The effect of random and density‐dependent variation in sampling efficiency on variance of abundance estimates from fishery surveys

Abundance indices (AIs) provide information on population abundance and trends over time, while AI variance (AIV) provides information on reliability or quality of the AI. AIV is an important output from surveys and is commonly used in formal assessments of survey quality, in survey comparison studies, and in stock assessments. However, uncertainty in AIV estimates is poorly understood and studies on the precision and bias in survey AIV estimates are lacking. Typically, AIV estimates are “design based” and are derived from sampling theory under some aspect of randomized samples. Inference on population density in these cases can be confounded by unaccounted process errors such as those due to variable sampling efficiency (q). Here, we simulated fish distribution and surveys to assess the effect of q and variance in q on design‐based estimates of AIV. Simulation results show that the bias and precision of AIV depend on the mean q and variance in q. We conclude that to fully evaluate the reliability of AI, both observation error and variability in q must be accounted for when estimating AIV. A decrease in mean q and an increase in the variance in q results in increased bias and decreased precision in survey AIV estimates. These effects are likely small in surveys with mean q ≥ 1. However, for surveys where q ≤ 0.5, these effects can be large. Regardless of the survey type, AIV estimates can be improved with knowledge of q and variance in q.     

Interactions between fishing strategies of Nephrops trawlers in the Bay of Biscay and Norway lobster diel activity patterns

Abstract  Norway lobster, Nephrops norvegicus (L.), in the Bay of Biscay exhibited diel activity patterns with more individuals outside their burrows at dawn and dusk, increasing catchability at these times. Data from an on board observer programme on Nephrops trawlers between 2002 and 2005 were used to assess variability in catchability in commercial catches. Catch numbers per haul varied spatially and between months, but no signal for diel variations was found. Fishing strategies developed by the Nephrops trawlers had several components. On a seasonal level, they started around sunrise. On a haul level, haul duration decreased from haul to haul, with the longest hauls taking place at the time of the highest catchability. By-catch of hake, Merluccius merluccius (L.), increased more than proportionally with haul duration.     

Explaining recreational angling catch rates of Eurasian perch,Perca fluviatilis: the role of natural and fishing‐related environmental factors

Angling catch records are frequently used to reveal fish population developments. It is therefore important to understand the determinants of angling catches. This study focused on angler‐related, biotic and abiotic factors influencing catchability of Eurasian perch, Perca fluviatilis L. A multi‐lake (21 lakes) study based on angling diaries collected in Mecklenburg‐Vorpommern, Germany (2006/2007), found that angler‐related factors such as fishing experience, species preference and bait/lure type had a large impact on perch catch rates. Additionally, environmental conditions (nutritional status and water transparency) affected either the size or the number of perch caught by anglers. Catch rates varied seasonally, which was confirmed by an experimental fishery on a gravel pit (2008). This portion of the study showed that altered food availabilities in the course of the year caused food limitation in perch, which in turn facilitated high catch rates and female‐biased exploitation in autumn. It is concluded that both angler‐related and abiotic factors interact affecting perch catch rates and size of perch captured in recreational angling.     

Model of trawlable area using benthic terrain and oceanographic variables—Informing survey design and habitat maps in the Gulf of Alaska

Bottom trawl surveys provide fishery‐independent data on relative abundance and life history parameters for a wide range of marine taxa. Survey data are used to assess species distribution, biological interactions, and ecosystem structure and to manage marine resources. Not all bottom types or oceanographic conditions accommodate this survey method. We applied National Ocean Service hydrographic smooth sheets to evaluate physical attributes associated with habitat available to surveys. Random forests were used to evaluate the relative influence of benthic terrain and oceanographic predictors in determining accessibility to bottom trawl gear. We examined the marginal importance of each predictor, quantified the response gradient, and applied piecewise regression to determine threshold breakpoint values. Thresholds were used to develop predictive maps and distinguish untrawlable habitat at the scale of discrete towpaths and survey stations. Untrawlable habitat was associated with increased complexity in terrain, roughness, slope, surface curvature, substrate coarseness, current, and aspect. Maps of critical thresholds suggest different variables constrain the probability of a successful trawl in the nearshore, shelf, and continental slope. Overlay analysis of the model projection demonstrates the utility of archived smooth sheet data and identifies areas where higher resolution data might improve results. The model and maps produced in this analysis might be used to identify habitats available to and impacted by commercial trawl fisheries, inform the relative availability of various species and habitat types to bottom trawl surveys, evaluate bias in assessment indices and ecosystem metrics derived from survey data, and advance habitat‐specific biomass estimates.     

Shooting fish in a barrel? Assessing fisher‐driven changes in catchability within tropical tuna purse seine fleets

With constant innovation to find more efficient ways to find, catch and process fish, catchability in wild fisheries can increase. Catchability is a combination of resource abundance, fishing effort and fishing efficiency: any increase in fleet efficiency can lead to undesirable effects not only on stocks, but also on the ability to assess them. When using effort controls as part of management, it is necessary to adjust for the increase in catchability due to the increases in efficiency over time to avoid stock depletion. Accounting for changes in catchability can be problematic for pelagic stocks, due to the changes in fishing behaviour and the continual change in fishing efficiency. This study investigates the success in finding patches of fish for fleets operating within the western and central Pacific purse seine fishery between 1993 and 2012. Three indices, widely used in ecological research, were used to study how spatial variation in fisher behaviour for sets on fish aggregating devices (FADs) and free‐school sets was related to catchability. For free‐school set types, the diversity index was negatively correlated with Katsuwonus pelamis catchability. When this index was low, catch rates were at their highest and there was a reduction in the area fished. In contrast, for FAD sets, catches increase when the patchiness index was low, implying a degree of random behaviour, potentially due to advances in FAD technology. An improved understanding of the spatial allocation of effort can improve catchability estimates widely used for fisheries stock assessments and in indices of global biodiversity.     

Density and temperature dependence of gill net catch per unit effort for perch, Perca fluviatilis, and roach, Rutilus rutilus

Abstract  The densities of perch, Perca fluviatilis L., and roach, Rutilus rutilus (L.), were estimated in six and three lakes, respectively, using mark–recapture and ranged from 25–1064 perch ha⁻¹ and 865–2749 roach ha⁻¹. Effects of fish density, net type and water temperature on catch-per-unit-effort (CPUE) were analysed by generalised linear models (GLM) and generalised additive models (GAM). GAMs were fitted to estimate the simultaneous linear and nonlinear effects of temperature and density on CPUE. These models showed significant nonlinear effects of density on CPUE – mostly for perch, and also for both species at high densities. The models also revealed that both species had distinct density–temperature criteria of expected maximum CPUE and zero CPUE values. Because of the nonlinear relationship between CPUE and density, it was concluded that CPUE should be used with caution as a proxy of density.     

金枪鱼渔业中人工集鱼装置生态影响研究进展

金枪鱼人工集鱼装置(Fish Aggregation Devices,FADs)分为漂流式和锚泊式两种,人工集鱼装置可以吸引热带金枪鱼类和其他中上层鱼类,在全球范围内支持了数千艘渔船的捕捞作业,大幅提高了捕捞效率和渔获量。但大规模投放的人工集鱼装置被认为会对金枪鱼种群和中上层生态系统造成潜在的生态影响:可能会对金枪鱼的集群、摄食、健康、生长、洄游、死亡等生活史活动产生负面影响,从而导致种质衰退;另一方面,兼捕多种硬骨鱼类、鲨鱼、蝠鲼、海龟等非目标鱼种也可能扰动大洋中上层生态系统的平衡。但是,对于人工集鱼装置生态影响的评估在不同类型不同海域的研究结果中存在矛盾并无法确定。本文梳理归纳了过去30年中人工集鱼装置生态影响评估的相关研究进展,在此基础上展望了今后研究的改进方向,以期为人工集鱼装置生态影响的研究和管理提供参考。     

Impacts of domestication on angling vulnerability of common carp,Cyprinus carpio: the role of learning,foraging behaviour and food preferences

Domestication in fish selection increases vulnerability to angling. Two common garden‐reared genotypes of common carp, Cyprinus carpio L., differing in degree of domestication (highly domesticated mirror carp and less domesticated scaled carp) were exposed to fishing in two environments (i.e. ponds and laboratory tanks) to quantify vulnerability to angling. Foraging behaviour and food preferences were quantified to explain variation in angling vulnerability in a mechanistic manner. Domesticated mirror carp were more vulnerable to angling gear than scaled carp in both environments, which was related to greater food intake and bolder‐foraging behaviour. Independent of genotype, catchability decreased and time until first capture increased over fishing time, indicating learned hook avoidance. No differences were observed in food preferences among genotypes, rendering bait‐selective feeding an unlikely explanation for differential vulnerability to angling. It was concluded that vulnerability to angling has a genetic basis in carp and that boldness plays a paramount role in explaining why more domesticated genotypes are more easily captured by angling.     

What makes fish vulnerable to capture by hooks? A conceptual framework and a review of key determinants

Considerable time and money are expended in the pursuit of catching fish with hooks (e.g., handlining, angling, longlining, trolling, drumlining) across the recreational, commercial and subsistence fishing sectors. The fish and other aquatic organisms (e.g., squid) that are captured are not a random sample of the population because external (e.g., turbidity) and underlying internal variables (e.g., morphology) contribute to variation in vulnerability to hooks. Vulnerability is the probability of capture for any given fish in a given location at a given time and mechanistically explains the population‐level catchability coefficient, which is a fundamental and usually time‐varying (i.e., dynamic) variable in fisheries science and stock assessment. The mechanistic drivers of individual vulnerability to capture are thus of interest to fishers by affecting catch rates, but are also of considerable importance to fisheries managers whenever hook‐and‐line‐generated data contribute to stock assessments. In this paper, individual vulnerability to hooks is conceptualized as a dynamic state, in which individual fish switch between vulnerable and invulnerable states as a function of three interdependent key processes: an individual fish's internal state, its encounter with the gear, and the characteristics of the encountered gear. We develop a new conceptual framework of “vulnerability,” summarize the major drivers of fish vulnerability, and conclude that fish vulnerability involves complex processes. To understand vulnerability, a shift to interdisciplinary research and the integration of ecophysiology, fish ecology, fisheries ecology and human movement ecology, facilitated by new technological developments, is required.     

Inter‐ and intra‐specific interactions affecting crustacean trap fisheries—Implications for management

The UK coastal trap fisheries target two key species, European lobster Homarus gammarus (L.) and brown crab Cancer pagurus L. Their stock status is assessed periodically using size‐based, yield‐per‐recruit analysis. Fishery trends are described using landings and, where available, effort data to estimate catch per unit of effort (CPUE), nominally proportional to abundance. Despite being caught together, assessments assume that concurrent capture of these species does not distort their individual CPUE estimates. Here, an in situ experiment tested impacts of inter‐specific and intra‐specific interactions by pre‐loading baited traps with different species and observing subsequent catches. Pre‐loaded European lobster significantly reduced brown crab catches, whereas, other species produced no such effects. The findings highlight the likely inconsistency of using CPUE as an index of abundance if landings data originate from a mixed‐species fishery in which species interactions and targeting behaviour of fishers are unknown or un‐quantified.