A generalised linear model for catch allocation: an example from Australia''s Northern Prawn Fishery

Two biologically distinct species, Penaeus semisulcatus and P. esculentus, are caught in the tiger prawn component of Australia's Northern Prawn Fishery. These species are recorded and marketed together as ‘tiger prawns’. A generalised linear model is used to separate the logbook catches of ‘tiger prawns’ into catches by individual species, even though only fragmentary historical survey data are available. We also consider generalised additive model and generalised linear mixed model approaches, and the extra benefits they might allow.     

VGLMs and VGAMs: An overview for applications in fisheries research

The vector generalized linear and additive model (VGLM/VGAM) classes of statistical regression models implement general maximum likelihood estimation and smoothing. The VGLM/VGAM framework is very general and is shown to include many popular fisheries regression models such as GLMs and GAMs, the negative binomial (NB), the zero-inflated Poisson (ZIP) and ZINB, the zero-altered Poisson (ZAP) and ZANB as special cases. The primary purpose of this article is to introduce the VGLM/VGAM methodology into fisheries science. To this end, data from the 2008 FIPS-MOUCHE World Fly Fishing Championships is used to illustrate the chief advantages of the framework, viz. its large size and its ability to fit each model in a very flexible manner. Having a large framework leads to greater efficiencies in the practical modelling of data. The specific questions examined fall under two categories: (i) what distribution do the fish lengths have in each of the sectors? (ii) can fish catch reduction be detected and if so, how can the effects be ameliorated? As well as the above models, the utility of several other seemingly disparate regression models to fisheries research are presented, such as the bivariate odds-ratio model, the generalized extreme value distribution, and several quantile regression techniques.     

Statistical analysis of the relationship among environmental variables, inter-annual variability and smolt trap efficiency of salmonids in the Tucannon River

Spring and fall chinook (Oncorhynchus tshawytscha), steelhead (Oncorhynchus mykiss) and hatchery spring chinook in the Tucannon River, Washington, USA are listed as “threatened” under the Endangered Species Act of 1973. Restoration and management of both species can be facilitated by understanding how biotic and abiotic factors affect their smolt trap efficiency. In this paper, we examine the effects of the rate of water flow, water temperature, the level of staff gauge, debris load, and Secchi disk readings on their weekly smolt trap efficiency from 1998 to 2003 using a generalized linear model (GLM) with a binomial response (link function – logit). The nonlinear relationships between the smolt trap efficiency and abiotic variables are also analyzed using a generalized additive model (GAM) with a binomial response (link function – logit). Both GLM and GAM analyses showed that the trap efficiency varied among years for fall chinook, steelhead, and wild spring chinook, but not for hatchery spring chinook, and that the level of staff gauge and the rate of water flow were the most important factors altering trap efficiency. The partial residuals from GAM analyses were used to determine the optimal number of sampled fish with a known efficiency and to detect possibly misleading results from GLM analyses.     

西北太平洋秋刀鱼CPUE标准化研究

秋刀鱼(Cololabis saira)是西北太平洋海域重要的渔业种类之一,其资源评估工作已成为热点问题,单位捕捞努力量渔获量(CPUE)标准化可以为开展有效的资源评估研究提供科学依据。为此,本研究利用2003~2017年中国大陆西北太平洋秋刀鱼渔业生产统计资料,结合卫星遥感获得的海洋环境数据,如海表面温度、海表温度梯度、海表面高度等,基于广义线性模型(General linear model, GLM)和广义可加模型(Generalized additive model, GAM)对中国大陆西北太平洋秋刀鱼渔业进行CPUE标准化。结果显示,根据BIC准则,在GLM模型结果中,年份、月份、经度、纬度、海表面温度、海表面高度、海表温度梯度及年份与月份对CPUE具有显著影响,并组成了GLM模型的最佳模型,对CPUE偏差的解释率为52.47%;在GAM模型结果中,除上述8个影响变量外,交互项月份与经度和月份与纬度也对CPUE影响较大,GAM的最佳模型对CPUE偏差的解释率为61.9%。通过5-fold交叉验证分析发现,GAM模型标准化结果较优于GLM模型,更适合于西北太平洋秋刀鱼渔业CPUE标准化。     

基于多维度抽检数据的全国食品安全状况分析及对策探究

为规范养殖生产者药物使用行为,促进中国水产养殖业的绿色发展,本文基于中国沿海11个省市的海水鱼养殖生产者调研数据,运用logit模型、线性回归模型及中介效应模型实证分析产业组织模式对海水鱼养殖生产者药物使用行为的影响及其作用机理。结果表明, (1)紧密型产业组织对生产者安全用药行为具有显著正向影响; (2)加入紧密型产业组织的生产者用药量显著降低; (3)不同类型的紧密型产业组织对生产者的药物使用行为影响不同,“合作社 (协会)＋生产者”模式显著优于“企业主导的生产基地+生产者”模式; (4)养殖培训在紧密型产业组织模式对生产者药物使用行为的影响中存在中介效应,能够通过培训知识技能、提供解决问题措施等途径进一步减少生产者药物使用。基于此,文章提出重视紧密型产业组织尤其是合作社 (协会)的作用、开展生产者绿色养殖培训、发展养殖保险等建议,以期加快推进中国水产养殖业绿色发展。     

Comparing GLM,GLMM, and GEE modeling approaches for catch rates of bycatch species: A case study of blue shark fisheries in the South Atlantic

Modeling and understanding the catch rate dynamics of marine species is extremely important for fisheries management and conservation. For oceanic highly migratory species in particular, usually only fishery‐dependent data are available which have limitations in the assumption of independence and if often zero‐inflated and/or overdispersed. We tested different modeling approaches applied to the case study of blue shark in the South Atlantic, by using generalized linear models (GLMs), generalized linear mixed models (GLMMs), and generalized estimating equations (GEEs), as well as different error distributions to deal with the presence of zeros in the data. We used fractional polynomials to deal with non‐linearity in some of the explanatory variables. Operational (set level) data collected by onboard fishery observers, covering 762 longline sets (1,014,527 hooks) over a 9‐year period (2008–2016), were used. One of the most important variables affecting catch rates is leader material, with increasing catches when wire leaders are used. Spatial and seasonal variables are also important, with higher catch rates expected toward temperate southern waters and eastern longitudes, particularly between July and September. Environmental variables, especially SST, also affect catches. There were no major differences in the parameters estimated with GLMs, GLMMs, or GEEs; however, the use of GLMMs or GEEs should be more appropriate due to fishery dependence in the data. Comparing those two approaches, GLMMs seem to perform better in terms of goodness‐of‐fit and model validation.     

The influence of multiyear drought and associated reduction in tributary connectivity on an adfluvial fish species

Multiyear drought is projected to increase in frequency and duration in arid and semiarid regions across the world, threatening native species and ecosystem function. The effects of multiyear drought are often exacerbated by human water use, which manifest in reduced lake elevation, reduced stream discharge, and disruption in hydrologic connectivity for aquatic species. Here, we demonstrate that drought-driven decreasing lake levels reduce the connectivity between tributaries and lakes by creating an elevation-explicit tributary distance map. We combined long-term fish catch data and a lake elevation time-series with our elevation-explicit tributary distance map to test whether population demographics are related to drought-driven changes in tributary connectivity. We surveyed the littoral zone of Bear Lake, Utah and Idaho, USA, from full pool to a depth of >12 m, totalling 94.86 km² surveyed. As lake elevation decreased from full pool to the lowest historical elevation, tributary channel distance increased by 3.5 km. Bear Lake Bonneville Cutthroat Trout (Oncorhynchus clarkii utah) catch per unit effort was strongly negatively correlated with tributary channel distance, though individual growth rates were not influenced by drought metrics. We predicted the response of age 0 to age 10 cutthroat under high and low cobble availability, estimating up to a 61% decline in cutthroat CPUE when tributary channel distance is at its maximum historical value. Our study provided a unique opportunity to identify quantitative linkages between climate-driven changes in habitat connectivity and an ecologically important endemic sportfish, expanding our understanding of potential pathways through which climate change may affect lentic ecosystems and fishes.     

Mortality of Diplodus annularis and Lithognathus mormyrus released by recreational anglers: implications for recreational fisheries management

Abstract  The factors affecting mortality in Diplodus annularis (L.) and Lithognathus mormyrus (L.) caught and released in a recreational fishery in the Balearic Islands (NW Mediterranean) were examined. A total of 194 and 214 specimens of each species, respectively, were caught and individually monitored in containment tanks for 10 days. The circumstances of the catch, such as capture depth, water temperature, fish size, hook type, hook location, bleeding, unhooking time and cutting the hook line were tested with a logistic regression model. Diplodus annularis experienced moderate rates of mortality (15%), and only deep-hooking was a significant predictor of death. The incidence of undersized fish for this species was 48%. By contrast, L. mormyrus exhibited higher mortality rates (33%) with over 90% of the catch under the minimum legal size. Deep-hooking was the strongest predictor of mortality. When circle hooks were used, or if the line was cut when the fish were deep-hooked, mortality was considerably reduced. Strategies, such as promoting the use of more selective gears that reduce the capture of undersized fish and implementing gentler release techniques, should be considered in managing these species.     

Multispecies fisheries management and conservation: tactical applications using models of intermediate complexity

Stakeholders increasingly expect ecosystem assessments as part of advice on fisheries management. Quantitative models to support fisheries decision‐making may be either strategic (‘big picture’, direction‐setting and contextual) or tactical (focused on management actions on short timescales), with some strategic models informing the development of tactical models. We describe and review ‘Models of Intermediate Complexity for Ecosystem assessments’ (MICE) that have a tactical focus, including use as ecosystem assessment tools. MICE are context‐ and question‐driven and limit complexity by restricting the focus to those components of the ecosystem needed to address the main effects of the management question under consideration. Stakeholder participation and dialogue is an integral part of this process. MICE estimate parameters through fitting to data, use statistical diagnostic tools to evaluate model performance and account for a broad range of uncertainties. These models therefore address many of the impediments to greater use of ecosystem models in strategic and particularly tactical decision‐making for marine resource management and conservation. MICE are capable of producing outputs that could be used for tactical decision‐making, but our summary of existing models suggests this has not occurred in any meaningful way to date. We use a model of the pelagic ecosystem in the Coral Sea and a linked catchment and ocean model of the Gulf of Carpentaria, Australia, to illustrate how MICE can be constructed. We summarize the major advantages of the approach, indicate opportunities for the development of further applications and identify the major challenges to broad adoption of the approach.     

Geostatistics in fisheries survey design and stock assessment: models, variances and applications

Over the past 10 years, fisheries scientists gradually adopted geostatistical tools when analysing fish stock survey data for estimating population abundance. First, the relation between model‐based variance estimates and covariance structure enabled estimation of survey precision for non‐random survey designs. The possibility of using spatial covariance for optimising sampling strategy has been a second motive for using geostatistics. Kriging also offers the advantage of weighting data values, which is useful when sample points are clustered. This paper discusses, with fisheries applications, the different geostatistical models that characterise spatial variation, and their variance formulae for many different survey designs. Some anticipated developments of geostatistics related to multivariate structures, temporal variability and adaptive sampling are discussed.     

Coupling an oceanographic model to a Fishery Observing System through mixed models: the importance of fronts for anchovy in the Adriatic Sea

Anchovy, Engraulis encrasicolus, forms the basis of Italian small pelagic fisheries in the Adriatic Sea. The strong dependence of this stock on environmental factors and the consequent high variability makes the dynamics of this species particularly complicated to model. Weekly geo‐referenced catch data of anchovy obtained by means of a Fishery Observing System (FOS) from 2005 to 2011 were referred to a 0.2 × 0.2 degree grid (about 20 km²) and associated with the environmental parameters calculated by a Regional Ocean Modelling System, AdriaROMS. Generalized Additive Mixed Models (GAMM) with and without random effects were used to identify a relationship between abundance in the catch and oceanographic conditions. The outcomes of models with no random effects, with random vessel effects and with the random vessel and random week‐of‐the‐year effects were examined. The GAMM incorporating a random vessel and week‐of‐the‐year effect were selected as the best model on the basis of the Akaike information criteria (AIC). This model indicated that catches (abundance) of anchovy in the Adriatic Sea correlate well with low temperatures, salinity fronts and sea surface height, and allowed the identification of areas where high concentrations of this species are most likely to occur. The results of this study demonstrate that GAMM are a useful tool to combine geo‐referenced catch data with oceanographic variables and that the use of a mixed‐model approach with spatial and temporal random effects is an effective way to depict the dynamics of marine species.     

Reducing bycatch impacts in recreational fisheries: Case study examining terminal tackle in the multispecies Gulf of Maine groundfish fishery

Terminal tackle regulations can be a valuable tool for fisheries management, especially in multispecies fisheries where bycatch and discards are common issues. In the Gulf of Maine, recreational anglers frequently discard critically depleted Atlantic cod Gadus morhua L. as bycatch when targeting the abundant haddock Melanogrammus aeglefinus (L.) stock. The present study investigated species catch composition, catch rates and animal welfare across various terminal tackle setups, and aspects of capture and handling with the goal of reducing bycatch and discard mortality. Overall, 2558 cod and 4266 haddock were captured with six terminal tackle setups in the western Gulf of Maine from April to October 2018. Along with angler experience and capture depth, lure type primarily influenced species catch composition and catch-per-unit-effort; hook types additionally influenced hook-removal times and physical injuries to fish. Results indicate that using baited hooks can both promote haddock catch and reduce cod bycatch, with specific hook types promoting increased survival.     

Environmental and spatial effects on the distribution of blue marlin (Makaira nigricans) as inferred from data for longline fisheries in the Pacific Ocean

Blue marlin is distributed throughout tropical and temperate waters in the Pacific Ocean. However, the preference of this species for particular habitats may impact its vulnerability to being caught. The relationship between spatio‐temporal patterns of blue marlin abundance and environmental factors is examined using generalized additive models fitted to catch and effort data from longline fisheries. The presence of blue marlin, and the catch rate given presence, are modeled separately. Latitude, longitude, and sea‐surface temperature explain the greatest proportion of the deviance. Spatial distributions of relative density of blue marlin, based on combining the probability of presence and relative density given presence, indicate that there is seasonal variation in the distribution of blue marlin, and that the highest densities occur in the tropics. Seasonal patterns in the relative density of blue marlin appear to be related to shifts in SST. The distribution and relative abundance of blue marlin are sufficiently heterogeneous in space and time that the results of analyses of catch and effort data to identify ‘hotspots’ could be used as the basis for time‐area management to reduce the amount of blue marlin bycaught in longline fisheries.     

南海西北部蓝圆鲹时空分布及其与环境因子的关系

蓝圆鲹(Decapterus maruadsi)是中国东南近海重要的经济鱼类之一。本研究根据2012—2018年南海西北部捕捞产量数据和海洋环境遥感数据,分析了该海域蓝圆鲹季节平均单位捕捞努力量渔获量(catch per unit effort, CPUE)的时空分布特征,并运用广义可加模型(generalized additive model, GAM)探究了CPUE与环境因子的关系。结果显示,蓝圆鲹的CPUE具有明显的季节性：夏季最高,CPUE达0.848 kg/(kW?d);冬季最低,CPUE为0.087 kg/(kW?d)。2016年CPUE的异常增加可能是受到2015—2016年超强厄尔尼诺事件的影响。GAM分析显示,该海域蓝圆鲹CPUE与经度、海表温度(sea surface temperature, SST)、叶绿素a (chlorophyll a, Chl-a) 浓度、海水深度、海表盐度(sea surface salinity, SSS)、涌浪波向、风浪波向及其周期显著相关。相对较高CPUE海域范围为110.5°~114°E,SST为26~30℃,Chl-a为0.2~1.0 mg/m3,海水深度<120 m,SSS为33.4~33.8,涌浪波向为75°~120°、150°~175°,风浪波向为50°~75°、120°~135°、175°~190°,风浪周期为3.0~4.5 s;其中,风浪波向对CPUE贡献最高,涌浪波向其次,然后是SST。南海西北部蓝圆鲹的资源丰度变化和其洄游特性与季风变化等引起的环境因子的变动有关。     

中西太平洋金枪鱼围网人工集鱼装置 (FADs)的集鱼特性

为了解鱼类在人工集鱼装置(FADs)周围的集群特性,基于2021年我国金枪鱼围网船在中西太平洋的回声探测浮标数据,对FADs投放后鱼类首次到达FADs的时间以及聚集的动态过程进行了探究。利用U检验和H检验分析了鱼类首次到达FADs时间的差异性,利用广义加性混合模型(GAMMs)分析了金枪鱼类聚集生物量随FADs海上漂流时间和漂流速度的变化情况,结果显示：(1)鱼类首次到达FADs的时间为(8.9±9.0) d,其中金枪鱼类为(3.8±4.2) d,非金枪鱼类为(16.0±8.9) d;(2)金枪鱼类在不同水下长度FADs下的首次到达时间存在显著差异,而非金枪鱼类无显著差异;(3)金枪鱼类在FADs周围的聚集生物量随FADs海上漂流时间呈现动态变化,约在其投放后第25天到达峰值,随后逐渐下降;(4)金枪鱼聚集生物量随着FADs漂流速度的增加而逐渐降低;(5)随机效应表明,水下长度为80 m的FADs下金枪鱼类聚集生物量一般最高,其次是60 m,90 m最低。研究表明,FADs投放后金枪鱼类往往先于非金枪鱼类到达,其首次到达时间与FADs的水下长度有关;具有较浅水下长度和缓慢漂流速度的FA...     

An application of generalized linear models in production model and sequential population analysis

In fitting production models and age-structured models to an index of the relative abundance of a fish population, errors are usually assumed to follow a log-normal or normal distribution, without any diagnostic analyses. A generalized linear model can readily deal with many types of error structures. In this paper, a generalized linear model is coupled with a production model and a sequential population model to assess the stock of the Atlantic cod (Gadus morhua) 2J3KL. This study suggests that the parameter estimates in these models can be greatly influenced by the assumption about the error structures in the estimation and that log-normal and gamma distributions are appropriate for the production model in assessing the Atlantic cod 2J3KL stock, whereas gamma distribution is appropriate for the sequential population model. We recommend that generalized linear models should be used to identify the appropriate error structure in modeling fish population dynamics.     

Variable variability: difficulties in estimation and consequences for fisheries management

Recent analyses propose that the key regulatory processes in fisheries are stochastic, characterized by increased recruitment variance at low stock sizes (heteroscedasticity). Here, we investigate the consequences of this idea, with the aim of testing its practical relevance to fisheries management. We argue that stock‐recruitment time series are at least one order of magnitude too short to reliably fit heteroscedastic models; indeed, they are typically insufficient even to establish in which direction recruitment variance changes with stock size. Unreliable estimates of heteroscedasticity can have important management implications, depending on the sign of the coefficient of heteroscedasticity. Maximum sustainable yield (MSY) estimates from simple models, which include heteroscedasticity can be volatile, unrealistically high and sometimes non‐existent, as illustrated by an analysis of North Sea cod (Gadus morhua) data. In contrast, for North Sea herring (clupea harengus) data, heteroscedasticity has a negligible effect on MSY estimates. Statistical models are useful to elucidate broad‐scale regulatory processes, but will need to combined with the mechanistic understanding offered by models of population dynamics before being applied in a management setting.     

Distribution,body length,and abundance of blue shark and shortfin mako offshore of northeastern Japan,as determined from observed pelagic longline data, 2000–2014

Longline surveys have been conducted in the Northwest Pacific Ocean from 2000 to 2014 using chartered commercial longline vessels. Each year, two cruises were conducted offshore of northeastern Japan from mid‐April to mid‐June. For each longline set during the surveys, onboard scientists collected detailed biological information about the species caught, such as the size and sex, and recorded the catch numbers for all species. Blue shark (Prionace glauca) and shortfin mako (Isurus oxyrinchus) have eurythermal distributions, but the application of a generalized additive model (GAM) showed that the sea surface temperatures (SSTs) at catch sites positive for shortfin mako were warmer than those for blue shark. On the basis of the GAM, the probabilities of occurrence of both sharks differed by size category: small sharks had a narrower SST range than that of large sharks. Most catches of both sharks were juveniles, and the nominal catch rate of blue shark was more than 10 times that of shortfin mako. The standardized catch per unit effort (CPUE) for both species was calculated using a generalized linear model (GLM) with negative binomial errors, or a delta‐lognormal GLM. The standardized CPUE for blue shark in the second quarter of the year peaked in the mid‐2000s and then decreased, but it has been increasing since 2012. The CPUE for shortfin mako in the second quarter generally increased, with fluctuations.     

基于线性混合模型的蓝点马鲛叉长和体重关系的月间及性别差异

为了研究蓝点马鲛（）生活史特征的异质性,根据2018年10月至2019年3月在东海外海渔场的拖网调查采样数据,对其叉长和体重关系的月间及性别差异进行了研究。依据收集的367尾蓝点马鲛样本,求得其叉长和体重关系（b的估计均值为2.794。本研究构建了广义线性模型和9个线性混合模型,用于研究蓝点马鲛的叉长和体重关系（）在时间及性别上的差异。贝叶斯信息准则（BIC）值和均方根误差值均表明,最复杂的线性混合模型（即月份和性别对两个参数P<0.01）。在最优模型中,a值则与此相反。本研究表明,月份和性别对蓝点马鲛叉长和体重关系具有显著的影响,线性混合模型能把月份和性别的异质性通过随机效应在单个模型中更准确、快速地体现,从而进一步证实了此模型在数据来源异质性研究中的优势。