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Cheng Zhou Rong Wan Jie Cao Liuxiong Xu Xuefang Wang Jiangfeng Zhu 《Fisheries Oceanography》2021,30(1):23-37
Habitat distribution is critically informative for stock assessment, since incorporating its variabilities can have important implications for the estimation of stock biomass or the relative abundance index. A refined ecological niche model with habitat characteristic parameterization was developed to reconstitute a 3‐D ecological map of bigeye tuna in the Pacific Ocean. We determined the boundaries and hierarchies of oceanographic features and hydrological conditions at horizontal and vertical scales to define the habitat preference of bigeye tuna associated with their feeding and physiological requirements. Ecogeographic projections underlined the depth‐ and region‐specific habitat distribution of bigeye tuna, with noticeable dynamic variations in the response to climate variability. Depths from 300 to 400 m represented layers of the most productive habitat, which was widespread through the equatorial Pacific Ocean and extended to the north‐central Pacific Ocean. The proportion of high‐quality habitat size in the north Pacific had a strictly regular intra‐annual cycle with peaks during the winter. Climate variability appeared to disturb the balance of the regular fluctuations in habitat size in the equatorial Pacific. Habitat hotspots during an El Niño period were characterized by their expansion to the north of the Hawaiian islands, shrinkage in the west for the hotspot band north of the Equator, and an eastern shift for the band south of the Equator. This variability may be the consequence of the incorporated fluctuations of the oxygen minimum zones (OMZ), current systems, and stratification in the open ocean. 相似文献
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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. 相似文献
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Seiji Ohshimo Yuki Fujinami Ko Shiozaki Mikihiko Kai Yasuko Semba Nobuhiro Katsumata Daisuke Ochi Hiroaki Matsunaga Hiroshi Minami Masashi Kiyota Kotaro Yokawa 《Fisheries Oceanography》2016,25(3):259-276
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. 相似文献
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RÉKA DOMOKOS 《Fisheries Oceanography》2009,18(6):419-438
The South Equatorial Counter Current (SECC) strongly influences the American Samoa Exclusive Economic Zone (EEZ) and changes strength on a seasonal and ENSO cycle. A strong SECC is associated with a predominantly anticyclonic eddy field as well as increased micronekton biomass and catch-per-unit-effort (CPUE) for albacore tuna, the economically important target species of the local longline fishery. A strong SECC carries chlorophyll a -rich waters from upwelling regions at the north coast of New Guinea towards the EEZ, most likely resulting in the observed increase in micronekton biomass, forage for albacore. Relatively stable anticyclonic eddies show a further increase in micronekton biomass, apparently advected from neighboring SECC waters. The presence of forage presumably concentrates albacore, thus resulting in the observed increase in CPUE. High shear regions of neither anticyclonic nor cyclonic eddies correlate with increased micronekton biomass. Areas characterized by South Equatorial Current (SEC) waters correspond to areas with the lowest micronekton biomass and the highest number of aggregative structures, which are most likely small pelagic fish shoals. Micronekton composition in SEC waters differs from that in the SECC. During El Niños, the seasonal signals at the north shore of New Guinea and in the SECC are exceptionally strong and correspond to higher albacore CPUE in the EEZ. My results suggest that the strength of upwelling and the resulting increase in chlorophyll a at New Guinea, as well as the Southern Oscillation Index, could be used to predict the performance of the local longline fishery for albacore tuna in the American Samoa EEZ. 相似文献
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A logistic production model was used to examine potential relationships between three climate indices, the North Pacific Gyre Oscillation (NPGO), the Pacific Decadal Oscillation (PDO), and the Multivariate El Niño‐Southern Oscillation Index (MEI), and productivity estimates of the North Pacific albacore tuna (Thunnus alalunga) population. Catch and standardized catch‐per‐unit‐effort data from three longline fisheries (Japan, US, and Taiwan) were used in the model. The climate indices were incorporated into the model by correlating time‐varying intrinsic population growth rate (ry) of the production model with the annual mean value for each index. The estimated probability that the NPGO is positively correlated with stock productivity, as measured by ry, was 0.99, and the calculated probability that MEI is negatively correlated with the productivity was 0.95. The time lag for these correlations is 4 yr, which is consistent with the timing of recruitment to the Japan longline fishery. The PDO did not seem to have any detectable relationship with stock productivity. However, it remains uncertain if there is a conclusive linkage between the albacore productivity and the NPGO or the MEI index, because model fit to the data is about the same as that of a base model which does not use any climate index and assumes a time‐invariant r. 相似文献
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Ramiro Castillo Luciano Dalla Rosa Walter García Diaz Lauro Madureira Mariano Gutierrez Luís Vsquez Rolf Koppelmann 《Fisheries Oceanography》2019,28(4):389-401
Oceanographic and hydroacoustic data were obtained by the Instituto del Mar del Peru (IMARPE) during 72 cruises off the Peruvian coast between 1985 and 2017 to determine the ranges of the abiotic parameters influencing the anchovy (anchoveta) distribution and to observe the effect of the 1997–1998 El Niño event. The hydroacoustic data show a high seasonal variability in anchoveta distribution related to differences of environmental parameters as well as changes in distribution after the very strong El Niño event in 1997–1998. Geostatistic variograms were used to describe the seasonal variability and generalized additive models (GAMs) with a Tweedie distribution were applied to study the relationships between anchoveta and oceanographic parameters. The dependent variable was the value for anchoveta obtained from echosounder (nautical area scattering coefficient [NASC] of anchoveta) and the tested covariates were temperature, salinity, and dissolved oxygen at the sea surface; distance to the coast; year, latitude–longitude; and Oceanic Niño Index 1 + 2. The results show a high variability of anchoveta with seasonal differences in its distribution. Preferred abiotic conditions (temperature, salinity, oxygen) of anchoveta were 17.6–23.7°C, 32.30–35.14, and 5.9–8.7 ml/L in summer and 14.5–18.8°C, 34.81–35.12, and 5.2–6.3 ml/L in winter. The values in autumn and spring were intermediate and are considered as in transition. The anchoveta were detected at higher values after the 1997–1998 El Niño event, probably influenced by reduced standing stocks of congener fish species and by the Pacific decadal oscillation (PDO) or by a changes in climate. 相似文献
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日本鲐是我国近海重要的中上层鱼类资源之一,评估其资源量需要对单位捕捞努力量渔获量（CPUE）进行标准化。影响CPUE标准化的因素很多,包括季节、区域和海洋环境等。本文利用广义线型模型（GLM）和广义加性模型（GAM）,结合时空、捕捞船、表温等因子,对1998-2006年东、黄海大型灯光围网渔业鲐鱼CPUE进行标准化,并评价各因子对CPUE的影响。首先应用GLM模型评价时间、空间、环境以及捕捞渔船参数对CPUE的影响,并确定显著性变量。其次,将显著性变量逐一加入GAM模型,根据Akaike信息法则（AIC）,选择最优的GAM模型。最后,利用最优的GAM模型对CPUE标准化,并定量分析时间、空间、环境以及捕捞渔船参数对鲐鱼CPUE的影响。GLM模型结果表明：8个变量对CPUE有重要影响,依次为年、船队、船队与年的交互效应、月、船队与月份的交换效应、经度、纬度和海表温。根据AIC,包含上述8个显著性变量的GAM模型为最优模型,对CPUE偏差的解释为27.78%。GAM模型结果表明：高CPUE分别出现在夏季海表温为28～31 ℃的东海中部和冬季海表温为12～16 ℃的黄海;1998-2006年,标准化后的CPUE呈逐年下降趋势,与持续增长的捕捞努力量有关。 相似文献
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- Striped marlin (Tetrapturus audax) is an oceanic pelagic migratory fish. The stock status of striped marlin in the Indian Ocean is now considered to be overfished and subject to overfishing. Quantifying the level of at-haulback mortality caused by longline fisheries for tuna and tuna-like species is critical to reducing fishing pressure and protecting the fate of billfish stocks.
- This study was based on data from 2482 longline fishing operations recorded by Chinese observers in the western Indian Ocean from 2012 to 2019. The dataset includes information on the survival status of 774 striped marlin and their corresponding details. We used a generalized linear model (GLM) to analyse the level of at-haulback mortality and its potential influencing factors. The results indicate that the distribution of 774 striped marlin had a lower jaw-fork length (LJFL) range from 130 to 220 cm, and 51.5% of the specimens died at the time of haul-back. The GLM model revealed that quarter, sea-surface temperature (SST), hook type, LJFL, chlorophyll (CHL) and longitude had significant effects on at-haulback condition when the fish were retrieved on board, with the quarter and sea surface temperature having the most significant effects. The interaction term between hook type and LJFL also had a significant effect on at-haulback mortality, with the model predictions showing that mortality increased with LJFL when using circle hooks but decreased when using Japanese tuna hooks.
- There has been limited observational analysis of hooking mortality rates for striped marlin, and the present study may provide an important reference for the conservation and management of striped marlin stocks in the Indian Ocean.
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Spatial variability can confound accurate estimates of catch per unit effort (CPUE), especially in highly migratory species. The incorporation of spatial structure into fishery stock assessment models should ultimately improve forecasts of stock biomass. Here, we describe a nonlinear time series model for producing spatially explicit forecasts of CPUE that does not require ancillary environmental or demographic data, or specification of a model functional form. We demonstrate this method using spatially resolved (1° × 1° cells) CPUE time series of North Pacific albacore in the California Current System. The spatial model is highly significant (P < 0.00001) and outperforms two spatial null models. We then create a spatial forecast map for years beyond the range of data. Such approaches can guide spatial management of resources and provide a complement to more data‐intensive, highly parameterized population dynamics and ecosystem models currently in use. 相似文献
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Aaron B. Carlisle Randall E. Kochevar Martin C. Arostegui James E. Ganong Michael Castleton Jason Schratwieser Barbara A. Block 《Fisheries Oceanography》2017,26(1):34-48
The blue marlin (Makaira nigricans) is a highly migratory pelagic predator of tropical and subtropical seas. Information on the habitat use of marine species is fundamental to understanding their ecology and population dynamics and is needed to inform responsible management strategies. Using a long‐term satellite tagging data set from The International Game Fish Association Great Marlin Race, we examined habitat use and how oxygen and temperature influence the horizontal and vertical distributions of blue marlin in the Central Pacific. Blue marlin primarily occurred in warm waters (26–30°C) and exhibited a diel bimodal depth distribution across the 5‐year data record (2009–2013), with fish spending the majority of their time near the surface at night and at deeper depths during the day (25–100 m). The depth distribution of blue marlin was limited in areas where low oxygen and/or temperature conditions occur closer to the surface, with the extent of habitat compression being greatest when both oxygen and temperature were limiting. The migrations of blue marlin appeared restricted during the 2010 La Niña, when increased equatorial upwelling resulted in an extension of the cold, low oxygen waters of the cold tongue into the Central Pacific, creating a barrier to the trans‐equatorial migrations that occurred during all other tagging years. If the frequency and intensity of La Niña events increases and the oxygen minimum layer continues to expand as has been predicted under certain climate change scenarios, the migratory behavior and habitat availability of blue marlin may be impacted. 相似文献
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A generalized additive model (GAM) was constructed to separate and quantify the effects of fishery‐based (operational) and oceanographic parameters on the bigeye tuna (Thunnus obesus) catch rates at Palmyra Atoll in the central Tropical Pacific. Bigeye catch, the number of hooks per set, and set location from 4884 longline sets spanning January 1994 to December 2003 were used with a temporally corresponding El Niño‐Southern Oscillation (ENSO) indicator built from sea surface height (SSH) data. Observations of environmental data combined with the results from the GAM indicated that there is an increase in bigeye catch rates corresponding to an increase in eastward advection during the winter months of El Niño events. A seasonal pattern with higher bigeye catch rates from December to April and a spatial pattern with higher rates to the northeast and northwest of the atoll were observed during this study period. It is hypothesized that the combination of the eastward advection of the warm pool coupled with vertical changes in temperature during the winter months of El Niño events increases the availability of bigeye tuna in this region. This increase in availability may be due to a change in exploitable population size, location, or both. 相似文献
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RISHI SHARMA LUIS A. VÉLEZ‐ESPINO ALEX C. WERTHEIMER NATHAN MANTUA ROBERT C. FRANCIS 《Fisheries Oceanography》2013,22(1):14-31
Pacific Northwest Chinook, Oncorhynchus tshawytscha, have exhibited a high degree of variability in smolt‐to‐adult survival over the past three decades. This variability is summarized for 22 Pacific Northwest stocks and analyzed using generalized linear modeling techniques. Results indicate that survival can be grouped into eight distinct regional clusters: (1) Alaska, Northern BC and North Georgia Strait; (2) Georgia Strait; (3) Lower Fraser River and West Coast Vancouver Island; (4) Puget Sound and Hood Canal; (5) Lower Columbia Tules; (6) Columbia Upriver Brights, Willamette and Cowlitz; (7) Oregon and Washington Coastal; and (8) Klamath River and Columbia River Summers. Further analysis for stocks within each of the eight regions indicates that local ocean conditions following the outmigration of smolts from freshwater to marine areas had a significant effect on survival for the majority of the stock groups analyzed. Our analyses of the data indicate that Pacific Northwest Chinook survival covaries on a spatial scale of 350–450 km. Lagged time series models are presented that link large‐scale tropical Pacific conditions, intermediate‐basin scale northeastern Pacific conditions, and local sea surface temperatures to survival of Pacific Northwest stocks. 相似文献
14.
根据1999—2011年我国鲐大型灯光围网渔业数据,使用广义线性模型(generalized linear model,GLM)和广义加性模型(generalized additive model,GAM)估算了影响CPUE的时间(年、月)、空间(经度、纬度)、捕捞性能和环境效应[海表面温度(sea surface temperature,SST)、海表面高度、海表面叶绿素浓度],并以年效应作为资源丰度指数,分析了东、黄海鲐资源丰度的年间变化,东、黄海鲐资源丰度指数的年间变化与产卵场海表面温度以及捕捞强度间的关系。GAM结果表明,时间、空间、捕捞和环境变量对CPUE偏差的解释率为11.69%,其中变量年的解释率最大,占总解释率的38%。结果显示,1999—2011年东、黄海鲐鱼资源丰度指数(abundance index,AI)总体上呈下降趋势,2008年以来更是持续下降,丰度指数由2008年的1.22降至2011年的0.82。东、黄海鲐资源丰度指数年间与产卵场呈正相关,关系式为AI=-3.51+0.23SST(P0.05),这表明较高的产卵场SST对鲐资源量增加有利。过高的渔获量以及我国群众围网渔业渔船数量的快速增长是导致近年来鲐鱼资源下降的重要原因。 相似文献
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The environmental processes associated with variability in the catch rates of bigeye tuna in the Atlantic Ocean are largely unexplored. This study used generalized additive models (GAMs) fitted to Taiwanese longline fishery data from 1990 to 2009 and investigated the association between environmental variables and catch rates to identify the processes influencing bigeye tuna distribution in the Atlantic Ocean. The present findings reveal that the year (temporal factor), latitude and longitude (spatial factors), and major regular longline target species of albacore catches are significant for the standardization of bigeye tuna catch rates in the Atlantic Ocean. The standardized catch rates and distribution of bigeye tuna were found to be related to environmental and climatic variation. The model selection processes showed that the selected GAMs explained 70% of the cumulative deviance in the entire Atlantic Ocean. Regarding environmental factors, the depth of the 20 degree isotherm (D20) substantially contributed to the explained deviance; other important factors were sea surface temperature (SST) and sea surface height deviation (SSHD). The potential fishing grounds were observed with SSTs of 22–28°C, a D20 shallower than 150 m and negative SSHDs in the Atlantic Ocean. The higher predicted catch rates were increased in the positive northern tropical Atlantic and negative North Atlantic Oscillation events with a higher SST and shallow D20, suggesting that climatic oscillations affect the population abundance and distribution of bigeye tuna. 相似文献
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- From a biodiversity conservation viewpoint it is crucial to estimate the sensitivity of species and populations to climate change, especially of key species such as top predators.
- Here, the El Niño‐Southern Oscillation phenomenon (ENSO) was used as a natural experiment to estimate the sensitivity of a population of the rainforest‐dwelling broad‐snouted caiman, Caiman latirostris, to extreme floods.
- Caiman abundance declined by 35% annually between 1996 and 1998, and then increased, without reaching 1996 levels, indicating a marked effect of the 1997 El Niño. Accordingly, the Southern Oscillation Index was positively correlated with caiman abundance, indicating lower caiman abundance with warm ENSO events.
- The relationship between the relative annual mean abundance of caimans and the maximum daily annual discharge of the Iguazú River was analysed. This relationship was parabolic, with caiman abundance increasing at discharges from 500 to 1500 m3 s‐1 and then decreasing at discharges from 1500 to 2500 m3 s‐1, indicating an adverse effect of both extreme low and high river discharge. No effect of illegal hunting was measurable.
- This study evaluated whether the negative effect of extremely high water levels on caiman abundance could be due to a decrease in the availability of the habitat more commonly used by small (<60 cm total length, TL) and medium (60–120 cm TL) caimans. Small and medium‐sized caimans used herbaceous/shrub habitats more frequently than large caimans (>120 cm TL), i.e. the type of habitat flooded during extreme floods.
- An increase in extreme floods, as forecast for the Atlantic rainforest owing to climate change, may seriously affect the population of rainforest caimans through the reduction of adequate habitat for juveniles. This counter‐intuitive result, in which an excess of water reduces the abundance of an aquatic top predator, should be considered in conservation plans of rainforest‐dwelling crocodilians.