells with dispersion greater than 1 were responsible for the majority of significant pairwise differences among cells (Table 16). In general there was no consistent pattern among pairwise comparisons that indicated cells within a site were more similar/different than cells in other sites, instead significant differences in pairings were spread across three of four sites (the reserve, the Moderate Fishing Pressure Area, and the High Fishing Pressure Area) indicating that differences in dispersions among cells is likely due to intrinsic variability in the system rather than a structural difference within or between sites.
These results suggests the significance identified in the PERMANOVA is likely a combination of both differences in dispersion and location by cell across sites and years, and is likely due to variability within the system rather than any distinct spatial or temporal trends.
\(~\) \(~\)
\(~\) \(~\)
\(~\) \(~\)
\(~\) \(~\)
Lingcod, Kelp Greenling and Black Rockfish drive the majority variation in fish community structure
We explored species-specific drivers of variation, and found that Lingcod, Kelp Greenling and Black Rockfish were driving the majority of variation in the data (Fig. 11). Principal coordinate analysis revealed that ~26% of the variation is explained by CPUE of Kelp Greenling and 19% of variation is described by trade-offs between Lingcod and Black Rockfish (Fig. 11). Together the abundance of these three species accounts for over 45% of model variability.
\(~\) \(~\)
\(~\) \(~\)
Including month and habitat variables accounted for little of the total variation in catch composition at the Cape Falcon Marine Reserve and its associated comparison areas.
DISTLM results indicate three environmental variables (month, proportion rock and average drift depth) were significant and the best model included all of these variables (Table 17). Average drift depth roughly correlated with the x axis and explained 69% of model variation, but only explained 6% of the total variation. This indicates that although significant, drift depth alone does not explain the variation in fish communities. Proportion of rock roughly correlated with the y axis and explained 24% of model variation, but only 2% of total variation. The small variability explained by these three factors indicates that while there is a habitat and temporal signature, it is small and not a significant source of variability in fish catch composition as currently incorporated.
\(~\) \(~\)
\(~\) \(~\)
\(~\) \(~\)
Significantly lower aggregate CPUE in the Cape Falcon Marine Reserve than the Moderate and High Fishing Pressure Comparison Areas.
The Cape Falcon Marine Reserve had statistically lower aggregate CPUE than the Moderate and High Fishing Pressure Comparison Areas (p < 0.05; Table 18). There was no difference in CPUE between the Cape Falcon Marine Reserve and the Low Fishing Pressure Comparison Area (p > 0.05; Table 18).
Significant yearly trends in aggregate CPUE only at the Low Fishing Pressure Comparison Area.
Significant yearly trends in aggregate CPUE were detected only at the Low Fishing Pressure Comparison Area (p < 0.05; Table 19), with a decline from initial survey efforts in 2014 to the most recent survey efforts in 2019. There were no significant yearly trends at the marine reserve or other comparison areas (p > 0.05; Table 19).
The random effect of cell (unit of replication) was a significant component of variation (Table 19).
GAMM model results can be found in the links below:
\(~\) \(~\)
\(~\) \(~\)
Significantly lower aggregate BPUE in the Cape Falcon Marine Reserve than the Moderate and High Fishing Pressure Comparison Areas.
The Cape Falcon Marine Reserve had statistically lower aggregate BPUE than the Moderate and High Fishing Pressure Comparison Areas (p < 0.05; Table 20). There was no difference in BPUE between the Cape Falcon Marine Reserve and the Low Fishing Pressure Comparison Area (p > 0.05; Table 20).
Significant yearly trends in aggregate BPUE at the Low Fishing Pressure Comparison Area.
The only significant yearly trend in aggregate BPUE was at the Low Fishing Pressure Comparison Area (p < 0.05; Table 21), with a decline from initial surveys in 2014 the most recent survey efforts in 2019. There were no significant yearly trends at the Cape Falcon Marine Reserve, the Moderate Fishing Pressure, or the High Fishing Pressure Comparison Areas (all p > 0.05; Table 21).
The random effect of cell (unit of replication) was a significant component of variation (Table 21).
GAMM model results can be found in the links below:
\(~\) \(~\)
\(~\) \(~\)
\(~\) \(~\)
\(~\) \(~\)
\(~\)
Significantly lower Black Rockfish CPUE in the Cape Falcon Marine Reserve than the Moderate Fishing Pressure Comparison Area.
The Cape Falcon Marine Reserve had statistically lower Black Rockfish CPUE than the Moderate Fishing Pressure Comparison Area (p < 0.05; Table 22). There was no difference in CPUE between the Cape Falcon Marine Reserve and the Low Fishing Pressure and High Fishing Pressure Comparison Areas (p > 0.05; Table 22).
Significant yearly trends in Black Rockfish CPUE only at the Low Fishing Pressure Comparison Area.
Significant yearly trends in Black Rockfish CPUE were detected only at the Low Fishing Pressure Comparison Area (p < 0.05; Table 23), with a decline from initial survey efforts in 2014 to the most recent survey efforts in 2019. There were no significant yearly trends at the marine reserve or other comparison areas (p > 0.05; Table 23).
The random effect of cell (unit of replication) was identified as a significant component of variation (Table 23).
GAMM model results can be found in the links below:
\(~\) \(~\)
\(~\) \(~\)
No difference in mean size of Black Rockfish between the Cape Falcon Marine Reserve and its comparison areas.
There were no significant differences in mean size of Black Rockfish among sites (all p > 0.05, Table 24).
No significant yearly trends in Black Rockfish mean size at the Cape Falcon Marine Reserve and two comparison areas, significant yearly trends at the Moderate Fishing Pressure Comparison Area.
There were no significant yearly trends in Black Rockfish mean size at the Cape Falcon Marine Reserve, Low Fishing Pressure or High Fishing Pressure Comparison Area (all p > 0.005, Table 25). The Moderate Fishing Pressure Comparison Area did detect a significant yearly trend, (p < 0.05, Table 25), with a gradual decline through time. Even though the model results reveal statistically significant yearly trends, the mean size timeseries 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.
The random effect of cell (unit of replication) was identified as a significant component of variation (Table 25).
GAMM model results can be found in the links below:
\(~\) \(~\)
Significant differences by site in top quartile sizes of Black Rockfish.
There were differences by site in the top quartile of sizes of Black Rockfish (F. 18.168, p. <0.05). The Cape Falcon Marine Reserve had significantly larger top quartile sizes of Black Rockfish than all comparison areas (all adj. p <0.05).
\(~\) \(~\)
\(~\) \(~\)
Significantly lower Black Rockfish BPUE in the Cape Falcon Marine Reserve than the Moderate and High Fishing Pressure Comparison Areas.
The Cape Falcon Marine Reserve had statistically lower Black Rockfish BPUE than the Moderate and High Fishing Pressure Comparison Areas (p < 0.05; Table 26). There was no difference in BPUE between the Cape Falcon Marine Reserve and the Low Fishing Pressure Comparison Area (p > 0.05; Table 26).
Significant yearly trends in Black Rockfish BPUE at the Low Fishing Pressure Comparison Area.
The only significant yearly trend in Black Rockfish BPUE was at the Low Fishing Pressure Comparison Area (p < 0.05; Table 27), with a decline from initial surveys in 2014 the most recent survey efforts in 2019. There were no significant yearly trends at the Cape Falcon Marine Reserve, the Moderate Fishing Pressure, or the High Fishing Pressure Comparison Areas (all p > 0.05; Table 27).
The random effect of cell (unit of replication) was identified as a significant component of variation (Table 27).
GAMM model results can be found in the links below:
\(~\) \(~\)
\(~\) \(~\)
\(~\)
Too few observations of Blue/Deacon Rockfish to detect differences in CPUE by site or year.
CPUE of Blue/Deacon Rockfish were very low across all sites and years (e.g. 1 fish caught per 15 angler hours fishing in comparison areas only, Fig. 17), so statistical analyses were not conducted. No Blue/Deacon Rockfish were caught in the Cape Falcon Marine Reserve throughout the four years of fishing effort.
\(~\) \(~\)
\(~\) \(~\)
Too few observations of Blue/Deacon Rockfish to detect differences in size by site or year.
CPUE of Blue/Deacon Rockfish were very low across all sites and years (e.g. 1 fish caught per 15 angler hours fishing in comparison areas only, Fig. 17),so statistical analyses were not conducted. No Blue/Deacon Rockfish were caught in the Cape Falcon Marine Reserve throughout the four years of fishing effort.
\(~\) \(~\)
Too few observations of Blue/Deacon Rockfish to detect differences in BPUE by site or year.
Catch rates of Blue/Deacon Rockfish were very low across all sites and years (e.g. 1 fish caught per 15 angler hours fishing in comparison areas only, Fig. 17) resulting in low BPUE estimates, so statistical analyses were not conducted. No BPUE of Blue/Deacon Rockfish was observed in the Cape Falcon Marine Reserve throughout the four years of fishing effort.
\(~\) \(~\)
\(~\) \(~\)
\(~\)
Too few observations of China Rockfish to detect differences in CPUE by site or year.
CPUE of China Rockfish were very low across all sites and years (e.g. 1 fish caught per 25 angler hours fishing at two comparison areas only (Fig. 19)), so statistical analyses were not conducted. No catch of China Rockfish observed in the Cape Falcon Marine Reserve or Low Fishing Pressure Comparison Area throughout the four years of fishing effort.
\(~\) \(~\)
\(~\) \(~\)
Too few observations of China Rockfish to detect differences in size by site or year.
CPUE of China Rockfish were very low across all sites and years (e.g. 1 fish caught per 25 angler hours fishing at two comparison areas only (Fig. 19)), so statistical analyses were not conducted.
\(~\) \(~\)
Too few observations of China Rockfish to detect differences in BPUE by site or year.
CPUE of China Rockfish were very low across all sites and years (e.g. 1 fish caught per 25 angler hours fishing at two comparison areas only (Fig. 19), resulting in low estimates of BPUE, so statistical analyses were not conducted. No catch of China Rockfish observed in the Cape Falcon Marine Reserve or Low Fishing Pressure Comparison Area throughout the four years of fishing effort.
\(~\) \(~\)
\(~\) \(~\)
\(~\)
Too few observations of Yelloweye Rockfish to detect differences in CPUE by site or year.
CPUE of Yelloweye Rockfish were very low across all sites and years (e.g. 1 fish caught per 15 angler hours fishing only at the moderate fishing pressure comparison area, Fig. 21), so statistical analyses were not conducted. No catch of Yelloweye Rockfish observed in the Cape Falcon Marine Reserve or Low or High Fishing Pressure Comparison Area throughout the four years of fishing effort.
\(~\) \(~\)
\(~\) \(~\)
Too few observations of Yelloweye Rockfish to detect differences in size by site or year.
CPUE of Yelloweye Rockfish were very low across all sites and years (e.g. 1 fish caught per 15 angler hours fishing at the moderate fishing pressure comparison area only; Fig. 21), so statistical analyses on size data were not conducted. No catch of Yelloweye Rockfish observed in the Cape Falcon Marine Reserve or Low or High Fishing Pressure Comparison Area throughout the four years of fishing effort.
\(~\) \(~\)
Too few observations of Yelloweye Rockfish to detect differences in BPUE by site or year.
CPUE of Yelloweye Rockfish were very low across all sites and years (Fig. 21), so statistical analyses on BPUE data were not conducted. No Yelloweye Rockfish BPUE was observed in the Cape Falcon Marine Reserve or Low or High Fishing Pressure Comparison Area throughout the four years of fishing effort.
\(~\) \(~\)
\(~\) \(~\)
\(~\)
Too few observations of Cabezon to detect differences in CPUE by site or year.
CPUE of Cabezon were very low across all sites and years (e.g. 1 fish caught per 10 angler hours fishing, Fig. 23), so statistical analyses on CPUE data were not conducted.
\(~\) \(~\)
\(~\) \(~\)
Too few observations of Cabezon to detect differences in size by site or year.
CPUE of Cabezon were very low across all sites and years (e.g. 1 fish caught per 10 angler hours fishing; Fig. 23), so statistical analyses on size data were not conducted.
\(~\) \(~\)
Too few observations of Cabezon to detect differences in BPUE by site or year.
CPUE of Cabezon were very low across all sites and years (e.g. 1 fish caught per 10 angler hours fishing; Fig. 23), resulting in low estimates of BPUE, so statistical analyses were not conducted.
\(~\) \(~\)
\(~\) \(~\)
\(~\)
Significantly lower Lingcod CPUE in the Cape Falcon Marine Reserve than the Moderate and High Fishing Pressure Comparison Areas.
The Cape Falcon Marine Reserve had statistically lower Lingcod CPUE than the Moderate and High Fishing Pressure Comparison Areas (p < 0.05; Table 28). There was no difference in CPUE between the Cape Falcon Marine Reserve and the Low Fishing Pressure Comparison Area (p > 0.05; Table 28).
No significant yearly trends in Lingcod CPUE at any site.
There were no significant trends in Lingcod CPUE by year at the Cape Falcon Marine Reserve or any of its comparison areas (p > 0.05, Table 29).
The random effect of cell (unit of replication) was identified as a significant component of variation (Table 29).
GAMM model results can be found in the links below:
\(~\) \(~\)
\(~\) \(~\)
No difference in mean size of Lingcod between the Cape Falcon Marine Reserve and the Low Fishing Pressure Comparison Area.
There were no significant differences in mean size of Lingcod between the Cape Falcon Marine Reserve and Low Fishing pressure Comparison Area (p > 0.05, Table 30). The mean size of Lingcod was significantly smaller in the Cape Falcon Marine Reserve than the Moderate or High Fishing Pressure Comparison Area (both p.<0.05).
Significantly yearly trends in Lingcod size at both the Moderate and High Fishing Pressure Comparison Areas.
There were no significant yearly trends in Lingcod mean size at the Cape Falcon Marine Reserve or Low Fishing Pressure Comparison Area (all p > 0.05, Table 31). The Moderate Fishing Pressure Comparison Area did detect a significant yearly trend in Lingcod mean size, (p < 0.05), with a gradual increase through 2017, followed by a slight decline in 2019. The High Fishing Pressure Comparison Area detected a different yearly trend, with a consistent decline in mean Lingcod size through time.
The random effect of cell (unit of replication) was identified as a significant component of variation (Table 31).
GAMM model results can be found in the links below:
\(~\) \(~\)
Significant differences by site in top quartile sizes of Lingcod.
There were differences by site in the top quartile of sizes of Lingcod (F. 18.168, p. < 0.05). The Cape Falcon Marine Reserve had similar top quartile sizes of Lingcod as the Lower Fishing Pressure Comparison Area (adj. p > 0.05), but significantly smaller top quartile sizes of Lingcod than the Moderate and High Fishing Pressure Comparison Areas (all adj. p < 0.05).
\(~\) \(~\)
\(~\) \(~\)
Significantly lower Lingcod BPUE in the Cape Falcon Marine Reserve than the Moderate and High Fishing Pressure Comparison Areas.
The Cape Falcon Marine Reserve had statistically lower Lingcod BPUE than the Moderate and High Fishing Pressure Comparison Areas (p < 0.05; Table 32). There was no difference in BPUE between the Cape Falcon Marine Reserve and the Low Fishing Pressure Comparison Area (p > 0.05; Table 32).
Significant yearly trends in Lingcod BPUE at the Low and Moderate Fishing Pressure Comparison Areas.
There were significant yearly trends in Lingcod CPUE detected at the Low and Moderate Fishing Pressure Comparison Areas (p < 0.05; Table 33). The Low Pressure Fishing Comparison Area had a decline from initial survey efforts in 2014 to the most recent survey efforts in 2019. Lingcod BPUE at the Moderate Fishing Pressure Comparison Area increased through 2017, and then declined through 2019. There were no significant yearly trends at the marine reserve or High Fishing Pressure Comparison Area (p > 0.05; Table 33).
The random effect of cell (unit of replication) was identified as a significant component of variation (Table 33).
GAMM model results can be found in the links below:
\(~\) \(~\)
\(~\) \(~\)
\(~\) \(~\)
\(~\)
No difference in Kelp Greenling CPUE between the Cape Falcon Marine Reserve and its associated comparison areas.
There was no difference in Kelp Greenling CPUE between the Cape Falcon Marine Reserve and any of its comparison areas (p > 0.05, Table 34).
No significant yearly trends in Kelp Greenling CPUE at the Cape Falcon Marine Reserve or its associated comparison areas.
There were no significant yearly trends in Kelp Greenling CPUE at the Cape Falcon Marine Reserve or its associated comparison areas (p > 0.05, Table 36, Fig. 35).
The random effect of cell (unit of replication) was identified as a significant component of variation (Table 35).
GAMM model results can be found in the links below:
\(~\) \(~\)
\(~\) \(~\)
No significant difference in mean size of Kelp Greenling across sites.
The mean size of Kelp Greenling was not significantly different between the Cape Falcon Marine Reserve and its comparison area (p> 0.05, Table 36).
Significant yearly trends in Kelp Greenling mean size at both the Cape Falcon Marine Reserve and the High Fishing Pressure Comparison Area.
There was a significant yearly trend in Kelp Greenling mean size at both the Cape Falcon Marine Reserve and the High Fishing Pressure Comparison Area (p<0.05, Table 37). At the marine reserve there was a gradual increase in Kelp Greenling mean size through 2017, followed by a slight decline (Fig. 37). The trend observed in Kelp Greenling mean size at the High Fishing Pressure Comparison Area has a stronger increase through 2017, followed by a decline through 2019. There were no significant yearly trends at either the Low or Moderate Fishing Pressure Comparison Areas (p > 0.05).
The random effect of cell (unit of replication) was identified as a significant component of variation for mean size of Kelp Greenling (Table 37).
GAMM model results can be found in the links below:
\(~\)
No difference in top quartile sizes of Kelp Greenling between the Cape Falcon Marine Reserve and its comparison areas.
There were no differences by site in the top quartile of sizes of Kelp Greenling (F.0.22, p.> 0.05).
\(~\) \(~\)
\(~\) \(~\)
No difference in Kelp Greenling BPUE between the Cape Falcon Marine Reserve and its comparison areas.
Kelp Greenling BPUE did not differ between the Cape Falcon Marine Reserve and its comparison areas (p > 0.05; Table 38).
No significant yearly trends in Kelp Greenling BPUE at either the Cape Falcon Marine Reserve or its comparison areas.
No significant yearly trends in Kelp Greenling BPUE were observed at either the marine reserve or its associated comparison areas (p > 0.05, Table 39).
The random effect of cell (unit of replication) was identified as a significant component of variation (Table 39).
GAMM model results can be found in the links below:
\(~\) \(~\)
\(~\) \(~\)
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 (2015). Oregon Marine Reserve Ecological Monitoring Report 2012-2013. Oregon Department of Fish and Wildlife. Marine Resources Program. Newport Oregon. 1-126.
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()