PHYSICAL CLIMATE VARIABLES ASSOCIATED WITH CALIFORNIA CURRENT LARGE MARINE ECOSYSTEM AND IMPLICATIONS IN RECREATIONAL FISHERIES MANGEMENT

Tiffany Miller Oregon State University 2019 ABSTRACT

Climate variations within the California Current Large Marine Ecosystem (CCLME) have impacts on marine fish populations. It is proposed that these impacts will be reflected in recreational fishing catches which is explored in this study. A Pearson correlation analysis compares data from El Niño

Southern Oscillation (ENSO) events and upwelling to recreational catch data for ten different species located within the CCLME. Catches for five out of ten species studied were found to have statistically significant correlations with climate variability. Results of this study indicate that climate variation has an impact on recreational fishery dynamics within the CCLME and this should be considered when managing recreational fisheries.

ACKNOWLEDGEMENT

I would like to thank my advisor Michael Harte for working with me on developing this project and guiding me throughout the entire process by giving multiple suggestions and edits. It would not have been possible without his help and encouragement. I would also like to thank Scott Heppell and

Grant Thompson, my committee members, whom also helped me along the way by providing great advice and suggestions. Lastly, I would like to thank Chuck Valle, a CDFW scientist, who helped me out by sending me relevant research papers as well as sitting down with me to discuss some of these fisheries.

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Table of Contents ABSTRACT ...... 1 ACKNOWLEDGEMENT...... 1 1. INTRODUCTION ...... 4 1.1 Climate Variability Impacts Marine Fish Populations ...... 4 1.2 Climate Variability Impacts on Recreational Fisheries ...... 5 1.3 Fisheries Management ...... 6 1.4 Study Overview ...... 7 2. BACKGROUND ...... 8 2.1 California Current Large Marine Ecosystem (CCLME) ...... 8 2.2 Climate Variability in CCLME ...... 10 2.2.1 Upwelling ...... 10 2.2.2 Pacific Decadal Oscillation (PDO) ...... 11 2.2.3 El Niño Southern Oscillation (ENSO) ...... 12 2.3 California’s Recreational Fisheries ...... 13 3. METHODS ...... 14 3.1 Timeline ...... 14 3.2 Recreational Fisheries Survey Data ...... 14 3.3 Sampling Modes ...... 16 3.4 Data Obtained from Recreational Fisheries Information Network (recFIN) ...... 17 3.5 Species Analysis ...... 17 4. RESULTS...... 18 4.1 Primary Target Data ...... 18 4.2 Reasoning Behind Species Selection ...... 20 4.3 Overall Catch Data ...... 21 4.4 Correlation Analysis ...... 25 5. DISCUSSION ...... 27 5.1 Primary Target Data in Response to Climate Variability ...... 27 5.2 Species Catch Data in Relation to Climate Variability ...... 28 5.2.1 Ocean Whitefish ...... 28 5.2.2 Sanddabs...... 29 5.2.3 Kelp Bass ...... 30 5.2.4 Barred Sand Bass ...... 30

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5.2.5 Sand Bass genus ...... 31 5.2.6 California Halibut ...... 32 5.2.7 Pacific Mackerel ...... 33 5.2.8 California Scorpionfish...... 33 5.2.9 Rockfish ...... 34 5.2.10 Yellowtail ...... 35 5.3 Explanation of Unexpected Results ...... 35 5.4 Study Extension ...... 36 5.5 Study Implications ...... 36 6. CONCLUSION ...... 37 6.1 Challenges of Managing Recreational Fisheries ...... 37 6.2 Fisheries Management Using Climate Variability within the CCLME ...... 38 6.3 Future of Fisheries Management ...... 39 7. REFERENCES ...... 41 Appendix A ...... 47 Ocean Whitefish (Caulolatilus princeps) ...... 47 Appendix B ...... 49 Sanddabs (Citharichthys spp.) ...... 49 Appendix C ...... 51 Sand Bass (Paralabrax spp.) ...... 51 Appendix D ...... 54 California Halibut (Paralichthys californicus) ...... 54 Appendix E ...... 55 Pacific Mackerel (Scomber japonicas) ...... 55 Appendix F ...... 56 California Scorpionfish (Scorpaena guttata) ...... 56 Appendix G ...... 58 Rockfish (Sebastes spp.) ...... 58 Appendix H ...... 61 Yellowtail (Seriola quinqueradiata) ...... 61

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1. INTRODUCTION

1.1 Climate Variability Impacts Marine Fish Populations

The National Oceanic and Atmospheric Administration (NOAA) defines climate as “long-term averages and variations in weather measured over a period of several decades” (NOAA n.d.). Along the

Pacific coast of California, Oregon and Washington State climate variations are measured using indices such as El Niño Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) (Link et al. 2015).

Upwelling events, which are associated with ENSO and PDO events are another source of variation within the ocean’s climate system. Climate variability can have significant impacts on marine fish populations and communities (Siegelman-Charbit et al. 2018).

Climate variability has been linked to changes in distributions of marine species and productivity by altering patterns of migration, reproduction, and recruitment (Hare et al. 2016). Marine fish populations can react to differently to each ENSO, PDO and upwelling event (McClatchie 2014). Within the variability of marine fish population reactions to climate events, there are some general patterns that have been observed. Different species have preferences for either warm or cool phases within the climate variation patterns (see figure 1.1) (Chavez et al. 2017). Strong upwelling events, which bring in nutrient rich water, have been associated with an increase in production of species such as Rockfish

(Sebastes spp.) and Sanddabs (Citharichthys spp.) (Santora et al. 2017). The effects of climate variability on marine fish populations are reflected in our fishery harvests.

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Figure 1.1 – A list of species known to favor warm or cool phases of climate variability within the California Current System (Chavez et al. 2017, I).

1.2 Climate Variability Impacts on Recreational Fisheries

Within the California Current Large Marine Ecosystem (CCLME) fisheries can be highly variable.

Causes of this variability can be attributed to various factors such as climate variability and overfishing

(Jarvis et al. 2004). Climate variability impacts on marine fisheries are noticeable when warming or cooling events are considered above or below average. Visible effects from unusually high or low warming or cooling events are seen for months or even years after the water returns to average temperatures (Harvey et al. 2018). Visible effects from these climate events include increases or decreases in catch. Unusually high temperatures during warming events can introduce fisheries that are generally found further south such as Tuna or Marlin. How marine fish populations react to climate variability is an important aspect for both fishery participants and fishery managers.

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The number of studies projecting effects that climate variability has on marine fish populations has been increasing (Hare et al. 2016). Jarvis et al. (2004) looked at environmental impacts on recreational fisheries for 44 species found in southern California between the years of 1980 and 2000.

They found that more than half of the species tested showed responses to climate variability. This implies that some species may be climate invariant. It is unclear whether climate variability is the main driver behind fisheries dynamics in southern California or if it is just part of the overall picture. Studying fisheries dynamics is essential because fisheries are important to local communities.

Knowing how climate variability impacts fisheries is crucial not only for the overall health of fish populations, but for the communities that rely on them for their livelihood. Fisheries are economically and socially important aspects of local communities. In 2012, commercial and recreational fisheries added $199 billion dollars to the United States economy. Approximately 1.7 million fisheries related jobs were generated that year (Link et al. 2015). Effective management of these fisheries is essential in order to prevent economic and social collapses in the communities that rely on them.

1.3 Fisheries Management

Traditionally, in fisheries management, each species is managed independently using factors such as mortality rates and harvest thresholds. The mortality rate considers the natural death rate while the harvest threshold is the amount of fish that can be sustainably removed from fisheries populations.

Using harvest thresholds in fisheries management can be challenging as thresholds for marine populations can change with different climate regimes (Chavez et al. 2017). Managing fisheries at this level has worked in the past for various fisheries, but it ignores other ecosystem components such as bycatch, and climate variability (Trochta et al. 2018). In order to help manage California’s fisheries, the

Marine Life Management Act (MLMA) was implemented. (constant harvest threshold)

The Marine Life Management Act was enacted in 1999 (Chavez et al. 2017). The MLMA directs the California Fish and Game Commission (FGC) and the California Department of Fish and Wildlife

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(CDFW) to manage the state’s fisheries at a sustainable level. The act “assures the long-term economic, recreational, ecological, cultural, and social benefits of these fisheries and the marine habitats on which they depend” (Chavez et al. 2017). Using the MLMA, a Master Plan was created in 2011 which encouraged California’s fisheries management agencies to develop Fishery Management Plans (FMPs) in order to manage individual fisheries. Most California FMPs do not consider climate variability. The only two that currently do are the FMPs for the commercial fisheries for Swordfish and Sardines (Chavez et al. 2017). When considering climate variability in fisheries management, Ecosystem-Based Fisheries

Management (EBFM) is one approach that could help.

Ecosystem Based Fisheries Management uses different approaches when managing fisheries. Ecosystem processes along with climate variability are considered (Townsend et al. 2019).

Fisheries management is focused on the ecosystem and how the different marine populations interact with each other (Townsend et al. 2019). This contrasts with the single species approach which is being used for several California fisheries. On a federal level, the National Oceanic and Atmospheric

Administrations (NOAA) has adopted a policy of using EBFM in order to consider the impact of their management decisions. Trade-offs and interactions between fisheries and their associated ecosystems will be considered within some of their mandates with a changing climate in mind (Link et al. 2015).

1.4 Study Overview

This study focuses on ten recreational fisheries found within the CCLME. Each fishery is explored to determine whether their catch dynamics can be associated with climate variability. Results are analyzed and discussed at species and ecosystem level. My hypothesis is that this study will show that catch dynamics are associated with climate variability.

Evidence of statistical associations found in this study could help explain catch dynamics within different fisheries. If a species is known to fare poorly in warm or cold-water regimes, it may be possible to incorporate stricter regulations in order to relieve some of the fishing pressure on marine fish

7 | Page populations. This may help marine fish populations withstand unusually high or low warming or cooling events. It is possible that this may help prevent a future fishery collapse due to climate impacts.

2. BACKGROUND

2.1 California Current Large Marine Ecosystem (CCLME)

The CCLME is an eastern boundary current system in the Pacific Ocean associated with the

North Pacific Gyre (Siegelman-Charbit et al. 2018). This current system is present year-round and experiences climate variability that occurs at seasonal, decadal and inter-annual timescales (Checkley &

Barth 2009). Sometimes an unusual climate event occurs, such as between 2014 and 2016 when a large area of warm water dubbed “the blob” persisted on the West Coast directly after an El Niño event

(Chavez et al. 2017).

The CCLME is composed of multiple currents and water sources. Six currents make up the

CCLME: the California Current, California Undercurrent, Davidson Current, Coastal Jet, North Pacific

Current, and the Southern California Eddy (Checkley & Barth 2009) (Figure 2.1). The California Current is a south flowing offshore current. California Undercurrent is present below the surface of the ocean and flows north (Frischknecht et al. 2015). The Davidson Current flows at the surface and is typically present during the winter (Siegelman-Charbit et al. 2018). Coastal Jet flows south and is responsible for about half of the CCLME’s total transport. The North Pacific Current is present in the north (Checkley & Barth

2009). Southern California Eddy is an area of recirculation (Siegelman-Charbit et al. 2018).

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Figure 2.1 – California Current Large Marine Ecosystem (CCLME) map showing the position and direction of the various currents (Checkley & Barth 2009, 50).

The CCLME has four main sources of water: Pacific Subarctic, North Pacific Central, Coastal

Upwelled, and Equatorial Pacific (Table 2.1) (McClatchie 2014). Pacific Subarctic water originates from the north. North Pacific Central water, which has also been referred to as the Subarctic Current, separates the gyres in the North Pacific (McClatchie 2014). North Pacific Central waters mix with the

Pacific Subarctic waters as they flow south. The third source of water present in the CCLME comes from the south and is known as the Equatorial Pacific water. Pacific Subarctic and Equatorial Pacific water come together deep in the ocean and create the fourth source of water, Coastal Upwelled (McClatchie

2014). Source waters in the CCLME are known to fluctuate with ENSO and PDO events (PFMC 2017).

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Table 2.1 – Water sources of California Current Large Marine ecosystem and their associated characteristics. L represents low and H represents high (McClatchie 2014, 19).

2.2 Climate Variability in CCLME

Seasonal upwelling, PDO and ENSO events are all drivers of variability within the CCLME. ENSO is the most important factor that drives climate variability within the CCLME because it modifies upwelling, thermoclines, sea-surface temperatures, circulation, and overall biological productivity

(Frischknecht et al. 2015). Variability such as reductions in primary productivity are felt throughout the entire food web and can have large impacts on recreational fisheries. There is a negative effect on zooplankton, marine mammals and fish (Frischknecht et al. 2015). Ability to predict variability could be useful in assessing future biological production and overall ecosystem health within the CCLME

(Frischknecht et al. 2015).

2.2.1 Upwelling

Upwelling is the process by which cold nutrient-rich water moves from deep in the ocean to the surface (Harvey et al. 2018). Gradients in sea level pressure produce alongshore winds that impact upwelling events (Harvey et al. 2018; Siegelman-Charbit et al. 2018). Timing, intensity and duration of winds conducive to upwelling have a lot of variability, which can have positive and negative effects on marine life (Chavez et al. 2017).

Productivity in the CCLME is partially caused from latitudinal shifts in the North Pacific Current’s position. (Schroeder et al. 2018). Primary and secondary productivity increases when upwelling occurs.

Upwelling was delayed in 2005, for example, which resulted in the failure of many species, including

10 | Page many species of Rockfish, to recruit (Chavez et al. 2017). The intensity of upwelling can be measured using indices.

The intensity of upwelling is estimated using a Coastal Upwelling Transport Index (CUTI). CUTI is an estimate of vertical transport to or from surface waters of the ocean. CUTI index is calculated using

“atmospheric sea level pressure fields” such as surface winds, depth of water layers, and sea surface height (Jacox et al. 2014). The CUTI has been above average in the southern CCLME for the last five years (Figure 2.2) (Harvey et al. 2018). With the increase in upwelling over the last five years, it’s possible there could be an increase in recreational fisheries catch that would reflect in the data due to higher primary productivity.

Figure 2.2 – Upwelling events in southern California CCS. Green area highlights last five years to indicate most recent trends, along with an arrow to show direction of recent trends. Dashed green line represents average index, with the solid green lines showing when CUTI is unusually high or low (NOAA 2018).

2.2.2 Pacific Decadal Oscillation (PDO)

The timescale of PDO cycles is typically 40-76 years while ENSO events usually run 2-7 year cycles. Since 1998, PDO+ (warm) and PDO- (cool) phases have shifted every five years (Figure 2.3). This is unusual and indicates an abnormal climatic pattern for the CCLME (PFMC 2017). Since 2014, PDO has been in a warm phase (NOAA n.d.).

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Changes in the strength of the Aleutian Low-pressure system are considered drivers for PDO

(PFMC 2017). Negative PDOs show an increase in the equatorward flow within the CCS (PFMC 2017).

When PDO is positive, there is an increase in onshore and poleward flow (PFMC 2017).

Figure 2.3 – Pacific Decadal Oscillation (PDO) shifts from 1925 to 2017. Values are taken from an average between May and September. Red indicates PDO+ and blue indicates PDO- (PFMC 2017, 59).

2.2.3 El Niño Southern Oscillation (ENSO)

ENSO events are characterized by a warming or cooling trend about every five years (Zhang et al. 2012). An El Niño event is declared when ONI exceeds 0.5°C for five consecutive months and La Niña events occur when ONI is less than -0.5°C for five consecutive months (Peterson et al. 2014). Warming or cooling can last through multiple seasons and have a direct impact on marine ecosystems (Checkley &

Barth 2009).

Oceanic Niño Index (ONI) is used by NOAA to forecast ENSO activity (Table 2.2). ONI is defined as the “three month running mean of SST anomalies in the Niño region of the equatorial Pacific” (Peterson et al. 2014). NOAA’s Climate Prediction Center (CPCIT 2018) monitors SST changes in order to track

ENSO events (CPCIT 2018). ENSO events are stochastic, which makes predicting them challenging

(Frischknecht et al. 2017). There has been a recent pattern of “unusual variability” from 2013 through

2016. A patch of warm water dubbed “the blob” was followed by an El Niño event. The blob, along with a strong El Niño in 2015 led to an anomalous warming of the CCS from 2013 to 2016, greatly altering the

CCLME (PFMC 2017). Some climate experts feel that the CCLME may be entering a phase of increased variability (Chavez et al. 2017).

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Table 2.2 – Oceanic Niño Index (ONI). Average SST temperatures by season. SST anomalies are indicated by red and blue text. Red indicates above normal SSTs and blue indicates below normal SSTs. Last column is a yearly average in order to remove seasonal biases (CPCIT 2018).

2.3 California’s Recreational Fisheries

California’s recreational fisheries have cultural and economic value (Bellquist et al. 2017).

Recreational fishing contributes millions of dollars to California’s economy (Jarvis et al. 2004). In 2012, on the west coast (California, Oregon and Washington), there were approximately 1.6 million recreational fishers that participated in about 7.4 million fishing trips. Approximately 5.3 million of those fishing trips were from California which amounted to around $3 billion in fishing related expenditures

(USDOC 2019). In 2016, on the west coast there was an estimated 5.2 million recreational fishing trips which resulted in about $3 billion in sales (USDOC 2019). The numbers for the entire west coast in 2016 are approximately the same as for California alone in 2011. Therefore, recognizing the magnitude of

California’s recreational fisheries is very important when it comes to making management decisions.

Recreational fisheries account for a large portion of marine fish total take in southern California

(Horning et al. 2014). Several fisheries have no commercial sector or a small commercial sector, so landings of recreational caught fish represent the majority of total take for these species (Figueira &

Coleman 2010). Bellquist et al. (2017) found that in 2011, total catch exceeded 12 million fish in

California’s recreational fisheries.

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3. METHODS

3.1 Timeline

Recreational fisheries catch data were obtained for the years 2007 through 2017. This time series helps ensure that changes in catch are not attributed to a single warming or cooling event associated with the CCLME. All data were examined on a yearly basis, using yearly averages, in order to remove any seasonal biases caused by weather or seasonal fisheries closures.

3.2 Recreational Fisheries Survey Data

The Marine Recreational Fisheries Statistical Survey (MRFSS) was the primary survey in which

California’s marine recreational fisheries data were obtained (CDFW 2018). Catch and effort estimates were analyzed using MRFSS data between 1979 and 2003. Surveys were conducted by the Pacific States

Marine Fisheries Commission (PSMFC), which was funded by NOAA, National Marine Fisheries Service

(NMFS), and CDFW (CDFW 2018).

In 2004, the California Recreational Fisheries Survey (CRFS) replaced MRFSS. Sampling adjustments were made between 2004 and 2010 in order to obtain more timely and accurate data

(CDFW 2018). CRFS is a statewide marine recreational finfish program. Catch and effort estimates are conducted monthly. Instead of an independent contractor conducting surveys, all sampling is now done by CDFW staff. All data are entered and edited in-house by CDFW staff. Data are managed by a state-of- the-art data management system (CDFW 2018). The CRFS program conducts surveys at the district level instead of using Northern and Southern California as was done with MRFSS.

The California coastline was divided up into six districts (Figure 3.1). Southern California is composed of District 2 and District 1. District 2 is the Channel District. It is composed of Santa Barbara and Ventura counties. This district is considered an ecological transition zone. This is where both warm and cold-water species can be found. Recreational fishing effort is year-round (CDFW 2018). District 1 is

14 | Page the South District. South District is composed of Orange, Los Angeles and San Diego counties. It is heavily urbanized. There are many harbors and marinas which are utilized by recreational boaters.

Recreational fishing is year-round (CDFW 2018). All data used for this study were obtained from District

1.

Figure 3.1 – Map of California Recreational Fisheries Survey (CRFS) districts. South (1) in navy blue is the area in which data were obtained for this study (CDFW 2018).

Once data are obtained and edited for accuracy, they are entered into the CRFS database. After database entry, data are further checked by multiple environmental scientists for accuracy. Data are sorted and analyzed before they are entered into the Recreational Fisheries Information Network

(recFIN) database (PSMFC 2016). The recFIN database was established in 1992 and is managed by

PSMFC. The recFIN database integrates marine recreational sampling efforts form federal and state sources into a single database” (PSMFC 2016). It provides important social, economic, and biological

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2016). All catch data used in this study, both MRFSS and CRFS, were obtained from the recFIN database.

3.3 Sampling Modes

Boat sampling modes were chosen for evaluation because boat-based fishers have access to a larger variety of fisheries than shore-based fishers. Two types of vessels account for landings of marine recreational fish in southern California: Private boaters and Commercial Passenger Fishing Vessels

(CPFVs) (Bellquist et al. 2017). Private boaters are not legally required to report their catch. Catch estimates were acquired from the CRFS program. Catch data is obtained from sampling launch ramps and intercepting private boaters after returning from their trips. Catch reporting from private boaters is voluntary (Bellquist et al. 2017).

Commercial Passenger Fishing Vessels (CPFVs) are referred to as party, charter or cattle boats

(Figueira & Coleman 2010). Passengers on board CPFVs are generally paying customers. They are paying for a spot to fish on the boat as well as for assistance in their fishing efforts. Fishing is often efficient on these trips because experienced fishers are guiding inexperienced fishers on where and how to fish.

Operators of these boats are largely motivated by profit, which increases when there is an increase in catch (Figueira & Coleman 2010). CPFVs are required by law to submit a logbook of catch (Bellquist et al.

2017). Catch in these logbooks is often not sorted to species level. One job of a CRFS sampler sampling on board these vessels is to obtain more species-specific data as well as biological data such as lengths and weights (Personal Observation).

The majority of the CPFV fleet is based in southern California, and “California’s CPFV fleet is the largest of its kind in the world based on the spatial scale of operation” (Bellquist et al. 2017, 134). As of

2017, southern California’s CPFV fleet contained approximately 260 vessels. Vessels in the CPFV fleet are generally large and can carry up to 149 passengers although each vessel carries 43 passengers on average (Bellquist et al. 2017).

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3.4 Data Obtained from Recreational Fisheries Information Network (recFIN)

For each species, a catch estimate report was obtained with several filters applied. Year range was set as 2007 through 2017. Fishing mode was set to Private/Rental Boats and Party/Charter Boats in order to filter out shore-based fishing trips. Subregion was selected as southern California and District 1 data were sorted out for analysis. A report of primary targets was also obtained with the same filters applied. Primary targets are what fishers are trying to catch on their trips. All reports were saved as

Excel files for evaluation and analysis.

3.5 Species Analysis

Ten species were selected for evaluation. Each species is described in further detail in appendices A through H. Species were chosen based on high primary target ranking as well as high total catch ranking. For each species, the number of retained, released alive, released dead, and total mortality were summed on a yearly basis by mode. Total mortality is the sum of retained and released dead. Total catch (retained + released alive + released dead) was calculated for each species on a yearly basis by mode. Correlation analyses were conducted for total catch by mode for each species against yearly ONI averages and CUTI index. PDO indices were not used for correlation analysis due to the timescale of this study being too short.

Pearson’s Correlation Index (R Score) was calculated with excel using total boat catch, CPFV total catch and private boat total catch for each species against the amount of times the species was targeted. Using R score, a t value was calculated using the following equation (Lowry 2019):

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A two tailed t distribution was used in order to obtain a p-value to determine significance. P<.05 and

P<.10 were both considered for evaluation. Results were placed in tables corresponding with each species.

4. RESULTS

4.1 Primary Target Data

For each recreational fishing trip, a primary target species is selected by the fishers. The primary target determines where the fishers will fish and which fishing gear they choose to use. Fishers will often have more than one target species or species group, but only primary target data were used in this study. Top three yearly targets were obtained for each mode based on how many times a target was listed each year (Tables 4.1, 4.2). Rockfish was the group most targeted by CPFV trips during the study period. Rockfish’s were a top three target for private boaters in all years but ranked second or third place in 2013 and later. One or more of the following Sand Bass groups were also found within the top three targets every year for CPFV trips: the overall Sand Bass genus (Paralabrax spp.), Kelp Bass

(Paralabrax clathratus) and Barred Sand Bass (Paralabrax nebulifer). For private boaters, one or more of these Sand Bass groups are in the top three in only two years of the study period (Tables 4.1, 4.2).

Private boaters are more inclined to target California Halibut (Paralichthys californicus) and Rockfish.

Yellowtail (Seriola quinqueradiata) begins showing up as a primary target for private boaters beginning in 2013 and CPFVs beginning 2014.

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Table 4.1 – Top three yearly primary targets on CPFV trips CPFV FIRST HIGHEST PRIMARY SECOND HIGHEST PRIMARY THIRD HIGHEST PRIMARY TARGET TARGET TARGET 2007 Rockfish genus California Scorpionfish Sand Bass genus (Sebastes spp) (Paralichthys californicus) (Paralichthys spp) 2008 Rockfish genus Kelp Bass Pacific Bonito (Sebastes spp) (Paralabrax clathratus) (Sarda lineolate) 2009 Rockfish genus Sand Bass genus Kelp Bass (Sebastes spp) (Paralichthys spp) (Paralabrax clathratus) 2010 Rockfish genus Barred Sand Bass Bottom fish (Sebastes spp) (Paralabrax nebulifer) (Ground fish) 2011 Rockfish genus Sand Bass genus California Scorpionfish (Sebastes spp) (Paralichthys spp) (Paralichthys californicus) 2012 Rockfish genus Pacific Barracuda Kelp Bass (Sebastes spp) (Sphyraena argentea) (Paralabrax clathratus) 2013 Rockfish genus Sand Bass genus California Scorpionfish (Sebastes spp) (Paralichthys spp) (Paralichthys californicus) 2014 Rockfish genus Sand Bass genus Yellowtail (Sebastes spp) (Paralichthys spp) (Seriola quinqueradiata) 2015 Rockfish genus Yellowtail Sand Bass genus (Sebastes spp) (Seriola quinqueradiata) (Paralichthys spp) 2016 Rockfish genus Sand Bass genus Yellowtail (Sebastes spp) (Paralichthys spp) (Seriola quinqueradiata) 2017 Rockfish genus Sand Bass genus California Scorpionfish (Sebastes spp) (Paralichthys spp) (Paralichthys californicus) (Data obtained from recFIN.org)

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Table 4.2 - Top three yearly primary targets on private boat trips. Private boaters often give a target of unidentified fish. When asked what fishers are targeting during the CRFS fisheries survey, they respond with “anything” or “fish”. These responses are recorded as “unidentified fish”. PRIVATE FIRST HIGHEST PRIMARY SECOND HIGHEST PRIMARY TARGET THIRD HIGHEST PRIMARY BOAT TARGET TARGET 2007 Rockfish genus California Halibut Unidentified Fish (Sebastes spp) (Paralichthys californicus) 2008 Rockfish genus California Halibut Unidentified Fish (Sebastes spp) (Paralichthys californicus) 2009 Rockfish genus California Halibut Bottom fish (Sebastes spp) (Paralichthys californicus) (Ground fish) 2010 Rockfish genus California Halibut Bottom fish (Sebastes spp) (Paralichthys californicus) (Ground fish) 2011 Rockfish genus Sand Bass genus California Halibut (Sebastes spp) (Paralichthys spp) (Paralichthys californicus) 2012 Rockfish genus Kelp Bass California Halibut (Sebastes spp) (Paralabrax clathratus) (Paralichthys californicus) 2013 Unidentified fish Rockfish genus Yellowtail (Sebastes spp) (Seriola quinqueradiata) 2014 Unidentified fish Yellowtail Rockfish genus (Seriola quinqueradiata) (Sebastes spp) 2015 Yellowtail Unidentified Fish Rockfish genus (Seriola quinqueradiata) (Sebastes spp) 2016 Unidentified Fish Yellowtail Rockfish genus (Seriola quinqueradiata) (Sebastes spp) 2017 Unidentified Fish Yellowtail Rockfish genus (Seriola quinqueradiata) (Sebastes spp) (Data obtained from recFIN.org) 4.2 Reasoning Behind Species Selection

Species were selected based on several factors described in Table 4.3. The idea was to get representation from southern California’s most popular and common fisheries. Sand Bass and Rockfish are the two most common fisheries so two species were selected from each of these groups. Sanddabs

(Citharichthys spp.) and California Halibut are the two most common flatfish groups caught, so they were selected as well. When Rockfish closes seasonally, fishers will often switch their target to California

Scorpionfish, so they appear in the analysis. Ocean Whitefish (Caulolatilus princeps) and Yellowtail were selected because seasonal variability has been observed and it would be interesting to see if this was due to climate variability or natural seasonal fluctuations. Pacific Mackerel was chosen because it is often used as bait as well as being one of the top species that are caught in southern California waters.

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Table 4.3 – Species that were chosen for further evaluation. Reason each species was selected is listed. COMMON NAME SCIENTIFIC NAME REASON CHOSEN OCEAN WHITEFISH Caulolatilus princeps Personally observed an increase in catch. Personal observation supported by catch data in Figure 4.2

SANDDABS Citharichthys spp. Persistently ranks in the top ten total catch KELP BASS Paralabrax clathratus One of the highest targeted and caught species BARRED SAND BASS Paralabrax nebulifer Persistently ranks in the top ten total catch CALIFORNIA HALIBUT Paralichthys californicus A highly targeted species for private boaters PACIFIC MACKEREL Scomber japonicas Persistently ranks in the top five total catch CALIFORNIA SCORPIONFISH Scorpaena guttata Persistently ranks in the top two total catch for CPFVs SQUARESPOT ROCKFISH Sebastes hopkinsi On average, the second most commonly caught rockfish VERMILION ROCKFISH Sebastes miniatus On average, the most commonly caught species of rockfish YELLOWTAIL Seriola quinqueradiata Personally observed an increase in catch. Personal observation supported by catch data in Figure 4.2

4.3 Overall Catch Data

Chosen species were ranked based on total catch (Tables 4.4, 4.5). The ranking system chosen was selected from a study conducted by Jarvis et al. (2014) because it gives a clear picture of changes in catch trends over time. Ocean Whitefish catch has increased over the years, moving into the top ten highest caught species in 2016 and 2017 (See Appendix A for additional Ocean Whitefish information).

Between 2010 and 2014 Sanddabs were in the top three most commonly caught fish on CPFVs, but they dropped to number 8 from 2015 through 2017 (See Appendix B for additional Sanddab information).

Kelp Bass and Barred Sand Bass are often in the top ten total catch with Kelp Bass being more commonly caught than Barred Sand Bass (See Appendix C for additional Sand Bass information). California Halibut ranks low in total catch for CPFVs but higher for private boaters. CPFVs do not often target California

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Halibut because it is a difficult, low profit fishery which results in a low amount of catch (personal observation) (See Appendix D for additional California Halibut information).

Pacific Mackerel is often the highest in total catch. This can be attributed to the fact that it is caught as bycatch in almost every fishery. It is also targeted at the beginning of a trip to be used as bait for later in the day or for future trips (See Appendix E for additional Pacific Mackerel information).

California Scorpionfish are in the top two total catch for CPFV boats. They are easy to catch and can be reliably found. When fishing conditions are challenging, CPFV boats rely on California Scorpionfish to keep their numbers up and customers happy. They rank a little lower when it comes to private boater’s total catch. They are venomous so it is possible fishers do not want to deal with the extra trouble involved with targeting this species (See Appendix F for additional California Scorpionfish information).

Squarespot and Vermilion Rockfish are often the two most common Rockfish species caught. Vermilions are often sought after while Squarespot is typically just bycatch when targeting more prized Rockfish

(See Appendix G for additional Rockfish information). Yellowtail are seasonal and are more abundant in catch in years when the water is warmer. This is reflected in the total ranking of Yellowtail catch (See

Appendix H for additional Yellowtail information).

For catch data between 2007 and 2017, there is an overall increase in catch for most species.

Barred Sand Bass and California Halibut are the only two that show a decline over the timespan of the study. Pacific Mackerel remain relatively stable. Ocean Whitefish, Squarespot Rockfish, Vermilion

Rockfish and Yellowtail all show a significant spike in catch but vary in terms of the year in which the catch peaks. Variations along with significant increases and decreases in catch were explored further in order to determine if changes were related to climate variability.

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Table 4.4 – Total CPFV catch ranked by year. Total catch includes all retained and released fish. Numbers that are in bold indicate species that were in the top five ranks for total catch for that year. COMMON NAME 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 OCEAN WHITEFISH 9 15 11 17 27 23 20 22 18 7 3 SANDDABS 6 5 4 2 1 2 2 3 8 8 8 KELP BASS 2 2 1 3 4 3 3 1 1 1 1 BARRED SAND BASS 5 4 5 5 3 6 9 11 9 17 11 CALIFORNIA HALIBUT 28 33 34 35 46 47 45 44 48 44 43 PACIFIC MACKEREL 3 3 3 4 5 8 4 4 3 3 4 CALIFORNIA SCORPIONFISH 1 1 2 1 2 1 1 2 2 2 2 SQUARESPOT ROCKFISH 21 16 15 21 13 17 8 6 5 4 6 VERMILION ROCKFISH 10 13 10 9 6 5 5 7 4 5 7 YELLOWTAIL 36 44 43 50 N/A 40 38 10 10 11 14 (Data obtained from recFIN.org)

Table 4.5 – Total private boat catch ranked by year. Total catch includes all retained and released fish. Numbers that are in bold indicate species that were in the top five ranks for total catch for that year. COMMON NAME 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 OCEAN WHITEFISH 16 17 18 20 37 23 30 25 13 10 6 SANDDABS 13 13 7 5 4 4 4 5 9 5 7 KELP BASS 1 1 1 2 2 1 1 1 1 1 1 BARRED SAND BASS 4 3 3 3 3 3 3 6 6 4 3 CALIFORNIA HALIBUT 6 6 10 10 10 10 10 16 19 21 14 PACIFIC MACKEREL 3 2 2 1 1 2 2 2 2 2 2 CALIFORNIA SCORPIONFISH 9 8 6 9 9 9 11 12 11 12 12 SQUARESPOT ROCKFISH 68 50 68 63 78 67 66 51 35 38 41 VERMILION ROCKFISH 12 14 16 8 8 5 7 8 8 7 10 YELLOWTAIL 20 21 19 32 49 12 15 3 3 9 8 (Data obtained from recFIN.org)

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Figure 4.2 – Total Catch per year by mode for each species. Total catch includes all kept and released fish. (Data obtained from recFIN.org) 4.4 Correlation Analysis

Five species - Ocean Whitefish, Sanddabs, Pacific Mackerel, California Scorpionfish and

Vermilion Rockfish did not correlate with climate factors (Table 4.6). Kelp Bass showed a possible negative correlation to CUTI with CPFV catch, but no correlation data showed for ONI. Barred Sand Bass catch on private boats showed a negative correlation to ONI and a positive correlation to CUTI. Sand

Bass catch on CPFVs did not correlate with climate factors. California Halibut showed negative correlations with ONI and positive correlations with CUTI for CPFVs and private boats. Squarespot

Rockfish showed a positive correlation with ONI for CPFVs and private boats. Only CPFVs showed a negative correlation to CUTI. Yellowtail showed a positive correlation with ONI and a negative correlation with CUTI for both modes. Having a difference in positive and negative correlations between

ONI and CUTI was expected because when ONI is high, CUTI tends to be low. It is important to note that just because correlations exist, the variation in catch cannot be attributed to climate variability alone without further study.

Table 4.6 – Correlation analysis of total catch for each species compared with ONI and CUTI. Total catch includes all kept and released fish.

CORRELATION ANALYSIS

OCEAN WHITEFISH Pearson's Index P-Value Significant Significant (R Score) (P < .05) (P < .10) CPFV VS ONI 0.141 0.679 No No PRIVATE BOAT VS ONI 0.049 0.886 No No

CPFV VS CUTI -0.313 0.349 No No PRIVATE BOAT VS CUTI -0.216 0.524 No No SANDDABS Pearson's Index P-Value Significant Significant (R Score) (P < .05) (P < .10) CPFV VS ONI -0.133 0.697 No No PRIVATE BOAT VS ONI -0.140 0.681 No No

CPFV VS CUTI -0.316 0.344 No No PRIVATE BOAT VS CUTI -0.442 0.173 No No

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KELP BASS Pearson's Index P-Value Significant Significant (R Score) (P < .05) (P < .10) CPFV VS ONI 0.474 0.141 No No PRIVATE BOAT VS ONI -0.035 0.919 No No

CPFV VS CUTI -0.544 0.084 No Yes PRIVATE BOAT VS CUTI 0.030 0.930 No No BARRED SAND BASS Pearson's Index P-Value Significant Significant (R Score) (P < .05) (P < .10) CPFV VS ONI -0.449 0.166 No No PRIVATE BOATS VS ONI -0.658 0.028 Yes Yes

CPFV VS CUTI 0.246 0.466 No No PRIVATE BOAT VS CUTI 0.604 0.049 Yes Yes CALIFORNIA HALIBUT Pearson’s Index P-Value Significant Significant (R Score) (P < .05) (P < .10) CPFV VS ONI -0.594 0.054 No Yes PRIVATE BOAT VS ONI -0.620 0.042 Yes Yes

CPFV VS CUTI 0.632 0.037 Yes Yes PRIVATE BOAT VS CUTI 0.724 0.012 Yes Yes PACIFIC MACKEREL Pearson's Index P-Value Significant Significant (R Score) (P < .05) (P < .10) CPFV VS ONI 0.136 0.690 No No PRIVATE BOAT VS ONI -0.252 0.455 No No

CPFV VS CUTI -0.433 0.183 No No PRIVATE BOAT VS CUTI -0.004 0.991 No No CALIFORNIA SCORPIONFISH Pearson’s Index P-Value Significant Significant (R Score) (P < .05) (P < .10) CPFV VS ONI 0.117 0.732 No No PRIVATE BOAT VS ONI -0.281 0.403 No No

CPFV VS CUTI -0.332 0.319 No No PRIVATE BOAT VS CUTI 0.315 0.345 No No SQUARESPOT ROCKFISH Pearson's Index P-Value Significant Significant (R Score) (P < .05) (P < .10) CPFV VS ONI 0.626 0.039 Yes Yes PRIVATE BOAT VS ONI 0.545 0.083 No Yes

CPFV VS CUTI -0.550 0.080 No Yes PRIVATE BOAT VS CUTI -0.184 0.588 No No VERMILION ROCKFISH Pearson’s Index P-Value Significant Significant (R Score) (P < .05) (P < .10) CPFV VS ONI 0.516 0.104 No No PRIVATE BOAT VS ONI 0.282 0.401 No No

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CPFV VS CUTI -0.377 0.253 No No PRIVATE BOAT VS CUTI 0.024 0.944 No No YELLOWTAIL Pearson’s Index P-Value Significant Significant (R Score) (P < .05) (P < .10) CPFV VS ONI 0.669 0.024 Yes Yes PRIVATE BOAT VS ONI 0.630 0.038 Yes Yes

CPFV VS CUTI -0.536 0.089 No Yes PRIVATE BOAT VS CUTI -0.525 0.097 No Yes

5. DISCUSSION

5.1 Primary Target Data in Response to Climate Variability

Several fluctuations in target rank occurred over the time period of this study. While Rockfish and Sand Bass are often in the top three most targeted groups, their positions within the top three vary.

Yellowtail begin to appear in the top three when a strong El Niño system was present. For private boaters, Sand Bass drop completely out of the top three during El Niño events. The number of trips where fishers on private boats target Rockfish moves from first place to third once the stronger El Niño came through. Overall, these results match the conclusions of Zhang et al. (2012).

Data in this study as well as past studies suggest that fishers will adjust their targets according to what is available at the time. Fishers on private boats will often check weather conditions and patterns before deciding on where and for what to fish. Captains on CPFV boats will check weather before most trips because their economic livelihood depends on their abilities to locate and catch fish (Zhang et al.

2012).

Fishers not only respond to weather patterns; they alter their fishing behavior according to climate variability. Zhang and co-workers (2012) found that CPFV trips targeted different species between El Niño and La Niña events (Figure 5.1). They also found that fishers preferred warm water (El

Niño) conditions. The warmer water increased their chances of catching pelagic species such as

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Yellowfin Tuna (Thunns albacares), Dorado (Coryphaena hippurus), and Yellowtail (Zhang et al. 2012).

These fish are often found further north than usual during warming events.

Figure 5.1 – Recreational fishers (CPFV captains in southern California) primary target adjustments during El Niño and La Niña events (Zhang et al. 2012, 469). 5.2 Species Catch Data in Relation to Climate Variability

5.2.1 Ocean Whitefish

Although data for the time period of this study did not show any catch and climate correlations for Ocean Whitefish, other studies have had different results when looking at longer time periods. Jarvis et al. (2004) found a negative correlation between sea surface temperatures and Ocean Whitefish populations using PDO data. This suggests that while Ocean Whitefish may not be as sensitive to short term climate variability, they may be more susceptible to overall change. It is important to note that catch and population size do not always trend together. Chavez et al. (2017), determined there was not enough data to state whether Ocean Whitefish are impacted by short term climate variability.

There was an increase in CPFVs targeting Ocean Whitefish in 2016 and 2017, which correlates with a significant spike in catch data. These two years were transitional years for the CCS. The current

28 | Page was experiencing cooler SSTs after a large El Niño. Pelagic fish were not as abundant and CPFV captains may have switched to Ocean Whitefish for a guaranteed target in order to ensure their catch numbers remained high. Currently research is insufficient to determine whether Ocean Whitefish are impacted by climate variability. This fishery will need to be studied in more depth to determine if climate-based management would be best.

Although not statistically tested, an increase in Ocean Whitefish numbers after El Niño events has been observed by Chuck Valle, a Senior Environmental Scientist for California Department of Fish and Wildlife. Ocean Whitefish larvae have not been found in southern California which could suggest that they are following the warm water into California from Mexico. Valle is not sure whether the Ocean

Whitefish leave after the water cools or if they are unsuccessful reproducing in southern California waters (Chuck Valle, CDFW, personal communication). The spike in catch in 2016 and 2017 matches

Valle’s theory of them following the warm currents into southern California from Mexico. Hopefully the results of Chuck Valle’s study will shed some light on how the Ocean Whitefish fishery is impacted by climate variability.

5.2.2 Sanddabs

Sanddab catch was not correlated with climate data. When looking at a longer time period using

PDO, Jarvis et al. (2004) found a significant correlation between Sanddab catch and upwelling. This suggests that, while Sanddabs may not be sensitive to short term climate variability, they may be impacted by long-term climatic factors. There was a strong decline in Sanddab catch between 2015 and

2017. During 2015 and into 2016 there was a strong El Niño that brought warmer waters to southern

California. These warmer waters brought prized species such as Tuna and Yellowtail much further north.

It is possible that the decline in Sanddab catch could be attributed to fishers switching from targeting ground fish to these prized pelagic species. Jarvis et al (2004) suggested that increases in Sanddab catch

29 | Page could be correlated to decreases in Rockfish targeting due to changing regulations. Changes in Sanddab catch may be more related to target species switching than environmental factors.

5.2.3 Kelp Bass

Kelp Bass catch does not appear to correlate directly with ONI. Total catch on CPFV boats has a moderate negative relationship with CUTI (r=-0.544; p<0.10). The data suggests that when upwelling is lower, Kelp Bass catch is higher. Upwelling events are lower during warm water phases. Chavez et al.

(2017), suggested that Kelp Bass prefer warm water phases, which matches the inverse correlation with upwelling events in my data. Correlations may not have appeared in my data because there could be a delay in direct effects from SST variations, upwelling and El Niño events.

While Kelp Bass may be affected directly by changing environment, they also have habitat requirements that can be affected by a changing ocean. Kelp Bass are often found around Giant Kelp and in rocky reef areas (Jarvis et al. 2014). When there is more kelp, there are generally more Kelp Bass, but the density of Giant Kelp drops during warm water events, particularly after El Niño. Kelp Bass prefer warm periods for reproduction, but if it gets too warm, the kelp dies which has a negative impact on

Kelp Bass populations. (Chuck Valle, CDFW, personal communication). This could help explain why contrasting information is given on Kelp Bass preferring warm water or cool water phases. Time lags as well as how strong an El Niño event is both play a role in how Kelp Bass react to climate variability.

5.2.4 Barred Sand Bass

Barred Sand Bass catch on private boats has a moderate negative correlation with ONI (r=-

0.658; p<.05). The cooler the water, the higher the Sand Bass catch. Barred Sand Bass catch for private boaters has a moderate positive correlation with CUTI (r=0.604; p<.05). This means that when upwelling increased, total Barred Sand Bass catch increased. These correlations match up because, when SSTs are lower, such as in La Niña years, upwelling will increase. Zhang et al. (2012) along with Jarvis et al.

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(2004) found that Barred Sand Bass catch increases with increased upwelling. Combined, these studies demonstrate that climate variability likely plays a role in overall Barred Sand Bass catch.

Jarvis et al. (2014) found that warmer water temperatures were more “conducive to successful larval survival” for Barred Sand Bass. Chavez et al. (2017) found the same pattern. There are several explanations for why these data do not match the catch trend that I found. There is a delay between larval survival and when the Bass is large enough to be caught in fisheries. A study using time lags may show a clearer pattern. Target species switching may also play a role as Zhang et al. (2012) found that

Barred Sand Bass were targeted more during La Niña events than El Niño.

Barred Sand Bass populations started to crash in 2004 (Chuck Valle, CDFW, personal communication) but my study begins in 2007 so the results of this study are showing fluctuations after a population crash. Compared to the catch trend over a longer time period, the catch between 2007 and

2017 appears to be relatively stable, as the populations had already plummeted by 2007. In 2013,

Barred Sand Bass stopped forming large spawning aggregations in southern California that were targeted by fishers (Chuck Valle, CDFW, personal communication). Without these aggregations, Barred

Sand Bass became increasingly hard to catch, as shown in the catch trends (figure 4.2). Increased fishing pressure most likely stopped the Barred Sand Bass from forming aggregations. Barred Sand Bass, along with other Bass species are currently being studied in depth by CDFW in order to determine causes of the population decline.

5.2.5 Sand Bass genus

Changes in ocean conditions affect Bass populations in various ways. Larval survival, success of habitat-dependent recruitment and changes in spawning cues can all be affected by ocean conditions

(Jarvis et al. 2014). It takes a while for these changes to show up in recreational fisheries as there is a time lag between larval development and when the fish are large enough to be caught in the recreational sector. Jarvis et al. (2014) found that “trends in Barred Sand Bass and Kelp Bass fishery

31 | Page recruitment strength showed significant, positive correlations with trends in Paralabrax larval abundance and coastal SSTs.” It was suggested that Barred Sand Bass may be more sensitive to changing oceanic conditions than Kelp Bass because Kelp Bass range further north (Jarvis et al. 2014). The correlation results in this study match that suggestion. Barred Sand Bass are much more restricted in range, which matches the information given by Jarvis and co-workers (2014) (Chuck Valle, CDFW, personal communication).

Changes in Sand Bass catch could also be attributed to target switching. More fishers target Bass during La Niña events than El Niño events (Figure 4.1) (Zhang et al. 2010). This could possibly be due to fishers switching their target species to warm water pelagic species that show up during El Niño events.

5.2.6 California Halibut

Total California Halibut catch for CPFV boats has a moderate negative correlation to ONI (r=-

0.594; p<.10). California Halibut catch for private boats has a moderate negative correlation to ONI (r=-

0.620; p<.05). The lower the average SST, the higher the Halibut catch, and catch is higher during La

Niña events. Total catch for CPFV boats has a moderate positive correlation with CUTI (r=0.632; p<.05).

California Halibut catch for private boats has a strong positive correlation with CUTI (r=0.724; p<.05).

Correlation between upwelling and catch matches inverse correlation with ONI. Chavez et al. (2017) found that California Halibut prefer warm water phases in contradiction to what was found in this study.

There are a few possible explanations for this.

Chavez et al. (2017) found that recruitment and larval survival is higher for California

Halibut during warm water phases. This would not reflect in the fisheries until the fish are large enough to be caught by hook and line. Accounting for time lags in the correlation analysis may reflect this trend.

Another possible explanation for the apparent contradiction may be attributed to target switching.

Priority warm water species such as Yellowtail began showing up in 2014 and private boaters started

32 | Page switching their primary targets in order to take advantage of these warm water species. Decline of catch may be directly attributable to fishers no longer targeting Halibut.

5.2.7 Pacific Mackerel

Pacific Mackerel catch remains relatively stable over time, with a few exceptions. In 2014, catch was a little higher and in 2012 and 2013 catch was a little lower. Pacific Mackerel catch does not appear to be correlated with ONI, or CUTI (Table 4.11). This could be because Pacific Mackerel is often caught as bycatch and not a primary recreational target. Jarvis et al. (2004) found that, over longer time periods,

Pacific Mackerel catch correlated significantly with upwelling events, which suggests a preference for cool water phases. During ENSO events, landings for Pacific Mackerel remained relatively consistent, which is reflected in the data for this study (PFMC 2017). Chavez et al. (2017) found that Pacific

Mackerel preferred warm water phases. This warm water preference found by Chavez most likely refers to larval success, which is why the opposite pattern is found in the fisheries, as time lags need to be considered when figuring out climate preferences for Pacific Mackerel.

The differences in results in climate variability correlation studies for Pacific Mackerel suggest that Pacific Mackerel are not as sensitive to short-term climate variability but may be affected by longer- term climate variables. Conflicting climate data correlations for Pacific Mackerel suggest that more research needs to be done in order to determine exactly how climate variability impacts the Pacific

Mackerel fishery. The answer may be as simple as including time lags, but this will need to be studied in depth in order to include other possibilities.

5.2.8 California Scorpionfish

Total California Scorpionfish catch does not appear to be correlated with ONI or CUTI. In a status report conducted on California Scorpionfish in 2017, recruitment was looked at and potential climate correlations were found, but it was determined that more research is needed in the area (Monk et al.

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2017). They found that Scorpionfish appear to be adaptable and might expand north if the CCLME shifts to a warmer baseline. They ended up not using climate data in their stock assessments due to lack of available climate data pertaining to California Scorpionfish (Monk et al. 2017).

5.2.9 Rockfish

Total catch of Squarespot Rockfish on CPFV boats has a moderate positive correlation with ONI

(r=0.626; p<.05). Total catch of Squarespot Rockfish on private boats has a moderate positive correlation with ONI (r=0.545; p<.10). The warmer the average SSTs, the more Squarespot Rockfish are caught, suggesting that Squarespot Rockfish prefer warm water phases. Total catch of Squarespot Rockfish on

CPFV boats has a moderate negative correlation with CUTI (r=-0.550; p<.10). The lower the upwelling event, the more Squarespot’s are caught. The pattern between ONI and CUTI correlations makes sense because El Niño events bring in warmer water and weaken upwelling events. Vermilion Rockfish catch does not appear to correlate with ONI or CUTI. Currently there are no climate-related studies pertaining to Squarespot Rockfish or Vermilion Rockfish as individual species.

Zhang et al. (2010) determined that there was a large increase in boats targeting Rockfish in La

Niña years relative to El Niño years (Figure 4.1). Schroeder et al. (2018) found large amounts of juvenile

Rockfish during the 2013-2016 warming events. This is reflected in the Squarespot Rockfish catch data.

Chavez et al. (2017) suggest that most groundfish prefer cool water phases, which is in direct contrast to what was found in this study as well as the study conducted by Schroeder et al (2018). This suggests that

Squarespot Rockfish may not belong in the “most groundfish” category Chavez et al. (2017) used.

Using CPFV logbook data, a large spike in Rockfish fishing effort was evident in 2013, which is directly after new bass regulations were implemented (Bellquist et al. 2017). The data in this study reflects this spike when looking at total catch for Squarespot Rockfish (Figure 4.19). More research is needed to explain the data.

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5.2.10 Yellowtail

Yellowtail catch on CPFV boats has a moderate positive correlation with ONI (r=0.669; p<.05).

Total Yellowtail catch on private boats has a moderate positive correlation with ONI (r=0.630; p<.05).

Catch on CPFV boats has a moderate negative correlation with CUTI (r=-0.536; p<.10). Total Yellowtail catch on private boats has a moderate negative correlation with CUTI (r=-0.525; p<.10). Zhang et al.

(2010) found that there was a large increase in Yellowtail being targeted in El Niño events over La Niña events (Figure 3.1). Dotson and Charter (2003) found the same results with catch being much higher in

El Niño years. This data can be attributed to the fact that many Yellowtail found in California are Mexico residents that follow the warm water cycles into California during El Niño events. (Baxter 1960). The increase in Yellowtail numbers during these years lead to higher counts in recreational Yellowtail catch.

5.3 Explanation of Unexpected Results

Catch for several species in the study was not correlated with climate variability. However, other research suggests correlations may exist. When conducting climate correlations, Jarvis et al. (2004) found correlations when time lags were considered. This study did not account for time lags that may have influenced the climate correlation data. If time lags were considered, there may have been an increase in the number of climate correlations found.

Recreational catch data may be better understood when looking at various factors such as larval recruitment, productivity and fecundity and how they respond to climate variability. Impacts of climate variability can vary with multiple life stages, depending on the species and can have an impact on overall productivity (Link et al. 2015). Some species have reduced fecundity during warming or upwelling events while others may experience an increase in the same conditions (Link et al. 2015). Certain changes, such as fecundity generally do not reflect in recreational catch data unless time lags are considered.

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5.4 Study Extension

Based on the results, there are several changes that would inform subsequent research. Ocean

Whitefish, Sanddabs, Pacific Mackerel, California Scorpionfish and Vermilion Rockfish had no apparent climate correlations with catch data in these results, but other long terms studies such as Jarvis et al.

(2004), Monk et al. (2017) and Zhang et al. (2010) did. If larger data sets over several decades had been used, the results would probably have been different. Several studies found climate correlations with catch using time lags. If time lags had been used, the data may have shown different correlation results.

Looking at catch numbers alone does not give the whole picture. Climate variability often impacts ecosystems by changing variables such as kelp density. These changes can then influence fish populations. Climate variability impacts on juvenile recruitment and fecundity should also be considered. These impacts often take time to show up in the fisheries (Jarvis et al. 2004).

There are also factors other than climate that influence changes in annual catch. Overall fishing pressure, as well as anglers switching target species for non-climate reasons should also be considered.

Target data should be looked at in depth to help determine why fisheries are fluctuating like they do.

There are also other events that have caused catch variation in the past, such as the arrival of Humboldt

Squid (Dosidicus gigas), algal blooms, regulation changes and pollution such as oil and sewage spills

(Jarvis et al. 2004). There are many factors that need to be addressed when looking at changes in recreational fishing catch and all should be considered.

5.5 Study Implications

Barred Sand Bass, Kelp Bass, California Halibut and Yellowtail catch were found to be correlated to measures of climate variability. This finding matches findings from Jarvis et al. (2004), Zhang et al.

(2012), and Chavez et al. (2017). Although this study did not find climate correlations with Ocean

Whitefish, Sanddabs or Pacific Mackerel, other studies have found correlations with indices of climate

36 | Page variability when looking at longer time periods and using covariates such as PDO instead of ENSO. This suggests that these species are affected by changes in climate over longer time periods that may not be apparent at shorter time intervals. Management of these species using climate variability could possibly be an option by decreasing the fishing pressure during times when difficult climate conditions are present. One way to do this would be to temporarily decrease bag limits.

Squarespot Rockfish and Vermilion Rockfish showed different catch dynamics in relation to climate variability. Squarespot Rockfish catch appeared to be correlated while Vermilion Rockfish catch was not. Incorporating climate variability data into managing these fisheries could be challenging.

Rockfish are targeted as a group and generally, the average fisher cannot differentiate between Rockfish species other than “Reds” or “Browns”. Understanding how various groups of Rockfish, such as shelf species or deep-water species react to climate variability, may help in future Rockfish management decisions.

California Scorpionfish catch did not correlate with climate variability metrics used in this study.

A stock assessment conducted by Monk et al. (2017) suggested otherwise when looking at recruitment, but results were not conclusive. There is currently a lack of climate related data on California

Scorpionfish. Whether this species is sensitive to climate variability remains to be seen. More studies need to be done in order to determine if climate variability should play a role when it comes to managing this species. It can be difficult to manage a fishery when we do not understand what drives fluctuations in catch.

6. CONCLUSION

6.1 Challenges of Managing Recreational Fisheries

Fisheries management seeks to balance fisheries removals with the need to maintain an appropriate level of reproductive potential within a population (Schroeder et al. 2018). Recreational

37 | Page fisheries dynamics make it difficult to track or predict catch (Horning et al. 2014) which can make management challenging. Factors such as climate variability, overfishing, disease, pollution, and habitat degradation play a role in catch variability (Schroeder et al. 2018). Understanding and predicting what drives catch dynamics for each fishery would be beneficial for fisheries managers as well as fishers.

6.2 Fisheries Management Using Climate Variability within the CCLME

Climate variability makes it challenging to manage a fishery because of the effects on fish populations as well as their associated fisheries (Zhang et al. 2012). Warming of the CCLME can increase stratification which reduces availability of nutrients (Checkley & Barth 2009). Pelagic species and groundfish will have different responses to climate variability because conditions at the surface are often independent of what is occurring at depth (Schroeder et al. 2018). “In order to improve fisheries management in a changing environment, fisheries managers not only require the knowledge of the exogenous shocks to the ecosystem such as climate change but also need to understand the endogenous changes such as fishermen’s responses to climate variability.” (Zhang et al. 2012, 466). The state of the ecosystem and consequently fisheries during the 2013-2016 warming trends in the CCLME may serve as a good indicator of what can be expected when faced with future climate variability and overall climate change (Schroeder et al. 2018).

“Of the numerous fishery species in the region, climate variables have only been directly incorporated into scientific advice and management in a few cases” (Hare et al. 2016, 3). The Pacific

Sardine fishery is one case for which climate indices have been incorporated into the management regime (Zhang et al. 2012). Stock assessors of Sardine fisheries include a climate indicator into their harvest control rules. Knowing how Sardines respond to cool and warm phases helps fisheries managers determine the level of harvest that will be sustainable (Chavez et al. 2017).

Overall, climate change is expected to alter variability in the CCLME which would make conditions more extreme. Periods of fluctuations within the CCLME may increase or decrease the length

38 | Page of time where the CCLME is experiencing its warm and cool phases (Chavez et al. 2017). Changing the dynamics of these natural cycles can lead to hypoxia, stratification, increased storm activity, extreme warming events, increased or decreased precipitation and changes to overall seasons. These changes could lead to a decline in kelp, such as occurred in 2015-2016, which will impact species that are dependent on the kelp for food, habitat and interactions with other species both directly and indirectly

(Chavez et al. 2017).

A better understanding of how climate variability impacts recreational fisheries can help ensure that southern California’s recreational fisheries remain sustainable in extreme climate conditions (Jarvis et al. 2004). While some long-lived species are more resilient to short term climate variability, some, such as Rockfish are affected in the long run. Species are not isolated from each other, which means that a decline in one species could alter the food web, which can have an impact on other species (Chavez et al. 2017).

6.3 Future of Fisheries Management

Many indicators are needed in order to successfully manage a fishery (Powers & Mark 2010).

“The objective is not to find the best indicator, but rather a relevant suite of indicators with known properties; developing methodologies for selecting indicators forms an integral part of the process.

Guidelines for how to test indicators and develop frameworks for their application are essential” (Cury &

Christensen 2005, 308). Having a network that can share fisheries information may help fisheries managers figure out which indicators would be best.

Santora et al. (2017) suggested establishing a Marine Biodiversity Observation Network (MBON).

The network would help quantify biodiversity patterns which can help give a deeper understanding of natural variability of biodiversity. The network would identify threats to biodiversity and serve as an early warning system for climate change and human pressure on fish populations (Santora et al. 2017). It is hoped that this network will help fisheries managers gain an improved understanding of commercially

39 | Page and ecologically important species (Santora et al. 2017). With an information sharing network such as

MBON, management of fisheries may become a little less complicated.

Using an ecosystem-based approach to fisheries management is a widely accepted concept in various management agencies. Ecosystem-based fisheries management (EBFM) is considered a more effective approach when managing fisheries according to some scientists (Zhou et al. 2010). The order of fisheries management is reversed: Management is first looked at from an ecosystem level instead of the species level. Using EBFM might ensure that marine ecosystems remain healthy which in turn supports fisheries (Pikitch et al. 2004) by keeping fish populations healthy. Ecosystem based management has been successful in bringing together multiple stakeholders by including input from all parties (Fulton et al. 2014). Climate variability considerations and EBFM are currently being used together in order to manage some fisheries.

Management approaches should be updated in order to ensure that they are adaptable and responsive to overall change. Overall change does not necessarily mean everything will be negative.

Fisheries management needs to be able to prepare for emerging fisheries as well as potential abundance increases while at the same time preparing for potential population crashes (Chavez et al. 2017).

Improving projections of fisheries reactions to climate variability could help fisheries managers react more quickly, which would help them plan for potential closures. On the other hand, the ability to manage fisheries adaptively will allow them to capitalize on new fishing opportunities when favorable conditions occur, which could help alleviate extra costs from poor planning and research (Chavez et al.

2017).

Research that includes possible outcomes of fisheries management actions under different ecosystem scenarios can help managers determine which approach will best enable them to achieve their goals using ecosystem-based management (Chavez et al. 2017). It is hoped that by using available climate data and EBFM information, negative fisheries impacts will be relatively few in the future.

40 | Page

Fisheries management is an adaptive science and new information is constantly being acquired. It is important that more studies are done on climate variability impacts on recreational fisheries. Future studies need to include impacts to the ecosystem as a whole and not just impacts to individual species.

Successful fisheries management relies on the best available science and needs to be consistently adjusted when new information becomes available. This will ensure that our fisheries remain healthy for future generations to enjoy.

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46 | Page

Appendix A Ocean Whitefish (Caulolatilus princeps)

Figure A1 – Photo of Ocean Whitefish. Picture taken in 2007 while scuba diving Catalina Island, CA.

Ocean Whitefish (Caulolatilus princeps) are in the tilefish family (Branchiostegidae) and are the only representative from that family found in California (Bellquiest et al. 2008). Occasionally a Pacific Golden-

Eyed Tilefish (Caulolatilus affinis) will show up, but it is rare (Wertz & Kato 2002). Ocean Whitefish can reach a maximum length of 42 inches and have an average lifespan of thirteen years (Wertz & Kato

2002). They do not mature until they are 19 inches long (Chuck Valle, CDFW, personal communication).

Ocean Whitefish distributions and population sizes seem to be influenced by ocean currents.

They will follow the warm water into California from Mexico after El Niño. It is unclear if they travel back to Mexico as they age or if they are unsuccessful with breeding in California as no larvae or spawning events have been observed (Chuck Valle, CDFW, personal communication). This suggests they may not be residents to California.

Ocean Whitefish are managed within the RCG (Rockfish, Cabezon, and Greenlings) complex in

California because they are often caught when fishers are targeting rockfish (Bellquist et al. 2008). The

RCG complex is closed to fishing seasonally in January and February. Depth restrictions apply when

47 | Page fishing for Ocean Whitefish (CDFWa 2019). Changes to depth restrictions occur often and have included mid-season changes in the past. Recreational fishers can keep ten Ocean Whitefish per person. While there is no size limit, there is a fillet length limit of six and half inches with the entire skin intact (CDFWa

2019). Having a size limit may seem the logical choice, but trying to figure out a size limit approach due to their large size of maturity may be an issue when managing this species (Chuck Valle, CDFW, personal communication).

Data gathered from multiple sources about Ocean Whitefish suggest that it may be more efficient to manage Ocean Whitefish as a separate species apart from the RCG complex (Bellquist et al.

2008). Their daily varied habitat preference sets them apart from other nearshore groundfish managed within the same complex (Bellquist et al. 2008). Chuck Valle does not think this will happen because the ground fish regulations are one of the few things currently protecting Ocean Whitefish (Chuck Valle,

CDFW, personal communication).

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Appendix B Sanddabs (Citharichthys spp.)

Figure B1 – Photo of Pacific Sanddab. Taken in 2011 while sampling on board the CPFV New Del Mar in Marina Del Rey, CA. All Sanddabs (Citharichthys spp.) were grouped into Sanddab genus category due to an average fishers’s inability to distinguish individual species although the majority of Sanddabs caught in southern California are Pacific Sanddabs (Citharichthys sordidus), with a few Longfin Sanddabs (Citharichthys xanthostigma) mixed in (personal observation). The third species of Sanddab found in southern California, which is almost never caught due to its small size is Speckled Sanddab (Citharichthys stigmaeus).

Sanddabs are an abundant species in southern California which are reflected in fisheries data

(He et al. 2013). Sanddabs are taken in large numbers by recreational fishers. They are mostly taken by private boaters and CPFVs (He et al. 2013). During the seasonal groundfish closure in January and

February, Sanddabs become a major targeted species in the CPFV industry (Love 2011). Sanddabs are not considered vulnerable to overfishing and therefore have relatively few recreational regulations (He et al. 2013). Sanddabs are managed along with other flatfish in the ground fish Fishery Management

Plan (He et al. 2013). There is no depth, size, or catch limit for Sanddabs (CDFWa 2019).

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CPFV boats will sometimes run Sanddab fishing trips in which fishers will catch hundreds of

Sanddabs per person. Sanddabs are easy to locate and catch so when they are targeted, catch can number in the thousands for a CPFV boat (personal observation). In general, private boaters do not target Sanddabs. When Sanddabs are caught by private boaters, they are either released or kept in low numbers. Sanddabs caught by private boaters are often the result of bycatch instead of intentional targeting (personal observation). The discard rate is high for Sanddabs due to their small size (He et al.

2013).

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Appendix C Sand Bass (Paralabrax spp.)

Figure C1 – Photo of Kelp Bass. Taken in 2007 while scuba diving Catalina Island, CA

Figure C2 – Photo of Barred Sand Bass. Taken in 2013 in Huntington Beach, CA

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There are three species of Sand Bass that are commonly caught in southern California: Spotted Sand

Bass (Paralabrax maculatofasciatus), Kelp Bass (Paralabrax clathratus), and Barred Sand Bass

(Paralabrax nebulifer). Kelp Bass and Barred Sand Bass are the two most commonly caught Bass species in southern California’s recreational fisheries. Fishers often do not distinguish between Sand Bass species when fishing for Bass, so they often target them as a group under Sand Bass genus.

Inexperienced fishers sometimes cannot tell the difference between species so when they report released bass catch to CRFS samplers, it is recorded as Sand Bass genus. Spotted Sand Bass, otherwise known as Bay Bass, is generally found in bays and the least targeted of the three species. Most recreational fishers will release Spotted Sand Bass when they are caught (personal observation).

Kelp Bass (Paralabrax clathratus) are often referred to as Calico Bass (Love 2011). They reach a maximum size of twenty-eight inches. They are most commonly caught south of Point Conception to central Baja California (CDFWb 2019). Historically it is a popular species with recreational fishers in southern California. It is caught from shore as well as from boats to depths of 150 feet (CDFWb 2019).

They are most commonly targeted using live anchovies near the surface in close association with kelp beds (CDFWb 2019).

Barred Sand (Paralabrax nebulifer) are often referred to as Sand Bass by recreational fishers.

They reach a maximum size of twenty-six inches (Love 2011). They range from Magdalena Bay in Baja

California north to Santa Cruz, California. They are found in shallow water down to 600 feet but are most commonly caught between 60 and 90 feet of water (CDFWb 2019). Most catch of Barred Sand Bass occurs between May and October in three main California locations: Huntington to Newport Beach,

Dana Point to Oceanside, and San Diego at the Silver Strand (CDFWb 2019).

New catch regulations were implemented for Sand Bass genus in 2013. The limit went from ten fish in aggregate to five (Jarvis et al. 2014). After the new regulations were implemented, majority of

CPFV captains surveyed by Bellquist et al. (2017) shifted more than 50% of their trips where they were

52 | Page normally targeting Bass to Rockfish trips instead. Overall catch has been decreasing (Jarvis et al. 2014), but the rate of decline is different between the two species (Bellquist et al. 2017).

Barred Sand Bass tend to be more sensitive to fishing pressure than Kelp Bass because of their propensity for forming spawning aggregations. All spawning aggregation spots for Barred Sand Bass in southern California are well known to fishers. The fishing pressure on these aggregations was immense until the aggregations stopped in 2013. Kelp Bass form smaller more dispersed aggregations which has helped save them from increased fishing pressure (Chuck Valle, CDFW, personal communication).

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Appendix D California Halibut (Paralichthys californicus)

Figure D1 – Photo of California Halibut. Taken in 2006 while scuba diving Catalina Island, CA.

California Halibut (Paralichthys californicus) reach a maximum length of five feet (Love 2011). They are found in highest numbers between central California and Baja California and as deep as 600 feet but are most commonly caught in 10 to 90 feet of water (CDFWb 2019). In southern California, the best

California Halibut fishing is in the springtime (CDFWb 2019). Most recreational catch of California

Halibut is done by boat; however, it remains a popular target for shore modes (Love 2011).

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Appendix E Pacific Mackerel (Scomber japonicas)

The official name of Pacific Mackerel (Scomber japonicas) is Pacific Chub Mackerel, but the name chub is rarely used (Love 2011). Their maximum length is twenty-five inches. They are a common schooling fish that is highly migratory (Love 2011). They are harvested in three different fisheries: California commercial fishery, southern California’s recreational fisheries, and Mexico’s commercial fisheries.

Pacific Mackerel often rank in the most important species caught in southern California, but this is mostly due to their abundance rather than their desirability (Konno et al. 2001).

Pacific Mackerel are managed as a CPS (Commercial Pelagic Species) fishery complex in combination with Pacific Sardine (Sardinops sagax), Northern Anchovy (Engraulis mordax), Jack

Mackerel (Trachurus symmetricus), market squid (Doryteuthis opalescens), and krill (Euphausiacea)

(PFMC 2018). In the recreational sector, Pacific Mackerel have no size, depth or catch limit (CDFWa

2019). There is an occasional ban for human consumption due to the presence of domoic acid (Love

2011).

Pacific Mackerel that are caught by fishers are often used for bait for targeting lobster, sharks, rays, or other large fish species (Love 2011). Private boaters and CPFV fleets tend not to report Pacific

Mackerel catch as it is often overlooked (PFMC 2017). This issue can cause large stock assessment errors when it comes to managing Pacific Mackerel recreational fisheries.

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Appendix F California Scorpionfish (Scorpaena guttata)

Figure F1 – Photo of California Scorpionfish. Taken in 2009 while scuba diving Laguna Beach, CA.

California Scorpionfish is often referred to as sculpin by recreational fishers (Love 2011). They can reach sizes up to 18.5 inches (Butler et al. 2012). California Scorpionfish range from central California to Baja

California (Butler et al. 2012). They have venomous spines which make handling this fish tricky (Love

2011). They have a very painful sting that can leave lingering sensitivity for months after initial puncture

(personal experience). Some recreational fishers will release Scorpionfish instead of keeping it in order to avoid dealing with painful stings (personal observation).

California Scorpionfish were a semi-important commercial species in southern California around

Catalina Island in the 19th century (Love 2011). The commercial fishery continued through the 20th century with fishers targeting spawning aggregations. Overall, commercial catch has been small (Monk et al. 2017). Scorpionfish were often taken as bycatch when targeting rockfish (Love 2011). As rockfish populations declined and recreational regulations became stricter, California Scorpionfish catch has increased (Love 2011). Beginning in the 1960s, recreational vessels ramped up catch and have dominated since (Monk et al. 2017).

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Largest source of California Scorpionfish catch comes from boat modes, but some are caught from shore (Love 2011). Scorpionfish have been the largest component of CPFV catch since the early

2000s (Monk et al. 2017). Regulations for California Scorpionfish have varied over the years which could have an influence on total catch data. Scorpionfish are managed within the RCG complex with seasonal closure variations (Table F1). Recreational fishers can keep five fish total per person and the size limit is ten inches (CDFWa 2019).

Table F1 – Recreational regulations listed by month for California Scorpionfish in the southern management area. Open indicates no depth restrictions. Black cells indicate closed Scorpionfish fishery. Numbers indicated depth restrictions listed in fathoms. *On November 15, 2014, fishery was closed. (Monk et al. 2017)

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Appendix G Rockfish (Sebastes spp.)

Figure G1 – Photo of Squarespot Rockfish. Picture taken in 2011 while sampling onboard a CPFV in Long Beach, CA

Figure G2 – Photo of Vermilion Rockfish. Picture taken in 2011 while sampling onboard a CPFV in Long Beach, CA. Rockfish are often referred to as “rock cod” by fishers and are members of the Sebastes genus. There are 102 species of Rockfish (Love et al. 2002). Most rockfish species are found in the northern Pacific and gulf of California. In southern California, Squarespot Rockfish can be found on the shallow shelf and

Vermilion Rockfish can be found from nearshore to deep shelf (Love et al. 2002).

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Squarespot Rockfish (Sebastes hopkinsi) are never specifically targeted as they are a small rockfish species. Their maximum size is eleven inches (Love 2011). They range from southern Oregon to

Baja California (Butler et al. 2012). They have been known to form aggregations numbering in the thousands (Love et al. 2002). Squarespot Rockfish are recreationally caught in large numbers mostly because local reefs have been fished out of larger species. They are possibly the “most abundant fish on medium-depth southern California reefs” (Love 2011). They are considered the most commonly caught

Rockfish in southern California’s recreational fisheries (Love et al. 2002).

Vermilion Rockfish (Sebastes miniatus) are often referred to as “Red Snapper” by fishers (Love

2011). They can reach sizes up to 30 inches (Love 2011). Vermilion Rockfish range from Alaska to Baja

California (Butler et al. 2012). In southern California, most recreational catch of Vermilion is composed of juveniles (Love et al. 2002). Genetics indicate Vermilion Rockfish are two separate species (MacCall

2005) but are currently grouped as one in the recFIN database. Juveniles of both Vermilion species are found at similar depths, but adults are separated by depth. One species lives around 328 feet of water

(Vermilion Rockfish) or less while the other (Sunset Rockfish) lives in deeper water (Butler et al. 2012).

Because depth ranges for both these species have not been officially set, they are continued to be treated as one species (Butler et al. 2012).

Rockfish genus is among the highest targeted group of fish every year in the recreational sector, making the number one spot for CPFV trips every year in the sample frame (Tables 4.1, 4.2). In general

Rockfish are targeted as a genus. Generally, fishers prefer the brighter colored rockfish species (reds) as opposed to the drabber (browns) but taste wise, they are about the same (Love 2011).

Rockfish are managed under the southern California RCG complex (CDFWa 2019). They have a seasonal closure in January and February. Rockfish are open year-round to shore based fishers. Fishers may keep ten Rockfish total in any combination. There is no size limit for Rockfish (CDFWa 2019). They

59 | Page are considered a challenging group to manage because they are slow growing, mature at a late age, are long lived and have large fluctuations in their recruitment characteristics. (Schroeder et al. 2018).

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Appendix H Yellowtail (Seriola quinqueradiata)

Yellowtail are a schooling fish and can often be found with Pacific Barracuda (Sphryaena argentea) and

Pacific Bonito (Sarda chiliensis) (Love 2011). They can reach sizes up to ninety inches and weighing 80 pounds (Crooke 2001). In southern California most landed Yellowtail weigh between four and twelve pounds. Offshore fishing generally yields Yellowtail between twelve and eighteen pounds (Crooke 2001).

Most Yellowtail will migrate out of southern California seasonally, but some of the larger ones will remain year-round (Love 2011).

In the late 19th century, there was a relatively small commercial fishery in southern California for

Yellowtail (Love 2011). Yellowtail are considered a “premier” sport fish in southern California for recreational fishers (Love 2011). They are an “exotic” that causes a lot excitement with recreational fishers when they show up in large numbers (Love 2011). They are most commonly caught in a few locations: Channel Islands, Catalina Island, San Clemente Island, La Jolla, Santa Monica Bay, Dana Point and Oceanside. Recreational fishers can keep ten Yellowtail with a minimum size limit of twenty-four inches. Five of the ten kept fish can be less than twenty-four inches (CDFWa 2019).

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