Ben Beardmore

Understanding the predictive ability of recreation specialization to explain behavior is important for wildlife and fisheries management given the widespread use of specialization to capture diversity among outdoor recreationists. Using allocation of days among fishing opportunities in a discrete choice experiment, we studied the extent that specialization predicted preferences for attributes describing the opportunities. Latent class modeling revealed that three groups of anglers optimally captured preference diversity in our sample. To this base model, we sequentially added 11 metrics of angler specialization and used information theory to select the metric that best predicted group membership, namely centrality to lifestyle. Weaker evidence existed for the specialization dimensions “importance of catch,” “specialized gear use,” and a multidimensional self-classification approach, whereas indices of skill, media use, trophy fish, and harvest orientation were not supported. General specialization constructs such as centrality to lifestyle, therefore, might be best suited for predicting general fishing preferences and subsequent behaviors of anglers.

Understanding how fishing effort responds to management interventions is important for conserving threatened fisheries resources such as the European eel (Anguilla anguilla). In this paper, we use a discrete choice survey to predict the allocation of recreational angling days directed at eel versus potential substitute fishing opportunities in northern Germany as a function of eel angling regulations, catch attributes and hypothetical eel fishing costs. We found the allocation model to accurately predict current eel effort allocation patterns. Using the validated statistical model as a forecasting tool, we found eel angling effort to be largely resilient to changes in individual eel angling regulations, including daily bag limits, daily rod limits and fishery closures for up to two weeks each month. An inelastic effort response to the most commonly discussed policy interventions suggests that managers cannot expect to substantially reduce eel fishing effort, and thus mortality exerted by anglers on eel, using moderate management interventions. However, when severe regulations, including a two week closure per month, with remaining days limited to a harvest of 1 eel, 60 cm or larger, per angler using a single rod, would be implemented, angling effort devoted to eel can be expected to be reduced by about 42% relative to current conditions at unaltered expected catches. This would reduce landings of eel by anglers by 73%. This reduction in landings has unknown effects on the future recruitment of eel while at the same time substantially reducing angler welfare. Angler welfare can be largely maintained by increases in minimum-size limits and reductions in daily bag limits, while at the same time reducing eel landings by anglers substantially. Such actions are therefore preferred from an angler welfare perspective.

Most conclusions from general assessments of angler motivations indicate that noncatch motives are more important to anglers than catch motives. Such research usually assesses the general motivation structure by anglers. To assess both general and more context-specific angler motivations, we surveyed the same anglers from northeastern Germany using two phases of a complementary survey design. First, a 1-year diary was used to collect trip-specific information; second, a personalized mail survey was used to elicit context-specific motivation information. Anglers selected their most important motives for their most frequent trip–target species combination (i.e., context) from a list of 10 salient fishing motives. Anglers frequently cited catch motives as the most important across a range of target species, large-bodied species such as northern pike Esox lucius being primarily associated with trophy fishing. Some species (such as small-bodied cyprinids) were targeted for noncatch reasons, while others (such as European perch [also known as Eurasian perch] Perca fluviatilis) attracted anglers seeking a multitude of psychological outcomes. Five distinct angler types were identified based on similarity of prime fishing motivation, namely, trophy-seeking anglers; nontrophy, challenge-seeking anglers; nature-oriented anglers; meal-sharing anglers; and social anglers. Members of these angler groups were similar in demographics and general angling behaviors but differed with respect to several indicators of angler specialization, indicating that committed anglers are more catch-oriented than previously assumed.

As with most fisheries, the assessment and management of salmon fisheries are highly dependent on the use of multiple indicators, yet methods for combining indicators have generally not been well developed or tested for consistency. This situation is exemplified well by the implementation of Fisheries and Oceans Canada’s (DFO’s) Wild Salmon Policy which requires the annual assessment of the biological status of Conservation Units (CUs) by combining the status (red, amber or green) of several indicators or metrics (spawner abundance, trends in spawner abundance, harvest rate, and spatial distribution). Existing methods for aggregating such metrics into an overall CU status assume either that all metrics are equally important or that they have some other pre-determined weighting. We developed a choice modeling questionnaire to quantitatively determine (1) the status of CUs, and (2) the relative importance of the various components contributing to that overall assessment. The questionnaire presented experts across British Columbia with a series of hypothetical CU scenarios, each one simultaneously presenting the biological metrics, the metric status, and the data quality and amount. The experts were asked to (1) rate the biological status of each CU scenario, and (2) identify which combination (of metric/metric status/data quality and amount) in each CU scenario pulled their CU status rating most towards a red or green rating. Metric status, regardless of the type of metric, was the single most important component contributing to the experts' assessment of CU status. Yet not surprisingly, considering the historical emphasis by salmon fisheries management agencies on spawner abundance estimates, we found the spawner abundance metric to be more important than the other three metrics. Data quality and amount became statistically significant only as an interaction effect with metric status. When data quality and amount was high, a red or green metric status resulted in a more extreme (more red or green) CU status rating. Overall, this more holistic quantitative evaluation of expert opinion may provide more consistent CU ratings across experts involved in such assessments. While not directly applicable to all CUs, the project is a case study of a novel method in fisheries management (use of choice modeling), which in the future could be modified for different regional or species contexts.

A novel variation of a multivariate stated preference method (the maximum difference conjoint approach) is presented in a survey designed to elicit the preferences of a fisheries stakeholder group (recreational anglers fishing in northern Germany) for a portfolio of measures to conserve European eel (Anguilla anguilla L.). Unlike other survey methods, our approach allows the separation of weight (i.e., relative importance of different conservation actions) and scale (i.e., perceived utility associated with different levels within one action) ascribed by stakeholders to conservation measures. The method also allows for trade-off decision-making and joint preference articulation for various conservation actions, and thus provides more realistic decision situations than other survey methods can achieve. We found that anglers prefer tighter than current eel fishing regulations but object to highly restrictive temporal closures. Confronted with an integrated eel conservation program, anglers were overwhelmingly willing to compromise, accepting tighter angling regulations provided that other sources of eel mortality are regulated concomitantly and eel stocking increased. Willingness to accept stricter regulation increased further when the suite of regulations delivered success in terms of increased eel escapement. We encourage the replication of the presented survey technique with other eel stakeholders groups, but also in other conservation contexts, to see if similar patterns of response behaviour emerge that would not have been visible in traditional opinion-type preference assessments. Our results suggest that implementation of eel conservation policies should consider joint regulation of sectors that potentially affect eel stock negatively. Otherwise, management failure and conflict is likely.

1.Wildlife tourism can be prone to unmitigated development to promote visitor satisfaction that is all too often progressed at the cost of ecological integrity. A manager is thus faced with the dual task of enhancing the tourist experience and protecting the wildlife species. Accordingly, this mandate requires research into how tourists would respond to proposed wildlife-management plans.2.This study examines the heterogeneity of tourist preferences for wildlife management at a stingray-feeding attraction in the Cayman Islands, using a latent class stated preference choice model. A sample of visitors to Stingray City Sandbar (SCS) evaluated hypothetical wildlife viewing experiences in a discrete choice experiment. Its scenarios were characterized by seven attributes such as animal-feeding and handling rules, ecological outcomes, social crowding, and management cost (defined as a conservation access fee).3.The latent class segmentation identified two groups in the population: approximately 68% preferred the implementation of fairly strict management rules, while the other 32% valued more the maintenance of status quo with its intensive human — wildlife interactions. Despite the differences between the ‘pro-management’ and the ‘pro-current’ segments, both exhibited a preference for the continuation of feeding and handling the stingrays (albeit at different levels of intensity) suggesting that one effective way to implement any management actions is to alter the promotional and marketing strategies for SCS. Other survey questions on trip experience, conservation values, and socio-demographics were used to define these classes further, with the main distinguishing trait being the level of concern for potential impacts occurring at SCS. The discrepancies between the two segments became most obvious when calculating their respective market shares of support for alternative management strategies.4.This approach to determining visitor preferences can help explain how the various segments will be affected by management options, and therefore can provide the basis for developing feasible strategies that will assist wildlife managers in maximizing tourist satisfaction while achieving wildlife-protection goals. Copyright © 2008 John Wiley & Sons, Ltd.