Volume 48, Issue 1 p. 8-19
Feature
Open Access

Citizen Science Surveys Provide Novel Nearshore Data

Jillian Campbell

Corresponding Author

Jillian Campbell

Fisheries and Oceans Canada, Pacific Biological Station, 3190 Hammond Bay Rd, Nanaimo, BC, V9T 6N7 Canada

Department of Biology, University of Victoria, Victoria, BC, Canada

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Jennifer Yakimishyn

Jennifer Yakimishyn

Parks Canada, Pacific Rim National Park Reserve, Ucluelet, BC, Canada

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Dana Haggarty

Dana Haggarty

Fisheries and Oceans Canada, Pacific Biological Station, 3190 Hammond Bay Rd, Nanaimo, BC, V9T 6N7 Canada

Department of Biology, University of Victoria, Victoria, BC, Canada

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Francis Juanes

Francis Juanes

Department of Biology, University of Victoria, Victoria, BC, Canada

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Sarah Dudas

Sarah Dudas

Fisheries and Oceans Canada, Pacific Biological Station, 3190 Hammond Bay Rd, Nanaimo, BC, V9T 6N7 Canada

Department of Biology, University of Victoria, Victoria, BC, Canada

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First published: 07 September 2022
Citations: 1

Abstract

Long-term data are key to understanding how species, communities, and habitats change over time. Citizen science programs can support data collection at greater spatial and temporal scales than other types of scientifically collected data, which tend to be project specific and are often tied to short funding periods. This is particularly true for environments that are difficult to sample, such as subtidal ecosystems. The Reef Environmental Education Foundation's (REEF) citizen science SCUBA surveyors have been collecting fish, invertebrate, and algae data in British Columbia since 1998. This study demonstrates how citizen science data from REEF can be used to answer scientific questions via two case studies: the first on Lingcod Ophiodon elongatus population responses to management decisions and the second on detecting rockfish Sebastes spp. young-of-year abundance pulses. The results of these case studies suggest that data from REEF, despite their limitations, can be used to improve our understanding of nearshore marine ecosystems.

image

Lingcod Ophiodon elongatus. Photo credit: Ed Bierman.

INTRODUCTION

As nearshore subtidal ecosystems face anthropogenic impacts on local (e.g., habitat destruction) and global (e.g., climate change) scales, understanding the impacts on these ecosystems and the species that inhabit them is a critical step in ensuring their conservation. As marine environments are increasingly impacted and diverge further from baseline conditions, the need for long-term data sets to assess species- or ecosystem-level changes is of growing importance. However, because subtidal data collection is expensive and challenging, few long-term data sets exist, making it difficult to detect changes in species abundances or community composition.

Scientific SCUBA data collection tends to be seasonally focused toward commercially valuable species or toward species and habitats of conservation concern, thus limiting the temporal, spatial, and taxonomic scope of the resulting data (LeClair et al. 2016; Frid et al. 2018; Olson et al. 2019). It is also difficult for organizations to gather data at the temporal and spatial resolutions necessary to manage and conserve our marine ecosystems due to the high costs and logistical challenges inherent to sampling these environments. Recreational SCUBA divers are one way to overcome these difficulties. These divers are often experienced naturalists who are excited to contribute data on the species that they encounter. Recreational divers typically dive year-round, return to specific locations frequently, provide their own SCUBA equipment and training, and are not limited by the strict dive safety protocols that scientific organizations are required to follow, thereby allowing them to collect data at depths, over durations, and in conditions that are not typically allowed by scientific organizations (WorkSafe BC 2020). Examples of citizen (or community) science organizations that collect subtidal data include the Reef Environmental Education Foundation (REEF; www.REEF.org), Reef Life (reeflifesurvey.com), and Reef Check (www.reefcheck.org). These organizations attempt to collect the highest quality data possible by providing consistent training to recreational divers, ensuring that divers either have carefully designed species lists or are instructed to collect data on all species encountered, gathering and curating the divers' observations, and providing opportunities for surveyors to improve their knowledge and skills. These data are often made publicly available, resulting in inexpensive data at scales of interest for scientists (Pattengill-Semmens and Semmens 2003; Heery et al. 2018) or resource managers (Tolimieri et al. 2017; Grüss et al. 2018; Safiq et al. 2018). For example, data from REEF were instrumental in determining the extent of species declines due to a sea star wasting disease in the North Pacific (Montecino-Latorre et al. 2016; Harvell et al. 2019; Gravem et al. 2021).

The quality of citizen science data is often cited as a concern, yet studies have found that the quality and taxonomic resolution of data collected by citizen scientists are as good as or better than those of data collected by research scientists. This could be due to the fact that scientific diver training does not typically include a species identification component, whereas recreational divers who are interested in citizen science programs are typically experienced naturalists (Gorgopa 2011; Cox et al. 2012). With training, recreational divers can improve their diving and species identification skills, both of which improve data resolution and quality (Gorgopa 2011). Here, we focus on the data from REEF since more surveys were conducted at more sites and over a longer duration of time by REEF than by either Reef Life or Reef Check for the west coast of British Columbia (BC), Canada. The Reef Environmental Education Foundation recognizes the value of experience and training and has established a series of five levels through which surveyors advance by completing surveys and species identification tests. These experience levels are indicated in the data set, and it is possible to use only data collected by more experienced surveyors as a means of quality control (see Appendix A). However, an important challenge in obtaining robust citizen science data is encouraging volunteer recreational divers to repeatedly collect data. The survey protocol used by REEF is simple, as it does not involve sampling along transects or in quadrats like Reef Life or Reef Check requires; rather, REEF allows surveyors to conduct their dives as they wish, recording the animals they observe as they go (Pattengill-Semmens and Semmens 2003). By keeping the survey methodology simple, REEF has ensured that surveys are easy to accomplish, do not require additional equipment other than a slate and data sheet, and do not alter the flow of a normal dive, which has resulted in a larger data set compared to other citizen science organizations.

There is considerable potential for citizen science data to inform basic ecology of the surveyed species and to inform the management of those species and the ecosystems they inhabit. To demonstrate this potential, we use data from REEF in two applied case studies to demonstrate how citizen science data can supplement traditional surveys to better inform fishery management and to provide novel information on nearshore ecosystems in support of conservation efforts. Citizen scientist surveyors have been collecting fish, invertebrate, and algae data for REEF since May 1998 in BC, generating over 7,000 surveys and over 150,000 species abundance observations as of August 2020. Most observations are from the southern coast of BC; however, a few surveys have been conducted along the central and north coasts of BC (Figure 1). We first outline the methodology used by REEF surveyors, explain how the data were prepared for use in this study, and then present two case studies. The first case study demonstrates that Lingcod Ophiodon elongatus populations did not improve after a fishery closure was mandated in 2006 along the southern BC coast. The second case study shows that across three different data sets, including data from REEF, abundance pulses of young-of-year (age-0) rockfish Sebastes spp. are sporadic, exhibit natural variation, and are highly localized. However, age-0 rockfish recruit to eelgrass Zostera spp. meadows, bull kelp Nereocystis luetkeana canopies, and rocky substrates in similar densities, and studies would benefit from making observations in a variety of habitats. Although citizen science data can lead to useful insights, this data set comes with some caveats, as is the case with all data sets. In the Discussion section, we highlight some of the biases in these data to ensure that other researchers have the necessary insight to design appropriate statistical methodology when using the data. Some of these caveats include the coarse categorical abundance records, species detection challenges, the inability to standardize effort across surveys and sites, and the non-random site selection.

Details are in the caption following the image
Map of Reef Environmental Education Foundation survey sites with data collected between May 10, 1998, and August 17, 2020, in British Columbia. Circle size and color indicate the number of surveys conducted at each site. There are currently no surveys recorded as taking place along the central coast, so this area was omitted from the map. The 14 surveys from 9 sites along the north coast near Prince Rupert are shown in the inset. (Map was created using the nepacLLhigh base map in the PBSmapping package in R; Schnute et al. 2019).

REEF SURVEY METHODOLOGY

The REEF Volunteer Fish Survey Project was started in the tropical western Atlantic in 1993 and has since expanded worldwide to almost all marine waters. Under REEF's protocol, surveyors employ a “roving diver strategy” (Schmitt and Sullivan 1996); they have no set transects, depths, or methods for navigating the sites. They simply go out and dive, recording the species and abundances they encounter, and they are encouraged to look in cracks and crevices and observe species in the water column. For surveys conducted in the northeastern Pacific, surveyors are encouraged to record all fish species that they can positively identify and those species' relative abundances, but they are limited to a set list of 59 invertebrates (including three invasive tunicates) and four algae species (including one nonnative species). Surveyors can survey fish only, invertebrates and algae only, or all species during a single survey. Species abundances are recorded as a category based on a log10 scale of abundance: Single (1 individual), Few (2–10 individuals), Many (11–100 individuals), or Abundant (101+ individuals). These categories are then represented by the numbers 1–4 in the data. Five invertebrate species and two algae species are recorded as presence/absence only due to their high abundance and aggregating nature (e.g., strawberry anemones Corynactis californica; brown seaweed Sargassum muticum). No size or demographic information is collected for any species, except that age-0 rockfish (defined as those <5 cm) are recorded separately. A summary of the available data for fish, invertebrates, and algae is provided in Table 1. The list of the invertebrate and algae species surveyed by REEF in the northeastern Pacific can be found on the REEF web site (www.REEF.org).

Table 1. Summary table of the Reef Environmental Education Foundation species observations for fish, invertebrate, and algae taxa from 512 sites throughout British Columbia. Since surveyors can survey fish only, invertebrates and algae only, or all species, the values in the bottom row are not totals of the columns but rather totals reflective of the entire data set. Data cover the time period from May 10, 1998, to August 17, 2020.
Taxon Number of species Number of surveys Number of sites where taxon was observed Number of survey hours Mean number of species observed per survey (±SD)
Fish 177 (39 families) 6,960 568 5,639 10.1 ± 4.42
Invertebrates 62 (8 phyla) 6,213 518 5,025 14.1 ± 5.43
Algae 4 (2 phyla) 1,136 183 1,070 1.4 ± 0.51
Data set total 243 7,040 572 5,698 22.6 ± 9.97

Surveyors also provide information about survey site location, date, surface and bottom temperatures (as recorded on surveyors' dive computers, if available), starting time, survey duration, maximum survey depth, average survey depth, visibility, current, and dominant habitat type (from a set list of 12 types: artificial reef, bull kelp forest, cobble/boulder field, eelgrass bed, kelp forest, mud/silt bottom, open ocean, pinnacle, rock/shale reef, sandy bottom, surfgrass Phyllospadix spp. bed, and wall). The REEF volunteers can conduct surveys anywhere in ocean waters, and all survey locations are assigned an eight-digit code within REEF's hierarchical Geographic Zone Code system. If surveyors conduct a survey at a site that has not yet been included in the REEF database, they can request its addition by contacting REEF directly.

REEF DATA PREPARATION

The data analyzed here were limited to sites in BC and included the date range from May 10, 1998 (the date of the first survey REEF received from the region), to August 17, 2020, when the data were requested (REEF 2020). The data were analyzed in R (R Core Team 2020). Sites for which REEF did not have associated GPS coordinates were dropped from the analysis, resulting in 356 surveys being dropped (5% of the total surveys), along with an associated 7,225 species abundance observations (4.5% of the total observations).

A map of the observations (Figure 1) shows each survey site denoted by a circle, with circle size indicating the number of surveys conducted at the site. Since there is an absence of observations in the data set along the central coast of BC, the area with no conducted surveys was omitted. Most sites had 50 or fewer surveys conducted during the time period of interest; however, there were 12 sites with over 100 completed surveys.

Species abundance observations are recorded on a categorical log10 scale, which makes it challenging to interpret the raw data. To better understand trends in abundances, the data can be interpreted by three metrics, as recommended by REEF (Wolfe and Pattengill-Semmens 2013): percent sighting frequency, density score, and abundance score.

Percent sighting frequency determines how often a particular species was recorded at a site over time:
Percent sighting frequency = Number of surveys in which a species was present at a site Total number of surveys at that site × 100 . ((1))
The density score is a weighted average of the recorded abundance categories of a particular species at a site over time:
Density score = n S × 1 + n F × 2 + n M × 3 + n A × 4 n S + n F + n M + n A , ((2))
where nS, nF, nM, and nA represent the number of times each abundance category (Single, Few, Many, and Abundant, respectively) was recorded for a given species at a site.
The abundance score uses the percent sighting frequency to correct the density score for surveys in which a species was not observed:
Abundance score = density score × percent sighting frequency 100 . ((3))

Studies have used either these metrics (Serafy et al. 2015) or others to analyze data from REEF. Schultz et al. (2016) and Harvell et al. (2019) tracked population changes over time by calculating 60-day or annual abundance score averages by site, respectively. Tolimieri et al. (2017) converted the categorical data into numeric data by using the minimum numbers for each abundance category (Single = 1; Few = 2; Many = 11; Abundant = 101) as species abundances. Rather than using the minimum category values, Montecino-Latorre et al. (2016) used count data from supplementary surveys to determine median abundance values of their target species in the Few and Many categories, and then substituted those median values into their data. Other authors, such as Grüss et al. (2018), Heery et al. (2018), and Safiq et al. (2018), converted the data to presence/absence values, which allowed them to combine data from REEF with other data sets to address various research questions.

CASE STUDY 1: LINGCOD POPULATION CHANGES

Species abundance data can be used to observe trends in populations over time at specific sites or in specific regions. In this case study, Lingcod survey abundances were analyzed using all of the data from REEF available from May 1998 to August 2020. Lingcod are territorial, large-bodied, piscivorous predators (Cass et al. 1990) that occupy a high trophic level, likely exerting a top-down effect on the marine ecosystem. Lingcod abundances reached historic lows within the Strait of Georgia (SoG) in the late 1980s due to pressure from targeted commercial and recreational fishing. As a result, commercial fishing was prohibited by the Department of Fisheries and Oceans Canada (DFO) in 1990 and recreational fishing was subsequently prohibited in 2002 in the SoG. During the late 1990s, DFO also implemented rockfish conservation areas (RCAs), prohibiting all hook-and-line fishing within the RCA boundaries to further assist Lingcod conservation, as Lingcod are common in these areas. Recreational fishing closures for Lingcod were lifted by DFO in certain areas of the SoG during 2006, but were maintained within Howe Sound and Indian Arm (HSIA). The conservation measures were maintained in this area due to a lack of evidence of recovery, possibly due to the severe depletion to only 1% of historic biomass in this region (Logan et al. 2005). These fishery closures for Lingcod provide an opportunity to demonstrate how data from REEF can be used to analyze Lingcod population abundance trends in response to conservation efforts, as data were collected before, during, and after the 2002–2006 closures. Data from three regions—HSIA, the SoG (excluding HSIA), and the west coast of Vancouver Island (WCVI; Figure 1)—were analyzed to compare Lingcod abundances across regions in BC. Fishing restrictions were not implemented in the WCVI region because the Lingcod population there is considered to be healthy (King et al. 2012). The proportion of abundance category observations by year from each region was plotted (Figure 2), and annual percent sighting frequencies (equation 1; Figure 3A), density scores (equation 2; Figure 3B), and abundance scores (equation 3; Figure 3C) were calculated for each region. The method used by Tolimieri et al. (2017), whereby the abundance category was reduced to the minimum numerical value, was also applied to these data to provide an estimate of numerical abundances (Figure 3D).

Details are in the caption following the image
Proportion of abundance category observations of Lingcod during each year at Reef Environmental Education Foundation survey locations in Howe Sound and Indian Arm (top panel), the Strait of Georgia (middle panel), and the west coast of Vancouver Island (bottom panel).
Details are in the caption following the image
Annual (A) percent sighting frequency (equation 1), (B) density score (equation 2), (C) abundance score (equation 3), and (D) average abundance using Tolimieri et al.'s (2017) method of converting the categorical data into numerical data for Lingcod (shaded areas represent confidence intervals) in Howe Sound and Indian Arm (HSIA; black), the Strait of Georgia (SoG; red), and the west coast of Vancouver Island (WCVI; blue). Vertical red dashed lines indicate fishery management efforts by Fisheries and Oceans Canada to limit the impact of the recreational fleet on Lingcod abundances in the SoG and HSIA; recreational fishing for Lingcod was permitted until 2002 (Rec Open), after which it was prohibited until 2006 (Rec Closed). In 2006, recreational fishing for Lingcod was permitted in certain areas of the SoG but was still prohibited in HSIA. These fishery closures did not apply to the WCVI population.

Throughout the time series, there were decreasing trends in percent sighting frequencies, density scores, and abundance scores for HSIA (Figure 3, black lines); steady trends in the three metrics for the SoG (Figure 3, red lines); and slightly increasing trends in the three metrics for the WCVI (Figure 3, blue lines). To determine whether there were significant differences in Lingcod abundance scores before and after the fishery closure, sites that had at least three surveys both before and after the closure were compared using Student's t-tests. Of the four sites in HSIA that were analyzed, only one site had statistically significant differences in Lingcod abundance scores and the abundance score declined at this site after the fishery closure. Of the 20 sites in the SoG that were analyzed, one site exhibited a significant increase in Lingcod abundance scores, whereas three sites had significant declines in Lingcod abundance scores after the fishery closure. Of the 12 WCVI sites that were analyzed, there were no significant differences in Lingcod abundance scores before and after the HSIA/SoG fishery closures (see Table 2 for summary statistics). These results suggest that Lingcod populations in both HSIA and the SoG have not increased after fishery closures were put in place, and in fact significantly declined at some sites, whereas the WCVI population appears to have been stable throughout the time series.

Table 2. Summary statistics of survey site Lingcod abundance scores before and after the 2006 fishery closures in Howe Sound and Indian Arm (HSIA) and the Strait of Georgia (SoG). The west coast of Vancouver Island (WCVI) was not subject to this fishery closure. Only sites with a minimum of three surveys both before and after the 2006 fishery closure were included in the analysis. Site coordinates are excluded to honor the Reef Environmental Education Foundation's data sharing policy. Data are arranged in ascending order by P-value.
Region Site Number of surveys Mean abundance score Test statistic (t) df P-value Increase/decrease in abundance score
Before closure After closure Before closure After closure
SoG Saskatchewan Wreck 8 5 0.088 0.018 −3.62 7.57 0.007 Decrease
SoG Maple Bay Government Dock and Reef 3 8 0.089 0.035 −3.16 4.80 0.026 Decrease
SoG Coopers Green (Halfmoon Bay) 5 4 0.332 0.052 −3.15 4.64 0.028 Decrease
SoG Toby Islet 4 10 0.054 0.100 2.43 10.22 0.035 Increase
HSIA Whytecliff Park 8 12 0.967 0.465 −2.29 11.51 0.042 Decrease
WCVI Pill Point Wall 3 12 0.032 0.080 2.28 8.37 0.051 Increase
SoG Maude Reef 3 5 0.054 0.033 −2.13 5.60 0.080 Decrease
SoG Madrona Point (Main/Big Wall) 5 10 0.229 0.100 −1.99 4.67 0.107 Decrease
SoG Mermaid Cove (Saltery Bay) 5 4 0.190 0.080 −1.66 6.00 0.148 Decrease
SoG Ford Cove Reef 4 9 0.050 0.113 1.56 9.21 0.152 Increase
SoG MV G. B. Church (Portland Island) 4 3 0.061 0.023 −1.55 4.40 0.190 Decrease
WCVI Tyler Rock 5 10 0.100 0.146 1.19 13.00 0.254 Increase
SoG Dodd Narrows 4 4 0.049 0.020 −1.32 3.16 0.275 Decrease
HSIA Porteau Cove Bay 6 11 0.626 0.476 −1.03 11.58 0.326 Decrease
SoG Sutton Islets 3 4 0.087 0.036 −1.23 2.24 0.334 Decrease
SoG Flora Islets West/Float 1 6 4 0.104 0.064 −1.04 4.50 0.353 Decrease
SoG Flora Islets East/Float 2 4 7 0.115 0.088 −0.92 5.87 0.393 Decrease
WCVI Mahk Reef 5 9 0.102 0.062 −0.92 5.66 0.396 Decrease
WCVI Renate's Reef 5 12 0.202 0.232 0.66 5.99 0.532 Increase
SoG West Snake Island 4 5 0.061 0.042 −0.62 6.98 0.557 Decrease
HSIA Ansel Point 5 5 0.200 0.136 −0.52 7.99 0.616 Decrease
SoG Clarke Rock 5 3 0.104 0.156 0.51 3.35 0.645 Increase
WCVI Rendezvous House Reef 3 8 0.131 0.111 −0.49 2.96 0.655 Decrease
WCVI Kyen Point 6 10 0.201 0.171 −0.45 7.53 0.664 Decrease
WCVI Diplock Island 3 7 0.131 0.115 −0.42 7.80 0.685 Decrease
WCVI West Race Wall and Rocks 3 5 0.075 0.067 −0.19 4.58 0.861 Decrease

The most recent Lingcod stock assessment by DFO (Holt et al. 2016) evaluated the SoG and HSIA populations using creel survey recreational CPUE data for released and retained fish. Lingcod CPUE in the SoG doubled from 9.46 Lingcod encountered/100 h of fishing effort in 1998 to 21.92 Lingcod encountered/100 h of fishing effort in 2010 before declining to levels only slightly above those recorded at the beginning of the time series by 2013 (10.25 Lingcod encountered/100 h of fishing effort). In HSIA, Lingcod remained consistently very low, at an average of 1.20 Lingcod encountered/100 h of fishing effort, throughout the time series. The trends in DFO creel data are very similar to those in the REEF data for the SoG and HSIA populations despite methodological differences between them. The REEF surveyors are constrained to depths shallower than 40 m, and Lingcod that inhabit deeper locations are not captured during these surveys. Conversely, recreational fishers typically target depths greater than 40 m (Cass et al. 1990). These depth differences mean that data from REEF can provide a useful complement to fishery-dependent data in these stock assessments, as a more complete survey of the depth distribution can be captured. Although REEF survey trends in HSIA after 2016 show that average abundance, density, and abundance scores have remained lower than those in the SoG, the percent sighting frequency has recently increased, potentially indicating that the Lingcod population in HSIA is recovering.

CASE STUDY 2: ROCKFISH YOUNG-OF-YEAR ABUNDANCE IN BARKLEY SOUND

Many nearshore rockfishes are particularly susceptible to overfishing due to their site fidelity, late sexual maturity, and episodic recruitment, as well as their closed swim bladder, which makes it difficult for the fish to survive when caught as bycatch (Parker et al. 2000; DFO 2009). Recruitment in many rockfish species is highly dependent on oceanographic currents and temperatures, resulting in numerous years of low recruitment along with sporadic years of exceptionally high recruitment (Markel et al. 2017; Markel and Shurin 2020). Three nearshore rockfish species are currently assessed as species at risk by the Committee on the Status of Endangered Wildlife in Canada: the Canary Rockfish Sebastes pinniger, Quillback Rockfish S. maliger, and Yelloweye Rockfish S. ruberrimus. The Yelloweye Rockfish is also listed as a species of special concern under Canada's Species at Risk Act. To aid in population rebuilding, regular stock assessments and/or rebuilding plans are conducted. The data that are used in stock assessments and rebuilding plans come primarily from DFO hard-bottom longline surveys that target large, older adults and from commercial fisheries in which many rockfish species are incidentally captured as bycatch (DFO 2009, 2012; Keppel and Olsen 2019). Very little data exist on recently recruited age-0 rockfish, although age estimation for sampled fish does provide a retrospective assessment of recruitment. This lack of data on the entire age structure limits our understanding of rockfish species' biology and life history. By not monitoring age-0 recruitment directly and incorporating this information into stock assessments, recruitment events may take years to decades to be realized given the late selectivity (20+ years) of many fishery-dependent and fishery-independent surveys for rockfishes (e.g., Cox et al. 2012).

Data from REEF can be used to fill the age-0 rockfish data gap, as observations of age-0 fish have been collected since 1998, when REEF surveys first started in BC (see Figure 4 for observation locations). From 1998 to 2010, age-0 individuals from all rockfish species were categorized together as unidentified young of the year, but in 2010, age-0 rockfish were categorized by species or by species complex categories (e.g., the Copper Rockfish S. caurinus, Quillback Rockfish, and Brown Rockfish S. auriculatus [CQB] complex) for species that are challenging to differentiate visually. The Reef Environmental Education Foundation has compiled age-0-specific identification resources to aid surveyors in obtaining accurate observations for these species complexes, and the surveyor experience level is associated with each observation in the data set. The log10 scale abundance categories used by REEF can be useful when observing the age-0 abundance pulses typical of many rockfish species, particularly when the Many category (11–100 fish) or the Abundant category (101+ fish) is recorded for age-0 rockfish.

Details are in the caption following the image
Map of Reef Environmental Education Foundation survey sites with age-0 rockfish observations. The left map shows all survey sites along the south coast of British Columbia; the right map shows all survey sites within Barkley Sound. Circle size and color indicate the total number of observations at each site from 1998 to 2020.

When citizen science observations are visualized alongside scientifically collected data, a more comprehensive understanding of nearshore subtidal ecosystems can be achieved. In this case study, age-0 abundances for all rockfish species, the CQB complex, and the Black Rockfish S. melanops and Yellowtail Rockfish S. flavidus (BY) complex are examined using three data sets. The first data set comprised REEF data from Barkley Sound only (Figure 4), where observations of age-0 rockfish of each species within each complex plus observations recorded using the species complex category were used. Only REEF surveys conducted from May to October were included since age-0 rockfish typically recruit to the benthos in the spring and rockfish are known to take refuge during the winter months (Carlson and Barr 1977; Tonnes et al. 2016). This date range also allowed us to compare age-0 abundances with the other two studies, which were conducted during similar time periods, while avoiding the detection of any differences due to seasonal trends. The density score (equation 2) for all rockfish species from 1998 to 2020 and for the CQB and BY complexes from 2010 to 2020 are shown in Figure 5 (black lines). The second data set was from a monitoring program within the Pacific Rim National Park Reserve (PRNPR; Figure 4; Robinson et al. 2011; Robinson and Yakimishyn 2013). The program recorded observations of CQB and BY complex age-0 rockfish collected in eelgrass meadows by beach seine from Barkley Sound (Figure 5, red lines) and Clayoquot Sound (Figure 5, blue lines). The seine abundances from PRNPR were converted into REEF categorical abundances, and annual density scores were calculated for each sound. The third data set was from Markel et al. (2017), who recorded observations of CQB complex and Black Rockfish age-0 individuals that were collected in standard monitoring units for the recruitment of fishes (“SMURFs”; e.g., cylinders made of plastic garden fencing filled with strips of snow-fencing) within bull kelp forests in Barkley Sound (Figure 5, yellow lines). As with the PRNPR data, the abundance data from Markel et al. (2017) were converted into REEF abundance categories and annual density scores were calculated.

Details are in the caption following the image
Age-0 (young-of-year [YOY]) abundance observations for all rockfish species (top panel); the Copper, Quillback, and Brown Rockfish (CQB) species complex (middle panel); and the Black and Yellowtail Rockfish (BY) species complex (bottom panel). Annual density scores (equation 2) were calculated using data from Reef Environmental Education Foundation (REEF) surveys in Barkley Sound only (black), Pacific Rim National Park Reserve (PRNPR) abundances from beach seining in eelgrass meadows within Barkley Sound (red) and Clayoquot Sound (blue), and abundances from standard monitoring units for the recruitment of fishes (“SMURFs”) as reported by Markel et al. (2017; yellow). Abundance pulses (asterisks) were defined as years in which the density score was more than 1.5 SDs above each data set and species complex mean. The color of the asterisk denotes the data set in which the abundance pulse was observed.

Here, we define an abundance pulse as a year in which the density score was more than 1.5 SDs above each data set and species complex mean. Years in which an abundance pulse occurred are indicated with an asterisk in Figure 5, and the color of the asterisk denotes the data set in which the pulse was observed. The REEF data from Barkley Sound indicate age-0 abundance pulses of all rockfish species in 2001 and 2006 and of the CQB complex in 2011. The PRNPR Barkley Sound data show an age-0 abundance pulse of all rockfish species in 2016 (driven by an abundance pulse of the BY complex) and 2020 and an abundance pulse of the CQB complex in 2019. The PRNPR Clayoquot Sound data indicate age-0 abundance pulses of all rockfish species in 2016 and 2020 (driven by an abundance pulse of the BY complex) and an abundance pulse of the CQB complex in 2008. The data set from Markel et al. (2017) indicates an abundance pulse of the BY complex in 2006; however, it is unclear whether the 2005 abundance pulse of the CQB complex is in fact an abundance pulse or whether it represents the start of a decline in CQB complex abundance, as no data are available from years previous to 2005.

Each of the three data sources collected age-0 rockfish from different habitats and used different methods, which is likely a leading contributor to the inconsistency in abundance pulses. The data from REEF were collected via SCUBA over primarily rocky substrates (80.2% of surveys), the PRNPR data were collected via beach seine over eelgrass habitat, and the data from Markel et al. (2017) and Markel and Shurin (2020) were collected via SMURFs near bull kelp canopies. Despite these differences, the three data sets indicate that age-0 rockfish recruited to rocky habitats, eelgrass, and bull kelp at similar densities; therefore, combining these data sets provides a more complete picture of age-0 rockfish abundance.

The trends highlighted by these data sets differ—even between the two PRNPR data sets, for which the same methodology was used. These differences indicate that recruitment events are sporadic, exhibit natural variation, and are highly localized, which is supported by the work of Markel et al. (2017) and Markel and Shurin (2020). Since rockfish recruitment is very localized, the fact that REEF surveyors tend to return to the same sites year after year can provide valuable insight into local recruitment patterns. However, since REEF surveyors may not always be recording age-0 fish, use of the density score to evaluate the positive sightings only is the preferred metric (as used here). The large number of REEF surveys in many regions of the BC south coast over the past 20 years offers researchers much-needed long-term data on rockfish life stages that are difficult to sample using conventional fishing methods. To best use age-0 data in stock assessments, we need to better understand how age-0 abundance pulses translate into adult abundances—an important aspect of rockfish biology that is not yet fully understood (Haggarty et al. 2017). Additional studies using the data from REEF and oceanographic models, such as those produced by DFO, may provide further insight into the abiotic requirements necessary for successful recruitment, which will make modeling of abundance pulses more plausible.

DISCUSSION

Our results demonstrate some of the analyses and visualizations that are possible with citizen science data from REEF. The 22 years of available data from BC and locations worldwide provide a source of invaluable long-term data that can be used to track species' population changes over time and to detect community composition differences. Additionally, citizen science data collection is a transparent, publicly available, and inexpensive way for organizations to amass quality marine population data at a broader scale than what might be possible through small scientific dive teams. Data from REEF can be used alongside scientifically collected biological data or oceanographic models to support species distribution models, identify potential research sites, support monitoring efforts, or assist in other targeted scientific analyses.

As with all data sets, there are limitations to these data, such as the following:
  • The log10 scale categorical nature of the abundance data might make subtle population trends difficult to discern. For example, large-bodied, predatory, and territorial species, such as Lingcod or some rockfish species, may experience substantial population changes over time while still remaining in the Many category (11–100 fish). These data also may not be suitable for detecting changes in schooling species, such as Pacific Herring Clupea pallasii or Shiner Perch Cymatogaster aggregata, which are often observed in the hundreds. However, due to the log10 scale nature of the observations, any statistically significant results achieved using data from REEF would be reliable, as the abundance categories indicate order-of-magnitude differences. Additionally, recently developed analytical tools using Bayesian approaches have shown that REEF data often track underlying population states captured from point-count survey methodologies, such as transects and rapid visual count surveys, in spite of the seemingly less-standardized and lower-resolution nature of REEF data (D. A. Greenberg, C. V. Pattengill-Semmens and B. X. Semmens, unpublished data).
  • Only species that can be positively identified by REEF surveyors are recorded. Therefore, some species may be present and observed but not recorded by surveyors if they are uncertain of the species' identity. However, a recent analysis of data from the Salish Sea showed that REEF divers encountered 62% (138 of 223) of the visually detectable species occurring in the region and 85% (102 of 120) of the species most likely to be observed by recreational divers (Ashley et al. 2022). These findings show that citizen scientists provide valuable monitoring data for over half of the 261 marine and anadromous fish species known to occupy the Salish Sea, many of which are not routinely monitored otherwise.
  • The lack of a standardized search area coupled with the categorical abundance data makes it difficult to determine any reliable count-per-unit-area metric. However, survey time is recorded and could be used as a metric of standardized effort.
  • The maximum diving depth of recreational divers (40 m) is shallow compared to the maximum depth that some of these species inhabit. However, age-0 fish are typically found above 40 m, as indicated by the scientific sampling programs highlighted in case study 2.
  • Survey sites are not randomly chosen over the entire BC coast, which could be an issue for some study designs.

Despite these limitations, citizen science data help to fill the knowledge gap arising from the paucity of available data on the habitat use of species that are not of commercial importance in nearshore ecosystems.

Marine conservation planning efforts could benefit from incorporating data from REEF into their work. For example, both marine spatial planning and oil spill response planning require knowledge of species distributions, for which data from REEF are well suited (Grüss et al. 2018). These data are also well suited for informing the placement of marine conservation areas and their subsequent monitoring. For example, future research with these data includes using them in support of evaluating the effectiveness of BC RCAs and to help determine which habitats or areas could be considered for future conservation efforts. Another potential application is to explore the relationship between areas of abundant age-0 rockfish observations and oceanographic conditions to determine the conditions that are most likely to result in strong recruitment years.

Overall, citizen science data serve as a valuable source of information that is often overlooked. Here, we have demonstrated two case studies detailing how these data can be used and we have indicated how they could inform marine conservation planning efforts. The breadth of fish, invertebrate, and algae species observation data is a strength of the citizen science data that has been collected along much of the southern BC coast year-round since 1998. While the amount of data is an advantage, there are some limitations to these data, such as the categorical abundance records, species detection challenges, an inability to standardize survey effort across surveys and sites, and non-random site selection. Few studies have employed these types of data, but as we have shown, the information provided can be a valuable long-term data source, and data generated by citizen science divers are more cost effective and temporally and spatially abundant than data generated by small—often seasonal—scientific dive teams.

ACKNOWLEDGMENTS

We wish to thank REEF and all of the REEF volunteers for collecting, curating, and generously providing 22 years of data to us. The REEF Volunteer Survey Project database is maintained and made publicly available thanks to the support provided by individual REEF members and grants to REEF from the Henry Foundation, the Curtis and Edith Munson Foundation, the Paul M. Angell Foundation, and the Lenstra Fund. We are grateful to the many Parks Canada staff, students, and volunteers who supported the eelgrass beach seining program over the years and to PRNPR for funding this program. J.C. was funded by a DFO Grants and Contributions Agreement and a Canadian Federation of University Women 1989 École Polytechnique Commemorative Award. F.J. was funded by the Liber Ero Foundation and the Natural Sciences and Engineering Research Council of Canada. There is no conflict of interest declared in this article.

    APPENDIX A: EXPERT VERSUS NOVICE SURVEYOR DATA COMPARISON

    Surveyors progress through the five experience levels by successfully completing species identification tests and conducting surveys. Species identification training is a large part of the Reef Environmental Education Foundation's (REEF) mandate, and species identification resources and REEF “Fishinars” (webinars) are provided to encourage surveyors to increase their skills in an entertaining group environment. Surveyors at levels 1, 2, and 3 are classified as novice surveyors, and those at levels 4 and 5 are classified as expert surveyors. To achieve level 4 or level 5 expert status, surveyors need to conduct 35 or 50 surveys and to achieve 90% or 95% accuracy, respectively, on a 100-question fish, invertebrate, and algae species identification test, in which pictures of species are displayed and the surveyor must correctly identify the species' common name and family (for fish) or phylum (for invertebrates and algae). Expert data comprise 49% of the surveys conducted in British Columbia between May 10, 1998, and August 17, 2020.

    Survey duration, fish species richness, and fish abundance observations collected by expert and novice surveyors were compared using non-parametric Mann–Whitney U-tests, as data were not normally distributed and did not display equal variance between groups. To enable a more accurate test of the species identification skills between the two experience levels, we used fish observations rather than observations of invertebrates or algae (which have set species lists that are monitored by REEF surveyors). Expert surveyors recorded 161 fish species, and novice surveyors recorded 130 fish species. Novice surveyors recorded 15 species that were not recorded by expert surveyors, and the number of unique observations ranged from 1 to 3, with the exception of unidentified surfperch, which had 28 observations (Table A1). Expert surveyors recorded 45 species that were not recorded by novice surveyors, with the number of unique observations ranging from 1 to 72 (Table A2). To reduce any variability due to survey location, species richness and abundance scores were tested using only the sites at which both experts and novices had conducted surveys. To accurately compare species abundances at the site level, only species that were observed by both expert and novice surveyors were included in the analysis. This resulted in data from 237 sites and 116 fish species.

    Expert surveyors spent 52 min (median value) surveying (n = 3,489 surveys), while novice surveyors spent 46 min surveying (n = 3,118 surveys), which represents a statistically significant difference in survey effort (U = 21.2, P < 0.001). Expert surveyors also observed significantly more fish species (median = 12 species) than did novice surveyors (median = 8 species; U = 28.111, P < 0.001). However, there were no significant differences in survey median site species abundances between expert (median fish abundance score = 1.10) and novice (median fish abundance score = 1.01) surveyor experience levels (U = 1.484, P = 0.138). These results indicate that while expert surveyors observed more species, perhaps due to their extended survey time and increased fish identification training, expert and novice surveyors observed similar abundances at the same site for the same species.

    Table A1. Summary table of fish observations made only by novice surveyors, organized from most to least sightings.
    Taxon Expert observations Novice observations
    Unidentified surfperch 0 28
    Barred Surfperch Amphistichus argenteus 0 3
    Black Perch Embiotoca jacksoni 0 3
    Threadfin Sculpin Icelinus filamentosus 0 3
    Arrow Goby Clevelandia ios 0 2
    Rainbow Seaperch Hypsurus caryi 0 2
    California Halibut Paralichthys californicus 0 1
    Giant Kelpfish Heterostichus rostratus 0 1
    Green Sturgeon Acipenser medirostris 0 1
    Lavender Sculpin Leiocottus hirundo 0 1
    Prickly Sculpin Cottus asper 0 1
    Reef Perch Micrometrus aurora 0 1
    Starry Skate Raja stellulata 0 1
    Unidentified greenling 0 1
    Yellowtail Rockfish Sebastes flavidus 0 1
    Table A2. Summary table of fish observations made only by expert surveyors, organized from most to least sightings.
    Taxon Expert observations Novice observations
    Yellowtail Rockfish Sebastes flavidus (age 0) 72 0
    Canary Rockfish Sebastes pinniger (age 0) 54 0
    Blue Rockfish Sebastes mystinus/Deacon Rockfish Sebastes diaconus (age 0) 16 0
    Black Rockfish Sebastes melanops (age 0) 14 0
    Unidentified Black Rockfish/Yellowtail Rockfish (age 0) 13 0
    Puget Sound Rockfish Sebastes emphaeus (age 0) 8 0
    Dusky Rockfish Sebastes ciliatus 7 0
    Thornback Sculpin Paricelinus hopliticus 6 0
    China Rockfish Sebastes nebulosus (age 0) 5 0
    Rosylip Sculpin Ascelichthys rhodorus 5 0
    Slim Sculpin Radulinus asprellus 5 0
    Unidentified snailfish 5 0
    Sharpnose Sculpin Clinocottus acuticeps 4 0
    Snubnose Sculpin Orthonopias triacis 4 0
    Widow Rockfish Sebastes entomelas (age 0) 4 0
    Coho Salmon Oncorhynchus kisutch 3 0
    Pacific Sardine Sardinops sagax 3 0
    Sand Sole Psettichthys melanostictus 3 0
    Vermilion Rockfish Sebastes miniatus (age 0) 3 0
    Dover Sole Microstomus pacificus 2 0
    Flathead Sole Hippoglossoides elassodon 2 0
    Marbled Snailfish Liparis dennyi 2 0
    Ocean Sunfish Mola mola 2 0
    Pacific Tomcod Microgadus proximus 2 0
    Ribbed Sculpin Triglops pingelii 2 0
    Slender Sole Lyopsetta exilis 2 0
    Tiger Rockfish Sebastes nigrocinctus (age 0) 2 0
    Black Prickleback Xiphister atropurpureus 1 0
    Butter Sole Isopsetta isolepis 1 0
    Chum Salmon Oncorhynchus keta 1 0
    Longnose Skate Raja rhina 1 0
    Pacific Lamprey Entosphenus tridentatus 1 0
    Pink Salmon Oncorhynchus gorbuscha 1 0
    Puget Sound Sculpin Ruscarius meanyi 1 0
    Red Gunnel Pholis schultzi 1 0
    Redstripe Rockfish Sebastes proriger 1 0
    Ribbon Prickleback Phytichthys chirus 1 0
    Rock Prickleback Xiphister mucosus 1 0
    Saddleback Sculpin Oligocottus rimensis 1 0
    Spotted Snailfish Liparis callyodon 1 0
    Stripefin Ronquil Rathbunella alleni 1 0
    Stripetail Rockfish Sebastes saxicola (age 0) 1 0
    Surf Smelt Hypomesus pretiosus 1 0
    Unidentified Copper Rockfish Sebastes caurinus/Quillback Rockfish Sebastes maliger (age 0) 1 0
    Unidentified salmon 1 0