Quantifying the influence of geography and environment on the northeast Atlantic mackerel spawning distribution

Mackerel (Scomber scombrus) in the northeast Atlantic have shown changes in distribution at certain times of the year, which have impacted their exploitation and management. In this study, mackerel spawning habitat over 21 recent years was characterised using generalised additive modelling, based on spatial egg density data collected every third year during targeted ichthyoplankton surveys. Mackerel spawning distribution was found to depend primarily on geographical variables (coordinates and bottom depth), with preferred spawning locations on the shelf‐edge from the north of the Iberian peninsula to the west of Scotland, with a maximum west of Ireland. Environmental drivers had a lesser influence on egg distribution. Dome shaped relationships were found with temperature and mixed layer depth, with respective optimum at 13°C and around –300 m. The model was used to reconstruct maps of the potential habitat (areas where conditions were suitable, but not necessarily used, for spawning). Little changes were observed over the years in the potential habitat, suggesting that the expansion of the egg distribution (realised habitat) was not triggered by changes in the environmental variables investigated. Little evidence was found for density‐dependent habitat selection. There was a tendency for mackerel to make more use of areas of lesser suitability in years with large stock size (1992 and 2010). This pattern, however, broke down in 2013, when stock size was the highest, as spawning occurred very south and concentrated in the most suitable habitat.     

Temporal and spatial availability of Atlantic Thread Herring,Opisthonema oglinum,in relation to oceanographic drivers and fishery landings on the Florida Panhandle

Since 1995, landings of Atlantic Thread Herring (Opisthonema oglinum) on the Florida Panhandle averaged 124 mt each spring (April–June) but declined to nearly zero in 1996–97 and 2006. To elucidate causes of recurring periods of low landings, we used generalized additive mixed models (GAMMs) to examine the relationship between Atlantic Thread Herring catch in a trawl survey on the west‐central coast of Florida and four environmental variables. Chlorophyll‐a was significant in the models, indicating a direct relationship between local abundance of baitfish and their planktonic food. Temperature and depth were also significant whereas salinity was not. During 2003 and 2012, synoptic satellite‐derived temperature and chlorophyll‐a maps were used with the GAMMs to predict monthly spatial availability on the Florida Panhandle fishing grounds (long. 85–88^o W and depth 12–25 m). The predicted monthly availability was significantly correlated with commercial catch rates (Pearson's r = 0.26, P = 0.004, d.f. = 118). We used multiple linear regression (MLR) with lags to describe the effect of river discharge and wind (as a transport mechanism) on surface chlorophyll‐a over the Panhandle fishing grounds. Discharge from local rivers was significant in all MLRs, and the Mississippi was only significant as an interaction with wind. We conclude that Atlantic Thread Herring are distributed over the Panhandle fishing grounds based on food availability that is driven by river discharge and eastward transport of Mississippi River plumes. This analysis improves our understating of baitfish dynamics, an important ecosystem component in the Gulf of Mexico.     

CPUE standardisation and the construction of indices of stock abundance in a spatially varying fishery using general linear models

Construction of annual indices of stock abundance based on catch and effort data remains central to many fisheries’ assessments. While the use of more advanced statistical methods has helped catch rates to be standardised against many explanatory variables, the changing spatial characteristics of most fisheries data sets provide additional challenges for constructing reliable indices of stock abundance. After reviewing the use of general linear models to construct indices of annual stock abundance, potential biases which can arise due to the unequal and changing nature of the spatial distribution of fishing effort are examined and illustrated through the analysis of simulated data. Finally, some options are suggested for modelling catch rates in unfished strata and for accounting for the uncertainties in the stock and fishery dynamics which arise in the interpretation of spatially varying catch rate data.     

我国东、黄海鲐鱼灯光围网渔业CPUE标准化研究

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。     

大西洋中上层鲨鱼资源状况的初步探讨

据1994—2001年4个航次在金枪鱼延绳钓渔船对热带大洋性中上层鲨鱼资源进行调查，并分析国际大西洋金枪鱼资源保护委员会提供的关于中上层鲨鱼的渔业数据。结果表明：延绳钓渔业共兼捕13种鲨鱼，其中，尖吻鲭鲨和大青鲨是优势种类。尖吻鲭鲨在第1、第2和第4航次的CPUE分别为每千钩0．3502、0．1754和0．0642尾，呈下降趋势。大青鲨在第1～3航次的的CPUE达到每千钩5～7尾，而在第4航次下降为每千钩0．8尾。研究报告了中国金枪鱼船队自1993年开始在大西洋兼捕尖吻鲭鲨和大青鲨的渔获量，并根据捕捞死亡系数和大西洋总渔获量数据，初步探讨了尖吻鲭鲨和大青鲨年平均资源量，影响CPUE的因素和大西洋中上层资源状况。     

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.     

Causes of walleye pollock (Theragra chalcogramma) recruitment decline in the northern Sea of Japan: implications for stock management

Recruitment of the northern Japan Sea stock (JSS) of walleye pollock has been decreasing since around 1990. In this study, I analyzed the factors causing this decrease in recruitment by investigating the relationship between recruitment, spawning stock biomass (SSB) and environmental factors using a generalized additive model (GAM). GAM fit to the data showed the importance of SSB, sea surface temperature (SST), ocean current strength (Tsushima Warm Current) and wind intensity (Asian monsoon) in determining the recruitment. Of these, the relationship between SSB and recruitment was positive and not negatively density‐dependent. On the other hand, the recruitment was negatively related to SST and ocean current strength, and a dome‐shaped relationship was observed between wind intensity and recruitment. Since around 1990, the values of SST and ocean current strength have mostly been high and that of wind intensity mostly low. In addition, SSB has been decreasing since the late 1990s. It is likely that the recruitment decline of JSS after approximately 1990 has been caused by warm water temperature, strong Tsushima Warm Current and weak Asian monsoon, and that the recent decrease in SSB has amplified this recruitment decline. According to the model’s estimation, a recruitment recovery due to environmental improvement will be highly restricted as long as SSB remains at its current low level. Significant recovery of SSB is urgently needed for JSS.     

Environmental modeling of occurrence of dolphinfish (Coryphaena spp.) in the Pacific Ocean off Mexico reveals seasonality in abundance,hot spots and migration patterns

Dolphinfish are little known migratory fish targeted by sport, artisanal and commercial fleets. In this study, we analyzed a 10 year database of incidental catches of the tuna purse seine fleet in the Pacific Ocean off Mexico with the aim to understand the environmental determinants of the spatial distribution and seasonal migration patterns of dolphinfish. We modeled the probability of occurrence of dolphinfish as a function of spatial (geographical coordinates), temporal (month/year) and environmental variables (sea surface temperature [SST], chlorophyll [CHL] and sea surface height [SSH], inferred from satellites) using logistic Generalized Additive Models. Dolphinfish preferred waters with SST values from 23 to 28°C, low (<0.2 mg/m³) CHL values, and primarily positive SSH values. Two dolphinfish hot spots were found in the study area: one in an oceanic zone (10°–15°N, 120°–125°W), which was more defined during spring, and one on the Pacific side of the Baja California Peninsula, which became important during summer. Models suggested that dolphinfish migrated through the study area following a “corridor” that ran from the Gulf of Tehuantepec along the Equatorial Upwelling zone to the oceanic hot spot zone, which in turn connected with the hot spot off the BCP. This “migratory corridor” went around the Eastern Pacific Warm Pool, which suggested that dolphinfish avoided this high temperature‐low production zone. Dolphinfish occupied zones close to certain oceanic features, such as eddies and thermal fronts. Results suggested that the primary cause of the biological hot spots was wind‐driven upwelling, because the hot spots became more important 3–4 months after the peak in upwelling activity.     

Tuna and swordfish catch in the U.S. northwest Atlantic longline fishery in relation to mesoscale eddies

To analyze the effects of mesoscale eddies, sea surface temperature (SST), and gear configuration on the catch of Atlantic bluefin (Thunnus thynnus), yellowfin (Thunnus albacares), and bigeye tuna (Thunnus obesus) and swordfish (Xiphias gladius) in the U.S. northwest Atlantic longline fishery, we constructed multivariate statistical models relating these variables to the catch of the four species in 62 121 longline hauls made between 1993 and 2005. During the same 13‐year period, 103 anticyclonic eddies and 269 cyclonic eddies were detected by our algorithm in the region 30–55°N, 30–80°W. Our results show that tuna and swordfish catches were associated with different eddy structures. Bluefin tuna catch was highest in anticyclonic eddies whereas yellowfin and bigeye tuna catches were highest in cyclonic eddies. Swordfish catch was found preferentially in regions outside of eddies. Our study confirms that the common practice of targeting tuna with day sets and swordfish with night sets is effective. In addition, bluefin tuna and swordfish catches responded to most of the variables we tested in the opposite directions. Bluefin tuna catch was negatively correlated with longitude and the number of light sticks used whereas swordfish catch was positively correlated with these two variables. We argue that overfishing of bluefin tuna can be alleviated and that swordfish can be targeted more efficiently by avoiding fishing in anticyclonic eddies and in near‐shore waters and using more light sticks and fishing at night in our study area, although further studies are needed to propose a solid oceanography‐based management plan for catch selection.     

Environmental effects on swordfish and blue shark catch rates in the US North Pacific longline fishery

Generalized additive models (GAMs) were applied to examine the relative influence of various factors on fishery performance, defined as nominal catch- per-unit-effort (CPUE) of swordfish (Xiphias gladius) and blue shark (Prionace glauca) in the Hawaii-based swordfish fishery. Commercial fisheries data for the analysis consisted of a 5 year (1991–1995) time series of 27 901 longline sets. Mesoscale relationships were analysed for seven physical variables (latitude, longitude, SST, SST frontal energy, temporal changes in SST (ΔSST), SST frontal energy (ΔSST frontal energy) and bathymetry), all of which may affect the availability of swordfish and blue shark to the fishery, and three variables (number of lightsticks per hook, lunar index, and wind velocity) which may relate to the effectiveness of the fishing gear. Longline CPUE data were analysed in relation to SST data on three spatiotemporal scales (18 km weekly, 1°-weekly, 1°-monthly). Depending on the scale of SST data, GAM analysis accounted for 39–42% and 44–45% of the variance in nominal CPUE for swordfish and blue shark, respectively. Stepwise GAM building revealed the relative importance of the variables in explaining the variance in CPUE. For swordfish, by decreasing importance, the variables ranked: (1) latitude, (2) time, (3) longitude, (4) lunar index, (5) lightsticks per hook, (6) SST, (7) ΔSST frontal energy, (8) wind velocity, (9) SST frontal energy, (10) bathymetry, and (11) ΔSST. For blue shark, the variables ranked: (1) latitude, (2) longitude, (3) time, (4) SST, (5) lightsticks per hook, (6) ΔSST, (7) ΔSST frontal energy, (8) SST frontal energy, (9) wind velocity, (10) lunar index, and (11) bathymetry. Swordfish CPUE increased with latitude to peak at 35–40°N and increased in the vicinity of temperature fronts and during the full moon. Shark CPUE also increased with latitude up to 40°N, and increased westward, but declined abruptly at SSTs colder than 16°C. As a comparison with modelling fishery performance in relation to specific environmental and fishery operational effects, fishery performance was also modelled as a function of categorical time (month) and area (2° squares) variables using a generalized linear model (GLM) approach. The variance accounted for by the GLMs was ≈ 1–3% lower than the variance explained by the GAMs. Time series of swordfish and blue shark CPUE standardized for the environmental and operational variables quantified in the GAM and for the time-area effects in the GLM are presented. For swordfish, both nominal and standardized time series indicate a decline in CPUE, whereas the opposite trend was seen for blue shark.     

1999—2011年东、黄海鲐资源丰度年间变化分析

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。     

南极大西洋扇区磷虾渔业渔获率突变特征及其致因分析

本研究利用CCARMLR数据库中提取的南极大西洋扇区(含48.1、48.2和48.3亚区)1982-2011年30年间的南极磷虾(Euphausia superba)年平均渔获率数据,运用Mann-Kendall法分析了其时间序列的发展趋势及突变特征.从趋势特征看,48区月均名义CPUE由1982年的5t/h左右,变化至2011年的10t/h左右.CPUE值时间序列呈现显著性周期波动,线性趋势年均增幅为0.221t/h.48.1亚区为主要捕捞区域,其CPUE线性趋势增幅最小,为年均0.088 t/h;而48.2亚区增幅最大,年增幅达0.323 9 t/h; 41.3亚区的年增幅为0.261 t/h.就渔获率突变特征而言,过去30年48区磷虾渔获率变化趋势为先缓后快的逐渐上升过程,渔获率突变点发生在1999年,这个突变在2001年后显著性存在.3个亚区磷虾渔获率均存在“上升突变”突变点.48.1亚区渔获率分别于2001年和2004年出现相交突变点,但均未通过α=0.05的显著线检验.48.2亚区分别于1995-1996年“向下突变”,但未通过α=0.05的显著线检验,1996-1997年出现“向上突变”,2000年通过α=0.05的显著线检验.48.3亚区突变发生在1992年,突变点通过α=0.05的显著线检验.结合海冰面积和捕捞(包括般队、捕捞技术、加工工艺)等因子分析突变的致因时,发现:(1)捕捞技术和加工工艺是最主要的致突变因子;(2)海冰面积在1983-1993年对渔获率突变有明显贡献;(3)空间上,越靠近南大陆,环境因子对突变的发生越容易产生作用.     

Spatio‐temporal trends of sailfish,Istiophorus platypterus catch rates in relation to spawning ground and environmental factors in the equatorial and southwestern Atlantic Ocean

Spatial and temporal trends of sailfish catch rates in the southwestern and equatorial Atlantic Ocean in relation to environmental variables were investigated using generalized additive models and fishery‐dependent data. Two generalized additive models were fit: (i) ‘spatio‐temporal’, including only latitude, longitude, month, and year; and (ii) ‘oceanographic’, including sea surface temperature (SST), chlorophyll‐a concentration, wind velocity, bottom depth, and depth of mixed layer and year. The spatio‐temporal model explained more (average ~40%) of the variability in catch rates than the oceanographic model (average ~30%). Modeled catch rate predictions showed that sailfish tend to aggregate off the southeast coast of Brazil during the peak of the spawning season (November to February). Sailfish also seem to aggregate for feeding in two different areas, one located in the mid‐west Atlantic to the south of ~15°S and another area off the north coast of Brazil. The oceanographic model revealed that wind velocity and chlorophyll‐a concentration were the most important variables describing catch rate variability. The results presented herein may help to understand sailfish movements in the Atlantic Ocean and the relationship of these movements with environmental effects.     

Thirty years later: the global growth of ITQs and their influence on stock status in marine fisheries

Individual transferable quota (ITQ) programmes have been incorporated into many marine fisheries management strategies for 30 years, but their implementation and utility remains controversial. This study provides an overview of the global status of ITQ programmes, the reasons they have been adopted and the changes in stock biomass after their implementation. Eighteen countries currently use ITQs to manage several hundred stocks of at least 249 species. ITQs were adopted in these countries for many reasons: overcapitalization, economic gains, safety concerns for fishers and political change. The implementation of ITQs does not translate into consistent changes in stock biomass. Improvements in 12 of 20 stocks after ITQs were introduced suggest that ITQs can be an effective component of fisheries management strategies, but eight of the stocks continued to decline after ITQs were introduced. This suggests that alternative or complementary measures are needed to sustain those fisheries, such as combining ITQs with more effective total allowable catches, better enforcement and monitoring, and implementing aspects of ecosystem-based fisheries management.     

Variation in the distribution of yellowfin sole Limanda aspera larvae in warm and cold years in the eastern Bering Sea

Multiyear periods of relatively cold temperatures (2007–2013) and warm temperatures (2001–2005 and 2014–2018) altered the eastern Bering Sea ecosystem, affecting ocean currents and wind patterns, plankton community, and spatial distribution of fishes. Yellowfin sole Limanda aspera larvae were collected from the inner domain (≤50 m depth) of the eastern Bering Sea among four warm years (2002, 2004, 2005, 2016), an average year (2006), and three cold years (2007, 2010, 2012). Spatial distribution and density of larvae among those years was analyzed using generalized additive models that included timing of sea-ice retreat, areal coverage of water ≤0°C, and water temperature as covariates. Analyses indicated a combination of temperature effects on the location and timing of spawning, and on egg and larval survival, may explain the variation in larval density and distribution among years. During warm years, higher density and wider spatial distribution of larvae may be due to earlier spawning, an expansion of the spawning area, and higher egg and larvae survival due to favorable temperatures. Larval distribution contracted shoreward, and density was lower during cold conditions and was likely due to fish spawning closer to shore to remain in preferred temperatures, later spawning, and increased mortality. Predicted drift trajectories from spawning areas showed that larvae would reach nursery grounds in most years. Years when the drift period was longer than the pelagic phase of the larvae occurred during both warm and cold conditions indicating that settlement outside of nursery areas could happen during either temperature condition.     

Environmental influences on Atlantic bluefin tuna (Thunnus thynnus) catch per unit effort in the southern Gulf of St. Lawrence

The Atlantic bluefin tuna (Thunnus thynnus) population in the western Atlantic supports substantial commercial and recreational fisheries. Despite quota establishment and management under the auspices of the International Commission for the Conservation of Atlantic Tunas, only small increases in population growth have been estimated. In contrast to other western bluefin tuna fisheries indices, contemporary estimates of catch per unit effort (CPUE) in the southern Gulf of St. Lawrence have increased rapidly and are at record highs. This area is characterized by the Cold Intermediate Layer (CIL) that is defined by waters <3°C and located at depths of 30–40 m in September. We investigated the influence of several in situ environmental variables on the bluefin tuna fishery CPUE using delta‐lognormal modelling and relatively extensive and consistent oceanographic survey data, as well as dockside monitoring and mandatory logbook data associated with the fishery. Although there is considerable spatial and temporal variation of water mass characteristics, the amount of available habitat in the southern Gulf of St. Lawrence (assuming a > 3°C thermal ambit) for bluefin tuna has been increasing. The percentage of the water column occupied by the CIL was a significant environmental variable in the standardization of CPUE estimates. There was also a negative relationship between the spatial extents of the CIL and the fishery. Properties of the CIL account for variation in the bluefin tuna CPUE and may be a factor in determining the amount of available feeding habitat for bluefin tuna in the southern Gulf of St. Lawrence.     

Influence of oceanographic conditions on abundance and distribution of post‐larval and juvenile carangid fishes in the northern Gulf of Mexico

Relationships between abundance of post‐larval and juvenile carangid (jacks) fishes and physical oceanographic conditions were examined in the northern Gulf of Mexico (GoM) in 2011 with high freshwater input from the Mississippi River. Generalized additive models (GAMs) were used to explore complex relationships between carangid abundance and physical oceanographic data of sea surface temperature (SST), sea surface height anomaly (SSHA) and salinity. The five most abundant carangid species collected were: Selene setapinnis (34%); Caranx crysos (30%); Caranx hippos (10%); Chloroscombrus chrysurus (9%) and Trachurus lathami (8%). Post‐larval carangids (median standard length [SL] = 10 mm) were less abundant during the spring and early summer, but more abundant during the late summer and fall, suggesting summer to fall spawning for most species. Juvenile carangid (median SL = 23 mm) abundance also increased between the mid‐summer and early fall. Most species showed increased abundance at lower salinities and higher temperatures, suggesting entrainment of post‐larval fishes or feeding aggregations of juveniles at frontal convergence zones between the expansive river plume and dynamic mesoscale eddy water masses. However, responses were species‐ and life‐stage specific, which may indicate fine‐scale habitat partitioning between species. Ordination methods also revealed higher carangid abundances at lower salinities for both post‐larval and juvenile life stages, with species‐ and life‐stage specific responses to SST and SSHA, further suggesting habitat separation between species. Results indicate strong links between physical oceanographic features and carangid distributions in the dynamic northern GoM.     

Spatial assessment of predator–prey relationships in the North Sea: the influence of abiotic habitat properties on the spatial overlap between 0‐group cod and grey gurnard

The understanding of spatio‐temporal dynamics of marine ecosystems is crucial for ecosystem‐based fisheries management and climate change impact assessments. We quantified temporal changes in the distribution of 0‐group cod (Gadus morhua) and grey gurnard (Eutriglia gurnardus), a primary predator of 0‐group cod, with the help of regression kriging and assessed the temporal dynamics of the related spatial predator–prey overlap of these two species at different spatial scales. We analysed the robustness of relationships among abiotic habitat properties (temperature, salinity and depth) and abundance. Small cod was mainly found in low salinity areas of the Skagerrak but larger year classes were able to expand their distribution area towards the central and northern North Sea. In contrast, grey gurnard was mainly found in waters with salinities above 33 and temperatures above 14°C. This species has expanded its high density areas in the central North Sea northward over the last two decades. Recruitment success of cod was negatively correlated to a Moran's I cross‐correlation index, a proxy for the degree of spatial overlap between both species. Strong cod year classes overlapped less with grey gurnard at the large and medium spatial scale. In general, the relationships between abiotic habitat properties and abundance showed an increased inter‐annual variability, which was likely caused by underlying factors not taken into account in the distribution models. Thus assemblage modeling approaches combining the strength of different model types should be considered in the future to predict potential distribution patterns under climate change scenarios.     

基于GAM的长江口鱼类资源时空分布及影响因素

根据2006至2017年长江口及其邻近海域鱼类资源调查,运用广义加性模型研究长江口鱼类资源密度与环境因子之间的关系,并对2017年鱼类资源密度的时空分布进行预测。结果显示,春夏秋冬四个季节最佳GAM偏差解释率分别为69.6%、55.9%、51.4%和47.4%,交叉验证回归线斜率的平均效应为0.62～0.88。盐度、水温和溶解氧是影响长江口鱼类资源密度的主要环境影响因子且在不同季节对鱼类资源密度有不同的影响机制。总体上,在春、夏、秋季,盐度与鱼类资源密度之间存在正向相关性;在夏、秋、冬季,水温对鱼类资源密度有显著影响,在秋季与鱼类资源密度之间存在正向相关性;在春、秋、冬季,溶解氧对鱼类资源密度有显著影响,在冬季与鱼类资源密度之间存在正向线性相关。研究表明,2017年夏季鱼类资源密度较高;在长江口南支的自然延伸水域存在鱼类资源密度的相对低值,在崇明岛向海自然延伸方向水域存在鱼类资源密度的相对高值。后续研究将对长江口鱼类资源进行不同生态类型区分,以期更加准确地掌握影响各生态类型鱼类时空分布的环境因素及其时空分布信息。