Dataciencia

Revista	ISSN
	2578-4854

Revista

ISSN

2578-4854

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WOS
Sin Disciplinas

WOS

Sin Disciplinas

Scopus
Sin Disciplinas

Scopus

Sin Disciplinas

SciELO
Sin Disciplinas

SciELO

Sin Disciplinas

Muestra la distribución de disciplinas para esta publicación.

Publicaciones WoS (Ediciones: ISSHP, ISTP, AHCI, SSCI, SCI), Scopus, SciELO Chile.

Ord.	Autor	Género	Institución - País
1	Snyder, Hunter T.	Hombre	Thayer School of Engineering at Dartmouth - Estados Unidos
2	Oyanedel, Rodrigo	Hombre	University of Oxford - Reino Unido Centro de Investigacion Dinamica de Ecosistemas Marinos de Altas Latitudes - Chile
3	Sneddon, Christopher S.	Hombre	Dartmouth College - Estados Unidos
4	Scheld, Andrew M.	Hombre	Virginia Institute of Marine Science - Estados Unidos

Ord.

Autor

Género

Institución - País

Snyder, Hunter T.

Hombre

Thayer School of Engineering at Dartmouth - Estados Unidos

Oyanedel, Rodrigo

Hombre

University of Oxford - Reino Unido
Centro de Investigacion Dinamica de Ecosistemas Marinos de Altas Latitudes - Chile

Sneddon, Christopher S.

Hombre

Dartmouth College - Estados Unidos

Scheld, Andrew M.

Hombre

Virginia Institute of Marine Science - Estados Unidos

Fuente
University of Cape Town
Greenland Fisheries License Control Authority
NASCO
Association of Hunters and Fishers in Greenland
APNN
UCT exercise
GFLK
KNAPK
salmon fishers endure structural challenges
Government of Greenland Fisheries Department

Fuente

University of Cape Town

Greenland Fisheries License Control Authority

NASCO

Association of Hunters and Fishers in Greenland

APNN

UCT exercise

GFLK

KNAPK

salmon fishers endure structural challenges

Government of Greenland Fisheries Department

Agradecimiento
We estimated that nearly all of Greenland's salmon fishers comply with salmon fishery regulations, especially salmon catch reporting. Specifically, the 2018 Executive Order on the Fishing of Salmon required salmon fishing license holders to report, or else lose their license renewal for the following year. The proportion of salmon fishers who reported their catch continued to increase from 2018 to 2019. This high level of compliance is perhaps unsurprising given the historic familiarity that Greenlanders have with reporting marine and terrestrial harvests (Dahl-Petersen et al., 2014). However, salmon catch reporting compliance levels have risen from 2017 to 2019, and is thought to be due in part to the implementation of new legislation (Government of Greenland, 2020). Using regulatory deterrents and nudges can help ensure high levels of compliance into the future (Snyder et al., 2021). In the face of changes to their routine, fishers do have the capacity to further comply. Even though fishers can earn an income from salmon catch, and enforcement is known to be lacking, few fishers indicated instrumental motivations to not report all their salmon catch. While it is not possible from our statistical analysis to conclusively infer what drives their compliance, fishers have generally positive perceptions of the regulations that govern their access and they look positively upon the authorities that enforce those regulations. In addition, high levels of compliance, high levels of agreement with normative attitudes, low levels of instrumental motivations, and high levels of perceived regulatory legitimacy is auspicious for a future where users, managers, and regulators work together to manage access to Atlantic salmon stocks. Voluntary compliance can persist if fishery managers are perceived to act professionally, honestly, and fairly. We anticipate that if Atlantic salmon stocks continue to decline, what is deemed fair will become controversial among salmon fishers in Greenland. These results also reaffirm the value of the compliance framework approach for understanding compliance in small-scale fisheries (Oyanedel et al., 2020b; Ramcilovic-Suominen & Epstein, 2012). Increasing collaboration between salmon fishers and managers is also likely feasible, given that nearly 60% of Greenland's salmon fishers said that they would provide more information by SMS message if the means to do so existed. Salmon fishers' willingness to share observations and ideas is substantial. The Association of Hunters and Fishers in Greenland (KNAPK) supports this level of communication during annual visits along the coast, and the sharing of ideas between and across individuals, local branch managers, and head office officials. Conservationists should continue to engage with local associations and participate in visits to maintain the common understanding that helps make compliance possible in this fishery. We illustrate how measuring fishers' attitudes can identify opportunities that arise for compliance or noncompliance. Crime script analysis, which parses noncompliance into a series of discrete events, identifies the specific components of salmon fishery compliance with catch reporting requirements. We identified an individual process, in this case, how salmon catch reporting is conducted. This isolates the process-based factors that contribute to perceptions of legitimacy, such as the professional conduct of fishery officers or the ease of reporting salmon catch. Our survey instrument made it possible to measure how people report salmon catch, how they think catch reporting can be improved, and among which groups salmon catch reporting is most challenging. Catch reporting is not mandatory in many recreational fisheries, and as a result, it is not normally possible to evaluate fisheries compliance by linking survey responses with official catch records (Midway et al., 2020). Because we were able to combine these data types, we can evaluate the possibility of respondent bias, given that achieving a census was unlikely and representative results are most valuable to fishery managers and intervention-oriented conservationists. Official catch records also shed light on the integrity of individual survey questions and associated responses. Salmon fishers more readily disclosed not reporting all of their catches when asked indirectly, and at the same time, we observed six cases where fishers said they reported all their catches, whereas the official records suggest that they did not. These six fishers who said that they reported all of their salmon catch to the Government of Greenland may have in fact reported their catch, even though the official record shows that they did not. It is possible that their reports could have been submitted, but were either never received, were never filed, or were submitted incorrectly. It is also possible that the respondents did not understand the question, or that they inputted the incorrect response. Responses to direct questions are doubted for their veracity, which further justifies the use of UCT for indirectly asking sensitive questions. UCT questions may increase the estimated incidence of salmon catch underreporting, but our results lack signifance to confidently support this claim. Even though the UCT estimate is larger, salmon catch underreporting is small, with <10% of respondents indirectly indicating that they underreported their salmon catch. These results should be interpreted with the likelihood that both direct and indirect questions could be underestimated. Apart from the UCT exercise, all other survey questions were direct questions. Given that the UCT exercise revealed that direct catch reporting may be underestimated, it is possible that all direct questions may be systematically underestimated. However, the majority of survey questions posed were not about sensitive behavior, so it is not justifiable to doubt their accuracy. This specific use of UCT shows that it can be an easy-to-administer tool (Nuno et al., 2013) and that UCT can even be conducted via online survey instruments. Our study reinforces the necessity of carefully selecting both sensitive and nonsensitive items in the design phase (Hinsley et al., 2017). Though not commonly included, our study provides respondents with a warm-up, practice UCT question, which gave respondents familiarity with how to answer the question and provides further assurance that the UCT questions were answered correctly (Hinsley et al., 2017). However, the variability that can arise in a UCT must be lessened for the effect to be detected and interpreted as significant; in this case, that is not possible. Future studies that use UCT should take extra care to revise nonsensitive statements and sensitive statements to reduce the likelihood of variability in the estimate. The results of this study also reaffirm that illegal behavior does not always translate to an unwillingness to divulge information (Hinsley et al., 2019). Instead, this study shows that illegal behavior can be shared, and we argue that the triviality of sanctions for such behavior in this specific setting may explain why resource users are willing to divulge such information. Linking official salmon catch records with survey responses also allowed us to identify an overall lack of variance in responses between reporters and nonreporters. We hypothesized that nonreporters have systematically different attitudes or perspectives to those who do report salmon catch. With the exception of two questions, we were unable to meaningfully show that a fishers' attitudes explain their actual salmon catch report status. However, results suggest that fishers who do not know how to report salmon catch or who find salmon catch reporting confusing are less likely to report salmon catch. There is a need to further simplify reporting to eliminate this confusion. Greenland's fishery managers also have the opportunity to familiarize license holders with how to report their catch when they are issued their licenses, especially among fishers with less experience in the fishery. As seen in this study and others, fishers with less experience are more likely to exhibit involuntary noncompliance, but experienced fishers can also find the rules confusing (Jentoft & Mikalsen 2004). Imbalanced samples are a persistent challenge for studying noncompliance because we most wish to hear from people who are understandably reluctant to answer questions about their noncompliant behavior (Larkin et al., 2010; van der Hammen et al., 2016). We were therefore pleased that 9% of responses came from salmon fishing license holders who did not officially report salmon catch to the Government of Greenland. This percentage is high, given that only 14% of all salmon fishing license holders did not report salmon catch in 2019 (Government of Greenland, 2020). While we cannot be certain, our tests that evaluated differences between the survey pool and the overall population, as well as comparisons between reporters and nonreporters, give us confidence that the survey pool is otherwise representative of the salmon fishing license holder population, in terms of salmon counts, catch, license types, and participating localities. However, we recommend eliciting more perspectives from the professional salmon fishing population, recognizing that professional salmon fishers are slightly underrepresented in the survey response pool. They are also the individuals catching the greatest quantities and weights of salmon. It is possible that this professional segment did not respond to the survey because they were participating in spring fishing or were affected by the economic shocks of the COVID-19 pandemic, which began during the period when the survey was issued. Future research could include follow-up surveys by phone or in person among salmon fishing license holders who did not submit their salmon catch reports during the 2019 season, or among those who chose not to participate in the salmon fishing survey. Having their responses included would capture a more complete picture of what drives salmon catch reporting. Scholars who are particularly interested in the attitudes of noncompliant resource users would especially benefit from a more complete survey of nonreporters. We saw a high response rate to the Salmon Fishing Survey of 37% despite the online format and completion during the COVID-19 pandemic. This participation suggests that Greenlanders have something to say about salmon fishing and want to be involved in how Greenland's fisheries are governed. This participation and compliance is consistent with studies that show that positive perceptions of governance structures are key to participation and support (Bennett & Dearden, 2014; Bubier, 1988; Evans et al., 2011). High levels of participation are also an auspicious indicator of research that lives up to goals and objectives to conduct inclusive, respectful, and beneficial research in, for, and with Inuit communities (National Inuit Strategy on Research, 2018). These results have been distributed among Greenland's salmon fishery policymakers and all salmon fishers were given access to results in summer 2020. They have informed the dialogue between NASCO members and Greenland's efforts to manage its access to Atlantic salmon stocks within its exclusive economic zone. Importantly, they have clarified long-standing beliefs about underreported salmon catch. While these results suggest that Greenland's salmon fishers have high moral standards and enforcement officials are professional role models, no fishery is flawless. First, it is not known how many Greenlanders fish for salmon without a license, and unreported salmon catch remains a possibility throughout their ranges (ICES, 2020). Second, salmon fishers endure structural challenges that limit salmon catch reporting, such as not having access to the internet or phone, or reside in localities where they are not as easily reached by the Association of Hunters and Fishers in Greenland. Lastly, Greenlanders failed to fish less than or equal to the quota in 2019 and 2020. As results from the survey reveal, some fishers take issue with current management plans. This discontent is not new; Greenlanders have indicated that they would like for managers to keep the season open longer (Nygaard, 2016), while at the same time, NASCO and other salmon stakeholders continue to encourage Greenland to fish no more than the annual quota. Individuals' attitudes provide key insights on how they behave in the immediate regulatory environment in which their resource use occurs. Linking fishers' attitudes and their actual reporting behavior is beneficial because it tests the integrity of the questions that surveyors ask, the prevalence of nonresponse bias, and how much attitudes between reporters and nonreporters differ. Knowing both a person's attitudes and behaviors may also reveal structural inequalities that fishers face (Allison & Ellis, 2001; Fabinyi et al., 2014; Pinkerton, 2017), and as we show, this linking can even identify technical or clerical issues with reporting salmon catch, which create opportunities for noncompliance (Cohen & Felson, 1979). Improving compliance requires consideration for these structural barriers or situational factors that fishers face, and carrying them through the design, implementation, and maintenance of their management systems. These process-based components of legitimacy are revealed by combining salmon fishers' attitudes and behaviors. The Government of Greenland has revised salmon reporting protocols based upon the results of this study (Government of Greenland, 2020) and there is also an opportunity to expand the thematic purview of the ICES Atlantic salmon working group (WGNAS). Including regulatory and human dimensions research in these fora would help guide specific policy design and implementation efforts, in both this and other highly migratory fisheries. Survey questions were drafted in English, reviewed by two recreational fisheries survey experts and a member of staff from the Association of Hunters and Fishers in Greenland (KNAPK). The survey was reviewed by Greenland Fisheries License Control Authority (GFLK) and the Government of Greenland Fisheries Department (APNN). Survey questions were broken into sections and were formatted to include Likert, number entry, multiple choice, and open text questions. The survey sections included introductory questions, asking fishers about how much experience they have had harvesting from the sea and land, familiarity with current salmon regulations, and how they utilize their salmon catch. We also asked fishers to identify how they report, how difficult each reporting option (e.g., by phone, by mail, by fax) is for them, and their reasons for not reporting, if any. We conclude the survey by asking fishers about their attitudes toward the regulations, the enforcement authorities, and the survey instrument (to view the full survey, see Supplementary Materials). Survey questions were translated into Danish and Greenlandic by a native Greenlandic speaker. The survey questions, including the UCT, were trialed for quality assurance of translations, user experience, and content, on nine persons familiar with salmon fishing but who did not have a 2019 salmon fishing license and therefore were not part of the sample. The survey was drafted and distributed in March 2020 using Qualtrics and was available in Greenlandic, Danish, and English. The online survey was distributed via email and SMS message to 500 of the 719 salmon fishing license holders. 219 salmon fishing license holders did not have contact information and could not be enrolled. The UCT groups were randomly assigned in R, and a group code (Group 1 or 2) assigned to each individual. Qualtrics read in this value and displayed the correct UCT statements for the group for which the individual was assigned. After the invitations were sent to the effective sample of 500, three reminder messages were sent by SMS and email to encourage participation. Five prizes of DKK 2000 or approximately USD 330 to a general store in Greenland were pledged. After the survey was completed, we randomly drew five respondents, each of whom were awarded a raffle prize. The survey closed 29 May 2020 (Figure 1). Our research objective was to evaluate compliance in this fishery by understanding the relationships between salmon fishers' reported fishing behavior and their attitudes. We use responses to a survey as a measure of attitudes, and salmon catch records as a measure of actual behavior. In 2019, we developed an anonymous, IRB-approved nationwide online survey instrument on salmon fishing in Greenland (STUDY00031018). We drew our survey pool from all 2019 salmon fishing license holders. Salmon fishing license holders were classified as either private or professional fishers (see Supplementary Materials for breakdown of license types and regulations). We queried their contact details with assistance from Greenland Fisheries License Control Authority (GFLK). GFLK sent us contact details including phone and email, with personal identifiers removed. License holders were assigned a unique but anonymous identifier code to access the survey. We later used this code to link survey responses with anonymized 2019 salmon catch records for each individual. Survey questions were drafted in English, reviewed by two recreational fisheries survey experts and a member of staff from the Association of Hunters and Fishers in Greenland (KNAPK). The survey was reviewed by Greenland Fisheries License Control Authority (GFLK) and the Government of Greenland Fisheries Department (APNN). Survey questions were broken into sections and were formatted to include Likert, number entry, multiple choice, and open text questions. The survey sections included introductory questions, asking fishers about how much experience they have had harvesting from the sea and land, familiarity with current salmon regulations, and how they utilize their salmon catch. We also asked fishers to identify how they report, how difficult each reporting option (e.g., by phone, by mail, by fax) is for them, and their reasons for not reporting, if any. We conclude the survey by asking fishers about their attitudes toward the regulations, the enforcement authorities, and the survey instrument (to view the full survey, see Supplementary Materials). Survey questions were translated into Danish and Greenlandic by a native Greenlandic speaker. The survey questions, including the UCT, were trialed for quality assurance of translations, user experience, and content, on nine persons familiar with salmon fishing but who did not have a 2019 salmon fishing license and therefore were not part of the sample. The survey was drafted and distributed in March 2020 using Qualtrics and was available in Greenlandic, Danish, and English. The online survey was distributed via email and SMS message to 500 of the 719 salmon fishing license holders. 219 salmon fishing license holders did not have contact information and could not be enrolled. The UCT groups were randomly assigned in R, and a group code (Group 1 or 2) assigned to each individual. Qualtrics read in this value and displayed the correct UCT statements for the group for which the individual was assigned. After the invitations were sent to the effective sample of 500, three reminder messages were sent by SMS and email to encourage participation. Five prizes of DKK 2000 or approximately USD 330 to a general store in Greenland were pledged. After the survey was completed, we randomly drew five respondents, each of whom were awarded a raffle prize. The survey closed 29 May 2020 (Figure 1). Calculating the incidence of catch underreporting is not possible with salmon catch records alone, but it can be estimated with Unmatched Count Technique (UCT) as a component of the survey. UCT is a popular, quasi-experimental technique for indirectly asking sensitive questions (Hinsley et al., 2019), which can reveal illegal behaviors, such as underreporting. With UCT, respondents are broken into a treatment and control group. Both groups are asked to indicate how many statements from a list of statements are true for them, but not which exact statements. For the treatment group, a sensitive statement is also added. If the treatment and control groups are randomly assigned, the difference in the means between the groups can reveal the prevalence of the sensitive statement among the overall population (Coutts & Jann, 2011). The use of UCT in fisheries cases has been limited to date (Bergseth et al., 2017), but is a simpler alternative to other methods, such as random response techniques (RRT) (Oyanedel et al., 2020a; Thomas et al., 2015). With UCT, we can ask respondents to indicate how many but not which behaviors they have engaged in from a list of other plausible behaviors, thus allowing underreporting behavior to be indicated indirectly (Droitcour et al., 2004). Using double-list UCT, we are able to evaluate underreporting of catch in a smaller study population (Glynn, 2013), because with double-list UCT, both the treatment and the control groups are given a sensitive statement, but with two separate UCT exercises, which improves UCT method efficiency. UCT's are also prone to floor and ceiling effects depending upon the content of the statements. Floor effects can occur if the nonsensitive statements provided are all so rare that the sensitive statement is the only plausible statement, and respondents over-report their true answer to conceal the sensitive statement. Conversely, ceiling effects can occur if the nonsensitive statements provided are all too common, which can cause respondents to under-report to avoid admitting directly to the sensitive statement. To avoid these potential issues, the selected UCT statements were also reviewed during the initial survey review process (Hinsley et al., 2017). During the survey review, we included at least one nonsensitive item that was deemed to be rare so as to avoid the possibility of a ceiling effect. We also included a warm-up question so respondents were less likely to answer the UCT question improperly. We were further able to ensure participant privacy and encourage participation because the survey could be taken online in a place of the informant's choosing. We estimated how often salmon fishers' did not report their salmon catch using both direct and indirect questioning, anticipating that fishers would be reluctant to honestly answer a direct question about reporting salmon catch (Coutts & Jann, 2011). We analyzed 2019 salmon catch records, and responses to the salmon fishing survey, including the UCT experiment responses. Survey responses served as a measure of individual salmon fishers' attitudes, and their individual catch records from 2019 served as a measure of their actual fishing behavior. We used RStudio version 1.2.5042 (R version 3.6.3) to summarize catch records for each license holder, and then joined them to the 186 salmon fishing survey responses. Because we did not receive survey responses from 533 salmon fishers, there was a risk of nonresponse bias. Using Stata version 15 and R version 3.6.3, we evaluated the possibility of nonresponse bias by comparing the survey population (n = 186) to the entire sample (N = 736), according to four key variables: fishcount (how many salmon each fisher caught), catchkg (how much fish each fisher caught), locality (the municipality where a fisher resides), and licensetype (either a recreational or professional fisher). A Pearson's Chi-squared test was performed on locality and licensetype and a Two-sample Wilcoxon rank-sum (Mann–Whitney) test was performed on fishcount and catch, in light of a right skew distribution. To evaluate whether fishers who report have similar or different attitudes to those who do not report, we conduct a Light Cohen's Kappa test on Likert scale questions to measure levels of agreement between questions and to potentially combine variables. We also create box and whiskers plots to depict the distribution of responses between fishers who did and did not report their salmon catch, for selected predictor variables. For questions where mean responses vary, we fit binomial general linear models (GLM) to detect significant differences between fishers who did and did not report their salmon catch. We fit the GLM to test the question of whether nonreporters have similar or different attitudes than reporters. We are motivated to test this because we could not anticipate whether the survey pool would consist of a balanced sample of fishers who reported and fishers who did not report salmon catch. To know these differences is also valuable to the targeted design of fisheries management, so as to avoid any change that would attempt to correct behavior among a small group while disproportionately affecting an otherwise compliant population of salmon fishing license holders. The anonymous identifier code created by GFLK made it possible to anonymously compare individual fishers' behaviors, in terms of their reported salmon catch records with attitudinal responses from survey questions. UCT responses cannot be linked to individual attitudinal responses because UCT estimates use the treatment and control groups—and not individual responses—as the unit of analysis. To analyze results, we created frequency statistics for the direct question (Did you report all of your catch in 2019?). To estimate the prevalence of catch underreporting with the double-list UCT, we used rgr and list packages in the R programming environment (R Version 3.6.3). We calculated the means for both the control question and sensitive question, calculated the overall estimate by average difference of means (see Equation 1). The equation, following Coutts & Jann (2011) and Hinsley et al. (2019), is as follows (Equation 1—Formula for double-list unmatched count [UCT]): 1 p=p1+p22 where px = mean(treatment groupx) − mean(control groupx), where p1 and p2 are the proportion of of participants engaged in sensitive behavior from list 1 and 2, respectively.

Agradecimiento

We estimated that nearly all of Greenland's salmon fishers comply with salmon fishery regulations, especially salmon catch reporting. Specifically, the 2018 Executive Order on the Fishing of Salmon required salmon fishing license holders to report, or else lose their license renewal for the following year. The proportion of salmon fishers who reported their catch continued to increase from 2018 to 2019. This high level of compliance is perhaps unsurprising given the historic familiarity that Greenlanders have with reporting marine and terrestrial harvests (Dahl-Petersen et al., 2014). However, salmon catch reporting compliance levels have risen from 2017 to 2019, and is thought to be due in part to the implementation of new legislation (Government of Greenland, 2020). Using regulatory deterrents and nudges can help ensure high levels of compliance into the future (Snyder et al., 2021). In the face of changes to their routine, fishers do have the capacity to further comply. Even though fishers can earn an income from salmon catch, and enforcement is known to be lacking, few fishers indicated instrumental motivations to not report all their salmon catch. While it is not possible from our statistical analysis to conclusively infer what drives their compliance, fishers have generally positive perceptions of the regulations that govern their access and they look positively upon the authorities that enforce those regulations. In addition, high levels of compliance, high levels of agreement with normative attitudes, low levels of instrumental motivations, and high levels of perceived regulatory legitimacy is auspicious for a future where users, managers, and regulators work together to manage access to Atlantic salmon stocks. Voluntary compliance can persist if fishery managers are perceived to act professionally, honestly, and fairly. We anticipate that if Atlantic salmon stocks continue to decline, what is deemed fair will become controversial among salmon fishers in Greenland. These results also reaffirm the value of the compliance framework approach for understanding compliance in small-scale fisheries (Oyanedel et al., 2020b; Ramcilovic-Suominen & Epstein, 2012). Increasing collaboration between salmon fishers and managers is also likely feasible, given that nearly 60% of Greenland's salmon fishers said that they would provide more information by SMS message if the means to do so existed. Salmon fishers' willingness to share observations and ideas is substantial. The Association of Hunters and Fishers in Greenland (KNAPK) supports this level of communication during annual visits along the coast, and the sharing of ideas between and across individuals, local branch managers, and head office officials. Conservationists should continue to engage with local associations and participate in visits to maintain the common understanding that helps make compliance possible in this fishery. We illustrate how measuring fishers' attitudes can identify opportunities that arise for compliance or noncompliance. Crime script analysis, which parses noncompliance into a series of discrete events, identifies the specific components of salmon fishery compliance with catch reporting requirements. We identified an individual process, in this case, how salmon catch reporting is conducted. This isolates the process-based factors that contribute to perceptions of legitimacy, such as the professional conduct of fishery officers or the ease of reporting salmon catch. Our survey instrument made it possible to measure how people report salmon catch, how they think catch reporting can be improved, and among which groups salmon catch reporting is most challenging. Catch reporting is not mandatory in many recreational fisheries, and as a result, it is not normally possible to evaluate fisheries compliance by linking survey responses with official catch records (Midway et al., 2020). Because we were able to combine these data types, we can evaluate the possibility of respondent bias, given that achieving a census was unlikely and representative results are most valuable to fishery managers and intervention-oriented conservationists. Official catch records also shed light on the integrity of individual survey questions and associated responses. Salmon fishers more readily disclosed not reporting all of their catches when asked indirectly, and at the same time, we observed six cases where fishers said they reported all their catches, whereas the official records suggest that they did not. These six fishers who said that they reported all of their salmon catch to the Government of Greenland may have in fact reported their catch, even though the official record shows that they did not. It is possible that their reports could have been submitted, but were either never received, were never filed, or were submitted incorrectly. It is also possible that the respondents did not understand the question, or that they inputted the incorrect response. Responses to direct questions are doubted for their veracity, which further justifies the use of UCT for indirectly asking sensitive questions. UCT questions may increase the estimated incidence of salmon catch underreporting, but our results lack signifance to confidently support this claim. Even though the UCT estimate is larger, salmon catch underreporting is small, with <10% of respondents indirectly indicating that they underreported their salmon catch. These results should be interpreted with the likelihood that both direct and indirect questions could be underestimated. Apart from the UCT exercise, all other survey questions were direct questions. Given that the UCT exercise revealed that direct catch reporting may be underestimated, it is possible that all direct questions may be systematically underestimated. However, the majority of survey questions posed were not about sensitive behavior, so it is not justifiable to doubt their accuracy. This specific use of UCT shows that it can be an easy-to-administer tool (Nuno et al., 2013) and that UCT can even be conducted via online survey instruments. Our study reinforces the necessity of carefully selecting both sensitive and nonsensitive items in the design phase (Hinsley et al., 2017). Though not commonly included, our study provides respondents with a warm-up, practice UCT question, which gave respondents familiarity with how to answer the question and provides further assurance that the UCT questions were answered correctly (Hinsley et al., 2017). However, the variability that can arise in a UCT must be lessened for the effect to be detected and interpreted as significant; in this case, that is not possible. Future studies that use UCT should take extra care to revise nonsensitive statements and sensitive statements to reduce the likelihood of variability in the estimate. The results of this study also reaffirm that illegal behavior does not always translate to an unwillingness to divulge information (Hinsley et al., 2019). Instead, this study shows that illegal behavior can be shared, and we argue that the triviality of sanctions for such behavior in this specific setting may explain why resource users are willing to divulge such information. Linking official salmon catch records with survey responses also allowed us to identify an overall lack of variance in responses between reporters and nonreporters. We hypothesized that nonreporters have systematically different attitudes or perspectives to those who do report salmon catch. With the exception of two questions, we were unable to meaningfully show that a fishers' attitudes explain their actual salmon catch report status. However, results suggest that fishers who do not know how to report salmon catch or who find salmon catch reporting confusing are less likely to report salmon catch. There is a need to further simplify reporting to eliminate this confusion. Greenland's fishery managers also have the opportunity to familiarize license holders with how to report their catch when they are issued their licenses, especially among fishers with less experience in the fishery. As seen in this study and others, fishers with less experience are more likely to exhibit involuntary noncompliance, but experienced fishers can also find the rules confusing (Jentoft & Mikalsen 2004). Imbalanced samples are a persistent challenge for studying noncompliance because we most wish to hear from people who are understandably reluctant to answer questions about their noncompliant behavior (Larkin et al., 2010; van der Hammen et al., 2016). We were therefore pleased that 9% of responses came from salmon fishing license holders who did not officially report salmon catch to the Government of Greenland. This percentage is high, given that only 14% of all salmon fishing license holders did not report salmon catch in 2019 (Government of Greenland, 2020). While we cannot be certain, our tests that evaluated differences between the survey pool and the overall population, as well as comparisons between reporters and nonreporters, give us confidence that the survey pool is otherwise representative of the salmon fishing license holder population, in terms of salmon counts, catch, license types, and participating localities. However, we recommend eliciting more perspectives from the professional salmon fishing population, recognizing that professional salmon fishers are slightly underrepresented in the survey response pool. They are also the individuals catching the greatest quantities and weights of salmon. It is possible that this professional segment did not respond to the survey because they were participating in spring fishing or were affected by the economic shocks of the COVID-19 pandemic, which began during the period when the survey was issued. Future research could include follow-up surveys by phone or in person among salmon fishing license holders who did not submit their salmon catch reports during the 2019 season, or among those who chose not to participate in the salmon fishing survey. Having their responses included would capture a more complete picture of what drives salmon catch reporting. Scholars who are particularly interested in the attitudes of noncompliant resource users would especially benefit from a more complete survey of nonreporters. We saw a high response rate to the Salmon Fishing Survey of 37% despite the online format and completion during the COVID-19 pandemic. This participation suggests that Greenlanders have something to say about salmon fishing and want to be involved in how Greenland's fisheries are governed. This participation and compliance is consistent with studies that show that positive perceptions of governance structures are key to participation and support (Bennett & Dearden, 2014; Bubier, 1988; Evans et al., 2011). High levels of participation are also an auspicious indicator of research that lives up to goals and objectives to conduct inclusive, respectful, and beneficial research in, for, and with Inuit communities (National Inuit Strategy on Research, 2018). These results have been distributed among Greenland's salmon fishery policymakers and all salmon fishers were given access to results in summer 2020. They have informed the dialogue between NASCO members and Greenland's efforts to manage its access to Atlantic salmon stocks within its exclusive economic zone. Importantly, they have clarified long-standing beliefs about underreported salmon catch. While these results suggest that Greenland's salmon fishers have high moral standards and enforcement officials are professional role models, no fishery is flawless. First, it is not known how many Greenlanders fish for salmon without a license, and unreported salmon catch remains a possibility throughout their ranges (ICES, 2020). Second, salmon fishers endure structural challenges that limit salmon catch reporting, such as not having access to the internet or phone, or reside in localities where they are not as easily reached by the Association of Hunters and Fishers in Greenland. Lastly, Greenlanders failed to fish less than or equal to the quota in 2019 and 2020. As results from the survey reveal, some fishers take issue with current management plans. This discontent is not new; Greenlanders have indicated that they would like for managers to keep the season open longer (Nygaard, 2016), while at the same time, NASCO and other salmon stakeholders continue to encourage Greenland to fish no more than the annual quota. Individuals' attitudes provide key insights on how they behave in the immediate regulatory environment in which their resource use occurs. Linking fishers' attitudes and their actual reporting behavior is beneficial because it tests the integrity of the questions that surveyors ask, the prevalence of nonresponse bias, and how much attitudes between reporters and nonreporters differ. Knowing both a person's attitudes and behaviors may also reveal structural inequalities that fishers face (Allison & Ellis, 2001; Fabinyi et al., 2014; Pinkerton, 2017), and as we show, this linking can even identify technical or clerical issues with reporting salmon catch, which create opportunities for noncompliance (Cohen & Felson, 1979). Improving compliance requires consideration for these structural barriers or situational factors that fishers face, and carrying them through the design, implementation, and maintenance of their management systems. These process-based components of legitimacy are revealed by combining salmon fishers' attitudes and behaviors. The Government of Greenland has revised salmon reporting protocols based upon the results of this study (Government of Greenland, 2020) and there is also an opportunity to expand the thematic purview of the ICES Atlantic salmon working group (WGNAS). Including regulatory and human dimensions research in these fora would help guide specific policy design and implementation efforts, in both this and other highly migratory fisheries. Survey questions were drafted in English, reviewed by two recreational fisheries survey experts and a member of staff from the Association of Hunters and Fishers in Greenland (KNAPK). The survey was reviewed by Greenland Fisheries License Control Authority (GFLK) and the Government of Greenland Fisheries Department (APNN). Survey questions were broken into sections and were formatted to include Likert, number entry, multiple choice, and open text questions. The survey sections included introductory questions, asking fishers about how much experience they have had harvesting from the sea and land, familiarity with current salmon regulations, and how they utilize their salmon catch. We also asked fishers to identify how they report, how difficult each reporting option (e.g., by phone, by mail, by fax) is for them, and their reasons for not reporting, if any. We conclude the survey by asking fishers about their attitudes toward the regulations, the enforcement authorities, and the survey instrument (to view the full survey, see Supplementary Materials). Survey questions were translated into Danish and Greenlandic by a native Greenlandic speaker. The survey questions, including the UCT, were trialed for quality assurance of translations, user experience, and content, on nine persons familiar with salmon fishing but who did not have a 2019 salmon fishing license and therefore were not part of the sample. The survey was drafted and distributed in March 2020 using Qualtrics and was available in Greenlandic, Danish, and English. The online survey was distributed via email and SMS message to 500 of the 719 salmon fishing license holders. 219 salmon fishing license holders did not have contact information and could not be enrolled. The UCT groups were randomly assigned in R, and a group code (Group 1 or 2) assigned to each individual. Qualtrics read in this value and displayed the correct UCT statements for the group for which the individual was assigned. After the invitations were sent to the effective sample of 500, three reminder messages were sent by SMS and email to encourage participation. Five prizes of DKK 2000 or approximately USD 330 to a general store in Greenland were pledged. After the survey was completed, we randomly drew five respondents, each of whom were awarded a raffle prize. The survey closed 29 May 2020 (Figure 1). Our research objective was to evaluate compliance in this fishery by understanding the relationships between salmon fishers' reported fishing behavior and their attitudes. We use responses to a survey as a measure of attitudes, and salmon catch records as a measure of actual behavior. In 2019, we developed an anonymous, IRB-approved nationwide online survey instrument on salmon fishing in Greenland (STUDY00031018). We drew our survey pool from all 2019 salmon fishing license holders. Salmon fishing license holders were classified as either private or professional fishers (see Supplementary Materials for breakdown of license types and regulations). We queried their contact details with assistance from Greenland Fisheries License Control Authority (GFLK). GFLK sent us contact details including phone and email, with personal identifiers removed. License holders were assigned a unique but anonymous identifier code to access the survey. We later used this code to link survey responses with anonymized 2019 salmon catch records for each individual. Survey questions were drafted in English, reviewed by two recreational fisheries survey experts and a member of staff from the Association of Hunters and Fishers in Greenland (KNAPK). The survey was reviewed by Greenland Fisheries License Control Authority (GFLK) and the Government of Greenland Fisheries Department (APNN). Survey questions were broken into sections and were formatted to include Likert, number entry, multiple choice, and open text questions. The survey sections included introductory questions, asking fishers about how much experience they have had harvesting from the sea and land, familiarity with current salmon regulations, and how they utilize their salmon catch. We also asked fishers to identify how they report, how difficult each reporting option (e.g., by phone, by mail, by fax) is for them, and their reasons for not reporting, if any. We conclude the survey by asking fishers about their attitudes toward the regulations, the enforcement authorities, and the survey instrument (to view the full survey, see Supplementary Materials). Survey questions were translated into Danish and Greenlandic by a native Greenlandic speaker. The survey questions, including the UCT, were trialed for quality assurance of translations, user experience, and content, on nine persons familiar with salmon fishing but who did not have a 2019 salmon fishing license and therefore were not part of the sample. The survey was drafted and distributed in March 2020 using Qualtrics and was available in Greenlandic, Danish, and English. The online survey was distributed via email and SMS message to 500 of the 719 salmon fishing license holders. 219 salmon fishing license holders did not have contact information and could not be enrolled. The UCT groups were randomly assigned in R, and a group code (Group 1 or 2) assigned to each individual. Qualtrics read in this value and displayed the correct UCT statements for the group for which the individual was assigned. After the invitations were sent to the effective sample of 500, three reminder messages were sent by SMS and email to encourage participation. Five prizes of DKK 2000 or approximately USD 330 to a general store in Greenland were pledged. After the survey was completed, we randomly drew five respondents, each of whom were awarded a raffle prize. The survey closed 29 May 2020 (Figure 1). Calculating the incidence of catch underreporting is not possible with salmon catch records alone, but it can be estimated with Unmatched Count Technique (UCT) as a component of the survey. UCT is a popular, quasi-experimental technique for indirectly asking sensitive questions (Hinsley et al., 2019), which can reveal illegal behaviors, such as underreporting. With UCT, respondents are broken into a treatment and control group. Both groups are asked to indicate how many statements from a list of statements are true for them, but not which exact statements. For the treatment group, a sensitive statement is also added. If the treatment and control groups are randomly assigned, the difference in the means between the groups can reveal the prevalence of the sensitive statement among the overall population (Coutts & Jann, 2011). The use of UCT in fisheries cases has been limited to date (Bergseth et al., 2017), but is a simpler alternative to other methods, such as random response techniques (RRT) (Oyanedel et al., 2020a; Thomas et al., 2015). With UCT, we can ask respondents to indicate how many but not which behaviors they have engaged in from a list of other plausible behaviors, thus allowing underreporting behavior to be indicated indirectly (Droitcour et al., 2004). Using double-list UCT, we are able to evaluate underreporting of catch in a smaller study population (Glynn, 2013), because with double-list UCT, both the treatment and the control groups are given a sensitive statement, but with two separate UCT exercises, which improves UCT method efficiency. UCT's are also prone to floor and ceiling effects depending upon the content of the statements. Floor effects can occur if the nonsensitive statements provided are all so rare that the sensitive statement is the only plausible statement, and respondents over-report their true answer to conceal the sensitive statement. Conversely, ceiling effects can occur if the nonsensitive statements provided are all too common, which can cause respondents to under-report to avoid admitting directly to the sensitive statement. To avoid these potential issues, the selected UCT statements were also reviewed during the initial survey review process (Hinsley et al., 2017). During the survey review, we included at least one nonsensitive item that was deemed to be rare so as to avoid the possibility of a ceiling effect. We also included a warm-up question so respondents were less likely to answer the UCT question improperly. We were further able to ensure participant privacy and encourage participation because the survey could be taken online in a place of the informant's choosing. We estimated how often salmon fishers' did not report their salmon catch using both direct and indirect questioning, anticipating that fishers would be reluctant to honestly answer a direct question about reporting salmon catch (Coutts & Jann, 2011). We analyzed 2019 salmon catch records, and responses to the salmon fishing survey, including the UCT experiment responses. Survey responses served as a measure of individual salmon fishers' attitudes, and their individual catch records from 2019 served as a measure of their actual fishing behavior. We used RStudio version 1.2.5042 (R version 3.6.3) to summarize catch records for each license holder, and then joined them to the 186 salmon fishing survey responses. Because we did not receive survey responses from 533 salmon fishers, there was a risk of nonresponse bias. Using Stata version 15 and R version 3.6.3, we evaluated the possibility of nonresponse bias by comparing the survey population (n = 186) to the entire sample (N = 736), according to four key variables: fishcount (how many salmon each fisher caught), catchkg (how much fish each fisher caught), locality (the municipality where a fisher resides), and licensetype (either a recreational or professional fisher). A Pearson's Chi-squared test was performed on locality and licensetype and a Two-sample Wilcoxon rank-sum (Mann–Whitney) test was performed on fishcount and catch, in light of a right skew distribution. To evaluate whether fishers who report have similar or different attitudes to those who do not report, we conduct a Light Cohen's Kappa test on Likert scale questions to measure levels of agreement between questions and to potentially combine variables. We also create box and whiskers plots to depict the distribution of responses between fishers who did and did not report their salmon catch, for selected predictor variables. For questions where mean responses vary, we fit binomial general linear models (GLM) to detect significant differences between fishers who did and did not report their salmon catch. We fit the GLM to test the question of whether nonreporters have similar or different attitudes than reporters. We are motivated to test this because we could not anticipate whether the survey pool would consist of a balanced sample of fishers who reported and fishers who did not report salmon catch. To know these differences is also valuable to the targeted design of fisheries management, so as to avoid any change that would attempt to correct behavior among a small group while disproportionately affecting an otherwise compliant population of salmon fishing license holders. The anonymous identifier code created by GFLK made it possible to anonymously compare individual fishers' behaviors, in terms of their reported salmon catch records with attitudinal responses from survey questions. UCT responses cannot be linked to individual attitudinal responses because UCT estimates use the treatment and control groups—and not individual responses—as the unit of analysis. To analyze results, we created frequency statistics for the direct question (Did you report all of your catch in 2019?). To estimate the prevalence of catch underreporting with the double-list UCT, we used rgr and list packages in the R programming environment (R Version 3.6.3). We calculated the means for both the control question and sensitive question, calculated the overall estimate by average difference of means (see Equation 1). The equation, following Coutts & Jann (2011) and Hinsley et al. (2019), is as follows (Equation 1—Formula for double-list unmatched count [UCT]): 1 p=p1+p22 where px = mean(treatment groupx) − mean(control groupx), where p1 and p2 are the proportion of of participants engaged in sensitive behavior from list 1 and 2, respectively.

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Departamento Gestión de Conocimiento, Monitoreo y Prospección