The North Carolina Charter Boat Fishery Changing ...

Fisheries Vol. 40 • No. 5 • May 2015

Top 10 Policy Opportunities State of the Great Lakes Charter Industry Survey of the North Carolina Charter Boat Fishery

SEE INSERT

Top of the line electrofishing products and unparalleled customer service

Sales Manager TAMMY LUCAS shows off her impressive catch. She recently went in the field to increase her boat electrofishing and safe fish handling knowledge. It is part of our commitment to you: our partners in fish conservation.

[email protected] | (360) 573-0202 | Vancouver, WA USA | www.smith-root.com

Fisheries Vol. 40 • No. 5 • May 2015 COLUMNS PRESIDENT'S COMMENTARY

191 Highlighting the 2014 AFS Award of Excellence Recipient—Kenneth A. Rose Donna L. Parrish POLICY

192 Top 10 Policy Issues for AFS Thomas E. Bigford

198

Liz Brooks at the AFS briefing on Capitol Hill. Photo credit: AFS.

200

A nice catch of Great Lakes salmonids from Lake Michigan. Photo credit: Michigan Sea Grant.

240

W.B. (“Bev”) Scott photographed in 2013 during the making of Recollections. Photo credit: Vanessa Minke-Martin.

JOURNAL SUMMARIES 194 AFS Journals Offer Insights into Conservation of Apex Predators • Why You Need Granders in a Blue Marlin Fishery • Thinking about Muskellunge at a Lakescape Scale Jeff Schaeffer 195 Whirling Disease Is Fortunately Not a Permanent Condition Jeff Schaeffer 195 A Novel and Efficient Way to Assess Net Pen Impacts Jeff Schaeffer 195 Sadly, Lionfish Are More Widespread than We Thought Jeff Schaeffer STUDENT ANGLE 196 How to Navigate Fisheries Education and Employment Andrew K. Carlson, Karen M. Dunmall, Ross E. Boucek, Nicholas W. Cole, Janice A. Kerns, Rebecca M. Krogman, M. Clint Lloyd, Vivian M. Nguyen, Tracy R. Wendt, Shannon L. White, and Kyle L. Wilson AFS NEWS 198 AFS Hosts Capitol Hill Briefings on Marine Fisheries Management Thomas E. Bigford

Fisheries | www.fisheries.org

189

Fisheries American Fisheries Society • www.fisheries.org EDITORIAL / SUBSCRIPTION / CIRCULATION OFFICES 5410 Grosvenor Lane, Suite 110•Bethesda, MD 20814-2199 (301) 897-8616 • fax (301) 897-8096 • [email protected] The American Fisheries Society (AFS), founded in 1870, is the oldest and largest professional society representing fisheries scientists. The AFS promotes scientific research and enlightened management of aquatic resources for optimum use and enjoyment by the public. It also encourages comprehensive education of fisheries scientists and continuing on-the-job training.

AFS OFFICERS

EDITORS

PRESIDENT Donna L. Parrish

CHIEF SCIENCE EDITORS Jeff Schaeffer Olaf P. Jensen

PRESIDENT-ELECT Ron Essig FIRST VICE PRESIDENT Joe Margraf SECOND VICE PRESIDENT Steve L. McMullin PAST PRESIDENT Bob Hughes EXECUTIVE DIRECTOR Doug Austen

FISHERIES STAFF SENIOR EDITOR Doug Austen DIRECTOR OF PUBLICATIONS Aaron Lerner MANAGING EDITOR Sarah Fox CONTRIBUTING EDITORS Beth Beard Sarah Harrison CONTRIBUTING WRITER Natalie Sopinka

SCIENCE EDITORS Kristen Anstead Marilyn “Guppy” Blair Jim Bowker Mason Bryant Steven R. Chipps Ken Currens Andy Danylchuk Michael R. Donaldson Andrew H. Fayram Stephen Fried Larry M. Gigliotti Madeleine Hall-Arbor Alf Haukenes Jeffrey E. Hill Deirdre M. Kimball Jeff Koch Jim Long Daniel McGarvey Jeremy Pritt Roar Sandodden Jesse Trushenski Usha Varanasi Jeffrey Williams

FEATURES 200 The Great Lakes Charter Fishing Industry: 2002 to 2011 Frank Lichtkoppler, Daniel M. O’Keefe, Joseph Lucente, and Tory Gabriel 214 Factors Influencing Charter Fishing Effort Trends in Lake Huron Daniel M. O’Keefe, Donna L. Wesander, and Chi-Ok Oh 222 The North Carolina Charter Boat Fishery Changing with the Times: A Comparative Analysis of the Catch Composition (1978 and 2007–2008) Andrea Dell’Apa, Evan Knight, Anthony S. Overton, Craig E. Landry, Christopher F. Dumas, John C. Whitehead, and James H. Herstine 234 AFS ANNUAL MEETING 2015 Continuing Education Program 236 AFS BOOTH REGISTRATION FORM JOURNAL HIGHLIGHTS 237 Transactions of the American Fisheries Society, Volume 144, Number 2, March 2015 237 CORRECTION 238 CALENDAR BACK PAGE 240 Fishy Tales from Science Communicators in the Pacific Northwest Natalie Sopinka

BOOK REVIEW EDITOR Francis Juanes ABSTRACT TRANSLATION Pablo del Monte-Luna ARCHIVE EDITOR Mohammed Hossain

DUES AND FEES FOR 2015 ARE: $80 in North America ($95 elsewhere) for regular members, $20 in North America ($30 elsewhere) for student members, and $40 ($50 elsewhere) for retired members. Fees include $19 for Fisheries subscription. Nonmember and library subscription rates are $191.

COVER

A happy Lake Erie Smallmouth Bass angler. Photo credit: Ohio Sea Grant.

Fisheries (ISSN 0363-2415) is published monthly by the American

isheries Society; 5410 Grosvenor Lane, Suite 110; Bethesda, MD 20814-2199 F © copyright 2015. Periodicals postage paid at Bethesda, Maryland, and at an additional mailing office. A copy of Fisheries Guide for Authors is available from the editor or the AFS website, www.fisheries.org. If requesting from the managing editor, please enclose a stamped, self-addressed envelope with your request. Republication or systematic or multiple reproduction of material in this publication is permitted only under consent or license from the American Fisheries Society. Postmaster: Send address changes to Fisheries, American Fisheries Society; 5410 Grosvenor Lane, Suite 110; Bethesda, MD 20814-2199. Fisheries is printed on 10% post-consumer recycled paper with soy-based printing inks.

190

Fisheries | Vol. 40 • No. 5 • May 2015

COLUMN

PRESIDENT'S COMMENTARY

Highlighting the 2014 AFS Award of Excellence Recipient—Kenneth A. Rose

AFS President Donna L. Parrish [email protected]

Donna L. Parrish, AFS President This month’s column is about an extraordinary American Fisheries Society (AFS) member—Kenneth A. Rose. Last year at the Annual Meeting in Québec, Rose received the AFS Award of Excellence, which is our highest award. Rose is the associate dean of research at the Louisiana State University (LSU) School of the Coast and Environment and a professor in the Department of Oceanography and Coastal Sciences. He received a bachelor’s degree in biology and mathematics from the University at Albany-SUNY in New York and his master’s and doctorate degrees in fisheries from the University of Washington. He worked at the Oak Ridge National Laboratory before joining LSU in 1998. He has published more than 150 papers and served on more than 30 national and international advisory committees and editorial boards. Below are questions and (edited) answers from an interview with Rose conducted by Tara Kistler, LSU Media Relations (November 2014): www.sce.lsu.edu/associate-dean-kenneth-rosereceives-american-fisheries-society-award-excellence. How did you become involved in the field of mathematical and computer modeling of aquatic populations, communities, food webs, and ecosystems? My undergraduate training at the University at Albany- SUNY was in biology and mathematics, and I grew up near water and was interested in aquatic ecology. As sometimes happens, three somewhat unplanned, or random, events occurred that led me to simulation modeling of aquatic food web and fisheries. While an undergraduate student, I was invited to give a seminar whose theme that year happened to be on combining mathematical methods and biology. Remember, this was a long time ago in the 1970s, when this was a new idea. I went to the library and found an example of a population model from the tuna fishery and gave that as my seminar. To this day, it remains a mystery why they asked an undergraduate to give what I know is a faculty seminar. The second event occurred when I was applying for graduate school and Gordon Swartzman at the University of Washington happened to see my letter, and he offered me a research assistantship. Later, I found out how strong the fisheries and oceanography group at the University of Washington was in quantitative modeling. Finally, before joining LSU, I spent 12 years as a research scientist at Oak Ridge National Laboratory and worked with some of the top ecological modelers in the world and collaborated with them on a 10-year project with the simple goal of developing better fish population and food web models. The opportunity of having more than a decade of

generous funding allowed me to fully explore the topic and even revisit near the end of the project some of my earlier not-so-successful attempts. Now, development and application of quantitative methods is very much in vogue and demand. What is the goal of your research? The goal of my research is to use mathematical and computer simulation modeling to predict the responses of key upper trophic level—often fish—populations and food webs to various factors, including harvest strategies, contaminant exposure, habitat loss, and restoration and climate change. You recently received the AFS Award of Excellence, the Society’s highest award for scientific achievement. What does that mean to you? I was both honored and humbled. The Society was started in 1870 with its mission being “to improve the conservation and sustainability of fishery resources and aquatic ecosystems by advancing fisheries and aquatic science and promoting the development of fisheries professionals.” This organization has been around for a long time and is the premier fisheries organization in the United States. This particular award has been awarded annually since 1969, and when I looked at the names of the past recipients, I was humbled. The list included the really big names in fisheries—the people whose papers and books I studied—names like Bill Ricker, Ray Beverton, David Cushing, Jim Kitchell, Carl Walters, Ray Hilborn, and Daniel Pauly. An expression that seems appropriate is “standing on the shoulders of giants.” Thus, receiving this award from my peers that viewed people on a national level was very meaningful for me. Was there a specific project or research focus submitted to AFS for the award? This award is more for lifetime achievement rather than a specific project. Most of my work has been on modeling, especially a method that simulates the population and food web by representing each individual. This method had only been used rarely and little noticed in fish ecology and fisheries, and I had the pleasure of working with a team at Oak Ridge National Laboratory, and then continuing the work at LSU, who initiated a swell of using individual-based modeling in fisheries and ecology in general. Now, the technique is widely used. A second major aspect of my research is its collaborative and multidisciplinary nature. I was recognized for working with many people. An example of this is that I have written scientific Continued on page 239


191

COLUMN POLICY

Top 10 Policy Issues for AFS Thomas E. Bigford, AFS Policy Director

In closing my last column, I promised to share the top 10 issues facing fisheries, an inclusive term defined here as the fish, the people who fish, and the recreational and commercial industries. This is my list, based largely on deep immersion in science, management, and policy issues during my 18 months on the AFS staff, supplemented with another 35 plus years in the fish world. Rather than attempting to mimic David Letterman’s well-oiled routine, I made a conscious effort to identify issues well within our Society’s reach and also to be optimistic. These are the top opportunities, not the worst tragedies. So, here goes, in ascending order to what I view as our top policy priorities. 10. Lost structure – I worry about coral reefs bleaching, oyster reefs dying, worm rock eroding, freshwater mussels declining, and other physical habitats losing their battle for permanence. We can build our own replacements, but I foresee the day when we better recognize the ecosystem values of structure

192


AFS Policy Director Thomas E. Bigford [email protected]

and work to protect it before we are forced into more expensive restoration. 9. Invasive species – Non-native species that take hold at the expense of indigenous species are definitely a concern. Control or eradication is feasible if we act decisively. This huge issue would rank higher if it weren’t so pervasive. Still, we can do better at prevention, as with ballast water controls. That’s as optimistic as I can be about a problem that will be complicated as climate shifts and species distributions adjust. 8. Protected areas – Some feel the jury is still deliberating, but I’m convinced protected areas can be a valuable tool for managing fish stocks and fishing behavior. Marking some areas “off limits” can serve multiple purposes. Imagine an area closed to fishing yet suitable for renewable energy that also might include a navigation buoy and host archeological resources. I sense these win-win-win-win situations abound, if we cooperate and collaborate.

Continued on page 239

JOURNAL SUMMARIES Jeff Schaeffer AFS Co-Chief Science Editor, E-mail: [email protected]

AFS Journals Offer Insights into Conservation of Apex Predators Why You Need Granders in a Blue Marlin Fishery

The capture of a marlin greater than 500 kg represents a major life achievement for billfish anglers, and fishers refer to marlin of that size using colloquial descriptors such as “Grander” or “Big Julie” depending on location and species. However, their presence in a fishery is valuable, not only for the excitement and interest they create, but because how often fishers encounter granders can tell resource managers about the status of the fishery. C. Phillip Goodyear modeled hypothetical Atlantic Blue Marlin Makaira nigricans populations under varying rates of fishing mortality and found that sample sizes required to detect large fish increased disproportionally with increased fishing. The number of observations required to detect a 350 cm individual increased by 43% when the population was depressed by only 25%, and the value rose 50-fold when the population was reduced below 10%. In contrast, mean lengths decreased by only 2 to 14%, and mean weights decreased by 5 to 45%. This suggests that frequency of trophy catches (individuals greater than a species-specific threshold) may be a good indicator of stock health and can be used as an early warning of overfishing or even a clear end point denoting stock recovery. That metric, defined by Goodyear as NZ50, seemed far more useful than traditional indicators, such as mean length or weight. And while his study focused on Blue Marlin, the idea may be transferable to other species. We urge readers to examine this article for possible applications in other fisheries. REFERENCE Goodyear, C. Phillip. 2015. Understanding maximum size in the catch: Atlantic Blue Marlin as an example. Transactions of the American Fisheries Society 144:274-282. dx.doi.org/10.1080/00028487.2014.986339

Thinking about Muskellunge at a Lakescape Scale Nearly all fisheries scientists think about spawning habitat, but too often we think about it only in terms of presence of the correct substrate. Joel Nohner and Jim Diana thought about it differently and used a GIS-based model to predict spawning site selection by Muskellunge Esox masquinongy in northern Wisconsin lakes. There, Muskellunge are popular and support trophy fisheries on many inland lakes, but managers are troubled by poor recruitment associated temporally with shoreline development. The trend has raised many questions about availability of spawning habitat and how it might be conserved. Nohner and Diana found that Muskellunge spawning site selection was complex and governed by larger-scale habitat features, such as shelter from fetch, shoreline direction, and local bathymetry, with east or west facing sheltered shorelines with moderate slopes being favored. Local conditions mattered, but spawning was influenced strongly by largerscale factors. The resulting model predicted spawning site Providing equipment for Mark and Relocate your Active and Passive tracking Underwater Equipment locations in novel lakes, and generates maps that can be used in communicating with the public. But most importantly, it helps managers focus conservation efforts on the specific areas within lakes that are the most important for recruitment.

Offering more than a Two Fold Approach

REFERENCE Nohner, J. K., and J. S. Diana. 2015. Muskellunge spawning site selection in northern Wisconsin lakes and a GIS-dased predictive habitat model. North American Journal of Fisheries Management 35:141-157. dx.doi.org/10.1080/02755947.2014 .977471

Sonotronics

“working together to make a difference in the world we share”

www.sonotronics.com • (520) 746 -3322 194


JOURNAL SUMMARIES

Whirling Disease Is Fortunately Not a Permanent Condition Whirling disease caused by Myxobolus cerebralis is a scourge for fish culturists and salmonid biologists, and rumors have circulated for decades that its myxospores remain viable for years. Nehring et al. (2015) used a carefully designed time-delay study that exposed susceptible oligochaetes to myxospores and then measured production of actinospores as evidence of myxospore viability. We might mention that the whirling disease organism has a complicated life cycle involving both a salmonid and an oligchaete Tubifex tubifex as well as life stages that are difficult to pronounce. They found that spore viability decreased by about 75% after 15 days and was negligible after 180 days. Continuing the experiment, no spores were viable after one year. Whirling disease is still an issue, but reinfections of salmonids are caused by current events and not by viable myxospores that have remained dormant for years or even decades. This is good news for culturists who have worried about this issue for years. REFERENCE Nehring, B. N., G. Schisler, L. Chiaramonte, A. Horton, and B. Poole. 2015. Assessment of the long-term viability of the myxospores of Myxobolus cerebralis as determined by production of the actinospores by Tubifex tubifex. Journal of Aquatic Animal Health 27:50-56. dx.doi. org/10.1080/08997659.2014.976671

A Novel and Efficient Way to Assess Net Pen Impacts Net pen culture has become widespread, and there is growing concern about impacts to benthic communities below the facilities. Potential impacts are hard to assess because the ideal sites for net pen culture are deep, often have currents or cold temperatures, and have patchy substrates that can’t be grab-sampled. Hamoutene et al. (2015) overcame this problem by developing a video monitoring protocol that was able to identify benthic organisms below pens to a high taxonomic level and quantify their abundance. They found that net pen effects were more complex than thought previously, with some impacts occurring away from pens and not directly underneath. Impacts varied substantially and were not uniform, with some sites showing few effects. Surprisingly, fallow pen sites were largely barren, which was difficult to reconcile with obvious cessation of organic enrichment from rearing activities. While some of their findings are yet to be explained fully, the technique seems applicable to impact assessments anywhere that net pens are being used. REFERENCE Hamoutene, D., F. Salvo, T, Bungay, G. Mabrouk, C. Couturier, A. Ratsimandresy, and S. C. Dufour. 2015. Assessment of finfish aquaculture effect on Newfoundland epibenthic communities through video monitoring. North American Journal of Aquaculture 77:117-127. dx.doi.org/ 10.1080/15222055.2014.976681

Sadly, Lionfish Are More Widespread Than We Thought The invasion of Caribbean reef systems by lionfish Pterois spp. is well documented, and they are now encountered commonly by anglers and sport divers in many areas. However, a trawl survey conducted by the authors found them to be even more widespread in deep (>30 m) low-relief habitats and abundance increased sharply during 2010–2013. This is problematic because it likely means that lionfish suppression or eradication at specific shallow sites will likely be temporary, as individuals invulnerable to capture would still be present in deeper waters. It also means that their potential impacts will extend beyond reef tracts into other habitats with potential interactions with the deepwater fish community. However, and fortunately for fisheries managers, the trawl survey was initiated just prior to lionfish establishment and will be able to track their future abundance and long-term consequences of invasion. REFERENCE Switzer, S. S., D. M. Tremain, S .F. Keenan, C. J. Stafford, S. L. Parks, and R. H. McMichael. 2015. Temporal and spatial dynamics of the lionfish invasion in the eastern Gulf of Mexico: perspectives from a broadscale trawl survey. Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Science 7:10-17. dx.doi.org/10.1080/19425120.2014.987888


195

STUDENT ANGLE

How to Navigate Fisheries Education and Employment Andrew K. Carlson South Dakota State University, Department of Natural Resource Management, NPBL 138, Box 2140B, Brookings, SD 57007. E-mail: [email protected] Karen M. Dunmall University of Manitoba, Department of Biological Sciences, Winnipeg, MB, Canada Ross E. Boucek Florida International University, Department of Biology, Miami, FL Nicholas W. Cole University of Nebraska, School of Natural Resources, Fisheries and Wildlife Cooperative Research Unit, Lincoln, NE Janice A. Kerns Wisconsin Cooperative Fishery Research Unit, College of Natural Resources, University of Wisconsin–Stevens Point, Stevens Point, WI Rebecca M. Krogman Iowa Department of Natural Resources, Chariton, IA M. Clint Lloyd Mississippi State University, Department of Wildlife, Fisheries & Aquaculture, Mississippi State, MS Vivian M. Nguyen Carleton University, Ottawa, ON, Canada Tracy R. Wendt University of Montana, Department of Ecosystem & Conservation Science, Missoula, MT Shannon L. White Department of Ecosystem Science Management, The Pennsylvania State University, University Park, PA Kyle L. Wilson University of Calgary, Department of Biological Sciences, Calgary, AB, Canada All authors are current or former members of the AFS Student Subsection of the Education Section Executive Committee. Authorship is alphabetical after the second author.

INTRODUCTION The old joke is true: fish are smart because they travel in schools. Taking a cue from fish themselves, a group of American Fisheries Society (AFS) students and young professionals from the Student Subsection of the Education Section schooled together to create a series of “How to …” documents to help our cohorts navigate the many steps of professional development in fisheries. The complete series is available online at students. fisheries.org. HOW TO CONDUCT UNDERGRADUATE RESEARCH Undergraduate research in fisheries can take many forms. For example, a student may assist a conservation agency in sampling sport fish in inland lakes, help a graduate student identify small-bodied native fishes from prairie streams, or design an angler survey instrument with a faculty member. Undergraduate students commonly conduct research for course credit, graduation with honors, professional experience, and/or intellectual enrichment. Research prepares undergraduate students for graduate school and future employment and is a valuable way to contribute to fisheries science early in one’s career. This “How to …” document:

196


1. Describes the process of undergraduate research and emphasizes the importance of scientific experience for graduate school; and 2. Teaches undergraduate students how to brainstorm research ideas, develop questions and hypotheses, plan for research, collect data, and complete additional steps of the scientific method in the context of a fisheries investigation. In the end, students are encouraged to reflect on their research experiences to celebrate personal growth, identify areas for improvement, and apply acquired skills in new situations. HOW TO PREPARE FOR GRADUATE SCHOOL Graduate school is an increasingly important component of fisheries education. A master’s of science (M.S.) degree is now the norm for agency biologist positions, making graduate school critical for attaining employment in a fisheries-related discipline. This “How to …” document: 1. Reviews and differentiates the processes of preparing for M.S. and Ph.D. research, offering valuable insights for success; 2. Explains the importance of developing a strong undergraduate record to prepare for graduate school; 3. Offers undergraduate students a roadmap for the next destination in their educational path (e.g., identifying research interests, taking the GRE, locating M.S. positions, contacting faculty, and scheduling visits); and 4. Gives important insights for doctoral success, including strategies for streamlining the project search, securing independent funding, and refining written and oral communication skills. HOW TO WRITE EFFECTIVE SCHOLARSHIP APPLICATIONS Writing effective scholarship applications is an art. This “How to …” document: 1. Describes the process by condensing scholarship applications into comprehensible steps; 2. Teaches readers how to locate scholarships that highlight their strengths and future promise and thus establish their credibility as worthy awardees; 3. Discusses the importance of having personalized reference letters; 4. Describes how to write effective research proposals and personal statements that highlight achievements within key categories often reviewed by scholarship committees; and 5. Empowers students to effectively advertise their skills and abilities as they craft high-quality scholarship applications. HOW TO ANALYZE YOUR DATA Data analysis is the formal process of deriving scientific conclusions from quantitative and/or qualitative information collected during a study. In fisheries, proper data analysis is critical for reliable research, high-quality publications, and sciencebased management. Students are often exposed to analytical procedures in courses (e.g., statistics, biometrics, quantitative fisheries science, and fisheries population analysis) that prepare them for graduate research, for which statistical acumen is indispensable. This “How to …” document:

1. 2.

Reviews the steps of data analysis and offers tips for success; and Introduces readers to database management, statistical software packages (e.g., R, SAS, and SPSS), types and assumptions of analytical procedures, and options for data interpretation and visualization.

HOW TO WRITE AND DEFEND YOUR THESIS Writing and defending your thesis helps authenticate your research findings and establish yourself as an expert in your field. This “How to …” document: 1. Demystifies thesis writing and defense, providing valuable insights for success during each stage of the process; 2. Shows students how to select an organizational structure and separate chapters as individual manuscripts for publication; 3. Encourages students to write early and often in graduate school, using their best writing from scholarship applications, thesis proposals, or literature reviews in their final theses; 4. Offers tips for avoiding writer’s block (e.g., changing environments, brainstorming with colleagues, spending time away); and 5. Teaches students how to prepare for their thesis defense by attending defenses of other students and researching the expertise of committee members to anticipate questions they may ask. Overall, this document describes valuable, applicable skills for succeeding at two of the greatest challenges of graduate school. HOW TO PUBLISH IN GRADUATE SCHOOL Publications are the currency of the sciences and one of the best ways to increase your marketability for graduate assistantships, scholarships, and jobs. Research suggests that the best predictor of employment in biological sciences is the number of publications a person produces before he or she finishes graduate school. Thus, publishing as a student may be one of the best career investments you can make. However, publishing research is challenging. From writing to submitting a manuscript, the publishing process can seem somewhat daunting at first, especially when considering the demands of other simultaneous academic obligations, such as teaching and assistantship assignments, studying for comprehensive exams, and writing proposals. This “How to …” document: 1. Provides a quick primer for publishing in graduate school that will smooth the process for young students; 2. Includes strategies, insights, and example documents to highlight the steps leading to an accepted publication; and 3. Describes how to write manuscript sections, select journals, write cover letters, and respond to reviewers. HOW TO WRITE A RÉSUMÉ/CV The first step in looking for a job or applying to graduate school is developing marketing materials. You need to sell potential employers and advisors on who you are. A strong résumé or curriculum vitae (CV), paired with a cover letter tailored to the opportunity at hand, is the key document that will get their attention. This “How to …” edition: 1. Describes differences between a résumé and a curriculum vitae, along with strategies for creating both types of documents; and 2. Shows how to format and write sections of résumés and

CVs and craft cover letters that strategically highlight achievements relevant to specific jobs. This document is beneficial for undergraduate and graduate students alike as they prepare and apply for careers in fisheries science. HOW TO GET A JOB Finding a job is not always an easy task, especially in the fisheries field where employment can be limited. During each step of the process, you must stand out among many (and oftentimes very competitive) candidates. This “How to …” document: 1. Introduces a variety of job search tools available for aspiring fisheries professionals to locate the position of their dreams; 2. Helps students tailor a cover letter and résumé/CV to fit specific jobs; and 3. Describes strategies for crafting applications, conquering interviews, and following up appropriately. Written by AFS members who have had recent success securing employment, this document is a must-read for aspiring fisheries professionals. HOW TO BE A YOUNG PROFESSIONAL Transitions can be exciting, scary, and rewarding. Becoming a young professional (YP) is no different. This “How to …” document: 1. Explains the changes that occur during the progression from student to full-fledged fisheries professional; 2. Details what it means to be a YP member in AFS; and 3. Describes financial benefits (e.g., lower cost of membership and meeting registration) and professional enrichment opportunities (e.g., awards, exchange programs, and new leadership and mentoring options) associated with being a YP. Many students who were AFS members during their formal education find themselves overwhelmed and underfunded when they enter the professional world. Young professional membership was developed by AFS to acknowledge the unique values recent graduates offer the Society and to help support them during this demanding time period. CONCLUSION There is safety in numbers, especially during risky times. Thus, schooling behavior helps fish and those studying fish, both during school and beyond. This “How to …” series was crafted to clarify and explain the steps of fisheries education. It is a “living” document online and thus can be updated with new topics and information as necessary. The collaborative, international nature of its development is indicative of the broad opportunities available for students and professionals in AFS. The AFS Student Subsection of the Education Section (Subsection) facilitates interactions among students and professionals, making education less confusing and creating opportunities for networking and personal and professional growth. Students and young professionals automatically become members of the Subsection with membership in AFS. We encourage students to get involved in the Subsection by visiting our website (students. fisheries.org), attending the Subsection Business Meeting (held annually at the AFS Annual Meeting), and emailing Subsection officers with questions and ideas, including volunteering to write new topics for the “How to …” series. As AFS students swim in their educational and professional directions, new perspectives broaden the stream. Welcome to the school.


197

AFS NEWS

AFS Hosts Capitol Hill Briefings on Marine Fisheries Management Thomas E. Bigford AFS Policy Director

The American Fisheries Society (AFS) has been retained by the National Oceanic and Atmospheric Administration (NOAA)/ National Marine Fisheries Service (NMFS) to convene briefings for House and Senate staff working on fisheries and aquatic resources. Based on demand and the range of issues, what was envisioned as one seminar has morphed into three panels, each with four speakers. This unprecedented opportunity places AFS at the intersection of science, management, policy, and education, with a primary audience of Capitol Hill staff but also including partners from state and federal agencies plus non-profits representing industry and environmental interests. The first briefing was March 19, 2015, with a focus on “Challenges Related to Managing Fish Stocks.” AFS Executive Director Doug Austen moderated a panel of four experts: • Liz Brooks, population research analyst, NOAA/NMFS Northeast Fisheries Science Center, Wood Hole, Massachusetts • Eric Schwaab, senior vice president and chief conservation officer, National Aquarium, Baltimore, Maryland • Charlotte Hudson, director, Lenfest Ocean Program, Washington, DC • Jon Hare, supervisory research oceanographer, NOAA/ NMFS Northeast Fisheries Science Center, Narragansett, Rhode Island The panel provided a quick tour through the complexities of managing oceanic stocks that often navigate through the waters of multiple nations, migrate between habitats with each life stage, and occupy waters from shallows to the deep continental slope. Liz Brooks opened with “Stock Assessment 101,” providing a glimpse of the mathematical and statistical tools used to measure stock health and detect change through careful manipulation of data and population models. Her insights provided valuable context for the challenges of understanding the health of individual stocks and how they interact in a complex ocean. Eric Schwaab focused on risk and uncertainty as key components of managing expectations. He summarized a 2014 National Aquarium report that identified sources of and treatments for uncertainty, shared best practices for reducing uncertainty, offered a special case in the context of environmental change, and offered specific recommendations to support risk-

198


based decision making and prioritizing responses to uncertainty. Charlotte Hudson provided an ecosystem context, connecting fish stocks to the ecological, environmental, and geographic systems that affect sustainability. She mentioned a special Lenfest task force convened on ecosystem-based approaches to fisheries management, aiming toward a shift from traditional “fishery management plans” to “fishery ecosystem plans.” Jon Hare closed the panel presentations by explaining how climate change is affecting ocean conditions and fish stock health. Climate change and variability are factors in changes to fish and shellfish populations. Because of those shifts, resource management must adjust. Fisheries experts from all disciplines need to integrate fisheries, cooperative, social, economic, ecological, ocean, and climate sciences to improve management. Together, the four speakers provided an excellent introduction to the challenges of managing fish stocks.

The second briefing took place on Earth Day, April 22, 2015, with a focus on a second set of issues identified by Capitol Hill and NOAA/NMFS leaders, namely “Applying Fish Habitat Knowledge in Fisheries Management.” Moderator Tom Bigford, AFS Policy Director and a former NOAA/NMFS habitat program director, led the panel: • Rich Seagraves, senior scientist, Mid- Atlantic Fishery Management Council, Dover, Delaware • Kara Meckley, chief, Habitat Protection Division, NOAA/NMFS Office of Habitat Conservation, Silver Spring, Maryland • Thomas Miller, director, University of Maryland Center for Environmental Science’s Chesapeake Biological Laboratory, Solomons, Maryland • Steve Brown, chief, Assessment and Monitoring Division, NOAA/NMFS Office of Science and Technology, Silver Spring, Maryland The second panel delved into more detail on the ecosystem context mentioned by each speaker on the first panel. Rich Seagraves opened with “Fisheries Management 101,” offering a quick peak at the processes used by regional fisheries councils to manage marine stocks with commercial and recreational value, with comments on how habitat and ecosystem aspects are becoming more relevant. Kara Meckley discussed the importance of habitat in managing habitat-dependent stocks/life stages. She explained how non-fishing mortality can affect the health of fish stocks and hence the number of fish caught and related economic implications. Her points were extended to forage fish as an entrée into the food chains that support marine ecosystems. Thomas Miller talked about ecological connections between nearshore/estuarine fish populations and offshore stocks. He used historical and ecological examples to make economic points about how what happens to inland streams directly affects fish stocks and fishing experiences well off shore. Steve Brown discussed habitat trends and the stressors that affect their production. The final panel is in the early planning stages, probably to be convened later this month (to get the latest news, visit: news.fisheries.org/policyinvitations). The “Need for Knowledge in Fisheries Management” will highlight the continuous need for scientific study and observations, resulting data sets, and careful analysis to convert information into knowledge. An opening “101” talk will be followed by presentations on general monitoring, directed basic and applied research inquiries, and breadth across different fields of study. Together, these panels promise to meet the collective need for House and Senate staff, and partners across disciplines and sectors, to familiarize themselves with the issues that affect bipartisan interests, agency budgets, and legislative debate. The AFS is proud to facilitate those discussions in 2015 and beyond.

AFS Executive Director Doug Austen opens the AFS Capitol Hill Briefing on “Marine Fisheries Issues – Challenges Related to Managing Fish Stocks.” Photo credit: AFS.

Liz Brooks discusses “Stock assessment 101 – Explaining the challenges of measuring the size and health of fish stocks” at the AFS briefing “Marine Fisheries Issues – Challenges Related to Managing Fish Stocks.” Photo credit: AFS.

Jon Hare talks about “Climate change – Addressing climate as a new challenge to fisheries managers” at the AFS briefing “Marine Fisheries Issues – Challenges Related to Managing Fish Stocks.” Photo credit: AFS.

Charlotte Hudson discusses "Ecosystem context – Managing broader geographic, environmental, and ecological considerations" at the AFS briefing “Marine Fisheries Issues – Challenges Related to Managing Fish Stocks.” Photo credit: AFS.

Eric Schwaab gives his presentation on "Managing uncertainty – Understanding environmental risk and change; managing expectations” at the AFS briefing “Marine Fisheries Issues – Challenges Related to Managing Fish Stocks.” Photo credit: AFS.


199

FEATURE

The Great Fishing Ind

200


Lakes Charter dustry: 2002 to 2011 We compare results of Great Lakes charter captain surveys from 2002 and 2011. Charter trips declined 27%, from over 103,000 in 2002 to less than 76,000 in 2011. Revenues between the two years fell 24%, from US$48.0 million to $36.4 million, after values were adjusted for inflation. An estimated 1,696 captains operated as small businesses in 2011: a decrease of over 12% from 2002. Fuel costs and age of the average charter vessel were significantly higher in 2011. Motivations for chartering were basically unchanged since 2002, and fishing continued to be a secondary income source for most captains. The economy and aquatic nuisance species were included among top concerns for the future of the industry in both years. Although the basic nature of the charter industry had not changed, captains were making management decisions to reduce costs and maintain the viability of their business.

La industria pesquera de botes de alquiler en los grandes lagos: 2002 a 2012 Se comparan los resultados de un sondeo realizado de 2002 a 2011 a los capitanes de embarcaciones alquiladas en los grandes lagos. Los viajes de pesca disminuyeron 27% de 103,000 en 2002 a menos de 76,000 en 2011. Los dividendos de la pesquería entre esos dos años, ajustando los valores por la inflación, se redujeron 24%, de $48 millones de dólares a $36.4 millones. Se estimó que en el año 2011, 1,696 capitanes operaban en la forma de negocio pequeño: una reducción de 12% con respecto a 2002. Los costos del combustible y la edad de la embarcación promedio fueron significativamente mayores en el año 2011. Los motivos por los cuales se utilizan barcos de alquiler no han cambiado desde 2002, y la pesca continúa siendo un insumo secundario para la mayor parte de los capitanes. En ambos años, la economía y las especies acuáticas nocivas aparecieron dentro de las principales preocupaciones para el futuro de la industria. Si bien la naturaleza de la industria pesquera con botes de alquiler no ha cambiado, los capitanes están tomando decisiones de manejo para reducir los costos y mantener la viabilidad de sus negocios.

Frank Lichtkoppler The Ohio State University Extension and Ohio Sea Grant College Program, 99 East Erie Street, Painesville, OH 44077. E-mail: [email protected] Daniel M. O’Keefe Michigan Sea Grant Extension, West Olive, MI Joseph Lucente The Ohio State University Extension and Ohio Sea Grant College Program, Toledo, OH Tory Gabriel The Ohio State University Extension and Ohio Sea Grant College Program, Oak Harbor, OH


201

INTRODUCTION The development and status of the Great Lakes charter fishing industry has been well documented by Dawson et al. (1995) and Kuehn et al. (2005). The charter fishing industry primarily evolved in the 1970s following the stocking of nonnative salmonids (predominantly Oncorhynchus spp.) in Lakes Huron, Michigan, Ontario, and Superior, and rehabilitation of naturally reproducing Walleye Sander vitreus and Yellow Perch Perca flavescens stocks in Lake Erie (Dawson et al. 1989). The growth of the charter industry in the U.S. waters of the Great Lakes has been enhanced by fishery management policies designed to favor sportfishing over commercial fishing (Kuehn et al. 2005). Both sport- and commercial fishing are supported by ongoing efforts of the interjurisdictional Great Lakes Fishery Commission (2011) to control Sea Lamprey Petromyzon marinus, coordinate fisheries research, and facilitate cooperative fisheries management. The last region-wide survey of the Great Lakes charter fishing industry was conducted by the Great Lakes Sea Grant Network in 2002. Since then, the Great Lakes region has experienced a deep economic recession, which may have contributed to changes in regional sportfishing activity. New introductions of aquatic nuisance species (ANS) and adverse weather may have had negative impacts on the fishery (Rasmussen et al. 2011; ODW 2012). Congressional concern over movement of ANS into and out of the Great Lakes led to the inclusion of legislation in the Water Resources Development Act of 2007, directing the U.S. Army Corps of Engineers (USACE) to conduct the Great Lakes–Mississippi River Interbasin Study (USACE 2014). In 2012, USACE economists asked the Ohio Sea Grant College Program to lead a regional effort to develop socioeconomic information on the Great Lakes charter fishing industry. These data provide a baseline status of the industry in 2011 that resource managers, researchers, charter industry associations,

and other interested parties may find useful. Our results provide an opportunity for new charter firms to compare business plans with industry averages and allow for more informed decision making among current operating firms. Additionally, fisheries professionals in other parts of the world may gain valuable ideas and insight into the charter industry and use this work as a model for assisting other charter industries. METHODS We compared the results from the 2011 charter fishing survey to results of the survey conducted in 2002. Both surveys focused on items that included numbers of trips by fish species and by lake, revenues, business costs, issues of concern, and plans for the future. We developed the 2011 charter captain sample list in the same manner as in 2002 (Kuehn et al. 2005). We obtained lists of charter captains from state management agencies except for New York. New York does not have a state license requirement. The New York captains list for both surveys was developed via mailing lists from tourism promotion organizations, chambers of commerce, and charter boat associations. We used the same definition of an active captain in both surveys. The typical charter captain is a person licensed by the U.S. Coast Guard to carry six passengers or less for hire (Kuehn et al. 2005). Using a modified mail survey technique (Dillman 1978, 2000), we mailed the survey in May 2012 to a total of 1,200 charter captains. Nonresponding captains received up to four contacts by mail at approximately two-week intervals. We planned to deal with potential nonresponse error because we anticipated that not all captains who received a survey would respond. Failure to address nonresponse error is an issue in social science (Lindner et al. 2001), particularly when response rates are less than 85% (Lindner and Wingenbach 2002). Comparing early and late respondents is an acceptable method of addressing nonresponse error (Miller and Smith 1983; Lindner et

A typical six passenger Great Lakes charter boat rigged for trolling. Photo credit: Ohio Sea Grant.

202


al. 2001; Lindner and Wingenbach 2002). Comparing early and late respondents using a one-way analysis of variance (ANOVA) allows for a comparison that serves as an indicator of differences between respondents and nonrespondents. Late respondents were defined as those returns that came in after the third contact by mail. Comparing the respondents received after the third mail contact would allow a sufficient number of late responses for analysis. Lindner et al. (2001) recommend the minimum number of late respondents for comparison be at least 30 in order to be meaningful, both practically and statistically. We adjusted the 2002 economic data for inflation to 2011 dollars by using the Bureau of Labor Statistics Consumer Price Index Inflation Calculator (BLS 2014). Multiplying the 2002 economic data by the derived inflation factor of 1.25 approximated the purchasing power of the 2002 data in terms of 2011 dollars. Inflation adjustments allow comparisons between the two years. We generalized the 2011 and 2002 survey responses to the entire Great Lakes charter industry for each year, after accounting for nonresponse error and inflation. We obtained our archived 2002 survey data set and merged like survey items with the 2011 survey data set using IBM SPSS statistical software. We sorted the data set by lake and by business model. The numbers of trips are extrapolations of respondent trip rates applied to the estimated population of active Great Lakes charter businesses in 2011 and 2002 (Kuehn et al. 2005). Multiplying the total number of trips by the average price per trip resulted in revenue estimates by species. We repeated this process for each species for 2011 and 2002. Finally, we used a one-way ANOVA to test for differences by lake or by business model between the two surveys using survey year as the independent variable.

RESULTS Returns and Tests for Nonresponse

Of the 1,200 mailed surveys, 28 were returned as undeliverable and 24 were returned indicating that the captains did not charter in 2011. Thus, 1,148 Great Lakes charter captains received surveys. A total of 342 captains returned surveys with usable data, producing a response rate of approximately 30%. This is lower than the 49% response rate of the 2002 regional survey (Kuehn et al. 2005). The lower return rate may be due in part to reporting deadlines that required the 2011 survey to be mailed during the busy spring/summer fishing season. In contrast, the 2002 survey mailing occurred during the charter industry’s relatively quiet late winter season. We tested for nonresponse error by using a one-way ANOVA to compare the early (N = 231) versus late respondents (N = 111) on 22 attitudinal variables. We found a significant difference (P ≤ 0.05) for just two of these variables. Early respondents were more concerned about obtaining new clients than late respondents (F = 5.280, df = 331, P = 0.02). Early respondents were also more concerned that ANS would impact their charter business than late respondents (F = 5.766, df = 307, P = 0.02). Of the 342 respondents, 304 captains operated their own charter business and provided some economic data on their business operations. We compared early (N = 211) and late respondents (N = 93) and found that there were no significant differences (P ≤ 0.05) for five demographic variables and 28 economic variables tested. Given the lack of statistical differences between early and late respondents, it appears that the sample is representative of the Great Lakes charter industry in 2011 (Miller and Smith 1983; Lindner et al. 2001; Lindner and Wingenbach 2002).

A nice catch of Great Lakes salmonids from Lake Michigan. Photo credit: Michigan Sea Grant.


203

There were some lake-by-lake differences in the percentage of respondents from 2011 and 2002. Of the responding captains who indicated a home port in 2011 and 2002, respectively, approximately 6% and 5% were based on Lake Superior, 7% and 5% were based on Lake Huron, and 40% and 42% were based on Lake Erie. Respondents from Lake Michigan increased from 33% of the total in 2002 to 42% in 2011. Respondents from Lake Ontario declined from 16% of the total in 2002 to 6% in 2011. Captain Characteristics and Business Organization

Almost 11% of respondents in 2011 did not operate as small businesses but rather identified themselves as freelance captains for hire on a temporary or seasonal basis. Multiplying 11% by the number of active captains resulted in 208 freelance captains in 2011, which was a 3% increase compared to 2002. Freelance non-boat-owning captains are paid for their labor. In 2011, the freelance captains reported gross earnings of $6,759 ± $13,507 (mean ± SD) compared to $6,088 ± $7,789 in 2002. Subtracting 208 freelance captains from the list of 1,904 active captains tallied 1,696 charter businesses in 2011, a decline of over 12% compared to 2002. Most of the 304 responding captains operating a small business in 2011 were licensed by the U.S. Coast Guard to carry no more than six passengers. The typical Great Lakes charter fishing captain in 2011 had been licensed for 12.8 ± 10.5 years and was not significantly different (F = 0.762, df = 1,152, P = 0.38) from 2002 at 13.4 ± 8.6 years. Notably, very few captains (about 11% in 2011 and less than 18% in 2002) relied on the charter business as a primary source of income. In both surveys, the major motivations for being a charter captain included a desire to help people enjoy fishing and the satisfaction of participating

in such work. The differences in motivations among captains may help explain the large standard deviations reported later in this article. The business organization of the charter industry in 2011 remained basically unchanged from 2002. Over 89% of responding captains in 2011 owned their boat and/or operated as a small business, compared to 92% in 2002. More than 77% operated their business as a sole proprietorship in 2011 compared to almost 84% in 2002. Charter businesses that operated as a sole proprietorship decreased by nearly 7% and businesses operating as a corporation increased by 7% when comparing 2011 and 2002 survey data (Kuehn et al. 2005). Trips and Revenues

Responding captains who operated their own business averaged 24.6 full-day and 20.2 half-day paid charter trips in 2011. The captains averaged 28.4 full-day and 25.1 half-day trips in 2002. A full-day trip is defined as being seven hours long from dock to dock or a limit catch of the target species. A half-day trip is defined as being less than seven hours in duration. Most of these trips targeted salmon (Oncorhynchus kisutch, O. tshawytscha, and O. mykiss) or Lake Trout Salvelinus namaycush, followed by Walleye, Yellow Perch, Smallmouth Bass Micropterus dolomieu, and other fish species. These results are found in Table 1 along with the F statistic, degrees of freedom (df), P values, and 95% confidence intervals (CIs) for significant differences between the two surveys. Charter fees varied with target species, length of the charter, and services offered. The most popular trip in 2011 was the halfday Lake Trout or salmon charter; its cost averaged $448 ± $95 per boat with an average of 4.4 ± 1.2 clients. Nominal charter

A youthful angler with a Lake Huron Chinook Salmon. Photo credit: Michigan Sea Grant.

204


TABLE 1. Estimated number of trips, average charge per trip, revenues earned, and percentage of total revenues by the Great Lakes charter industry in 2002 and 2011 are listed by fish species and by trip length. The 2002 dollar values are adjusted for inflation to 2011 dollars. Number of respondents in 2002 was 689. Number of respondents in 2011 was 275. Revenues may not equal direct multiplication of number of trips by mean charge per trip due to rounding errors. Fish species

Trip length

Estimated number of trips

Mean charge per tripa ($)

Revenues earnedb ($)

Percentage of total revenues

Trout or salmon

Full-day 2002

25,232

561c

14,153,001

29.5

Full-day 2011

16,349

566

9,243,420

25.6

Half-day 2002

38,988

407

15,878,103

33.1

Half-day 2011

27,713

448d

12,405,290

34.4

Full-day 2002

20,866

502

10,464,292

21.8

Full-day 2011

18,792

484

9,103,450

25.3

Half-day 2002

5,854

386

2,255,417

4.7

Half-day 2011

4,155

365

1,513,137

4.2

Full-day 2002

3,536e

422

1,492,315f

3.1

Full-day 2011

5,376e

419

2,248,862f

6.2

Half-day 2002

2,531

347

879,833

1.8

Half-day 2011

1,492

377

564,497

Full-day 2002

5,178

475

2,455,823

Full-day 2011

1,679g

500

836,043h

2.3

Half-day 2002

1,101

336

373,204

0.8

Half-day 2011

373

331

122,417

0.3

Full-day 2002

NA

NA

NA

NA

Full-day 2011

797

404

321,409

0.9

Half-day 2002

NA

NA

NA

NA

Half-day 2011

204

405

84,919

0.2

Full-day 2002

54,803

Full-day 2011

41,799

Half-day 2002

48,488

Half-day 2011

34,184

2002

103,285i

47,951,989j

100.0

2011

75,913

36,443,444j

100.0

Walleye

Yellow Perch

Smallmouth Bass

Other fish species

Subtotal

Totals

g

cd

i

1.6 h

5.1

Rounded to the nearest dollar. The numbers of trips are extrapolations of respondent trip rates applied to the estimated population of 1,932 and 1,696 active Great Lakes charter businesses in 2002 and 2011, respectively (excluding party and head boats). Revenues are extrapolated from the mean number of trips per firm multiplied by the mean charge per trip and may not be exact due to rounding errors. Data for 2002 are from Lichtkoppler et al. (2003) and are adjusted for inflation to 2011 dollars. c In the 2002 survey, Steelhead O. mykiss was reported separately from Lake Trout and salmon and the mean price is a weighted average. d Significantly different, F = 11.974, df = 963, P < 0.01; 95% CI 2002 (2,859, 4,212), 95% CI 2011 (3,969, 6,784). e Significantly different, F = 11.645, df = 963, P < 0.01; 95% CI 2002 (1,209,625, 1,775,025), 95% CI 2011 (1,660,130, 2,837,578). f Significantly different, F = 8.099, df = 963, P < 0.01; 95% CI 2002 (3,825, 6,511), 95% CI 2011 (628, 2,714). g Significantly different, F = 7.515, df = 963, P < 0.01; 95% CI 2002 (1,817,722, 3,093,924), 95% CI 2011 (316,694, 1,355,409). h Significantly different, F = 7.003, df = 963, P < 0.01; 95% CI 2002 (96,330, 110,240), 95% CI 2011 (67,738, 84,088). i Significantly different, F = 5.377, df = 963, P < 0.05; 95% CI 2002 (44,724,699, 51,179,279), 95% CI 2011 (32,086,641, 39,987,593). a

b

prices increased from 2002 to 2011. However, when adjusted for inflation, only the price of the half-day Lake Trout and salmon trip increased significantly (F = 14.175, df = 500, P < 0.001). Most revenues were generated from half-day Lake Trout or salmon trips, full-day Lake Trout or salmon trips, and full-day Walleye trips in both 2011 and 2002. The total population of 1,696 active charter businesses in 2011 was estimated to have made 75,913 charter trips, of which 41,799 (55%) were full-day trips and 34,184 (45%) were half-day trips. Comparing 2011 to 2002, full-day trips declined about 24% and half-day trips declined 30%. The overall 27% decline in the total number of charter trips in 2011 compared to 2002 was statistically signifi-

cant (F = 7.003, df= 963, P < 0.01). Total estimated revenues for the Great Lakes charter industry was $47.9 million in 2002, declining to $36.4 million in 2011. This overall 24% decline in revenues from 2002 to 2011 was statistically significant (F = 5.377, df = 963, P < 0.05). The 2011 survey results reflect lower level of charter activity and provide a conservative benchmark for future comparisons should conditions change dramatically. Respondents reported a significant (F = 7.003, df = 963, P < 0.01) 16% decline in the mean number of trips taken from 2011 to 2002 (Table 2). However, the 11% decline in revenues per respondent was not statistically significant (F = 2.072, df = 916, P = 0.15). Mean charter trips per respondent for Lake Superior Fisheries | www.fisheries.org

205

in 2011 declined 16%, and mean charter revenues per respondent declined over 37% from 2002. Mean trips per respondent for Lake Michigan declined 22%, and mean charter revenues per respondent decreased by less than 9%. The number of trips per respondent for Lake Michigan was significantly lower in 2011 (F = 6.035, df = 331, P < 0.05) compared to 2002, but reported revenues were not (F= 0.627, df =325, P = 0.429). Mean charter trips for Lake Huron respondents declined 52%, and mean revenues decreased by 55%. The number of trips and revenues per respondent for Lake Erie were lower by 12% and 13%, respectively, in 2011 compared to 2002 but not significantly (trips: F = 1.220, df = 380, P = 0.270; revenues: F = 0.924, df = 355, P = 0.337). Respondents from Lake Ontario actually increased the mean number of trips by 23%, and their mean revenues increased by 78%. However, there was a large standard error (±13.4 for trips and ±$8,034 for revenues) for the Lake Ontario respondents. The low number of respondents in 2011 for Lakes Superior, Huron, and Ontario should be considered when interpreting individual lake results in Table 2. Total revenue for the captains who operated their own business and provided their gross sales figures was $19,478 ± $20,776. Reported revenues for 2002 were $21,797 ± $22,380. An explanation for the large standard deviations and ranges may be that most captains view their charter business as a secondary enterprise, but it is the primary income source for some. Thus, the incentive to promote, book, and make charter trips varies widely. A wide variation in earned revenues, costs, and returns was expected and was consistently large in both surveys. Costs and Returns

Each charter firm is an independent small business that may operate under a variety of business models as illustrated in Table 3. Charter firm averages vary depending upon whether or not the firm is paying off a boat loan or depreciating the cost of the charter vessel. Some firms do both, and thus the number of respondents does not sum across the rows in Table 3. We

analyzed each business model with a separate one-way ANOVA with the survey year as the independent variable. These different business models illustrate that costs may vary by how a business is managed. Overall operating costs for Great Lakes charter boat businesses in 2011 was not significantly different than in 2002 (F = 0.164, df = 929, P = 0.685; 2002 CI, 12,383 to 14,043; 2011 CI, 11,992 to 15,152). The cost to fuel a charter boat in 2011 accounted for 31% of operating costs and was significantly higher compared to 2002 (F = 29.908, df = 869, P < 0.001). Boat-owning captains operating their own business reported boat fuel and dockage as the largest annual operating expenses in both years. Notably, overall fuel costs increased over 47% ($1,349) from 2002 to 2011. Businesses with a boat loan cost $616 less to operate than in 2002, and businesses with depreciation cost $1,355 less to operate in 2002. However, businesses with either boat loans or depreciation cost more to operate than the overall mean operating cost in both 2011 and 2002. Businesses with no boat loan and no depreciation cost $503 more to operate in 2011 than they did in 2002. The average cash requirement to operate a charter business is the sum of operating expenses plus boat loan payments. The annual payment was $5,064 ± $3,406 for 72 responding captains in 2011 who had a boat loan (Table 4). The 232 captains reporting a boat loan in 2002 made annual payments of $5,857 ± $4,660. By summing the average operating costs and the boat loan payments, we calculated the total cash needed to operate the charter business. The total cash necessary was estimated to be $15,300 in 2011 and $18,264 in 2002. The typical charter business that owned and operated a single vessel would have to generate sales of $15,300 in 2011 and $18,264 in 2002 just to have a positive cash flow. Except for businesses with a boat loan in 2011, overall net cash flow in both years was positive for the business models presented in Table 4. All businesses in 2011 reported a 9% de-

TABLE 2. Mean trips per captain and mean revenues per captain by Great Lake for 2002 and 2011. Significant differences are noted by alphabetical superscripts, and the statistics are reported below the table. Lake Superior Year

N

2002

42

2011

Trips 43.9

N 216

Trips 62.8a

Lake Huron N 39

Trips 51.6b

Lake Erie N 276

Lake Ontario Trips

45.8

Trips 60.9

N 689

Trips 53.5c

SD

(35.6)

(53.0)

(34.0)

(42.2)

(56.8)

(48.1)

(5.5)

(3.6)

(5.5)

(2.5)

(5.5)

(1.8)

18

37.0

116

48.9a

18

24.8b

105

40.5

15

74.7

275

44.8c

SD

(27.1)

(40.8)

(18.1)

(41.1)

(51.9)

(40.6)

SE

(6.4)

(3.8)

(4.3)

(4.0)

(13.4)

(2.5)

Year

N 39

20,286

SD

(18,447)

Revenues ($)

SE

(2,953.8)

19

12,688

N 216

Revenues ($) 23,878

N 35

(21,940)

21,781

Revenues ($) 21,783d

N 259

(16,446)

(1,492.8) 110

9,704d

N 101

(23,982)

(2,779.9) 18

Revenues ($) 19,795

17,258

23,990e

N 659

(21,969)

(1,490.2) 97

Revenues ($)

(22,380)

(2,186.0) 12

42,754e

Revenues ($) 21,797

(871.8) 258

19,478

SD

(13,352)

(23,894)

(8,614)

(16,274)

(27,831)

(20,776)

SE

(3,063.5)

(2,278.2)

(2,030.3)

(1,652.4)

(8,034.3)

(1,293.5)

Significantly different, F = 6.035, df = 331, P < 0.05; 95% CI 2002 (55.7, 69.9), 95% CI 2011 (41.4, 56.4). Significantly different, F = 9.779, df = 55, P < 0.01; 95% CI 2002 (40.5, 62.6), 95% CI 2011 (15.8, 33.8). Significantly different, F = 7.003, df = 963, P < 0.01; 95% CI 2002 (49.9, 57.1), 95% CI 2011 (39.9, 49.6). d Significantly different, F = 8.458, df = 52, P < 0.01; 95% CI 2002 (16,133, 27,432), 95% CI 2011 (5,420, 13,987). e Significantly different, F = 7.382, df = 112, P < 0.01; 95% CI 2002 (19,653, 28,327), 95% CI 2011 (25,071, 60,438). a

b c

206

N 106

All

SE

2002

2011

Lake Michigan


crease in revenues ($19,478 ± $20,776) compared to revenues of all businesses in 2002 ($21,797 ± $22,380). The only significant difference between the two survey years was in the average revenues reported for firms with a boat loan (Table 4). Businesses with a positive annual cash flow could pay the day-to-day bills to operate the charter business. Charter firms with negative cash flow would need resources outside the charter business to meet the cash needs of the firm. Total economic costs of operating a charter firm include all costs of operating the charter business, plus capital costs (Table 5). The analysis in Table 5 is by business model. The three models are not summative. Each business model is independent of the others, and each should be seen as a different management situation. Capital costs include boat depreciation and the opportunity cost of owning a boat instead of investing in stocks, bonds, or some other enterprise. Boat loan costs are a cash requirement if a loan exists but are not part of the total economic costs of operating a business. Mean estimated replacement costs for the charter boat and all business-related onboard equipment in 2011 were not significantly different from 2002 (boat: F = 2.509, df= 1,006, P = 0.113; equipment: F = 0.065, df= 947, P = 0.799). Average charter boat length was higher in 2011 at 8.96 m ± 1.6 (29.4 feet) than 2002 at 8.78 m ± 1.23 (28.8 feet). The age of the charter fleet in 2011 was significantly older (F = 57.018, df= 1,074,

P < 0.001) by over four years (20.2 years ± 10.0 vs. 15.9 years ± 8.3) than it was in 2002 (Kuehn et al. 2005). Reported depreciation was $3,864 ± $6,275 in 2011 and $6,086 ± $7,359 in 2002. We estimated interest costs at 5% of the value of the capital equipment, and we considered capital equipment to be the charter boat and all business-related onboard equipment. A total of 26 captains provided estimates for both the replacement cost of their primary charter boat and all onboard equipment. The total economic cost of operating a typical Great Lakes charter business in 2011 was $23,394 compared to $24,717 in 2002. Any revenue in excess of the total economic cost is the return to owner for his or her time and labor. Charter businesses operated at a negative net return of $3,916 in 2011 and negative $2,920 in 2002. Charter fishing is an enterprise that may help subsidize the costs of owning and operating a Great Lakes seaworthy boat. On average, only charter firms with no boat loan and no depreciation costs actually made money for the business owner in 2011 and 2002. Some captains subsidize their business with their own personal funds or in-kind labor and/or management. There is no net return to the business for the owner on average. However, every charter business is a unique enterprise, and some do make money. At an average cost of $481 per trip in 2011 and $464 in 2002, it would take over 32 paid charter trips in 2011 and 40 paid charter trips in 2002 to meet cash flow needs of the

TABLE 3. Average annual operating costs for all reporting boat-owning captains and for three business models (captains reporting boat loans, captains reporting depreciation, and captains not reporting a boat loan or depreciation) are presented. Responses include only six-pack charter businesses that own, lease, or have other boat arrangements. N = number of respondents. The number of businesses reporting boat loans, depreciation, and no boat loans or depreciation exceeds the total number of all businesses reporting due to the fact that a number of respondents reported both a boat loan and depreciation. The 2002 dollar values are adjusted for inflation to 2011 dollars. All businesses Item

Expense ($)

Businesses with boat loan N

Expense ($)

N

Businesses with depreciation

Businesses without boat loan or depreciation

Expense ($)

Expense ($)

N

N

Boat fuel 2002

2,852a

635

3,483

232

3,831

130

2,398b

335

2011

4,201a

235

4,136

67

4,867

50

4,058b

133

Boat dockage 2002

1,771

637

2,037

232

1,912

130

1,599

337

2011

1,764

241

1,782

71

1,565

49

1,775

136

Equipment repair 2002

1,354

636

1,395

232

1,464

130

1,344

336

2011

1,418

242

1,402

72

1,772

48

1,239

137

Boat maintenance and repair 2002

965c

635

1,059

232

1,115

130

892

335

2011

1,236c

247

1,350

71

1,537

49

1,189

142

Miscellaneous 2002

1,029

632

1,299d

231

1,300

129

835

334

2011

821

224

862d

66

1,161

47

703

125

Advertising 2002

1,121

627

1,519

231

1,508

129

842

329

2011

1,124

235

1,060

69

1,406

48

1,078

132

Insurance 2002

982

637

1,076

232

1,168

130

915

337

2011

909

249

919

72

978

50

893

142

Boat storage fees 2002

775e

636

918

232

946

130

670f

336

2011

974e

236

982

71

984

50

965f

130


207

TABLE 3. (continued) Office and communications 2002

785

626

1,136

230

1,320

129

540

329

2011

687

227

690

69

773

49

644

124

Labor (hired) 2002

1,610

624

2,049

230

2,108

129

1,415

327

2011

1,192

211

1,204

67

843

46

1,261

112

Boat repair not covered by insurance 2002

444

636

530

232

619

130

317

336

2011

479

211

415

68

519

44

463

112 335

License fees 2002

203g

632

224

230

251h

129

185i

2011

296

230

297

70

366

49

265

g

h

i

126

Drug testing/professional dues 2002

157

638

191

231

156

129

135

340

2011

125

230

121

67

163

46

113

131

Boat launch fees 2002

66

635

50

231

40

130

82

336

2011

51

217

52

69

45

46

50

117

15,485

230

16,260

130

12,009

416

12,512

128

Total operating costsj 2002

13,213

714

SD

±11,296

2011

13,572

216

SD

±11,779

±13,273 14,869

61

±15,657 14,905

±12,905

40 ±8,044

±10,236

±11,741

Significantly different, F = 29.908, df = 869, P < 0.001. 2002 SD = 2,974, SE = 118.0, 95% CI (2,620, 3,084); 2011 SD = 3,839, SE = 250.5, 95% CI (3,708, 4,694). Significantly different, F = 26.081, df = 467, P < 0.001. 2002 SD = 2,572.8, SE = 140.6, 95% CI (2,122, 2,675); 2011 SD = 4,330.1, SE = 375.5, CI (3,315, 4,801). Significantly different, F = 5.666, df = 881, P < 0.05. 2002 SD = 205.8, SE = 47.9, 95% CI (872, 1,059); 2011 SD = 2,110.4, SE = 34.3, 95% CI (971, 1,500). d Significantly different, F = 4.371, df = 296, P < 0.05. 2002 SD = 1,602.4, SE = 105.4 95% CI (1,091, 1,506); 2011 SD = 1,030.8, SE = 126.9, 95% CI (609, 1,116). e Significantly different, F = 8.014, df = 871, P < 0.01. 2002 SD = 823.6, SE = 32.7, 95% CI (711, 839); 2011 SD = 1,144.9, SE = 74.5, 95% CI (827 to 1,121). f Significantly different, F = 9.040, df = 465, P < 0.01. 2002 SD = 763.3, SE = 41.6, 95% CI (579, 752); 2011 SD = 1,314.5, SE = 115.3, 95% CI (736, 1,193). g Significantly different, F = 18.288, df = 861, P < 0.001. 2002 SD = 219.8, SE = 8.7, 95% CI (186, 220); 2011 SD = 410.7, SE = 27.1, 95% CI (243, 350). h Significantly different, F = 5.274, df = 177, P < 0.05. 2002 SD = 247.0, SE = 21.8, 95% CI (208, 294); 2011 SD = 404.0, SE = 57.7, 95% CI (250 to 482). i Significantly different, F = 8.123, df = 460, P < 0.01. 2002 SD = 211.3, SE = 11.5, 95% CI (163, 209); 2011 SD = 381.1, SE = 34.0, 95% CI (198, 332). j Estimated by taking the mean of the sum of the individual operating costs (where all individual operating costs were given) and the estimated total operating costs (where all operating costs were not given and an estimate of the total operating costs were given). If both were provided, we used the sum of the individual operating costs for the estimate of the total cost. a

b c

business. In 2011 it would take 49 trips and 54 trips in 2002 to provide a net return to the business owner. In 2011, 52% of captains had a positive cash flow and 34% made enough trips to have a positive net return to their charter business. In 2002, these figures were 47% and 36%, respectively. Industry Issues and the Future

Captains in both the 2011 and 2002 surveys were asked to identify the most important problems facing the charter industry. A direct comparison of responses between the two surveys is not possible because survey issue items were different and were asked in a different way in each survey. The top concerns in 2011 were cost of fuel, followed by ANS, the economy, and fisheries management out of a list of 16 items (Table 6). In 2002, top concerns were the economy, lack of fish/reduced abundance, impacts of exotic species such as zebra mussels Dreissena polymorpha, and boating equipment and operating costs (Kuehn et al. 2005). Notably, most concerns are not within control of individual charter captains and have more to do with the economy, state and federal management decisions, fish abundance, and impacts of nonnative invasive species. We asked captains in 2011 and 2002 to respond to a series of items about their plans for the coming five years (Table 7). The majority of charter captains stated that they plan to increase their number of trips and increase prices in both years. Captains indicating no business changes were nearly the same between

208


the 2011 and 2002 surveys (22% vs. 25%, respectively). In 2011, over one-fifth (22%) planned to leave the charter business, and 18% of the responding captains planned to quit in 2002. The actual decline in the number of Great Lakes charter firms from 2002 to 2011 was 12.2%. Although we expect that some new captains will enter the industry, the percentage of captains planning to quit the business in 2011 will likely lead to a decline in the number of charter firms in the future. The final 2011 survey item asked captains to provide additional comments on the impact of ANS regarding their charter fishing business. Over 80% of 122 captains who provided comments were concerned about current or future impacts that ANS have on the Great Lakes and their charter business. Over 20% of the respondents highlighted concerns with three common invasive species found in the Great Lakes: zebra and quagga mussels Dreissena spp., and the Round Goby Neogobius melanostomus. Over 20% of respondents reiterated their concerns regarding the potential arrival of Asian carps (Hypophthalmichthys molitrix, H. nobilis, Ctenopharyngodon idella, and Mylopharyngodon piceus) in the Great Lakes. About 12% of captains who provided comments felt that if Asian carps enter the Great Lakes, the fishery would be devastated. Charter captains were concerned for their businesses and client satisfaction. Concerns also existed for the Great Lakes ecosystem health as a whole, including issues such as water quality, fish consumption safety, and local tourism.

TABLE 4. Average revenue, cash flow needs, and net cash flow to the business for Great Lakes charter boat businesses in 2002 and 2011 estimated by all businesses and for three business models (businesses reporting boat loan payments, businesses reporting depreciation, and businesses not reporting boat loan payments and/or depreciation). Negative numbers are indicated in parentheses. N is the number of actual respondents. The N of businesses reporting boat loans, depreciation, and no boat loans or depreciation exceeds the total N of all businesses reporting due to the fact that a number of respondents reported both a boat loan and depreciation. Responses include only six-pack charter businesses that own, lease, or have other boat arrangements. The 2002 dollar values are adjusted for inflation to 2011 dollars. Income/ expenses

All businesses Amount ($)

Businesses reporting boat loan

Businesses reporting depreciation

Businesses not reporting boat loan payments or depreciation

N

Amount ($)

N

Amount ($)

N

Amount ($)

N

Average revenue 2002

21,797

659

27,635a

215

28,461

126

18,773

379

2011

19,478

258

19,872a

68

20,958

48

19,142

157

Cash flow needs Average operating costs 2002

13,213

714

15,485

230

16,260

130

12,009

416

2011

13,572

216

14,869

61

14,905

40

12,512

128

Boat loan payments 2002

5,051b

269

5,857

232

6,600c

69

NA

NA

2011

1,728

211

5,064

72

1,970

45

NA

NA

b

c

Cash neededd 2002

18,264

21,342

22,860

12,009

2011

15,300

19,933

16,875

12,512

2002

3,533

6,293

5,601

6,764

2011

4,177

(−61)

4,083

6,630

Net cash flowe

a Significantly different, F = 4.619, df = 282, P < 0.05. 2002 SD = 27,449.3, SE = 1,872.0, 95% CI (23,945, 31,325); 2011 SD = 20,506.4, SE = 2,486.8, 95% CI (14,909, 24,836). b Significantly different, F = 76.587, df = 479, P < 0.001. 2002 SD = 4,775.0, SE = 291.1, 95% CI (4,478, 5,625); 2011 SD = 3,116.9 SE = 214.6, 95% CI (1,305, 2,151). c Significantly different, F = 32.753, df = 113, P < 0.001. 2002 SD = 4,545.2, SE = 547.2, 95% CI (5,508, 7,692); 2011 SD = 3,665.7, SE = 546.5, 95% CI (869, 3,072). d Sum of average operating costs and average boat loan payments. e Average revenue minus the cash needed to operate the business.

CONCLUSION We have provided a considerable amount of detail on the business operations of a large freshwater charter industry. Our research may assist those interested in the charter fishing industry to make more informed decisions. A better understanding of the economic and social dimensions of the Great Lakes charter industry may be helpful to fishery professionals and resource managers in making management decisions. Additionally, our work with the Great Lakes charter industry may be a useful model for others interested in the development of charter industries in other parts of the world. With almost 76,000 paid charter trips taken in 2011, accounting for an estimated $36.4 million in revenues, the charter fishing industry is a significant presence in the Great Lakes. The industry offers many anglers the opportunity to safely and successfully fish open waters of the Great Lakes. However, we document a decline in the number of charter businesses (12%), number of trips (27%), and total revenues generated (24%) in 2011 compared to 2002. Multiple factors can impact angler decisions to participate in charter fishing, and some of these are not dependent on the professionalism or aptitude of captains (Oh et al. 2005, 2012). For example, weather was a major factor in 2011 as some of the Great Lakes experienced a stormy spring and summer. Some captains indicated that the poor weather may have caused more

cancellations than in other years. Increased frequency of harmful algal blooms, new ANS introductions, fish habitat loss due to development or pollution, and declining sportfish populations may all have a negative influence on the industry. Additionally, in unsettled economic times, households might choose to focus on personal finances rather than recreation, which may decrease the number of anglers utilizing the charter industry. Captains have management options when attempting to keep their businesses viable. Factors within the individual captain’s control such as marketing, people skills, fishing expertise, and the quality of customer service can impact their success. Captains may be cutting costs where possible to offset price increases. Some businesses may reduce or eliminate boat loan payments and reduce cash flow needs by holding onto their boats longer. Captains may also reduce or eliminate depreciation costs by relying on older boats, thus lowering the total economic cost of running a charter business. These savings could help offset significant increases in boat fuel, storage, maintenance, and license fees seen in 2011 compared to 2002. The nature of the charter industry has not changed significantly over the time period we examined. Declining numbers of paid trips and declining revenues are a concern, and 2011 may provide a conservative benchmark for future comparisons. However, the attraction of being in the charter industry remains fairly constant. Captains want to help people enjoy fishing and like the Fisheries | www.fisheries.org

209

TABLE 5. Economic cost components, total economic cost, and net return to the operator for Great Lakes charter boat businesses in 2002 and 2011 estimated by all businesses and for three business models (businesses reporting boat loan payments, businesses reporting depreciation, and businesses not reporting boat loan payments and/or depreciation). Negative numbers are indicated in parentheses. N is the number of actual respondents. The N of businesses reporting boat loans, depreciation, and no boat loans or depreciation exceeds the total N of all businesses reporting due to the fact that a number of respondents reported both a boat loan and depreciation. Responses include only six-pack charter businesses that own, lease, or have other boat arrangements. The 2002 dollar values are adjusted for inflation to 2011 dollars. Item

All businesses Amount ($)

Businesses reporting boat loan

Businesses reporting depreciation

Businesses not reporting loan or depreciation

N

Amount ($)

N

Amount ($)

N

Amount ($)

N

Average revenue 2002

21,797

659

27,635a

215

28,461

126

18,773

379

2011

19,478

258

19,872

68

20,958

48

19,142

157

a

Economic cost Average operating costs 2002

13,213

714

15,485

230

16,260

130

12,009

416

2011

13,572

216

14,869

61

14,905

40

12,512

128

Capital costs Opportunity costsb 2002

5,418

677

5,827

210

6,773

123

5,035

405

2011

5,958

265

6,171

64

6,521

48

5,769

166

2002

6,086c

138

7,526

62

6,460

130

NA

NA

2011

3,864c

87

7,355

18

6,723

50

NA

NA

Depreciation

Total capital costs 2002

11,504

13,353

13,233

5,035

2011

9,822

13,526

13,244

5,769

Total economic cost

d

2002

24,717

28,838

29,493

17,044

2011

23,394

28,395

28,149

18,281

Net return to operatore 2002

(−2,920)

(−1,203)

(−1,032)

1,729

2011

(−3,916)

(−8,523)

(−7,191)

861

Significantly different, F = 4.619, df = 282, P < 0.05. 2002 SD = 27,449.3, SE = 1,872.0 95% CI (23,945, 31,325); 2011 SD = 20,506.4, SE = 2,486.8, 95% CI (14,909, 24,836). b Opportunity costs are estimated at 5% of the average estimated replacement cost of the boat and onboard equipment. c Significantly different, F = 5.435, df = 224, P < 0.05. 2002 SD = 7,359.0, SE = 626.4 95% CI (4,847, 7,324); 2011 SD = 6,275.2, SE = 672.8, 95% CI (2,527, 5,202). d Total economic cost equals average operating costs plus total capital costs (opportunity cost plus depreciation). e Net return is equal to the average revenue minus the total economic cost of running the charter business. a

work. The opportunity to make additional income is a secondary reason for being a charter captain. Captains are concerned about external factors such as ANS and the economy that could impact success. Captains appear to have made management decisions, such as keeping boats that are paid off and/or fully depreciated, as a way to improve the economic viability of their business. Not all of the Great Lakes experienced the same changes in revenues and number of trips per charter captain between 2002 and 2011. O’Keefe et al. (this issue) note that Lake Huron experienced what could be described as a crash in charter fishing, whereas other Great Lakes saw less drastic changes. Knowing why changes occurred is a necessary step if we are to further assist fishery managers and the industry. Identifying possible causes of why changes in the industry occur is an open field for future research. Our data suggest that one would need to look at

210


each Great Lake separately in order to discover why changes in the charter fishery occur. The accompanying article by O’Keefe et al. (this issue) does just that, by documenting efforts to identify existing data that may explain why the Lake Huron change was so dramatic. ACKNOWLEDGMENTS The authors thank Carmina Chiappone, Dena Abou-elSeoud, and Lorraine Cordova for their assistance with this study. We thank our Great Lakes Sea Grant Network coworkers Jeff Gunderson, Karla Kaczmarek, Dave MacNeill, Phil Moy, Kathleen Schmitt-Klein, and Sarah Zack for their contributions to the project . Thanks to Eugene Braig, Justin Chaffin, Kristin Stanford, Thomas Blaine, and two anonymous reviewers for their helpful reviews of manuscript drafts.

A successful Lake Erie Walleye angler. Photo credit: Ohio Sea Grant.

TABLE 6. Concerns of the Great Lakes charter fishing industry in 2011. Respondents were asked to rate each of the listed issues on a scale of 1 = least important to 5 = most important. Means and standard deviations are rounded to the nearest tenth. Concern

Mean score

Standard deviation

TABLE 7. Five-year plans of Great Lakes charter captains in 2002 and 2011 (number of respondents is 868 in 2002 and 335 in 2011). Respondents were asked to select all of the plans that applied to them. Percentage of respondents selecting a change planned for their charter activities in the next 5 years

Number of respondents

Cost of fuel

4.4

±0.9

338

Aquatic nuisance species

4.4

±0.9

334

Activity

2011

2002a

Increase number of annual trips

58.5

57.9

Economy

4.2

±0.9

335

Fisheries management

4.0

±1.1

330

Increase prices of charter services

41.0

49.3

Decrease in the forage fish population

4.0

±1.1

329

No major changes

21.8

25.4

Low sportfish populations

4.0

±1.2

332

Quit the charter business

17.7

21.5

Harmful algal blooms

3.8

±1.4

328

Buy/operate a newer boat

19.2

17.0

Obtaining new clients

3.7

±1.2

332

Buy/operate a bigger boat

14.1

14.3

Habitat loss

3.6

±1.3

325

Branch out into other fishingrelated businesses

9.6

12.5

Sportfish catch limits

3.2

±1.3

327

Decrease number of annual trips

6.5

11.3

Illegal fishing practices

3.2

±1.4

327

Hire additional first mate(s)

7.7

11.3

Poor weather

3.1

±1.3

331

11.0

2.7

±1.2

329

Expand into multi-activity and/or nonfishing charters

8.5

Fish consumption advisories

Hire additional charter captain(s)

5.8

10.1

Overcrowding of the fishery

2.6

±1.1

326

Buy/operate an additional boat

4.8

8.7

Interstate licensing

2.4

±1.2

328

Other

7.8

7.2

Other

4.7

±0.8

58

Buy your own charter boat

2.2

3.3

Decrease prices

0.7

0.7

a

2002 data from Kuehn et al. (2005).


211

Charter boats docked and ready to go at Grand River, Ohio. Photo credit: Ohio Sea Grant.

Finally, we thank all of the captains who responded to the 2011 Great Lakes Charter Captains survey. FUNDING This work was supported, in part, by grants from the U.S. Department of Commerce, National Oceanic and Atmospheric Administration (NOAA grant NA12OAR4170059 and NOAA grant NA10OAR4170074) to the Ohio Sea Grant College Program. The NOAA grant NA12OAR4170059 was made possible by an interagency pass through of funds from the USACE as part of the Great Lakes Mississippi River Interbasin Study (GLMRIS) authorized by Section 3061(d) of Water Resources Development Act of 2007. Support was also provided by the Ohio Board of Regents, the Ohio State University, and Ohio State University Extension. REFERENCES BLS (Bureau of Labor Statistics). 2014. Consumer price index inflation calculator. Available: www.bls.gov/data/inflation_calculator. htm. (January 2014). Dawson, C. P., F. R. Lichtkoppler, D. Kuehn, and C. Pistis. 1995. Great Lakes charter fishing industry: 1973–1994. Pages 573–576 in J. L. Thompson, D. W. Lime, B. Gartner, and W. M. Sames, editors. Proceedings of the Fourth International Outdoor Recreation and Tourism Trends Symposium and the 1995 National Recreation Resource Planning Conference. University of Minnesota, College of Natural Resources and Minnesota Extension Service, St. Paul. Dawson, C. P., F. R. Lichtkoppler, and C. Pistis. 1989. The charter fishing industry in the Great Lakes. North American Journal of Fisheries Management 9:493–499. Dillman, D. A. 1978. Mail and telephone surveys: the total design method. John Wiley & Sons, New York. ———. 2000. Mail and Internet surveys: the tailored design method, 2nd edition. John Wiley, New York.

212


Great Lakes Fishery Commission. 2011. Strategic vision of the Great Lakes Fishery Commission 2011–2020. Available: www.glfc.org/ pubs/SpecialPubs/StrategicVision2012.pdf. (December 2013). Kuehn, D., F. Lichtkoppler, and C. Pistis. 2005. The Great Lakes charter fishing industry; 1973 to 2002. Fisheries 30(3):10–17. Lichtkoppler, F., C. Pistis, and D. Kuehn. 2003. The Great Lakes charter fishing industry in 2002. Ohio Sea Grant, OHSUTS-039, Columbus. Lindner, J. R., T. H. Murphy, and G. E. Briers. 2001. Handling nonresponse in social science research. Journal of Agricultural Education 42(4):43–53. Lindner, J. R., and G. J. Wingenbach. 2002. Communicating the handling of nonresponse error in Journal of Extension Research in Brief articles. Journal of Extension 40(6). Available: www.joe. org/joe/2002december/rb1.php. (December 2013). Miller, L., and K. Smith. 1983. Handling nonresponse issues. Journal of Extension 21(5):45–50. ODW (Ohio Division of Wildlife). 2012. Ohio’s Lake Erie Fisheries, 2011. Annual status report. Federal Aid in Fish Restoration Project F-69-P. Ohio Department of Natural Resources, Division of Wildlife, Lake Erie Fisheries Units, Fairport and Sandusky. Oh, Chi-Ok, R. Ditton, B. Gentner, and R. Riechers. 2005. A stated preference approach to understanding angler preferences for management decisions. Human Dimensions in Wildlife: An International Journal 10(3):173–186. Oh, Chi-Ok, S. Lyu, and S. Holand. 2012. Understanding tourists’ preferences for boat fishing trips. Tourism Economics 18(2):413–429. Rasmussen, J. L., H. A. Regier, R. E. Sparks, and W. W. Taylor. 2011. Dividing the waters: the case for hydrologic separation of the North American Great Lakes and Mississippi River Basins. Journal of Great Lakes Research 37:588–592. USACE (United States Army Corps of Engineers). GLMRIS Team. 2013. Great Lakes charter fishing industry—baseline economic assessment. Appendix D: Economic assessment; Attachment 3: Charter fishing; D-443-D484. Available: glmris.anl.gov/glmrisreport. (January 2014). ———. 2014. Summary of the GLMRIS report—Great Lakes and Mississippi River Interbasin Study. Available: glmris.anl.gov/documents/docs/glmrisreport/GLMRISSummaryReport.pdf. (January 2014).

FROM THE ARCHIVES The World Leader & Innovator in Fish Tags

• Call 800-843-1172 to discuss your custom tagging needs • Email us at [email protected] • View our website for our latest catalog www.floytag.com

“Westward the Star of Empire Takes Its Way.”-Berkeley When the poet wrote the above line, he little recked how soon they would come true, especially in fishery matters. First the Atlantic Coast of North America wrested the fishery preeminence from the old world, and for many years our fishing vessels, manned by the hardiest and most daring fishermen the world has seen up to that time, plowed the seas from the icebound fastnesses of the Arctic to the even more difficult ones of the Antarctic. As time went on, and the shore of the Pacific gradually became peopled with the hardy pioneers of the East and Middle West, including also some of those who had participated in the later stages of the wonderful development of the Atlantic fisheries, and the descendants of others, the infant fisheries of the Pacific began to attract attention. John N. Cobb (1923): The Future of the Fisheries of the Pacific, Transactions of the American Fisheries Society, 53:1, 65.

floy tag ad3.indd 1

1/24/2013 6:45:34 PM

A GRADER THAT MAKES YOUR JOB EASIER Now you can adjust grading sizes without juggling multiple baskets. Our graders float, adjust quickly and have larger bars so fish pass through with little chance of gill damage. Perfect for fresh or salt water, choose either the 30 or 50 settings model. 15” x 17” x 11.5” Larger size also available.

Check out our aerators and feeder too!

Visit www.freshflo.com for more details.

Wisconsin • USA • 920-208-1500


213

FEATURE

214


Factors Influencing Charter Fishing Effort Trends in Lake Huron From 2002 to 2011, the number of charter fishing trips in Michigan waters of Lake Huron declined by 51%. Declines in catch rates, rising gasoline prices, and the economic downturn have been suggested as possible reasons for this decline. To better understand the relative importance of these factors, five catch-based and six economic variables were evaluated using multiple regression, with charter effort from 1992 to 2011 as the response variable. Declining catch rate of introduced Chinook Salmon Oncorhynchus tshawytscha was more closely linked to declining effort than catch rate of native Lake Trout Salvelinus namaycush or Walleye Sander vitreus. The price of gasoline was a better predictor of effort than other economic variables. Although Chinook Salmon catch rate explained more variation in charter effort than any other variable, factors beyond the influence of fisheries management also influenced effort. Ecosystem changes that led to declines in salmon abundance created favorable conditions for Walleye, leading to some localized increases in charter effort.

Factores que influencian las tendencias del esfuerzo pesquero con embarcaciones de alquiler en el Lago Hurón En aguas del Lago Hurón, en Michigan, de 2002 a 2011, el número de días de pesca realizados con embarcaciones de alquiler disminuyó 51%. La reducción de las tasas de captura, el alza de los precios de la gasolina y la recesión económica, se sugieren como las razones de esta caída. Con el fin de conocer la importancia relativa de estos factores, se evaluaron seis variables basadas en la captura y cinco variables económicas mediante una regresión múltiple; el esfuerzo de pesca de 1992 a 2011 se utilizó como variable de respuesta. La reducción en la tasa de captura del salmón introducido Oncorhynchus tshawytscha fue la variable que mejor se relacionó con la disminución del esfuerzo, más que la tasa de captura de la trucha nativa Salvelinus namaycush o la de la lucioperca americana Sander vitreus. El precio de la gasolina fue un mejor predictor del esfuerzo en comparación a cualquier otra variable económica. De todas las variables, la tasa de captura del salmón real explicó una mayor variación del esfuerzo de pesca con embarcaciones alquiladas, no obstante existen factores independientes al manejo pesquero que tienen influencia en el esfuerzo. Los cambios en el ecosistema que provocan modifican la abundancia de salmón crearon condiciones favorables para la lucioperca, lo que provocó condiciones favorables localizadas para que se incrementara el esfuerzo de embarcaciones alquiladas.

Daniel M. O’Keefe Michigan Sea Grant, Michigan State University Extension, 12220 Fillmore Street, Stuite 122, West Olive, MI 49460. E-mail: [email protected] Donna L. Wesander Michigan Department of Natural Resources, Charlevoix Fisheries Research Station, Charlevoix, MI Chi-Ok Oh Graduate School of Culture, Chonnam National University, Kwangju, South Korea


215

INTRODUCTION Great Lakes charter fishing expanded rapidly following the stocking of Chinook Salmon Oncorhynchus tshawytscha and Coho Salmon O. kisutch in the late 1960s (Dawson et al. 1989). These introduced piscivores preyed heavily on abundant exotic Alewife Alosa pseudoharengus. Abundant prey, along with development of an effective Sea Lamprey Petromyzon marinus control program and a shift in fisheries management philosophy, led to the development of recreational and charter fisheries and a decline in commercial fisheries (Bence and Smith 1999; Brown et al. 1999). Steelhead O. mykiss, Brown Trout Salmo trutta, and Lake Trout Salvelinus namaycush are now caught along with Chinook and Coho salmon by charter anglers using fishing methods that successfully target a variety of salmonine species (Bence and Smith 1999). Walleye Sander vitreus and Yellow Perch Perca flavescens support charter fishing opportunities that have more limited overlap with salmonines (Bence and Smith 1999) due to thermal and physical habitat differences and vulnerability to different fishing methods. Since 2002, the fish community of Lake Huron (Figure 1) has undergone drastic changes. During this time period, Lake Huron experienced a severe decline in Chinook Salmon abundance following a period of increasing natural reproduction and the collapse of Alewife (Roseman and Riley 2009; Johnson et al. 2010). The decline of Alewife in turn led to a substantial increase in recruitment of Walleye (Fielder et al. 2007). These changes have been particularly important for Saginaw Bay (Figure 1), where shallow water and warmer temperatures are more suitable for Walleye than salmonines. As the species composition of charter catches changed (Figure 2), charter fishing effort in Michigan waters of Lake Huron dropped from 2,880 trips in 2002 to 1,399 in 2011 (Wesander and Clapp 2013). Several studies have documented lower food web changes caused by exotic species in Lake Huron (Nalepa et al. 2007; Bunnel et al. 2011), the collapse of the Lake Huron demersal fish community (Riley et al. 2008), and resulting changes in piscivorous fish populations (Fielder et al. 2007; Riley et al.

2007; Johnson et al. 2010). Although the decline of Alewife in the early 2000s was perhaps the most dramatic example of Lake Huron’s changing forage base, changes in the lake’s demersal fish community began in the mid-1990s (Figure 3) and occurred at a time when the quagga mussel Dreissena rostriformis bugensis was expanding within the Lake Huron basin (Nalepa et al. 2007). Though ecological changes have influenced catch rates and catch composition, charter captains also cite the difficult economic climate and high gasoline prices as reasons for declining business. The Great Global Recession of 2009 was particularly problematic for the automobile manufacturing industry. Lake Huron captains may historically have been more dependent upon automobile industry employees from the metropolitan areas of Flint and Detroit, Michigan, than captains on other lakes closer to more diversified economies (Michigan Sea Grant 2009). While the customer base from southeast Michigan was declining (O’Keefe and Miller 2011), the price of gasoline more than doubled. The cost of fuel was at the top of the list of Great Lakes charter operators’ concerns in a 2011 survey (Lichtkoppler et al., this issue). Understanding the relative importance of economic vs. catch-based factors may help fisheries managers determine whether ecological changes have been driving charter effort trends or whether economic factors beyond their influence are likely responsible for the recent decline. Our first objective was to identify the catch-based variable most strongly related to charter fishing effort in Michigan waters of Lake Huron. Our second objective was to identify the most important economic variable in a similar manner. We then sought to incorporate possible lag-time effects and investigate the relative importance of the best-performing economic and catch-based variable. METHODS Charter Catch and Effort Reporting

Reporting of fishing effort and harvest by the charter fishing industry is required under Michigan’s Public Act 451 (Part 445) of 1994. The law stipulates that charter operators keep an up-todate daily log of their fishing activity onboard their vessel at all times. Charter fishing catch and effort have been reported to the Michigan Department of Natural Resources (MDNR) by each charter operator on a monthly basis since 1990. For purposes of charter effort reporting, “Lake Huron” includes the lake proper from its outlet at the St. Clair River north through the St. Marys River to its source at Lake Superior and west through the Straits of Mackinaw at St. Ignace and Mackinaw City. Charter reporting for Michigan waters of Lake Huron also includes Saginaw Bay and tributaries such as the AuSable and Saginaw rivers. For the remainder of this article, Lake Huron will be used to refer to state of Michigan waters of the lake proper in addition to the above-mentioned connecting waters. Regression Methods

Figure 1. The Lake Huron watershed straddles the border between the United States and Canada. Saginaw Bay is shallower and more productive than offshore waters. Image credit: Todd Marsee.

216


Time series data refer to sequentially observed data points collected at consistent time intervals. Regression techniques are often used to analyze time series data that include catch and effort (Hubert and Fabrizio 2007), and the inclusion of a lag-time variable in multiple regression modeling is one approach to account for the possibility of autocorrelation. Our use of a 20-year annual data series limits the number of predictor variables that can be included in multiple regression models to three based on the recommendation of Hair et al. (2010) to keep the ratio of observations to variables above 5:1. Given this limitation, the complexity of Great Lakes fisheries, and the large number of factors

Model Selection

The best predictor variable for each of the three classes noted above was selected for inclusion in allsubsets regression based on its performance relative to other variables in its class (Table 1). Performance criteria included statistical significance (F test; α = 0.05 with Bonferroni correction for 13 variables) and greater R2 value than other variables in the same class. Log transformation was necessary to meet the assumption of linearity for most variables and was applied to all independent variables. Assumptions of residual normality, homoscedasticity, and linearity were met for all variables with the exception of salmonine catch per unit effort Figure 2. The number of charter fishing trips taken in Michigan waters of Lake Huron declined in (CPUE), Lake Trout CPUE, and U.S. the 2000s as catch composition changed dramatically. Data provided by Michigan Department of Natural Resources. gross domestic product (GDP). Salmonine and Lake Trout CPUE residuals did not appear to follow a normal distribution when using the conservative Anderson-Darling test (null hypotheses were rejected at α = 0.05), but the less conservative Jarque-Berra test failed to detect deviation from normality (failed to reject null hypotheses at α = 0.05). Linear regression is not particularly sensitive to minor violations of the normality assumption (Kleinbaum et al. 2007), and the differing results of the two normality tests suggest that any deviation of salmonine and Lake Trout CPUE residuals from normality was not severe. Although both tests found that U.S. GDP residuals followed a normal distribution (Anderson-Darling test and Jarque Berra test failed to reject null hypothesis at α = 0.05), the Figure 3. Biomass estimates based on bottom trawl surveys conducted from 1976 to 2013 illusrelationship between U.S. GDP and trate declines in Trout-perch Percopsis omiscomaycus, Ninespine Stickleback Pungitius pungitius, charter effort was nonlinear. Low Deepwater Sculpin Myoxocephalus thomsonii, Slimy Sculpin Cottus cognatus, Bloater Coregonus hoyi, Rainbow Smelt Osmerus mordax, and Alewife in Lake Huron from 1994 to 2005 along with effort occurred at both high and low the arrival of Round Goby Neogobius melanostomus. Figure credit and data source: U.S. Geologivalues of U.S. GDP with high effort cal Survey (reprinted from Riley et al. 2014). occurring at intermediate U.S. GDP. Late in the time series, U.S. GDP reached its highest point while that could influence charter fishing effort, we chose a multiple effort declined, suggesting that the Lake Huron charter fishery regression approach that balanced the strengths and weaknesses did not benefit from improving national economic trends. of both sequential search and combinatory approaches. Limiting the number of variables included in all-subsets reThe sequential search phase (forward inclusion) was used to gression to one from each class reduced the potential for multiselect the best single predictor variable from a suite of varicollinearity, which would have been severe if multiple variables ables within a given class (catch-based, economic, and effort within a given class had been included. This approach was also time lag), and the combinatory phase (all-subsets regression) parsimonious and appropriately limited the number of independsubsequently incorporated these forward-included variables in a ent variables given the limited time series available. Multicolfull model that was compared with all possible subsets containlinearity among top variables from each class was evaluated ing one or more of these included variables (Hair et al. 2010). using variance inflation factors (VIFs), with VIF values above This two-phase approach allowed for the possible inclusion of 5 considered indicative of multicollinearity (Rahel and Jackson all variable classes relevant to our objectives while limiting the 2007). Two quality-of-fit measures were calculated for competmaximum number of full-model predictor variables to three ing models: second-order Akaike’s information criterion (AICc) (Hair et al. 2010). Fisheries | www.fisheries.org

217

and adjusted R2 (Rahel and Jackson 2007). We calculated Akaike weights (wi) to provide the probability of each model being correct in the context of all models being considered (Burnham and Anderson 2002; Rook et al. 2012). Catch-Based Variables

We considered five catch-based variables for forward inclusion during the sequential search phase of analysis. We calculated catch rates (number of fish harvested per angler hour) on an annual basis from 1992 to 2011 using recreational angler catch and effort data from the MDNR creel census program (see Rakoczy and Svoboda [1997] for detailed methods). These CPUE values did not include charter angler data, which would have compromised the independence of the charter effort response variable. We excluded pier and shore angler catch and effort from CPUE calculations; therefore, calculations only included recreational anglers fishing from boats and using methods similar to those employed by charter anglers. Total effort for all species was used to calculate catch rates because recording of targeted effort did not begin until 1997. Recreational angler CPUE was calculated for Walleye, Chinook Salmon, Chinook and Coho salmon combined, and all salmonines (Chinook Salmon, Coho Salmon, steelhead, Lake Trout, and Brown Trout combined). The ability of each of these CPUE variables to predict charter effort in a given year was evaluated using linear regression. The CPUE for the species or combination of species that best predicted charter effort was subsequently included in all-subsets regression. Economic Variables

Indicators of economic climate include total employment, unemployment rate, and GDP or gross regional product. RelTABLE 1. Linear regressions were used to select the topperforming independent variable within each of three classes (catch-based, economic, and effort lag time); each independent variable was log-transformed. The annual number of charter fishing trips taken from 1992 to 2011 in Michigan waters of Lake Huron served as the response variable. Class and variable

β

R2

P valuea

Catch-based (CPUE) All salmonines

0.887

0.786