Influence of anglers’ specializations on catch, harvest, and bycatch of targeted taxa

Fishery managers often use catch per unit effort (CPUE) of a given taxon derived from a group of anglers,those that sought said taxon, to evaluate fishery objectives because managers assume CPUE for this group of anglers is most sensitive to changes in fish taxon density. Further, likelihood of harvest may differ for sought and non-sought taxa if taxon sought is a defining characteristic of anglers’ attitude toward harvest.We predicted that taxon-specific catch across parties and reservoirs would be influenced by targeted taxon after controlling for number of anglers in a party and time spent fishing (combine to quantify fishing effort of party); we also predicted similar trends for taxon-specific harvest. We used creel-survey data collected from anglers that varied in taxon targeted, from generalists (targeting “anything” [no primary target taxa, but rather targeting all fishes]) to target specialists (e.g., anglers targeting largemouth bass Micropterus salmoides) in 19 Nebraska reservoirs during 2009–2011 to test our predictions. Taxon-specific catch and harvest were, in general, positively related to fishing effort. More importantly, we observed differences of catch and harvest among anglers grouped by taxon targeted for each of the eight taxa assessed. Anglers targeting a specific taxon had the greatest catch for that taxon and anglers targeting anything typically had the second highest catch for that taxon. In addition, anglers tended to catch more of closely related taxa and of taxa commonly targeted with similar fishing techniques. We encourage managers to consider taxon-specific objectives of target and non-target catch and harvest

Influence of anglers’ specializations on catch, harvest, and bycatch of targeted taxa

Fishery managers often use catch per unit effort (CPUE) of a given taxon derived from a group of anglers,those that sought said taxon, to evaluate fishery objectives because managers assume CPUE for this group of anglers is most sensitive to changes in fish taxon density. Further, likelihood of harvest may differ for sought and non-sought taxa if taxon sought is a defining characteristic of anglers’ attitude toward harvest.We predicted that taxon-specific catch across parties and reservoirs would be influenced by targeted taxon after controlling for number of anglers in a party and time spent fishing (combine to quantify fishing effort of party); we also predicted similar trends for taxon-specific harvest. We used creel-survey data collected from anglers that varied in taxon targeted, from generalists (targeting “anything” [no primary target taxa, but rather targeting all fishes]) to target specialists (e.g., anglers targeting largemouth bass Micropterus salmoides) in 19 Nebraska reservoirs during 2009–2011 to test our predictions. Taxon-specific catch and harvest were, in general, positively related to fishing effort. More importantly, we observed differences of catch and harvest among anglers grouped by taxon targeted for each of the eight taxa assessed. Anglers targeting a specific taxon had the greatest catch for that taxon and anglers targeting anything typically had the second highest catch for that taxon. In addition, anglers tended to catch more of closely related taxa and of taxa commonly targeted with similar fishing techniques. We encourage managers to consider taxon-specific objectives of target and non-target catch and harvest

Bipartite networks improve understanding of effects of waterbody size and angling method on angler–fish interactions

Networks used to study interactions could provide insights to fisheries. We compiled data from 27 297 interviews of anglers across waterbodies that ranged in size from 1 to 12 113 ha. Catch rates of fish species among anglers grouped by species targeted generally differed between angling methods (bank or boat). We constructed angler–catch bipartite networks (angling method specific) between anglers and fish and measured several network metrics. There was considerable variation in networks among waterbodies, with multiple metrics influenced by waterbody size. Number of species-targeting angler groups and number of fish species caught increased with increasing waterbody size. Mean number of links for species-targeting angler groups and fish species caught also increased with waterbody size. Connectance (realized proportion of possible links) of angler–catch interaction networks decreased slower for boat anglers than for bank anglers with increasing waterbody size. Network specialization (deviation of number of interactions from expected) was not significantly related to waterbody size or angling methods. Application of bipartite networks in fishery science requires careful interpretation of outputs, especially considering the numerous confounding factors prevalent in recreational fisheries. Résumé : Les réseaux utilisés pour étudier les interactions pourraient fournir de l’information utile sur les pêches. Nous avons compilé des données de 27 297 entrevues de pêcheurs a` la ligne dans différents plans d’eau allant de 1 ha a` 12 113 ha. Les taux de prise de différentes espèces de poisson de pêcheurs regroupés selon l’espèce ciblée varient généralement selon la méthode de pêche (de la rive ou d’une embarcation). Nous avons construit des réseaux bipartites pêcheur–prises (selon la méthode de pêche) entre les pêcheurs et les poissons et mesuré plusieurs paramètres de ces réseaux. Il y a des variations considérables des réseaux entre plans d’eau, plusieurs paramètres étant influencés par la taille de ces derniers. Le nombre de groupes de pêcheurs ciblant des espèces précises et le nombre d’espèces de poissons pêchées augmentent avec la taille du plan d’eau. Le nombre moyen de liens pour les groupes de pêcheurs ciblant des espèces et les espèces pêchées augmente également avec la taille du plan d’eau. La connectance (proportion de liens possibles réalisés) des réseaux d’interactions pêcheur–prises diminue plus lentement pour les pêcheurs en embarcation que pour les pêcheurs de la rive pour des plans d’eau de plus en plus grands. La spécialisation des réseaux (écart entre le nombre d’interactions observées et prévues) n’est pas significativement reliée a` la taille du plan d’eau ou a` la méthode de pêche. L’application de réseaux bipartites aux sciences halieutiques nécessite une interprétation soigneuse des données de sortie, étant donné, notamment, les nombreux facteurs de confusion qui caractérisent les pêches récréatives

Simulating detection-censored movement records for home range analysis planning

Home range estimation is an important analytical method in applied spatial ecology, yet best practices for addressing the effects of spatial variation in detection probability on home range estimates remain elusive. We introduce the R package “DiagnoseHR,” simulation tools for assessing how variation in detection probability arising from landscape, animal behavior, and methodological processes affects home range inference. We demonstrate the utility of simulation methods for home range analysis planning by comparing bias arising from three home range estimation methods under multiple detection scenarios. We simulated correlated random walks in three landscapes that varied in detection probability and constructed home ranges from locations filtered through a range of sampling protocols. Home range estimates were less biased by reduced detection probability when sampling effort was increased, but the effects of sampling day distribution were minimal. Like others, we found that kernel density estimates were the least affected by variation in detection probability, while minimum convex polygons were most affected. Our results illustrate the value of quantifying uncertainty in home range estimates and suggest that field biologists working in environments with low detection may wish to weight sample-size greater than concerns about temporal autocorrelation when designing sampling protocols

Motivations to participate in hunting and angling: a comparison among preferred activities and state of residence

Motivations for hunting and fishing extend beyond harvesting game and include social, psychological, emotional, and physical benefits. We used data from a web-based questionnaire to compare relationships between preferred hunting or fishing activity types, state of residence, and motivations of hunters and anglers across the central United States (U.S.). Exploratory factor analysis yielded four motivation factors: nature, social, food, and challenge. Differences in terms of state were negligible across all motivation factors (η2p \u3c .01), indicating similarity across states. Nature (η2p = .01) and social (η2p \u3c .01) factors were the first and second most important factors across activity types. We observed larger differences among the challenge (η2p = .03), and food (η2p = .15) factors, primarily driven by big game hunters. Big game hunters rated the food motivation factor greater than the other activity types. Overall, our results indicate that there might be a greater universality in these motivation factors among activity types and locations in the U.

Variation in angler distribution and catch rates of stocked rainbow trout in a small reservoir

We investigated the spatial and temporal relationship of catch rates and angler party location for two days following a publicly announced put-and-take stocking of rainbow trout (Oncorhynchus mykiss). Catch rates declined with time since stocking and distance from stocking. We hypothesized that opportunity for high catch rates would cause anglers to fish near the stocking location and disperse with time, however distance between angler parties and stocking was highly variable at any given time. Spatially explicit differences in catch rates can affect fishing quality. Further research could investigate the variation between angler distribution and fish distribution within a waterbody

Variation in angler distribution and catch rates of stocked rainbow trout in a small reservoir

We investigated the spatial and temporal relationship of catch rates and angler party location for two days following a publicly announced put-and-take stocking of rainbow trout (Oncorhynchus mykiss). Catch rates declined with time since stocking and distance from stocking. We hypothesized that opportunity for high catch rates would cause anglers to fish near the stocking location and disperse with time, however distance between angler parties and stocking was highly variable at any given time. Spatially explicit differences in catch rates can affect fishing quality. Further research could investigate the variation between angler distribution and fish distribution within a waterbody

Heterogeneity of recreationists in a park and protected area

Limited information and resources have caused many parks and protected areas (PPAs) to functionally manage recreationists as a single homogeneous group, despite potential negative social and ecological consequences. We aimed to evaluate the homogeneity of recreationists at the Valentine National Wildlife Refuge (NWR) by 1) quantifying frequencies of consumptive (i.e., hunting), intermediate-consumptive (i.e., fishing), and non-consumptive recreational-activity groups (e.g., wildlife viewing), and 2) evaluating sociodemographic differences among these groups. We used onsite surveys to determine that Valentine NWR supports heterogeneous groups of recreationists. The intermediate-consumptive group was most frequent (77% of all parties). All three recreational-activity groups varied in party size, distance traveled, household income, population type (urban or rural residence), and vehicle type (two-wheel or four-wheel drive). Tracking and accounting for diverse recreationists will equip managers with the ability to sustain recreational activities while also preserving ecological systems

Ecosystem size predicts social-ecological dynamics

Recreational fisheries are complex adaptive systems that are inherently difficult to manage because of heterogeneous user groups (consumptive vs. nonconsumptive) that use patchily distributed resources on the landscape (lakes, rivers, coastlines). There is a need to identify which system components can effectively predict and be used to manage nonlinear and cross-scale dynamics within these systems. We examine how ecosystem size or water body size can be used to explain complicated and elusive angler-resource dynamics in recreational fisheries. Water body size determined angler behavior among 48 Nebraska, U.S.A. water bodies during an 11- year study. Angler behavior was often unique and nonlinear across water body sizes. For example, anglers spent more time fishing and harvested more fish at larger water bodies compared to smaller water bodies. Time fished increased across smaller water bodies, but reached a threshold at larger water bodies. The number of fish released increased as a function of water body size across smaller water bodies and then plateaued. Subtle changes in water body size caused abrupt changes in angler behavior, that is, water body size structures angler-resource dynamics in recreational fisheries. We believe that including water body size, a simple and easily measured metric, in fisheries management will increase effectiveness of cross-scale actions and minimize unintended consequences for recreational fisheries. Applying uniform management actions, e.g., harvest regulations, across small and large water bodies may elicit contrasting anglerresource responses. Water body size may also be useful for understanding angler typologies. Based on our findings, we expect that ecosystem size is a prominent and valuable system component that will determine and explain coupled user-resource dynamics in other complex adaptive systems

Angler effort and catch within a spatially complex system of small lakes

Spatial layout of waterbodies and waterbody size can affect a creel clerk’s ability to intercept anglers for interviews and to accurately count anglers, which will affect the accuracy and precision of estimates of effort and catch. This study aimed to quantify angling effort and catch across a spatially complex system of19 small (\u3c100 ha) lakes, the Fremont lakes. Total (±SE) angling effort (hours) on individual lakes ranged from 0 (0) to 7,137 (305). Bank anglers utilized 18 of the 19 lakes, and their mean (±SE) trip lengths(hours) ranged from 0.80 (0.31) to 7.75 (6.75), depending on the waterbody. In contrast, boat anglers utilized 14 of the 19 lakes, and their trip lengths ranged from 1.39 (0.24) to 4.25 (0.71), depending on the waterbody. The most sought fishes, as indexed by number of lakes on which effort was exerted, were anything (17 of 19 lakes), largemouth bass Micropterus salmoides (15 of 19 lakes), and channel catfish Ictalurus punctatus (13 of 19 lakes). Bluegill Lepomis machrochirus, crappie Pomoxis spp., and largemouth bass were caught most frequently across the lakes, but catch rates varied considerably by lake. Of the1,138 parties interviewed, most parties (93%) visited a single lake but there were 77 (7%) parties that indicated that they had visited multiple lakes during a single day. The contingent of parties that visited more than one lake a day were primarily (87%) bank anglers.. The number of lake-to-lake connections made by anglers visiting more than one waterbody during a single day was related to catch rates and total angling effort. The greater resolution that was achieved with a lake specific creel survey at Fremont lakes revealed a system of lakes with a large degree of spatial variation in angler effort and catch that would be missed by a coarser, system-wide survey that did not differentiate individual lakes