1 Introduction: Otter Rock Marine Reserve Lander Video Fish Report
The video lander is a stationary, underwater camera system used to target benthic fish communities on rocky reefs. The video lander is deployed for approximately eight minutes of video collection at a time. Video from lander deployments(hereafter called ‘drops’) are quality controlled using established criteria for visibility (water clarity), view (visible camera angle), and benthic habitat type. Usable video is then reviewed to identify all fish to species or species groups and estimate the relative abundance for all fishes observed.
Lander sampling began at the Otter Rock in 2010, two years before harvest restrictions began. Sampling is conducted in the marine reserve and its associated comparison area, Cape Foulweather Comparison Area (see methods Appendix for additional information about comparison area selection). We sampled at these sites over several years, with varied levels of success in achieving usable data - data that met requirements for view, visibility, and benthic habitat type (rocky substrates). These efforts results in six years of usable data for our analysis and inclusion in the synthesis report.
Data from lander monitoring efforts can be used to explore questions about fish relative abundance from a non-extractive, fisheries-independent tool used elsewhere in Oregon and the US West Coast. We can use metrics for diversity and community composition derived from these data to compare across monitoring tools, to understand tool bias, or to validate trends in relative abundance observed across tools. Data on relative abundance also enables us to explore how fish communities change 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 Otter Rock Marine Reserve
Fig. 1: Map of Lander Drops at Otter Rock Marine Reserve and Cape Foulweather Comparison Area
1.2 Research Questions
Diversity
- Does species diversity vary by site or year?
Community Composition
- Does community composition vary by site or year?
- If yes, what species drive this variation?
Aggregate Abundance
- Does aggregate density vary by site or year?
Focal Species Abundance
- Does focal species density vary by site or year?
- Does focal species size vary by site or year?
2 Takeaways
Here we present a summary of our lander 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 Lander Fish Results Summary
Similar species diversity between the Otter Rock Marine Reserve and Cape Foulweather Comparison Area.
Observed and estimated species richness was similar at the Otter Rock Marine Reserve and Cape Foulweather Comparison Area. There were similar numbers of unique, common, and rare species across both sites, and both sites had similar effective number of species as represented with Hill diversity numbers. The Otter Rock Marine Reserve and its comparison area also had similar mean species richness per lander video drop.
Community Composition was similar between sites and years.
Fish community composition was similar between the marine reserve and Cape Foulweather Comparison Area across sites and years. The relative abundances of two species drove most of the variation in community composition - Black Rockfish and Kelp Greenling.
Aggregate MaxN did not differ between sites.
We found no differences in aggregate MaxN between the Otter Rock Marine Reserve and Cape Foulweather Comparison Area.
Species specific MaxN differed by site for Black Rockfish and Kelp Greenling.
Lower abundance (MaxN) in Black Rockfish and greater abundance (MaxN) in Kelp Greenling were observed in the Otter Rock Marine Reserve compared to the Cape Foulweather Comparison Area. There were no differences in MaxN found for Blue/Deacon Rockfish or Lingcod between sites. There were too few observations of China Rockfish, Yelloweye Rockfish and Cabezon to detect differences in MaxN by site, so statistical analyses were not conducted.
Limited sample sizes prevented analysis of trends through time with lander data for this report.
This monitoring tool evolved over time to reflect both configuration, technological and methodological changes. In the early years sampling effort focused specifically on this tool with dedicated days for lander sampling only; however beginning in 2014/2015 lander sampling was paired with dive surveys because of limited staffing and weather windows to complete monitoring with all tools across all sites. This led to a reduction in effort with this survey tool, that resulted in a reduction of useable drops for analysis per year. The result of all these changes led to unequal sample sizes (useable drops) available for analysis to understand changes through time, so we focused on pooling the available data to focus on documenting differences between sites.
2.2 Conclusions
Slight differences between the result of this report and the 2010-2011 ODFW Ecological Monitoring report support the need for long-term monitoring.
Black Rockfish, Lingcod and Kelp Greenling were consistently the most abundant species in both this report and the 2010-2011 Ecological Monitoring report, however there are different conclusions about species abundances between sites in the two reports. In summarizing baseline data collection, the 2010-2011 report concluded that aggregate and species specific (Black Rockfish, Lingcod and Kelp Greenling) MaxN were higher in the Cape Foulweather Comparison Area than the Otter Rock Marine Reserve. However, the results of this report show no difference by site in aggregate or Lingcod Max N, and higher abundance of Kelp Greenling at the Otter Rock Marine Reserve. These changes are likely due to natural variation in fish populations, rather than any meaningful biological differences between sites, highlighting the importance of long-term monitoring to understand such changes. Our results provided the first community composition analysis for the lander fish community at this site, which can also be used to evaluate future changes at these sites.
Lander monitoring can be used to detect site specific differences of the most common species.
Otter Rock lander monitoring provided useful data on site comparisons of aggregate fish and the most common species (Black Rockfish, Kelp Greenling, and Lingcod). In addition to the species analyzed in this report, Striped Surfperch were frequently observed, particularly at the marine reserve, and the lander would provide useful data to explore differences by site for this species.
The year with the most dedicated lander-only sampling days resulted in the greatest sample sizes
The number of dedicated lander-only sampling days at Otter Rock has varied considerably over the development of the Ecological Monitoring Program. In 2015, our team conducted the greatest number of lander-only sampling days and it resulted in the largest number of useable drops out of all years, approximately five times as many useable drops than any other year of sampling. After 2015, the number of lander-only days dropped considerably at this site as lander monitoring became paired with SCUBA monitoring efforts. This was in part because of the challenge to implement multiple monitoring tools across all marine reserve sites with limited staff. Future use of this monitoring tool may include the possibility of returning to lander-only sampling days, but will be dependent on budget and staff capacity.
Detecting trends in nearshore ocean changes with lander surveys remains challenging and inefficient, future use of monitoring with this tool at this site is uncertain.
The biggest challenge with the lander monitoring tool is the high effort required to generate useable data (drops) for analysis. There are many reasons why lander drops may be excluded throughout the process from data collection to analysis (e.g. video review, methodological/technical changes). The result has led to unequal sample sizes through the years, despite fieldwork efforts intended to yield equal and much larger sample sizes. This combined with the long staff time required to perform video review and quality assurance / control on the data (Watson & Huntington 2021) makes this an inefficient monitoring tool as it is currently used. The first ODFW monitoring report questioned the use of the lander for detecting change between sites because of low abundances and limited species-specific identification, and that challenge remains after five additional years of tool development and sampling effort. However, the lander does provide useful data for several species including Black Rockfish, Kelp Greenling, Lingcod, Striped Surfperch and Pile Perch, the most commonly observed species for this tool at this site.
Lander video monitoring was developed with monitoring nearshore fishes in mind, but our program developed methods to gather additional data from these same videos on the invertebrate and biogenic habitat communities (e.g. Lawrence et al 2015, Lander Methods Appendix). However, we found the data unsuitable for inclusion in this report. Initial exploration into the invertebrate data, resulted in high percentages of lander drops with either unidentified invertebrate species or no invertebrate species recorded. For example, with our focal invertebrate species, the percent of lander drops with zeros ranged from 80 - 99%, even when we pooled data across sites. This is likely a result of lander development, where its construction focused on camera angles and view frames appropriate for assessing fish, and invertebrates typically require different camera position and video review requirements. With our biogenic habitat data, we found that two most commonly observed categories (Understory and Turf/Crust) were also the categories with the largest error amongst reviewers documented in the early development of this tool (Lawrence et al 2015). A simulation revealed that the current distribution of cover in these categories was within the range of random guessing, and with staff turnover through the years we had low confidence in the reliability of data. Therefore we felt it inappropriate to use these data to monitor changes in biogenic habitat over time. These data may still be useful in exploring fish-habitat relationships, but this was beyond staff capacity for inclusion in this report. With other monitoring tools more efficient than the lander at monitoring the invertebrate community and benthic habitat cover, the future use of monitoring these components with the lander is unlikely. While the lander can detect changes between sites for the most abundant fish, the challenges associated with appropriate sample sizes through time to understand yearly trends, in addition to the high staff time required for data collection and video review, make the future use of monitoring with this tool uncertain.
3 Lander Video Methods
Lander fish sampling is conducted in the Otter Rock Marine Reserve and Cape Foulweather Comparison Area. The purpose of lander fish sampling is to generate a relative abundance estimate, mean MaxN, of select species at depths shallower than 20m,the maximum depth of hard bottom habitat in the Otter Rock Marine Reserve. Lander drops at the Otter Rock Marine Reserve and its comparison areas targeted hard bottom, rocky substrates at depths shallower than 20m. Drops were randomly generated using hard bottom habitat maps and separated by a minimum distance of 100 m to assure independence.
Monitoring began in 2010 and data has been collected across 7 years. The first years of lander surveys were marked by tool exploration and development as ODFW attempted to adapt survey methods for the nearshore Oregon environment. Monitoring efforts prior to 2014 used a different camera configuration (standard definition cameras) and variable drop times based on recommendations from previous ODFW lander work in Oregon (Hannah and Blume 2012). In 2014, a more cost-effective, lighter camera configuration (HD GoPro Hero 3 cameras) was created and tested in nearshore waters to determine appropriate methods to continue lander monitoring (Watson and Huntington 2016). In 2014, drop duration was also standardized to 8 minutes.
All videos are reviewed to confirm the lander was oriented up right and that the benthic habitat in view met predetermined conditions of visibility, camera view and rocky reef habitat. All fish are identified to species, or species group. Relative abundance is recorded using the metric MaxN. Fish are counted in the video frame that contains the greatest single count of a given species which is a conservative approach to avoid double counting of schooling fishes and represents the minimum known count for a particular species (Ellis and DeMartini 1995, Harvey et al 2007). The unit of replication is at the drop level and only drops that were 4 minutes or longer in duration were used for analysis. This was previously determined to be a minimum drop time needed to achieve both time of first arrival and time to MaxN for more than half of 15 nearshore species known to be surveyed by the lander, including all common species (Watson and Huntington 2016).
Possibly missing: a sentence talking about how variable the resulting sample sizes are annually. Specifically, how much do we highlight the fact that we essentially did not sample OR marine reserve 2010-2011 (in usable drops), or that 2017/2019 were also poorly sampled. We can probably rely on the first sentence of the results section to make the first point
The video lander tool configuration and survey methods have evolved since 2010. With each configuration or methodological change, data were statistically evaluated for significant differences in the relative abundance metric MaxN. The migration from standard-definition to high-definition cameras was found to have no detectable influence on our ability to identify fishes to species (i.e. no statistical reduction in the number of ‘unknown’ species), and therefore no known influence on aggregate MaxN. Similarly, we excluded drops with durations shorter than 4 min to account for previously documented time of first arrival and time to MaxN. For the remaining drops between 4 and 8 minutes, there were no statistically significant relationships between drop duration and either species richness or MaxN. We therefore felt it was appropriate to pool data across lander surveys between 2010-2019 for this analysis.
For additional details on method development, data collection, data review, and confounding factor analyses, please review documentation in the Methods Appendix.
3.1 Diversity
With scuba fish surveys, 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 species turnover at each site (reserve or comparison area) likely occurs on timescales greater than one year.
To calculate estimated species richness, we used a rarefaction and extrapolation technique as described in Hsieh et al 2016, to calculate the effective number of species at each given site. This is the equivalent of calculating Hill diversity = 0. Hill numbers represent a unified standardization method for quantifying and comparing species diversity across multiple sites (Hill 1973), and they represent an intuitive and statistically rigorous alternative to other diversity indices (Chao et al 2014).
We used the same sampling based incidence data as used to document total observed species richness, using the iNext package in R to estimate the asymptote of the species accumulation curve, or the estimated total number of species observable by lander fish drops 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. The species count tables include a total count for each species summed for all years by site, and for each year-site combination, as well as mean frequency of occurrence across all samples. This information can tell us both about how frequently the species is observed, as well as its relative abundance.
From the species count tables we identified rare species, as those with a frequency of occurrence of 10% or less (Green and Young 1993), and common species as those with a frequency of occurrence greater than 50% (in other words, the species is observed on one of every two transects). We also identified species that were unique to each marine reserve and comparison area.
3.1.3 Diversity Indices
To gain additional insight into species diversity, we explored several diversity indices by comparing Hill diversity numbers, also known as the 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 each species yearly rarefaction curve against the total cumulative rarefaction curve for all years combined to determine if we had sampled appropriately to compare species diversity from year to year. When our sampling effort was not adequate to compare across years, we pooled data from all years to compare average lander drop diversity using an analysis of variance (ANOVA).
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 mean Max N 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 species-specific drivers of variation.
To explore variation by site and year, we used fish mean Max N data collected on lander video drops with a log transformation to downweight dominant species without overly enhancing importance of rare species (Clarke et al. 2006).Densities were calculated from lander Max fish count data (# Max N / area) so a similarity-based resemblance matrix was selected. A dummy variable (=1) was added prior to creating the resemblance matrix due to the high prevalence of zeros in the dataset. To visualize the data, we ran a cluster analysis and generated nMDS plots by site and year.
To test the statistical significance in our data of variation by site we ran a permutational analysis of variance (PERMANOVA), using a model with site as a fixed factor. Because survey efforts and video quality resulted in such varying amounts of useable data per year, we decided not to explore statistical differences by year. To explore if any significant results of the PERMANOVA were related to true differences in location or differences in dispersion of samples, we ran a PERMDISP, a distance based test for homogeneity of multivariate dispersions for any factor of significance 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 species-specific drivers in the variation of 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 Bray-Curtis resemblance matrix, which provides information on the percent of variation explained by each axis.
All analyses and graphs were made in PRIMERe version 7 with PERMANOVA extension.
3.3 Abundance
We explored changes in aggregate and focal species MaxN by site with generalized linear models (GLMs). We modeled raw MaxN data with no offset (Maunder and Punt 2004, Zuur 2012) and a negative binomial distribution. GLMs were selected because we lacked consistent data across the timeseries to apply generalized additive models (GAMs) to explore non-linear trends through time (Veneables and Dichmont 2004, Zuur et al. 2009). GLMs were fitted using the MASS and DHARMa packages in R. Site was treated as a fixed categorical variable (Zuur et al 2009; Zuur 2012).
Specifically we analyzed aggregate Max N and species-specific Mean Max N for focal species.
There are six focal fish species for the Oregon 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 MASS (version 4.0.4), and DHARMa packages. Models were structured in R as follows:
MaxN model = MASS::glm.nb(MaxN ~ Site)
4 Otter Rock Results
Lander fish sampling efforts at Otter Rock and its comparison area resulted in seven years of data collection, where varying sample sizes were collected per year (Fig. 2). Even though sampling efforts occurred in both areas every year, in several years, sampling efforts did not result in useable data in either the marine reserve or Cape Foulweather Comparison Area because of visibility or view requirements.
Fig. 2: lander fish monitoring efforts at the Otter Rock Marine Reserve and Cape Foulweather Comparison Area resulted in varied sample sizes over the seven years of data collection. Sample size is represented in number of useable drops.
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4.1 Diversity
4.1.1 Species richness
Fish species richness is similar across the Otter Rock Marine Reserve and Cape Foulweather Comparison Area.
Over the seven years of sampling with lander fish surveys, a total of 7 species (or species groups) were observed in the Otter Rock Marine Reserve (Table 4). The Cape Foulweather Comparison Area had similar total number of observed species (n = 6). These observed numbers of species richness are similar to the estimated numbers of total species richness.
library(kableExtra)
pna <- data.frame(Area = c("Otter Rock Marine Reserve",
"Cape Foulweather Comparison Area"),
Observed_Richness = c("7","6"),
Estimated_Richness = c("7","6"),
LCL = c("7","6"),
UCL = c("8", "6"))
kbl(pna, caption = "Table 4: Observed and estimated fish species richness by site with lower (LCL) and upper (UCL) 95% confidence limits") %>%
kableExtra::kable_classic()| Area | Observed_Richness | Estimated_Richness | LCL | UCL |
|---|---|---|---|---|
| Otter Rock Marine Reserve | 7 | 7 | 7 | 8 |
| Cape Foulweather Comparison Area | 6 | 6 | 6 | 6 |
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Species rarefaction curves highlight that for any samples size, including those for any given year, the species richness among sites is very similar (Fig. 3). Both rarefaction curves appear to level off, suggesting saturation in species richness with this tool at these sites.
Fig. 3: Species rarefaction curves for the Otter Rock Marine Reserve and Cape Foulweather Comparison Area. Data are pooled across all years of sampling for each site.
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4.1.2 Unique, common and rare species
Similarities in unique, common and rare species between the Otter Rock Marine Reserve and Cape Foulweather Comparison Area.
The Otter Rock Marine Reserve had similar numbers of unique species (n = 1) to the Cape Foulweather Comparison Area (n = 0). Cabezon was the only unique species observed at the marine reserve.
With the exception of Cabezon, the same species were observed at Otter Rock Marine Reserve and Cape Foulweather Comparison Area. Low numbers of common species were observed at both areas; Striped Surfperch and Kelp Greeling were common at the marine reserve and Black Rockfish were common at Cape Foulweather. Only one rare species was observed in the marine reserve (Cabezon) and no rare species were observed in the Cape Foulweather Comparison Area (Table 5).
Many fish species were not observed 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:
Table 7: Cape Foulweather Comparison Area Pooled Species Counts
Table 8: Cape Foulweather Comparison Area Species Counts by Year
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4.1.2.1 Otter Rock Marine Reserve
Fig. 4: Relative frequency of occurrence of fish species observed at the Otter Rock Marine Reserve and Cape Foulweather Comparison Area from SCUBA transects. See separate tabs for each site.
4.1.2.2 Cape Foulweather Comparison Area
Fig. 4: Relative frequency of fish species observed at the Otter Rock Marine Reserve and Cape Foulweather Comparison Area from SCUBA transects. See separate tabs for each site.
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4.1.3 Diversity Indices
The Otter Rock Marine Reserve and Cape Foulweather Comparison Area have similar diversity indices for fish.
The effective number of species is similar across all three diversity indices for the lander fish community at the Otter Rock Marine Reserve and Cape Foulweather Comparison Area (Fig. 5).
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Fig. 5: Comparing effective number of species (Hill diversity numbers) between the Otter Rock Marine Reserve and Cape Foulweather Comparison Area from SCUBA fish transects. 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 Otter Rock Marine Reserve and its comparison areas.
Species rarefaction curves by year for each site indicated that we did not sample enough on a yearly basis to compare changes in mean species richness through time (Fig. 6-7).
Fig. 6: Otter Rock Marine Reserves species rarefaction curves by year from lander fish drops.
Fig. 7: Cape Foulweather Comparison Area species rarefaction curves by year from lander fish drops.
4.2 Community Composition
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4.2.1 Variation by Site and Year
Fish community composition was similar by site and year at the Otter Rock Marine Reserve and Cape Foulweather Comparison Area with lander video data.
There was minimal structuring of fish community composition data across sites but not years with lander video fish data at the Otter Rock Marine Reserve and its surrounding comparison area. (Fig. 8). A subset of samples at the Cape Foulweather Comparison Area appear to be somewhat distinct from the marine reserve.
Multivariate statistics indicate differences by site.
PERMANOVA results indicate that site was a factor of significance with video lander fish data (p > 0.05, Table 9). However average similarity between samples within a site was similar (<5% difference) to average similarity of samples between sites, so it is likely that there are not strong community differences between the marine reserve and comparison Area. The dispersion test by site indicates no significant differences in dispersion between sites, so the significance of site in the PERMANOVA is likely due to a true difference in location.
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4.2.1.1 Site
Fig. 8: Results from nMDS plots with lander video fish data, demonstrating similarity in fish community composition at the Otter Rock Marine Reserve and its associated comparison areas. See separate tabs for site and year.
4.2.1.2 Year
Fig 8: Results from nMDS plots with lander video fish data, demonstrating similarity in fish community composition at the Otter Rock Marine Reserve and its associated comparison areas. See separate tabs for site and year
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4.2.2 Other drivers of variation
Two species drive variation in fish community composition data at both the Otter Rock Marine Reserve and Cape Foulweather Comparison Area.
We explored species-specific drivers of variation, and found that Black Rockfish and Kelp Greenling were driving the majority of the variation in fish community structure (Fig. 9). Principal coordinate analysis revealed that ~43% of the variation is explained by the x axis and is associated with mean Max N of Black Rockfish. The y-axis explained ~20% of the variation and is driven largely by Kelp Greenling (Fig. 9). Together the abundance of these two species accounts for over 63% of model variability. Differences between the marine reserve and comparison area largely appear to be driven by a number of samples at Cape Foulweather with no Kelp Greenling observations.
4.2.2.1 PCO Vector Plot
Fig. 9: Results from species correlations and principal coordinate analysis demonstrating that Black Rockfish and Kelp Greenling drive variation in community structure at the Otter Rock Marine Reserve and its surrounding comparison areas. See separate tabs for vector and bubble plots. Bubble color / size represents species-specific densities in each sample (species density range indicated in legend).
4.2.2.2 PCO Bubble Plot
Fig. 9: Results from species correlations and principal coordinate analysis demonstrating that Black Rockfish, and Kelp Greenling drive variation in community structure at the Otter Rock Marine Reserve and its surrounding comparison areas. See separate tabs for vector and bubble plots. Bubble color / size represents species-specific densities in each sample (species density range indicated in legend).
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4.3 Aggregate Abundance
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4.3.1 Aggregate MaxN
No significant difference in aggregate fish MaxN between the Otter Rock Marine Reserve and Cape Foulweather Comparison Area.
No significant difference in aggregate MaxN between the marine reserve and its comparison area (p > 0.05; Table 12).
GLM model results can be found in the links below:
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4.3.1.1 Aggregate Mean Max N by site
Fig. 10: Aggregate mean MaxN by site with 95% confidence intervals, at the Otter Rock Marine Reserve and its associated comparison area.
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4.4 Focal Species Abundance
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4.4.1 Black Rockfish, S. melanops
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4.4.1.1 MaxN
Significantly lower Black Rockfish MaxN observed at the Otter Rock Marine Reserve than at the Cape Foulweather Comparison Area.
There was a significant difference in Black Rockfish MaxN between sites, with a lower Black Rockfish MaxN at the marine reserve than the comparison area (p < 0.05; Table 13).
GLM model results can be found in the links below:
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4.4.1.1.1 Black Rockfish Mean MaxN by Site
Fig. 11: Black Rockfish mean MaxN by site with 95% confidence intervals, at the Otter Rock Marine Reserve and its associated comparison area.
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4.4.2 Blue/Deacon Rockfish, S.mystinus / S.diaconus
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4.4.2.1 MaxN
No significant difference in Blue/Deacon Rockfish MaxN between the Otter Rock Marine Reserve and Cape Foulweather Comparison Area.
No significant difference in Blue/Deacon Rockfish MaxN between the marine reserve and its comparison area (p > 0.05; Table 14).
GLM model results can be found in the links below:
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4.4.2.1.1 Blue/Deacon Rockfish Mean MaxN by Site
Fig. 12: Blue/Deacon Rockfish mean MaxN by site with 95% confidence intervals, at the Otter Rock Marine Reserve and its associated comparison area.
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4.4.3 China Rockfish, S. nebulosus
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4.4.3.1 MaxN
No China Rockfish observed at either site over seven years of monitoring.
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4.4.4 Yelloweye Rockfish, S.ruberrimus
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4.4.4.1 MaxN
No Yelloweye Rockfish observed at either site over seven years of monitoring.
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4.4.5 Cabezon, Scorpaenichthys marmoratus
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4.4.5.1 MaxN
Only two Cabezon observed at the Otter Rock Marine Reserve over seven years of monitoring.
MaxN of Cabezon was very low across sites and years, so statistical analyses were not conducted.
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4.4.6 Lingcod, Ophiodon elongatus
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4.4.6.1 MaxN
No significant difference in Lingcod MaxN observed at the Otter Rock Marine Reserve than at the Cape Foulweather Comparison Area.
No significant differences in Lingcod MaxN between the marine reserve and its comparison area (p > 0.05; Table 15).
GLM model results can be found in the links below:
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4.4.6.1.1 Lingcod Mean MaxN by Site
Fig. 13: Lingcod mean MaxN by site with 95% confidence intervals, at the Otter Rock Marine Reserve and its associated comparison area.
4.5 Additional Species Density
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4.5.1 Kelp Greenling, Hexagrammos decagrammus
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4.5.1.1 MaxN
Significantly higher Kelp Greenling MaxN observed at the Otter Rock Marine Reserve than at the Cape Foulweather Comparison Area.
There was a significant difference in Kelp Greenling MaxN between sites, with higher Kelp Greenling MaxN at the marine reserve than the Cape Foulweather Comparison Area (p< 0.05; Table 16).
GLM model results can be found in the links below:
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4.5.1.1.1 Kelp Greenling Mean MaxN by Site
Fig. 14: Kelp Greeling mean MaxN by site with 95% confidence intervals, at the Otter Rock Marine Reserve and its associated comparison area.
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
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.
Ellis, D., DeMartini, E., 1995. Evaluation of a video camera technique for indexing abundances of juvenile pink snapper, Pristipomoides filamentosus, and other Hawaiian insular shelf fishes. Fish. Bull. 93 (1), 67-77.
Green, R. H., & Young, R. C. (1993). Sampling to detect rare species. Ecological Applications, 3(2), 351-356.
Hannah, R. W., & Blume, M. T. (2012). Tests of an experimental unbaited video lander as a marine fish survey tool for high-relief deepwater rocky reefs. Journal of Experimental Marine Biology and Ecology, 430, 1-9.
Harvey, E.S., Cappo, M., Butler, J.J., Hall, N., Kendrick, G.A., 2007. Bait attraction affects the performance of remote underwater video stations in assessment of demersal fish community structure. Mar. Ecol. Prog. Ser. 350, 245-254.
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.
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/.
Venables, W. N., & Dichmont, C. M. (2004). GLMs, GAMMs and GLMMs: an overview of theory for applications in fisheries research. Fisheries research, 70(2-3), 319-337.
Watson, J.L. and Huntington, B.E. (2016). Assessing the performance of a cost-effective video lander for estimating relative abundance and diversity of nearshore fish assemblages. J. Exp. Mar. Biol. Ecol., 483: 104–111.
Watson, J.L. and Huntington, B.E. (2021). Comparing angling, underwater visual census, and video sampling methods to refine [fishery independent] long-term monitoring of a reef fish assemblage in a temperate marine reserve. ODFW Science Bulletin 2021-15. Oregon Department of Fish and Wildlife, Newport. Mar. Biol. Ecol., 483: 104–111.
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()