The relative influence of temperature and size‐structure on fish distribution shifts: A case‐study on Walleye pollock in the Bering Sea

Research has estimated associations between water temperature and the spatial distribution of marine fishes based upon correlations between temperature and the centroid of fish distribution (centre of gravity, COG). Analysts have then projected future water temperatures to forecast shifts in COG, but often neglected to demonstrate that temperature explains a substantial portion of historical distribution shifts. We argue that estimating the proportion of observed distributional shifts that can be attributed to temperature vs. other factors is a critical first step in forecasting future changes. We illustrate this approach using Gadus chalcogrammus (Walleye pollock) in the Eastern Bering Sea, and use a vector‐autoregressive spatiotemporal model to attribute variation in COG from 1982 to 2015 to three factors: local or regional changes in surface and bottom temperature (“temperature effects”), fluctuations in size‐structure that cause COG to be skewed towards juvenile or adult habitats (“size‐structured effects”) or otherwise unexplained spatiotemporal variation in distribution (“unexplained effects”). We find that the majority of variation in COG (including the north‐west trend since 1982) is largely unexplained by temperature or size‐structured effects. Temperature alone generates a small portion of primarily north–south variation in COG, while size‐structured effects generate a small portion of east–west variation. We therefore conclude that projections of future distribution based on temperature alone are likely to miss a substantial portion of both the interannual variation and interdecadal trends in COG for this species. More generally, we suggest that decomposing variation in COG into multiple causal factors is a vital first step for projecting likely impacts of temperature change.     

Cloudy with a chance of sardines: forecasting sardine distributions using regional climate models

Despite the significant advances in making monthly or seasonal forecasts of weather, ocean hypoxia, harmful algal blooms and marine pathogens, few such forecasting efforts have extended to the ecology of upper trophic level marine species. Here, we test our ability to use short‐term (up to 9 months) predictions of ocean conditions to create a novel forecast of the spatial distribution of Pacific sardine, Sardinops sagax. Predictions of ocean conditions are derived using the output from the Climate Forecast System (CFS) model downscaled through the Regional Ocean Modeling System (ROMS). Using generalized additive models (GAMs), we estimated significant relationships between sardine presence in a test year (2009) and salinity and temperature. The model, fitted to 2009 data, had a moderate skill [area under the curve (AUC) = 0.67] in predicting 2009 sardine distributions, 5–8 months in advance. Preliminary tests indicate that the model also had the skill to predict sardine presence in August 2013 (AUC = 0.85) and August 2014 (AUC = 0.96), 4–5 months in advance. The approach could be used to provide fishery managers with an early warning of distributional shifts of this species, which migrates from the U.S.–Mexico border to as far north as British Columbia, Canada, in summers with warm water and other favorable ocean conditions. We expect seasonal and monthly forecasts of ocean conditions to be broadly useful for predicting spatial distributions of other pelagic and midwater species.     

Marine environment‐based forecasting of coho salmon (Oncorhynchus kisutch) adult recruitment

Generalized additive models (GAMs) were used to investigate the relationships between annual recruitment of natural coho salmon (Oncorhynchus kisutch) from Oregon coastal rivers and indices of the physical ocean environment. Nine indices were examined, ranging from large‐scale ocean indicators, e.g., Pacific Decadal Oscillation (PDO), to indicators of the local ecosystem (e.g., coastal water temperature near Charleston, OR). Generalized additive models with two and three predictor variables were evaluated using a set of performance metrics aimed at quantifying model skill in short‐term (approximately 1 yr) forecasting. High explanatory power and promising forecast skill resulted when the spring/summer PDO averaged over the 4 yr prior to the return year was used to explain a low‐frequency (multi‐year) pattern in recruitment and one or two additional variables accounted for year‐to‐year deviations from the low‐frequency pattern. More variance was explained when averaging the predictions from a set of models (i.e., taking the ensemble mean) than by any single model. Making multiple forecasts from a set of models also provided a range of possible outcomes that reflected, to some degree, the uncertainty in our understanding of how salmon productivity is driven by physical ocean conditions.     

Environmentally driven forecasts of northern rock sole (Lepidopsetta polyxystra) recruitment in the eastern Bering Sea

Northern rock sole recruitment in the eastern Bering Sea has been hypothesized to (a) depend on wind‐driven surface currents linking spawning and nursery areas, (b) be density‐dependent, and (c) be negatively impacted by cold bottom temperatures over a large nursery area during the first summer of life. A suite of models was developed to test these hypotheses. Data included 32 years of recruitment and spawning biomass estimates derived from a stock assessment model and wind and temperature indices customized to the environmental exposure of age‐0 northern rock sole in the eastern Bering Sea. The predictive ability of the models was evaluated, and the models were used to forecast recruitment to age‐4 for recent year classes which are poorly retained by the standard multi‐species bottom trawl survey gear. Models which included wind and temperature indices performed better than a naïve forecast based on the running mean. The best‐performing model was a categorical model with wind and temperature thresholds, which explained 49% of the variation in recruitment. Ricker models performed more poorly than models without a spawning biomass term, providing no evidence that recruitment is related to stock size. The models forecast higher recruitment for the most recent year classes (2015–2018) than for prior year classes with observed poor recruitment (2006–2013). These environment‐based recruitment forecasts may improve recruitment estimates for the most recent year classes and facilitate study of the effects of future climate change on northern rock sole population dynamics.     

Modeling and forecasting pelagic fish production using univariate and multivariate ARIMA models

ABSTRACT:   Univariate and multivariate autoregressive integrated moving average (ARIMA) models were used to model and forecast the monthly pelagic production of fish species in the Mediterranean Sea during 1990–2005. Autocorrelation (AC) and partial autocorrelation (PAC) functions were estimated, which led to the identification and construction of seasonal ARIMA models, suitable in explaining the time series and forecasting the future catch per unit of effort (CPUE) values. Univariate and multivariate ARIMA models satisfactorily predicted the total pelagic fish production and the production of anchovy, sardine, and horse mackerel. The univariate ARIMA models demonstrated a good performance in terms of explained variability and predicting power. The current findings revealed a strong autoregressive character providing relatively high R ² and satisfactory forecasts that were close to the recorded CPUE values. The present results also indicated that the multivariate ARIMA outperformed the univariate ARIMA models in terms of fitting accuracy. The opposite was evidenced when testing the forecasting accuracy of the two methods, where the univariate ARIMA models overall performed better than the multivariate models. The observed seasonal pattern in the monthly production series was attributed to the intrinsic nature of the pelagic fishery. As anchovy, sardine, and horse mackerel represent main target species in the Mediterranean pelagic fishery, the findings of the present study provided direct support for the potential use of accurate forecasts in decision making and fisheries management in the Mediterranean Sea.     

The emblematic minnows of the North American Great Plains: A synthesis of threats and conservation opportunities

Anthropogenic changes to the Great Plains rivers of North America have had a large, negative effect on a reproductive guild of pelagic‐broadcast spawning (PBS) cyprinid fishes. The group is phylogenetically diverse, with multiple origins of the PBS mode. However, because of incomplete life‐history information, PBS designation often relies only on habitat and egg characteristics. We identified 17 known or candidate PBS fishes and systematically synthesized the literature on their biology and ecology in relation to major threats to persistence. Research output on an individual species was unrelated to conservation status, but positively correlated with breadth of distribution. The PBS species have opportunistic life‐history strategies and are typically short‐lived (generally 1–3 years) fishes. Many PBS species have truncated ranges showing declines in both distribution and abundance, especially those endemic to the Rio Grande catchment. Fundamental habitat associations are unknown for many species, particularly regarding seasonal shifts and early life stages. Critical thermal tolerances have been quantified for five PBS species and are generally >35°C. Turbidity and salinity changes are linked to responses at multiple life stages, but information is lacking on interactions between water quality and quantity. Hydrologic alteration appears to be a primary threat to PBS species, through complex interactions with landscape fragmentation, and habitat change. We highlight areas where scientific and management communities are lacking information and underline areas of potential conservation gain.     

Extending electronic length frequency analysis in R

Electronic length frequency analysis (ELEFAN) is a system of stock assessment methods using length‐frequency (LFQ) data. One step is the estimation of growth from the progression of LFQ modes through time using the von Bertalanffy growth function (VBGF). The option to fit a seasonally oscillating VBGF (soVBGF) requires a more intensive search due to two additional parameters. This work describes the implementation of two optimisation approaches (“simulated annealing” and “genetic algorithm”) for growth function fitting using the open‐source software “R.” Using a generated LFQ data set with known values, the accuracy of the soVBGF parameter estimation was evaluated. The results indicate that both optimisation approaches are capable of finding high scoring solutions, yet settings regarding the initial restructuring process for LFQ bin scoring (i.e. “moving average,”) and the fixing of the asymptotic length parameter (L_∞) are found to have significant effects on parameter estimation error. An outlook provides context as to the significance of the R‐based implementation for further testing and development, as well as the general relevance of the method for data‐limited stock assessment.     

Historical anecdotes of fishing pressure: Misconstrued “sea serpent” sightings provide evidence for antecedent entanglement of marine biota in the British Isles

Marine scholars have come to realize the importance of including historical perspectives as part of comprehensive assessments made of the social–ecological systems involved in sustainable fisheries management. In particular, there is increasing recognition of the value in examining information contained within historical anecdotes as a prelude to implementing current conservation actions as well as setting future restoration objectives. The present study demonstrates that careful parsing of eyewitness accounts of unidentified marine objects which at the time were purported to be sea serpents—of the “many‐humped” or “string‐of‐buoys” typology—actually reveals that marine fauna in the British Isles have been victims of entanglement in fishing gear for a much longer period than is customarily assumed. The temporal baseline for the onset of entanglement in this region certainly predates, by more than a century, the advent and widespread use of plastic in fisheries and other maritime operations.     

Where do you think you’re going? Accounting for ontogenetic and climate‐induced movement in spatially stratified integrated population assessment models

Understanding spatial population structure and biocomplexity is critical for determining a species’ resilience to environmental and anthropogenic perturbations. However, integrated population models (IPMs) used to develop management advice for harvested populations have been slow to incorporate spatial dynamics. Therefore, limited research has been devoted to understanding the reliability of movement parameter estimation in spatial population models, especially for spatially dynamic marine fish populations. We implemented a spatial simulation–estimation framework that emulated a generic marine fish metapopulation to explore the impact of ontogenetic movement and climate‐induced distributional shifts between two populations. The robustness of spatially stratified IPMs was explored across a range of movement parametrizations, including ignoring connectivity or estimating movement with various levels of complexity. Ignoring connectivity was detrimental to accurate estimation of population‐specific biomass, while implementing spatial IPMs with intermediate levels of complexity (e.g. estimating movement in two‐year and two‐age blocks) performed best when no a priori information about underlying movement was available. One‐way distributional shifts mimicking climate‐induced poleward migrations presented the greatest estimation difficulties, but the incorporation of auxiliary information on connectivity (e.g. tag‐recapture data) reduced bias. The continued development of spatially stratified modelling approaches should allow harvested resources to be better utilized without increased risk. Additionally, expanded collection and incorporation of unique spatially explicit data will enhance the robustness of IPMs in the future.     

Effects of current and future climates on the growth dynamics and distributions of two riverine fishes

1. To facilitate conservation planning, there is a need for improved confidence in forecasts of climate change impacts on species distributions. Towards that end, there have been calls for the development of process-based models to test hypotheses concerning the mechanisms by which temperature shapes distribution and to corroborate forecasts of correlative models.
2. Models of temperature-dependent growth (TDG) were developed for two Australian riverine blackfishes with disjunct longitudinal distributions: Gadopsis marmoratus (occupies lower, warmer elevations) and Gadopsis bispinosus (occupies higher, cooler elevations). The models were used to (a) predict blackfish monthly and annual growth dynamics under current and future climate scenarios within different elevation bands of their current distribution, and (b) test the hypothesis that, under the current climate, the distributions of each species would be positively correlated with predicted TDG.
3. Increases in mean annual growth were forecast for both species under all warming scenarios, across all elevation bands. Both species currently occupy annual habitat temperatures below those optimal for growth. Under certain warming scenarios, the predicted increases in annual growth belie forecasts of within-year dynamics that may interact with the phenology of blackfish to impair recruitment.
4. There was not a significant positive linear relationship between predicted TDG and observed abundance among river segments for either species. Both species were strongly under-represented where annual growth rates were forecast to be optimal and over-represented where growth rates were forecast to be intermediate.
5. Confidence in forecasts of climate change impacts based on correlative models will increase when those forecasts are consistent with a mechanistic understanding of how specific drivers (e.g. water temperature) affect processes (e.g. growth). This process-based study revealed surprises concerning how future climates may affect fish growth dynamics, showing that although the blackfish distributions are correlated with temperature the temperature-dependent mechanisms underpinning that correlation require further investigation.

     

Abundance and distribution of the white shark in the Mediterranean Sea

Conservation of apex predators is a key challenge both in marine and terrestrial ecosystems. The white shark is a rare but persistent inhabitant of the Mediterranean Sea and it is currently assessed as “critically endangered” in the region. However, the population trends and dynamics of this species in the area are still unknown. Little is known about white shark distribution, habitat use and population abundance trends, aspects that are critical for conservation and management. In this study, we built the most comprehensive database of white shark occurrence records in the region. We collected 773 different records from different sources and used them to characterize the spatial and temporal patterns of abundance of Mediterranean white sharks between 1860 and 2016. We analysed these data by using generalized additive models and used spatially disaggregated information on human population abundance as a proxy of observation effort. Our results suggest a complex trajectory of population change characterized by a historical increase and a more recent reduction (61%, range 58%–72%) since the second half of the 20th century. In particular, analyses reveal a 52% (range 37%–88%) to 96% (range 92%–100%) overall decline in different Mediterranean sectors and a contraction in spatial distribution. Here, we provide the first reconstruction of abundance trends and offer new hypotheses regarding the drivers of change of white sharks in the Mediterranean. Our approach can be broadly applied to data‐poor contexts to reconstruct change and inform the conservation of endangered top predators in the Mediterranean Sea and other intensely used marine regions.     

网箱养殖大黄鱼溃疡病的预报模型

本文以舟山市网箱养殖大黄鱼Pseudosciaena crocea (Richardson)为研究对象，根据对2001-2005年间网箱养殖大黄鱼发病情况的观察分析、养殖水域环境因子的监测及其收集的气象资料，对大黄鱼溃疡病的发生规律和养殖环境的状况进行了全面分析，结果表明大黄鱼溃疡病的发生不仅与季节有关，而且还与环境因子的状况密切相关。在此基础上，进一步研究了环境因子对大黄鱼溃疡病发生的影响程度和影响方式，筛选出与大黄鱼溃疡病发生密切相关的环境因子，从而建立了网箱养殖大黄鱼溃疡病发生的预报模型。经检验该模型对预报大黄鱼的溃疡病是否发生及发生的程度有高度显著的效果，用该模型对舟山市2005年大黄鱼溃疡病的发生情况进行了预报，预报的正确率达到81.2%。为能有效、适时地对发病季节大黄鱼疾病的控制，本文还同时给出了网箱养殖大黄鱼发病季节溃疡病的预报模型。     

Harvest models and stock co‐occurrence: probabilistic methods for estimating bycatch

A primary goal of ecosystem‐based fishery management is to reduce non‐target stock impacts, such as incidental harvest, during targeted fisheries. Quantifying incidental harvest has generally incorporated fishery‐dependent catch data, yet such data may be biased by gear non‐retention, observation difficulties, and non‐random harvest patterns that collectively lead to an impartial understanding of non‐target stock capture. To account for such issues and explicitly recognize the combined influence of ecological and harvest factors contributing to incidental capture within targeted fisheries, we demonstrate a probabilistic modelling framework that incorporates: (i) background rates of target and non‐target stock co‐occurrence as the primary ecological basis for incidental harvest; (ii) the probability of harvesting at localities exhibiting co‐occurrences; (iii) the probability of selecting for non‐target species with fishery gear; and, (iv) as a function of harvest effort, the overall probability of incidental capture for any non‐target stock contained in the species pool available for harvest. To illustrate application of the framework, simulation models were based on fishery‐independent data from a freshwater fishery in Ontario, Canada. Harvest simulations of empirical stock data indicated that greatest species‐specific capture values were over 4000 times more likely than for species with lowest values, indicating highly variable capture probabilities because of the combined influence of stock heterogeneity and harvest dynamics. Estimated bycatch–effort relationships will allow forecasting incidental harvest on the basis of effort to evaluate future shifts in fishing activity against specific ecosystem‐based fishery management objectives, such as reducing the overall probability of bycatch while maintaining target landings.     

Climate change projections of commercial fish distribution and suitable habitat around north western Europe

Under future climate change, modification of temperature and salinity are expected to result in distribution shifts of marine organisms, including commercial fish and shellfish. Changes are anticipated everywhere, including in the seas of many important fishing nations. Species turnover will in turn result in both opportunities and threats to fishing industries. To determine the impacts for northwest European shelf fisheries, we project changes for 49 commercially important fish and shellfish species using an ensemble of five ecological niche models and three different downscaled climate change projections. The habitat suitability and latitudinal shifts projected from the recent past (1997–2016) to two futures (2030–2050; 2050–2070) were calculated for waters around the United Kingdom. Of the species examined, around half were projected to have consistently more suitable habitat in the future, including European seabass (Dicentrarchus labrax, Moronidae), sardine (Sardina pilchardus, Alosidae) and anchovy (Engraulis encrasicolus, Engraulidae). Conversely, it is suggested that UK waters will become less suitable for species including Atlantic cod (Gadus morhua, Gadidae) and saithe (Pollachius virens, Gadidae). Our comprehensive approach using a number of models and climate change scenarios shows that while there are differences in the magnitude of change between models, and while some models perform better for certain species compared with others, overall, the general trends in habitat suitability and abundance are robust across models and climate scenarios. This emphasises the value in using more than one modelling technique with different climate scenarios (i.e., an ensemble approach) to capture the uncertainty or agreement around climate change projections.     

Habitat preferences of striped marlin (Kajikia audax) in the eastern Pacific Ocean

Striped marlin (Kajikia audax) is an epipelagic species distributed in tropical and temperate waters of the Pacific Ocean. In the central and eastern Pacific Ocean, it is captured principally in commercial longline fisheries, and in small artisanal fisheries, however, it is also taken throughout its range in this region as an incidental catch of the tuna purse‐seine fishery. Previous studies suggest that overexploitation and climate change may reduce abundance and cause changes in spatial distributions of marine species. The main objective of this study was to describe the habitat preferences of striped marlin and the changes in its distribution in response to environmental factors. Habitat modeling was conducted using a maximum entropy model. Operational level data for 2003–2014, collected by scientific observers aboard large purse seine vessels, were compiled by the Inter‐American Tropical Tuna Commission and were matched with detailed (4 km) oceanographic data from satellites and general circulation models. Results showed that the spatial distribution of habitat was dynamic, with seasonal shifts between coastal (winter) and oceanic (summer) waters. We found that the preferred habitat is mainly in coastal waters with warm sea surface temperatures and a high chlorophyll‐a concentration.     

Environmental associations of Pacific bluefin tuna (Thunnus orientalis) catch in the California Current system

We investigate the impact of oceanographic variability on Pacific bluefin tuna (Thunnus orientalis: PBF) distributions in the California Current system using remotely sensed environmental data, and fishery‐dependent data from multiple fisheries in a habitat‐modeling framework. We examined the effects of local oceanic conditions (sea surface temperature, surface chlorophyll, sea surface height, eddy kinetic energy), as well as large‐scale oceanographic phenomena, such as El Niño, on PBF availability to commercial and recreational fishing fleets. Results from generalized additive models showed that warmer temperatures of around 17–21°C with low surface chlorophyll concentrations (<0.5 mg/m³) increased probability of occurrence of PBF in the Commercial Passenger Fishing Vessel and purse seine fisheries. These associations were particularly evident during a recent marine heatwave (the “Blob”). In contrast, PBF were most likely to be encountered on drift gillnet gear in somewhat cooler waters (13–18°C), with moderate chlorophyll concentrations (0.5–1.0 mg/m³). This discrepancy was likely a result of differing spatiotemporal distribution of fishing effort among fleets, as well as the different vertical depths fished by each gear, demonstrating the importance of understanding selectivity when building correlative habitat models. In the future, monitoring and understanding environmentally driven changes in the availability of PBF to commercial and recreational fisheries can contribute to the implementation of ecosystem approaches to fishery management.     

High‐resolution modelling of ocean circulation can reveal retention spots important for biodiversity conservation

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Cohort‐specific variation in juvenile coho salmon habitat use

In this study, we examined summer and fall freshwater rearing habitat use by juvenile coho salmon (Oncorhynchus kisutch) in the quickly urbanising Big Lake drainage in south‐central Alaska. Habitat use was assessed by regressing fish count data against habitat survey information across thirty study sites using generalised linear mixed models. Habitat associations were examined by age‐0 and age‐1+ cohorts separately, providing an opportunity to compare habitat use across different juvenile coho salmon life stages during freshwater rearing. Regression results indicated that the age‐0 cohorts were strongly associated with shallow, wide stream reaches with in‐stream vegetation, whereas age‐1+ cohorts were associated with deeper stream reaches. Furthermore, associations between fork length and habitat characteristics suggest cohort‐specific habitat use patterns are distinct from those attributable to fish size. Habitat use information generated from this study is being used to guide optimal fish passage restoration planning in the Big Lake drainage. Evidence for habitat use partitioning by age cohort during freshwater juvenile rearing indicates that pooling age cohorts into a single “juvenile” stage for the purposes of watershed management may mask important habitat use dynamics.     

Earlier migration and distribution changes of albacore in the Northeast Atlantic

Marine species have exhibited trends in their geographic distribution and phenology in recent decades, and these changes are triggered by climate variability or anthropogenic pressures. Northeast Atlantic albacore has recently been identified to show changes of this nature, although the underlying causes are still uncertain. The aim of this work was to analyse the Northeast Atlantic albacore distribution shifts and phenological changes during the trophic migration that juveniles undertake from late spring to autumn and to identify potential causes of such variability. Specifically, time series of albacore catches of the Basque trolling fleet were studied and compared with trends derived from a null ecological niche model using very large number of catch observations (27,982). The results showed an earlier albacore migration of 2.3 days per decade during the period of 1981–2017, which was partly associated with the recent warming of the sea. The trend analysis of the catch distribution also detected a significant north‐westward trend in catch observations and a northward trend in species habitat. In contrast, both latitudinal trends were uncorrelated. This result suggests that interannual species distribution shifts are mainly related to factors other than oceanic‐climatic variability, such as fleet behaviour or prey changes.