Projecting species distributions using fishery-dependent data

Many marine species are shifting their distributions in response to changing ocean conditions, posing significant challenges and risks for fisheries management. Species distribution models (SDMs) are used to project future species distributions in the face of a changing climate. Information to fit SDMs generally comes from two main sources: fishery-independent (scientific surveys) and fishery-dependent (commercial catch) data. A concern with fishery-dependent data is that fishing locations are not independent of the underlying species abundance, potentially biasing predictions of species distributions. However, resources for fishery-independent surveys are increasingly limited; therefore, it is critical we understand the strengths and limitations of SDMs developed from fishery-dependent data. We used a simulation approach to evaluate the potential for fishery-dependent data to inform SDMs and abundance estimates and quantify the bias resulting from different fishery-dependent sampling scenarios in the California Current System (CCS). We then evaluated the ability of the SDMs to project changes in the spatial distribution of species over time and compare the time scale over which model performance degrades between the different sampling scenarios and as a function of climate bias and novelty. Our results show that data generated from fishery-dependent sampling can still result in SDMs with high predictive skill several decades into the future, given specific forms of preferential sampling which result in low climate bias and novelty. Therefore, fishery-dependent data may be able to supplement information from surveys that are reduced or eliminated for budgetary reasons to project species distributions into the future.     

Spatial distribution of Antarctic minke whales (Balaenoptera bonaerensis) in relation to spatial distributions of krill in the Ross Sea,Antarctica

The spatial distribution of Antarctic minke whales in the Ross Sea with relation to spatial distributions of their prey – krill – was investigated in this study using generalized additive models (GAMs). Spatial distributions of two species of krill (ice and Antarctic krill) were estimated by GAMs. Three abiotic factors – distance from the continental shelf break (800 m isobaths), the mean temperature and salinity from the surface to 200 m (MTEM‐200 and MSAL‐200), and latitude and longitude – were used as covariates for models of krill. Estimated spatial distributions of krill were then used with other covariates to model the spatial distribution of Antarctic minke whales. In the selected model of Antarctic minke whales, Antarctic krill were more influential than ice krill. The number of Antarctic minke whales increased as the density of Antarctic krill increased to around 1.5 g m^?2. Beyond that, the number of Antarctic minke whales decreased as the density of Antarctic krill increased. High densities of the Antarctic minke whales were estimated along the sea ice edge in the eastern part of the Ross Sea. Specifically, the densities were high in the north of the continental shelf break where low MTEM‐200 and MSAL‐200 and intermediate densities of Antarctic krill were observed. Further data collection is needed to investigate interannual variations and trends in their relationship. The results show that the spatial distribution of Antarctic minke whales is a function of longitude, distance from the shelf break, oceanographic condition (temperature and salinity), and densities of ice and Antarctic krill.     

海州湾双斑蟳栖息分布特征与环境因子的关系

为了解双斑蟳栖息分布规律,实验根据2011—2016年多个季度航次在海州湾进行的渔业资源和环境调查数据,采用广义线性模型(GLM)、广义可加模型(GAM)以及随机森林3种物种分布模型(SDMs)方法,结合AIC(akaike information criterion)准则、累积偏差解释率和交叉检验等评判指标筛选和构建了双斑蟳栖息分布模型,并分析了环境因子对双斑蟳分布的影响。结果显示,3种模型在解释因子与响应变量间的关系上基本一致;其中GAM在模型拟合上具有优势,而随机森林的预测性能明显高于传统的GLM和GAM。双斑蟳相对渔获量在年份和月份间的变异性最为显著,两个因子的解释率分别在18%和3.8%以上。水深和表层盐度对双斑蟳资源分布的影响较大,均与双斑蟳相对丰度呈正相关关系;双斑蟳分布总体呈现冬季相对较高,夏季东北部海域高、西南部低的特点,与海州湾水深分布特点基本一致。本研究还根据FVCOM(finite-volume coasta ocean model)模拟环境数据,利用随机森林分布模型估计了双斑蟳在海州湾海域2011年各个季节的空间分布,为渔业资源的开发和保护提供依据。     

Predictive spatial modelling of seasonal bottlenose dolphin (Tursiops truncatus) distributions in the Mississippi Sound

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Estimation of the abundance of the sei whale <Emphasis Type="Italic">Balaenoptera borealis</Emphasis> in the central and eastern North Pacific in summer using sighting data from 2010 to 2012

The abundance of the sei whale Balaenoptera borealis in the central and eastern North Pacific (north of 40°N, south of the Alaskan coast including both the US and Canadian Exclusive Economic Zones between 170°E and 135°W), from July to August, was estimated by the line transect method using sighting data obtained during the 2010–2012 International Whaling Commission-Pacific Ocean Whale and Ecosystem Research cruises. The probability of detecting whales at a perpendicular distance from the transect was estimated using two different models: hazard rate and half-normal models. Because the difference in Akaike’s information criterion between the two models was small, the Akaike weighted average of the two models was taken, which gave an estimated abundance of 29,632 (coefficient of variation, 0.242; 95% confidence interval, 18,576–47,267). This is the first abundance estimate of sei whales in this region based on systematic sighting survey data, which contributes to an understanding of the current status of this species.     

Predicting the age of fish using general and generalized linear models of biometric data: A case study of two estuarine finfish from New South Wales, Australia

Direct ageing of fish can be a laborious and expensive task when age estimates from a large population are required, and often involves a degree of subjectivity. This study examined the application of general and generalized linear models that predict the age of fish from a range of efficiently and objectively measured covariates. The data sampled were from yellowfin bream (Acanthopagrus australis (Sparidae) (Owen, 1853)) and sand whiting (Sillago ciliata (Sillaginidae) Cuvier, 1829) populations from New South Wales, Australia. The covariates evaluated in the models were fish length, otolith weight, sex and location (the estuary from which the fish were sampled). Akaike Information Criteria were used for model selection and residual plots of the final models revealed a satisfactory fit to the observations. The best fitting model for each species included all covariates. An additional investigation considered whether general and generalized linear models that predict age from two different categories of biometric information outperform age-length keys with respect to subsequent estimates of total mortality from catch-curve analysis. The two categories of biometric information differed in the ease and cost with which the information could be collected. The first category only included fish length and location as covariates, whilst the second category also included otolith weight and sex. It was found that traditional age-length keys outperformed the predictive models that estimated age from only fish length and location, because the results from the models were prone to significant bias. However, when otolith weight and sex were added as covariates to the predictive models, some of them, including a generalized linear model with a Poisson-distributed response variable, performed similarly to the age-length key. Given that otolith weight and the sex of fish are cheaper to quantify than age from a sectioned otolith in many situations, general or generalized linear models may represent a cheaper and faster method of estimating mortality compared to age-length keys. Such models can also easily incorporate the influence of spatial, temporal and demographic variation.     

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.     

Spatial distribution pattern and physical – biological interactions in the larval notothenioid fish assemblages from the Bransfield Strait and adjacent waters

The Bransfield Strait and adjacent waters represent one of the most important areas of larval retention off the Antarctic Peninsula. The species composition of larval fish assemblages has been described in detail in previous surveys carried out in the area, but the role of environmental parameters influencing the spatial distribution of early life stages was poorly known. By applying generalized additive models and multivariate analyses, we evaluated the role of environmental variables in shaping the small‐scale distribution of larval fish and investigated the spatial structure of the larval assemblage. It consisted of a few dominant notothenioid species, such as Champsocephalus gunnari, Lepidonotothen squamifrons, Lepidonotothen larseni, Pleuragramma antarctica and Trematomus scotti, and several other rarely caught species. Sea water temperature, salinity and sampling depth were the most important factors determining the spatial distribution of fish with different relative contributions, together explaining more than 80% of total deviance observed. Species richness was mostly affected by salinity, probably due to the narrow range of salinity preference by the species. Cluster analysis of abundance and presence data identified six and five distinct groups, respectively, each of them with substantial contributions of single or rarely two species. Differences in reproductive strategies of adult populations and spatial distribution of early life stages driven by different larval behaviour in response to environmental factors contribute to maintaining a well‐structured larval fish assemblage, ensuring spatial and food niche partitioning.     

Spatial and temporal variation in the distribution of juvenile southern bluefin tuna Thunnus maccoyii: implication for precise estimation of recruitment abundance indices

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Influence of adaptive stations in a transect-based sampling design for a multispecies fish survey

A multispecies transect-based survey with an adaptive sampling design was evaluated to determine the import of adding stations adaptively at sea in order to better resolve the cross-shelf distribution of species in regions of rapid bathymetric change. The dataset came from a series of transects occupied in November, January, March, and May from May 2003 to November 2005 along transects northeast of Hudson Canyon and northeast of Baltimore Canyon in the Mid-Atlantic Bight region of the western Atlantic. The transect survey results demonstrate the necessity of high sample density in this region of the continental shelf where fish aggregate patchily over scales of a few kilometers. Species cross-shelf distributions were often bimodal. The adaptive sampling protocol demonstrated the expected tendency of fish to be underestimated or overestimated given inadequate sampling density. However, on the average, low sample density led to an underestimation of biomass or abundance and often strongly so. Modeling of the transect design reveals that the overestimates and underestimates, as well as the bias towards underestimation, originate from variations in patch location and, even more importantly, patch shape, with the sampling design. The transect model shows that extreme overestimates and underestimates can occur when patch size is small relative to the distance between stations, but the occurrence of routine, predictable, persistent underestimates in some species is not so easily explained. The model clearly resolves the importance of bimodality and a patch form represented by a dome shape in determining the vulnerability of a species to a biomass or abundance underestimate. Cases where the fixed stations alone provide data clearly inadequate for the estimate of abundance or biomass occur when sampling density is inadequate to identify the center of the patch or to identify the shape of the patch. It is the improved understanding of patch shape that is the single most important contribution of the adaptive sampling protocol, not a better knowledge of the location of the patches. Patch shape is a principal determinant of the adequacy of sample density.     

Spatial and temporal distribution of Lepeophtheirus salmonis (Kr?yer) larvae in a sea loch containing Atlantic salmon, Salmo salar L., farms on the north-west coast of Scotland.

A plankton survey investigated spatial and temporal distributions of larval sea lice in a sea loch on the north-west coast of Scotland. Plankton tows were collected approximately weekly at two depths (0 and 5 m) at five sample stations over a 2-year period. The survey began in March 2002 when Atlantic salmon, Salmo salar L., farms in the study area stocked with fish and finished in March 2004, after farms completed harvesting. Over 90% of lice recovered were Lepeophtheirus salmonis (Kr?yer); therefore, the results of this paper refer largely to that species. The data were analysed using generalized additive models with explanatory variables for time, depth and station. Greatest densities of nauplii were recovered at stations adjacent to farms indicating that the local salmon farms were a likely source of larvae at times during the production cycle. There were significant temporal trends in larval densities and the stocking and harvesting of farms can possibly account for these increases and decreases, particularly at the start and at the end of the production cycle. The distribution of copepodids was more widespread than that of nauplii, indicating that the larvae can be transported several kilometres from the point of release.     

Changes in the distribution of Atlantic cod (Gadus morhua) in the southern Gulf of St Lawrence — effects of environmental change or change in environmental preferences?

Density-independent redistribution in response to changing temperature conditions and density-dependent redistribution in response to changing temperature preferences are two contrasting hypotheses to explain changes in the distribution of cod populations. I tested these hypotheses using survey data on the distribution of cod during the feeding season in the southern Gulf of St Lawrence. These tests used indices of cod distribution as the dependent variable and indices of cod abundance and bottom temperature as explanatory variables. Both hypotheses were often supported in univariate tests that ignored confounding between the two explanatory variables. Tests that accounted for this confounding indicated an effect of cod abundance on distribution for ages 4–8⁺ years, and 3⁺, but provided no support for an effect of environmental conditions on distribution except for age 3. Variation in the temperature distribution of cod was consistent with an effect of abundance on interannual variation in distribution and with no effect of environment except for age 3 cod. Age 3 cod were consistently under-represented in areas of very cold bottom water but older cod were not. As predicted by bioenergetic considerations, cod tended to occupy colder water at high levels of abundance, suggesting a mechanism for density-dependent shifts in distribution. Shifts in cod distribution during the feeding season in the southern Gulf appear to be more closely linked to density-dependent changes in environmental preferences than to density-independent responses to changing environmental conditions.     

Potential distribution and population trends of the smalltail shark Carcharhinus porosus inferred from species distribution models and historical catch data

1. Updated distribution ranges are crucial for conservation status assessments. Comprehensive analyses combining published literature and available data on historical catches and species distribution models (SDMs) are effective tools that could improve the prediction of more realistic scenarios for some species, especially those with limited information available and facing multiple threats.
2. The present study aimed at generating an updated distribution for the smalltail shark Carcharhinus porosus, one of the most threatened and understudied shark species of the western Atlantic Ocean. Estimates of the key areas for this species conservation based on the SDMs, and trends in catch probabilities throughout its distribution range are provided.
3. Four algorithms (BIOCLIM, Domain, Mahalanobis, and Maximum Entropy) were used to model the distribution of C. porosus and calculate its habitat suitability based on marine environmental variables. To assess historical catch probability trends, we built a generalized linear model from published and grey literature data. This analysis was used to estimate catch probability as an indication of population trends.
4. SDMs suggest that the northern coast of South America (NCSA) harbours the most suitable habitats for C. porosus in the world, which was expected given its historically high catch rate in this region. In addition, there was a continuously declining catch probability trend starting in the 1970s. However, the decline was smaller for the NCSA as compared with the Gulf of Mexico and the eastern South America coast.
5. Results indicate that the NCSA should be considered the currently most important area in the world for this species conservation. Furthermore, the lack of data throughout Central and South American marine regions hampers the evaluation of extinction risk throughout its updated distribution. Thus, research in these areas is urgently required for a more comprehensive conservation status assessment.

     

Population status and distribution of whitespotted conger (Conger myriaster) in Yellow Sea: An important migratory species along coastal China with limited data

Whitespotted conger (Conger myriaster) is a marine migratory species with important economic and ecological values in Northwestern Pacific. The population status and distribution of whitespotted conger may have changed in the eastern coastal water of China owing to the intensive fishing pressure and human activities in the past few decades. There have been miscellaneous concerns about its population trend and potential environment‐driven variations in spatiotemporal distribution. Delta‐generalized linear models, generalized linear mixed models, and a set of correlation analyses were performed to answer the above concerns, and a stratified random sampling‐designed bottom trawl survey from 2011 to 2017 in Haizhou Bay of the central Yellow Sea was conducted to collect samples. Our study suggested that whitespotted conger remained a relatively stable population status with slight fluctuations likely caused by climate variability during 2011–2017. The hierarchical generalized linear mixed models with spatial random effect performed better than the generalized linear model and the common generalized linear mixed models. Spatiotemporal differences of whitespotted conger were significantly associated with bottom water salinity, depth, sampling time, and space, which were probably mainly influenced by a combination of the Cold Water Mass, the Yellow Sea Warm Current, and the Yellow Sea Coastal Current. The predicted spatiotemporal distribution of whitespotted conger has a monthly variation matching its seasonable migration and an overall higher abundance in the deeper water than that in the neritic areas in Haizhou Bay.     

Spatial structure of co-occurring anchovy and sardine populations from acoustic data: implications for survey design

A geostatistical analysis has been undertaken on the spatial structure of co-occurring adult and recruit populations of anchovy, Engraulis capensis , and sardine, Sardinops sagax , in the southern Benguela upwelling region, using information from two acoustic surveys. The study was prompted by the need for a more efficient design for surveying sardine abundance, which is increasing in relation to that of anchovy; the current acoustic survey design is based on the distribution of anchovy. Variograms of fish density and density indicator variables were computed, as well as cross-variograms between the indicator variables. The sardine variograms were less structured than the anchovy variograms, with slightly greater nugget effects, indicating greater randomness in space at small scales. The indicator variograms showed progressive loss of structure with increasing density. Anchovy formed high-density schools during the day, breaking into larger, low-density aggregations at night. Sardine, on the other hand, remained in relatively high-density schools throughout the day. The cross-variograms revealed some spatial continuity between low- and high-density areas for anchovy, but no such transitional structures were evident for sardine. It was concluded that sardine are more patchily distributed than anchovy and, unlike anchovy, they may not have a single common way of occupying space at the population level, perhaps partly because of the broader age structure of the population. It is concluded that, while the current acoustic survey design is well suited to the spatial distribution of anchovy, it is not as well suited to that of sardine. Future survey designs should be more tailored to the spatial distribution of sardine, possibly by using sampling methods to cope with the highly patchy distributions expected.     

Spatiotemporal distribution and habitat use of commercial demersal species in the eastern Mediterranean Sea

Generalized additive models (GAMs) were applied to investigate the influence of spatial (subarea), temporal (season) and environmental variables (substrate characteristics, depth, temperature and salinity) on the relative abundance of 27 demersal species of commercial importance in the Aegean Sea. Twelve species exhibited decreasing population density with increasing depth, whereas the abundance of the remaining species peaked at intermediate depths. Most of the species were mainly distributed on the continental shelf and upper continental slope. The dry weight percentage of sand in the sediment was included as an important predictor in the best models of all species with a lifecycle closely related to the substrate (flatfish, skates, gurnards, mullets, anglers, scorpionfish) and in most benthopelagic species (seven of 12). The weight percentage of carbonates in the sediment was also included in the best models of most species (19 of 27). Seasonal patterns in the relative abundance of species were observed, related in most cases to the seasonal differentiation of temperature and salinity gradients. During the period of water stratification (summer and autumn) the influence of temperature or salinity on fish abundance was always greater than during the period of vertical mixing (winter). The present results are discussed in the light of fostering the current perception as to factors influencing the spatiotemporal distribution of fish, which is a prerequisite for the sustainable exploitation of commercial stocks.     

Modeling environmental,temporal and spatial effects on twaite shad (Alosa fallax) by‐catches in the central Mediterranean Sea

Modeling the relationships between environmental factors and the distribution at sea of species of conservation interest can be useful in predicting their occurrence from a local to a regional scale. This information is essential for planning management and conservation initiatives. In this study, generalized additive models (GAMs) were applied to investigate the influence of environmental, temporal and spatial variables on the catch rates of the twaite shad Alosa fallax (Lacepède) by the pelagic trawl fishery in the north‐central Adriatic Sea. Presence/absence and abundance [catch per unit effort (CPUE)] data between 2006 and 2012 were separately modeled, and the two models were then validated using a test data set. The most important factor influencing the presence and abundance of adult twaite shads was the spatial predictor (latitude × longitude). Two areas of major shads aggregations were observed, the most important of which being located near the estuaries of three main river systems of northern Italy. The twaite shad presence was also significantly affected by season, the largest and lowest occurrences being observed in autumn and spring, respectively. Among the environmental variables tested, only sea surface temperature was included in both models. Alosa fallax showed a wide thermal tolerance (6–27°C) with preference for temperature around 23°C. The model developed from the abundance data showed a moderate predictive power, whereas the accuracy of the presence/absence model was rather low. Some conclusions on the ecological requirements of A. fallax at sea arising from this study are useful to orient future monitoring and research programs and to develop effective conservation actions.     

An investigation of avoidance by Antarctic krill of RRS James Clark Ross using the Autosub-2 autonomous underwater vehicle

The autonomous underwater vehicle (AUV) Autosub-2 was deployed on eight missions ahead of RRS James Clark Ross in the northern Weddell Sea and in the Bransfield Strait, Southern Ocean, to assess avoidance of the research vessel by Antarctic krill Euphausia superba. The AUV was equipped with the same type of scientific echosounder as the research vessel (Simrad EK500 operating at 38 and 120 kHz) and measured the density of krill along transect acoustically (g m⁻² wet mass) prior to the ship’s arrival. We hypothesised that if krill avoided the ship, perhaps in response to radiated noise, then the ship should detect less krill than the AUV which is known to have much lower noise levels than the ship. We were unable to detect any significant difference between the density of krill detected by the ship or the AUV, either at the transect level or at finer scales within transects. We conclude, therefore, that avoidance by krill of RRS James Clark Ross will not significantly bias acoustic estimates of krill abundance by this vessel.