Article

Integrated modelling of Atlantic mackerel distribution patterns and movements: A template for dynamic impact assessments

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Abstract

Modelling is important for impact assessments of anthropogenic pressures on wildlife. Models are particularly useful when dealing with complex dynamic systems (as pelagic ecosystems) where data are limited and if various ‘what if’ scenarios should be tested. The aim of this study was to produce and implement an integrated modelling approach, linking high resolution hydrodynamic models (HDM) of the marine environment with correlative species distribution models (SDM) and agent-based models (ABM), for describing the spatio-temporal distribution and movements of Atlantic mackerel (Scomber scombrus) in the Norwegian Sea. The SDM was fitted with scientific mackerel trawl data as response variables (collected in July and August 2006–2014) and temperature (from the HDM), water depth and time period as predictors of spatial distributions. The SDM was able to produce dynamic predictions of a similar order of magnitude as observed catch per unit effort (CPUE) as well as realistic large-scale distribution patterns, when tested on independent data (not included in the modelling). The ABM was calibrated, with normalized SDM predictions (habitat suitability as a proxy for food availability) and hydrodynamics as input and simulated on a single year (2013) for the period May–October, when the migratory mackerel is present in the study area. A pattern-oriented modelling (POM) approach was used to verify if the model reproduced multiple observed real-world patterns. The ABM produced similar patterns as observed regarding migration timing, growth and large scale geographic distribution. Fine scaled information on mackerel movement and behaviour is limited, which is also reflected in the results. More data and knowledge are therefore required to improve the patterns emerging from fine scaled processes. The potential of the model for assessing an impact of a single seismic survey (mimicking a real survey) was finally evaluated. The exercise allowed estimating the number of affected fish (within 50 km from the sound source) and potential changes in local migrations, with the specific assumed minimum sound pressure thresholds (resulting in a fleeing reaction by the mackerel) set to 165 dB re 1 μPa. The model framework was shown to be useful by allowing simulations of impact scenarios in a realistic and dynamic environment. The model can be further updated when data on fine scale movements of mackerel and most importantly when improved data on response behaviour to impacts of sound become available.

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... Energy use patterns may change with time due to temporal differences in food availability or energetic requirements, such as Biological Reviews (2021) Guidance for pattern-oriented modelling with seasonal shifts in mass or body composition at different life-history events [e.g. reproduction or maturity (Beltran et al., 2017, Heinänen et al., 2018, Desforges et al., 2019]. ...
... While many kinds of movement are considered behaviour, we treat these separately due to the wealth of movement information being currently collected using rapidly developing bio-logging technologies. Empirical patterns in animal movement are often derived from animals equipped with tags (Liukkonen et al., 2018;Nabe-Nielsen et al., 2018;Merkle et al., 2019;Chudzinska et al., 2021) or by using point observations such as checkpoints or scent marks (Lewis, White & Murray, 1997;Heinänen et al., 2018). Broadly speaking, these patterns can describe either path characteristics or space use of individuals. ...
... Messager & Olden (2018) used population-level presence-absence distribution maps from surveys as a pattern when predicting spread of an invasive crayfish species (rusty crayfish; Faxonius rusticus) in a river system. Distributions are often combined with local abundances or densities to characterise where and to what extent locations are used by species Chudzi nska et al., 2016;Heinänen et al., 2018). They can also be visualised both in time and space, as in Le Fur & Simon (2009), where spawning distribution of round sardinella (Sardinella aurita) was compared to empirical knowledge both by location and by month of the year. ...
Article
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To robustly predict the effects of disturbance and ecosystem changes on species, it is necessary to produce structurally realistic models with high predictive power and flexibility. To ensure that these models reflect the natural conditions necessary for reliable prediction, models must be informed and tested using relevant empirical observations. Pattern‐oriented modelling (POM) offers a systematic framework for employing empirical patterns throughout the modelling process and has been coupled with complex systems modelling, such as in agent‐based models (ABMs). However, while the production of ABMs has been rising rapidly, the explicit use of POM has not increased. Challenges with identifying patterns and an absence of specific guidelines on how to implement empirical observations may limit the accessibility of POM and lead to the production of models which lack a systematic consideration of reality. This review serves to provide guidance on how to identify and apply patterns following a POM approach in ABMs (POM‐ABMs), specifically addressing: where in the ecological hierarchy can we find patterns; what kinds of patterns are useful; how should simulations and observations be compared; and when in the modelling cycle are patterns used? The guidance and examples provided herein are intended to encourage the application of POM and inspire efficient identification and implementation of patterns for both new and experienced modellers alike. Additionally, by generalising patterns found especially useful for POM‐ABM development, these guidelines provide practical help for the identification of data gaps and guide the collection of observations useful for the development and verification of predictive models. Improving the accessibility and explicitness of POM could facilitate the production of robust and structurally realistic models in the ecological community, contributing to the advancement of predictive ecology at large.
... Deterrence effects may include: delays or obstruction of migration, spatial displacement relative to local variation in habitat quality, redistribution of relative density patterns with competing individuals or species, and separation from group members. Detection issues related to masking or effects such as physiological stress are usually not yet incorporated into PCAD models, but energy budget changes due to disturbance and deterrence effects are implemented in some cases (Heinänen et al. 2018, Nabe-Nielsen et al. 2018, and can cause changes in parameters that are considered vital rates: growth, maturation, reproduction and survival. Changes in vital rates can then have knockon effects on population dynamics (Fig. 1). ...
... (B) Agent locations in Liverpool Bay in or close to a cross-hatched area in which pile driving sound levels interrupt the migratory swimming behaviour of acoustically sensitive Atlantic cod (red points), but not for insensitive individuals (black points), which will therefore arrive earlier in the feeding and spawning areas (Rossington et al. 2013). (C) Super-agents in the Norwegian Sea with spatially variable habitat quality reflected in the background colour and the vessel track pattern of a seismic survey: black squares are schools of Atlantic mackerel moving unaffected by the seismic sound pulse, while red squares are schools that alter speed and direction due to the local SPL exceeding the threshold level (Heinänen et al. 2018). (D) Agent tracks, reflecting harbour porpoise swimming trajectories, of simulated movements near continuous pile-driving (black x) somewhere in the North Sea: the harbour porpoises that enter the yellow circle will be deterred away from the sound source (Nabe-Nielsen et al. 2018). ...
... In the third case study, distribution patterns and migratory movement of Atlantic mackerel in the Norwegian Sea were used to explore the possibility of dynamic impact assessment of moving animals and a moving source of noise pollution (Heinänen et al. 2018). The schools of mackerel were modelled applying the principle of super-individuals, i.e. one agent representing a large number of individuals (Scheffer et al. 1995). ...
Article
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Marine ambient sound levels have risen due to noisy human activities, such as shipping, fishing, seismic surveys and piling for windfarms. Marine mammals and fishes are two prominent taxonomic groups that are exposed to this noise pollution, which may experience detrimental effects at the population level. Acoustic effects on individual behaviour such as deterrence, disturbance, distraction and masking of biologically relevant sounds, can be translated energetically to changes in vital rates (growth, maturation, reproduction and survival) in a population consequences of acoustic disturbance (PCAD) approach. However, we typically neglect spatial variation in species distributions and noise pollution, while abiotic factors like temperature, bathymetry and currents, as well as habitat quality in terms of feeding or hiding opportunities, will also have a geographically variable impact on potential consequences. We here address the conceptual integration of agent based models (ABM) into the PCAD framework, as a suitable theoretical tool with high potential for the exploration of these spatial factors and their modifying role in noise impact assessment studies. We review five ABM case studies, including investigations into: 1) effects of movement strategy on the impact of explosions in harbour porpoise; 2) effects of disturbance sensitivity on pile driving impact on migrating cod; 3) impact of seismic survey sounds on Atlantic mackerel distribution and movement; 4) population‐level impact of mitigation of harbour porpoise bycatch with pingers; and 5) population effects of alternative windfarm construction scenarios in harbour porpoise. We discuss similarities and differences among these studies in sound and species mapping approaches and we evaluate model realism and pattern validation. We believe that ABMs are a valuable tool for integrating spatial information into ecological impact studies that investigate acoustic disturbance, for any type of sound source, and for both marine mammals and fish.
... The model complex has been developed and tested during the MARAMBS (Marine Animal Ranging Assessment Model Barents Sea) project between 2017 and 2019 (Madsen et al., 2019; see also https:// www.dhigroup.com/data-portals/marine-animal-movement-portal). The model complex provides a comprehensive description of the presence and movement of vulnerable species of seabirds in the Barents Sea using a combination of high-resolution 3D hydrodynamic modelling, dynamic habitat suitability modelling (HABM) and agent-based modelling (ABM, Heinänen et al., 2018). An overview of the model complex is shown below (Fig. 1). ...
... By combining statistical and agent-based modelling techniques we have beeen able to use all available information to create a predictive model that is more realistic than using only survey data (Heinänen et al., 2018). In our model setup we utilize both spatial observations as well as knowledge on behavior allowing us to describe both general patterns as well as movements. ...
Article
Current knowledge of the distribution of sensitive seabirds is inadequate to safeguard seabird populations from impacts of oil spills in the Arctic. This gap is mainly driven by the fact that statistical models applied to survey data are coarse-scale and static with limited documentation of the distributional dynamics and patchiness of seabirds relevant to risk assessments related to oil spills. This paper describes a dynamic modelling framework solution for prediction of fine-scale densities and movements of seabirds in close-to-real time using fully integrated 3-D hydrodynamic models, dynamic habitat suitability models and agent-based models. The modelling framework has been developed and validated for the swimming migration of Brünnich's Guillemot Uria lomvia in the Barents Sea. The results document that the distributional dynamics of Brünnich's Guillemot and other seabird species to a large degree can be simulated with in-situ state variables and patterns reflecting the physical meteorology and oceanography and habitat suitability.
... One mechanistic approach that is becoming increasingly popular as a way to predict fish distribution is with individual-based models (IBMs, also called agent-based models) (e.g. Tu et al., 2012;Watkins and Rose, 2017;Heinänen et al., 2018). In IBMs animal populations are represented by their constituent individuals in real-world mapped landscapes (Uchmański and Grimm, 1996;McLane et al., 2011). ...
... The model is now able to make predictions about both the spatial distribution of the mackerel stock and its population dynamics (though further validation, testing, and possibly development, is needed to ensure its predictive power). Other bioenergetics IBMs have been applied to the summer feeding distribution of Atlantic mackerel Heinänen et al., 2018). However, our model differs in that it is multi-generational and includes the full life cycle, i.e. what happens outside of the feeding period. ...
Article
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Over recent years the summer feeding distribution of Northeast Atlantic mackerel (NEAM, Scomber scombrus) has expanded from its traditional core in the Norwegian Sea, northwards towards Svalbard, and westward as far as Greenland. Food availability, temperature and an increase in spawning stock biomass (SSB) are reported to be possible drivers of the distribution, but quantifying the relative contributions of these factors is difficult. Previously we developed a bioenergetics individual-based model (IBM) that uses satellite-derived maps of food availability and temperature to predict NEAM population dynamics. Here, we extend the model to explore the ways in which individuals move in search of food in the summer. We construct models of four possible search mechanisms differing in (1) the extent of the area over which individuals can perceive the environment; and (2) whether or not individuals respond to the local density of conspecifics by avoiding areas in which competition is more intense. We report that the best matches to available data over 2007–2015 are obtained when the local density of competitors is taken into account, and individuals move in response to local gradients in feeding opportunities. To determine whether the IBM is able to reproduce the observed north and westward expansion, we record total distribution area, and predicted centre of gravity in terms of latitude and longitude, over 2005–2015. The IBM successfully predicts an increase in distribution area, and a northward shift in centre of gravity, over the time series. It also predicts a westward shift in centre of gravity, but to a much lesser extent than has been observed in surveys and the fishery. The inability of our IBM to capture the full extent of the westward expansion suggests that it does not account for all relevant drivers of the NEAM summer distribution. Going forward we hope that our model can be: (1) extended to explore additional drivers of the summer distribution (e.g. currents); and (2) used in a strategic capacity to predict how the NEAM stock may respond to future climate and management scenarios
... Second, SS3 does not represent the effects of environmental variability on the stock; for this reason it cannot make predictions about how the stock will develop against uncertain climate backdrops, or how climate uncertainty might interact with harvesting scenarios e.g., Boyd, Thorpe, et al., 2020 developed an individual-based model for European sea bass. This model and others like it are widely used to simulate the spatial distribution of fish populations (Watkins and Rose, 2017;Heinänen et al., 2018;Boyd, Walker, et al., 2020), as well as population size and structure (Politikos, Huret and Petitgas, 2015;Boyd, Walker, et al., 2020;Bueno-Pardo et al., 2020). In Walker et al. (2020) the stock's spatial distribution results from algorithms that govern the movements of the individuals, but the population dynamics component is that of SS3. ...
Article
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The northern stock of European sea bass (Dicentrarchus labrax) is a large, high value, slow growing and late maturing fish that is an important target species for both commercial and recreational fisheries. Around the UK, scientific assessments have shown a rapid eight-year decline in spawning stock biomass since 2010 attributed to poor recruitment; this was likely driven by environmental factors and high fishing mortality. Management of the stock is informed by scientific assessments in which a population model is fitted to the available data and used to forecast the possible consequences of various catch options. However, the model currently used cannot represent the spatial distribution of the stock or any effects of environmental variability. One approach that may be used to represent the effects of spatial and temporal variation in environmental drivers is with Individual based models (IBMs). In IBMs populations are represented by their constituent individuals that interact with their environment and each other. The mechanistic nature of IBMs is often advantageous as a management tool for complex systems including fisheries. Here we add to an existing IBM to produce a spatio-temporally explicit IBM of the northern stock of sea bass in which individual fish respond to local food supply and sea surface temperature. All life stages (i.e., pelagic stages, juvenile and mature fish) are modelled and individual fish have their own realistic energy budgets driven by observed dynamic maps of phytoplankton density and sea surface temperature. The model is calibrated using Approximate Bayesian Computation (ABC). After calibration by ABC the model gives good fits to key population parameters including spawning stock biomass. The model provides a mechanistic link between observed local food supplies and sea surface temperatures and overall population dynamics. Plots of spatial biomass distribution show how the model uses the energy budget to predict spatial and temporal change in sea bass biomass distribution in response to environmental variability. Our results indicate that the IBM is a promising approach that could be used to support stock assessment with scope for testing a range of spatially and temporally explicit management scenarios in addition to testing stock responses to novel environmental change.
... For example, using dynamic habitat modelling, animal distribution can be correlated to environmental variables (e.g. current speed) to identify those habitat variables that drive the distribution of marine fauna in space and time (Heinänen et al., 2018). Furthermore, agent-based models (ABM) simulate the movement of individual animals in response to habitat drivers and pressures such as noise, providing more realistic assessments of exposure to sound than those based on stationary animals ...
Book
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Anthropogenic underwater noise impacts have become a hot topic for environmental managers and regulators in Europeand beyond. Sounds from human activity at sea include shipping and other marine craft, construction and installations, sonar and seismic surveys. This Future Science Brief presents an update on the previous EMB publication on underwater noise, Position Paper N° 13 on “The effects of anthropogenic sound on marine mammals: A draft research strategy". This Future Science Brief expands the scope of the discussion beyond marine mammals to fishes and invertebrates, and outlines key developments that have taken place since the Position Paper’s publication. The main chapters of the document focus on: the advances in our knowledge on anthropogenic underwater sound in the Ocean; the new knowledge that has been developed on the effects of noise on marine organisms; and the measures that have been taken to address the issue of underwater noise. While significant progress has been made, knowledge gaps still remain. The document therefore presents these outstanding issues and highlights priority actions for addressing them. This Future Science Brief states that the most urgent priority actions/questions are to: 1. Develop collaborative international standards applicable to all steps of the risk framework; 2. Conduct comprehensive monitoring combined with spatial ecological modelling of marine species’ dynamic habitat use, movements, behaviour and distribution to establish baselines; 3. Foster comprehensive monitoring and data collection of current soundscapes / ambient noise, including via joint monitoring programmes in existing and new areas; 4. Shortlist high priority (and biologically relevant) sound sources and perform standardized source characterization studies; 5. Undertake hearing studies on baleen whales and on selected fish and invertebrate species; 6. Conduct field and modelling studies on changes in acoustic habitats to identify masking risks to communication in fishes and marine mammals; 7. Conduct further studies on behavioural response of marine mammals and fishes due to exposure to high intensity impulsive sounds to assess population consequences; 8. Conduct taxa-relevant studies on hearing impairment and physiological stress to address existing knowledge gaps in invertebrates, fishes and marine mammals; 9. Conduct dedicated studies including multi-species investigations, predator-prey interactions, and interaction with other food web levels, addressing the question of how noise impacts combine with other stressors; 10. Develop frameworks and conduct studies to allow population-level assessment of effects from cumulative impact of noise and other pressures; 11. Conduct dedicated modelling and field studies to improve understanding on effectiveness, safety and cost-effectiveness of noise mitigation devices, mitigation measures and management options; 12. Develop regional action plans and guidelines for Environmental Impact Assessment and policies; and 13. Initiate international collaborative transdisciplinary projects to develop stakeholder and societal capacity in understanding and addressing underwater noise.
... The present study uses an ABM comprised of a hydrodynamic model of the Charlotte Harbor estuarine system (Dye et al. 2020) and an ecological modeling module (MIKE ECO Lab; DHI 2017) to simulate oyster larval transport and dispersal within the CRE and the larger, encompassing Charlotte Harbor estuarine system hereafter CHES (Fig. 1). MIKE ECO Lab is a process-based customizable ecosystem modeling tool widely used to study the transport, dispersal, as well as foraging traits of various organisms such as eelgrass, coral larvae, starfish, sea birds, and marine mammals (Tay et al. 2012;Elsäßer et al. 2013;Canal-Verges et al. 2014;Heinänen et al. 2018;Kuusemäe et al. 2018;Cavalcante et al. 2020). The MIKE ECO Lab model template created specifically for C. virginica oyster larvae was tested in its ability to simulate dispersal patterns observed in situ in the CRE. ...
Article
An agent-based modeling (ABM) framework was developed to support oyster reef restoration efforts in the Caloosahatchee River Estuary located within the encompassing Charlotte Harbor estuarine system, Southwest Florida. The modeling approach is novel for this shallow estuary which experiences heavily managed freshwater inflow known to be an ecological stressor to the estuary's oysters. The aims of the study were to (1) determine the ABM's accuracy in simulating larval dispersal patterns when compared with measured in situ larval settlement data; (2) establish connectivity patterns between various oyster reefs within the estuary; and (3) discover larval transport pathways within the Charlotte Harbor estuarine system. Key characteristics of the ABM, in particular the agents serving as simulated larvae, include settlement behavior and salinity tolerance and associated mortality. The ABM accurately recreated larval dispersal patterns during the peak spawning season, providing fundamental insight into the importance of protecting the furthest upstream oyster reef as a sustained larval source to the downstream reefs. Thus, supporting the effectiveness of using field measurements for the validation of ABMs and subsequently using ABM simulations to bolster future field studies. Ultimately, this study provides an effective, generally applicable, approach to model larval ecology for restoration purposes.
... This is important as effect ranges are too large to measure in the lab. Ecological/spatial models can help to identify parameters to measure and power analysis should be conducted prior to initiating field work, such that field studies are appropriately designed to test the chosen hypothesis (see Heinänen et al. 2018). • A suggested focus is on displacement specifically during spawning or other aggregation periods, since: (1) spawning areas are discrete locations with suspected sensitivity to sound, and (2) a focus on spawning (or other biologically important life functions) facilitates an understanding of the fitness consequences of behavioral changes that are observed. ...
Technical Report
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This report is one outcome from a broader effort to review the state of knowledge regarding offshore wind energy development's effects on wildlife and identify short-term research priorities to improve our understanding of cumulative biological impacts as the offshore wind industry develops in the eastern United States. This effort, titled State of the Science Workshop on Wildlife and Offshore Wind Energy 2020: Cumulative Impacts, included a week of plenary presentation sessions and contributed talks in November 2020, as well as the formation of six other workgroups similar to the fishes and aquatic invertebrates workgroup that met over the winter of 2020-2021. This report, and those from the six other workgroups, are available on the workshop website at https://www.nyetwg.com/2020-workgroups.
... Prema našoj spoznaji, do sada nisu javno prezentirani rezultati istraživanja integriranih hidrodinamičkih modela i ABM-a ribljih staza (Eulerov model za polje strujanja i Lagrangeov model za gibanje ribe) s ciljem kvantifikacije utjecaja konfiguracije riblje staze s vertikalnim otvorima ili drugih konfiguracija na intenzitet promjene energije ribe pri njenom uzvodnom kretanju. U dosadašnjim istraživanjima vezanim uz integraciju hidrodinamičkih modela i ABM-a analizirana je problematika pronalaska privlačne struje na nizvodnom ulazu u riblju stazu [24,25,26], migracija ribe u područjima riječnih estuarija [27] i sezonska migracija riba u morima [28]. U radovima [24][25][26] prezentirane su trajektorije riba samo od mjesta upuštanja u analizirani vodotok do ulaza u riblju stazu, bez provedene analize uzvodnog plivanja kroz riblju stazu. ...
Article
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Physical and 3D numerical hydrodynamic flow models and an agent-based model are developed with the principal objective of analysing fish behaviour in two vertical slot fishway configurations. Fish energy consumption due to swimming represents a crucial criterion for selecting an appropriate fishway configuration. The modelled fish detects ambient flow conditions, makes decisions based on its sensing and cognitive abilities, adapts to the changes in its environment, and moves toward the regions of less turbulent kinetic energy. The results show that fishways with longer pools enable passage of fish at a lower energy consumption.
... The use of explanatory variables extracted from dynamic models covering coastal areas has been included in PHMs for many marine species, such as benthos, fish, marine mammals and seabirds (e.g. Skov and Thomsen, 2008;Reiss et al., 2011Reiss et al., , 2014Skov et al., 2014;Gilles et al., 2016;Heinänen et al., 2018) and the importance of hydrodynamic variables in species and habitat distribution is well established. In deeper waters, especially in areas with changing and complex seabed topography, internal waves may support strong turbulence and mixing (e.g. ...
... We attempted to include inputs from the IPSL ESM but found that an underprediction of SST on the NEAM spawning grounds led to frequent recruitment failures in our IBM. With respect to the fish population model, we are aware of other IBMs representing NEAM (Utne et al., 2012;Heinänen et al., 2018). However, to our knowledge these IBMs were designed primarily to represent the stock's spatial distribution and do not make multi-generational predictions of stock size. ...
Article
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Climate change and fishing represent two of the most important stressors facing fish stocks. Forecasting the consequences of fishing scenarios has long been a central part of fisheries management. More recently, the effects of changing climate have been simulated alongside the effects of fishing to project their combined consequences for fish stocks. Here, we use an ecological individual-based model (IBM) to make predictions about how the Northeast Atlantic mackerel (NEAM) stock may respond to various fishing and climate scenarios out to 2050. Inputs to the IBM include Sea Surface Temperature (SST), chlorophyll concentration (as a proxy for prey availability) and rates of fishing mortality F at age. The climate scenarios comprise projections of SST and chlorophyll from an earth system model GFDL-ESM-2M under assumptions of high (RCP 2.6) and low (RCP 8.5) climate change mitigation action. Management scenarios comprise different levels of F, ranging from no fishing to rate F lim which represents an undesirable situation for management. In addition to these simple management scenarios, we also implement a hypothetical area closure in the North Sea, with different assumptions about how much fishing mortality is relocated elsewhere when it is closed. Our results suggest that, over the range of scenarios considered, fishing mortality has a larger effect than climate out to 2050. This result is evident in terms of stock size and spatial distribution in the summer months. We then show that the effects of area closures are highly sensitive to assumptions about how fishing mortality is relocated elsewhere after area closures. Going forward it would be useful to incorporate: (1) fishing fleet dynamics so that the behavioral response of fishers to area closures, and to the stock's spatial distribution, can be better accounted for; and (2) additional climate-related stressors such as ocean acidification, deoxygenation and changes in prey composition.
... As such, IBMs are now widely used to simulate the spatial distribution of fish populations (e.g. Heinänen et al., 2018;Watkins and Rose, 2017), as well as population size and structure (Boyd et al., 2018(Boyd et al., , 2020Bueno-Pardo et al., 2020;Politikos et al., 2015). ...
Article
The European sea bass (Dicentrarchus labrax) is a slow growing and late maturing high value fish that is exploited by both commercial and recreational fisheries. In recent years, scientific assessments have shown a rapid decline in spawning stock biomass around the UK attributed to poor recruitment (driven by environmental factors) and high fishing mortality. This resulted in significant reductions in the harvest of sea bass following technical measures implemented by the European Commission to conserve stocks. Individual-based models (IBMs) are simulations of individual ‘agents’ of organisms that interact with each other and their environment locally and have been shown to be effective management tools in many systems. Here, an IBM that simulates the population dynamics and spatial distribution of sea bass was developed to assess how technical management measures applied to subsets of the population impact the overall stock. Conventional stock assessment techniques were used to model the processes affecting population dynamics, while the spatial distribution was simulated using a combination of temperature preferences and information from tagging studies. The IBM was parameterised using existing knowledge from the literature and can mimic key assessment outputs used to inform management and advice on fishing opportunities. Utility of the IBM is demonstrated by simulating the population consequences of several key management scenarios based on those implemented by the European Commission, including short-term bans on pelagic trawling in spawning areas, commercial and recreational catch limits and increasing the minimum conservation reference size. The IBM has potential to complement the annual stock assessment in managing European sea bass because it models individual movement, environmental drivers and emergent spatial distribution, thereby providing enhanced predictions of management strategy outcomes that could inform spatial advice on fishing opportunities and policy.
Article
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There are substantial knowledge gaps regarding both the bioacoustics and the responses of animals to sounds associated with pre-construction, construction, and operations of offshore wind (OSW) energy development. A workgroup of the 2020 State of the Science Workshop on Wildlife and Offshore Wind Energy identified studies for the next five years to help stakeholders better understand potential cumulative biological impacts of sound and vibration to fishes and aquatic invertebrates as the OSW industry develops. The workgroup identified seven short-term priorities that include a mix of primary research and coordination efforts. Key research needs include the examination of animal displacement and other behavioral responses to sound, as well as hearing sensitivity studies related to particle motion, substrate vibration, and sound pressure. Other needs include: identification of priority taxa on which to focus research; standardization of methods; development of a long-term highly instrumented field site; and examination of sound mitigation options for fishes and aquatic invertebrates. Effective assessment of potential cumulative impacts of sound and vibration on fishes and aquatic invertebrates is currently precluded by these and other knowledge gaps. However, filling critical gaps in knowledge will improve our understanding of possible sound-related impacts of OSW energy development to populations and ecosystems.
Article
An Individual-based model (IBM) for studying the blue mackerel larval transport in East China Sea (ECS), for the first time, is developed based on Ichthyop model. Coastal and Regional Ocean Community model (CROCO), a typical hydrodynamic model, is configured as well to provide Ichthyop with the physical variables (e.g. temperature, salinity, current). Effects of physical environments (current and temperature), spawning ground/depth/time and diel vertical migration (DVM) on aspects of the early life stage of blue mackerel, including connectivity between spawning ground and nursery area, temperature-dependent mortality, transportation and dispersal distance, are discussed in detail for the first time based on IBM. Two transport scenarios are considered in our simulations: (1) passive Lagrangian transport and (2) DVM. The experimental results show that the transport of the blue mackerel in ECS is principally controlled by the Kuroshio Current (KC) and Tsushima Warm Current (TSWC). Most of the larvae that affected by TSWC are mainly remained in ECS stock, while those controlled by KC are generally confined in the Pacific stock. In passive Lagrangian transport, the larvae from the largest spawning ground do not only remain in ECS stock but also drift to the Pacific stock in February. In travelling to the Pacific stock, the larvae will experience a long-distance trip and may spread away from the suitable growth area, which is not conducive to their survival. Whereas in DVM scenario, cases with different vertical migration mechanisms all have shorter dispersal distances comparing to the first scenario, the long-distance movement is significantly reduced during the simulating period, particularly in February. DVM tends to prevent the larvae entering the Pacific stock from the largest spawning ground in ECS, thus could increase the recruitment and survival for ECS stock.
Chapter
With the increase of worldwide population, the environment has suffered intensely, where climate change issues are some of the top priorities for decision-makers worldwide. The extreme events recently witnessed have affected a countless number of people, with the loss of lives, properties and livelihood. Resourcing to technologies that facilitate decision-making is one of the viable options to correct our current path into the future. By using agent-based modelling coupled with geographical information systems, an effective platform can be created to design a bottom-up approach in policy creation and planning. This review paper analyses studies that have applied this methodology, yielding a vast range of results that were divided into nine different sustainable development categories: natural resources, social participation and trust, material welfare and economy, climate and energy, technology, biodiversity and landscape, mobility, safety and land development. The number of results shows that these studies are extremely relevant to the sustainable development topic. Although having manifested some limitations related to the transparency of the model design or validation issues, the application of agent-based modelling coupled with geographical information systems proved a competent tool for implementation in environmental and sustainability subjects.
Article
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The present study uses bioenergetics modeling to estimate the annual consumption of the main zooplankton groups by some of the most commercially important planktivorous fish stocks in the Northeast Atlantic, namely Norwegian spring-spawning (NSS) herring (Clupea harengus), blue whiting (Micromesistius poutassou) and NEA mackerel (Scomber scombrus). The data was obtained from scientific surveys in the main feeding area (Norwegian Sea) in the period 2005–2010. By incorporating novel information about ambient temperature, seasonal growth and changes in the diet from stomach content analyses, annual consumption of the different zooplankton groups by pelagic fish is estimated. The present study estimates higher consumption estimates than previous studies for the three species and suggests that fish might have a greater impact on the zooplankton community as foragers. This way, NEA mackerel, showing the highest daily consumption rates, and NSS herring, annually consume around 10 times their total biomass, whereas blue whiting consume about 6 times their biomass in zooplankton. The three species were estimated to consume an average of 135 million (M) tonnes of zooplankton each year, consisting of 53–85 M tonnes of copepods, 20–32 M tonnes of krill, 8–42 M tonnes of appendicularians and 0.2–1.2 M tonnes of fish, depending on the year. For NSS herring and NEA mackerel the main prey groups are calanoids and appendicularians, showing a peak in consumption during June and June–July, respectively, and suggesting high potential for inter-specific feeding competition between these species. In contrast, blue whiting maintain a low consumption rate from April to September, consuming mainly larger euphausiids. Our results suggest that the three species can coexist regardless of their high abundance, zooplankton consumption rates and overlapping diet. Accordingly, the species might have niche segregation, as they are species specific, showing annual and inter-annual variability in total consumption of the different prey species. These estimates and their inter-annual and inter-specific variation are fundamental for understanding fundamental pelagic predator-prey interactions as well as to inform advanced multispecies ecosystem models.
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The Norwegian spring-spawning (NSS) herring (Clupea harengus), blue whiting (Micromesistius poutassou) and Northeast Atlantic (NEA) mackerel (Scomber scombrus) are extremely abundant pelagic planktivores that feed in the Norwegian Sea (NS) during spring and summer. This study investigated the feeding ecology and diet composition of these commercially important fish stocks on the basis of biological data, including an extensive set of stomach samples in combination with hydrographical data, zooplankton samples and acoustic abundance data from 12 stock monitoring surveys carried out in 2005-2010. Mackerel were absent during the spring, but had generally high feeding overlap with herring in the summer, with a diet mainly based on calanoid copepods, especially Calanus finmarchicus, as well as a similar diet width. Stomach fullness in herring diminished from spring to summer and feeding incidence was lower than that of mackerel in summer. However, stomach fullness did not differ between the two species, indicating that herring maintain an equally efficient pattern of feeding as mackerel in summer, but on a diet that is less dominated by copepods and is more reliant on larger prey. Blue whiting tended to have a low dietary overlap with mackerel and herring, with larger prey such as euphausiids and amphipods dominating, and stomach fullness and feeding incidence increasing with length. For all the species, feeding incidence increased with decreasing temperature, and for mackerel so did stomach fullness, indicating that feeding activity is highest in areas associated with colder water masses. Significant annual effects on diet composition and feeding-related variables suggested that the three species are able to adapt to different food and environmental conditions. These annual effects are likely to have an important impact on the predation pressure on different plankton groups and the carrying capacity of individual systems, and emphasise the importance of regular monitoring of pelagic fish diets.
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The Northeast Atlantic (NEA) mackerel (Scomber scombrus) is a widely distributed pelagic fish species that plays a key role in the marine ecosystem. In recent years, there has been a large fishery targeting mackerel in the NEA. At the same time as the geographic range of the mackerel fishery has expanded and the spatial distribution of the stock been defectively determined, the stock assessment has been considered to be highly uncertain by ICES. Limited tuning data, with only a triennial egg survey, have created challenges for the assessment and management of NEA mackerel, and ICES has repeatedly stated the need for an annual age-disaggregated abundance index of this stock. These were the motivations for establishment of an international pelagic trawl survey in 2007, the International Ecosystem Summer Surveys in the Nordic Seas (IESSNS). The estimated total biomass indices for NEA mackerel based on coordinated and standardized swept-area surface trawling in July–August from IESSNS increased from 1.96 million t [relative standard error (RSE) = 30.35%] in 2007 to 8.77 million t (RSE = 7.95%) in 2014. Simultaneously, the mackerel stock expanded its geographic range during the feeding season from 1.3 million km2 in 2007 to at least 2.9 million km2 in 2014, mainly towards western and northern regions of the Nordic seas. Estimates of abundance indices by age group were fairly precise (RSE ∼20%) for ages 3–12, while the precision was poorer for ages 1 and 2 and for age groups 13 and older (RSE > 50%). Furthermore, evaluation of the performance of the estimated abundance indices by age for this time-series, based on internal consistency and catch curves, suggest that the abundance indices of ages 3–12 track the temporal variation in abundance reasonably, and thus is applicable for stock assessments.
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Human activities in coastal and marine ecosystems provide a suite of benefits for people, but can also produce a number of stressors that can act additively, synergistically, or antagonistically to change ecosystem structure, function, and dynamics in ways that differ from single stressor responses. Scientific tools that can be used to evaluate the effects of multiple stressors are needed to assist decision making. In this paper, we review indicator selection methods and general approaches to assess indicator responses to multiple stressors and compare example ecosystem assessments. Recommendations are presented for choosing and assessing suites of indicators to characterize responses. Indicators should be chosen based upon defined criteria, conceptual models linking indicators to pressures and drivers, and defined strategic goals and ecological or management objectives. Indicators should be complementary and nonredundant, and they should integrate responses to multiple stressors and reflect the status of the ecosystem. An initial core set of indicators could include those that have been tested for the effects of climate and fishing and then expanded to include other pressures and ecosystem-specific, feature-pressure interactions. Identifying indicators and evaluating multiple stressors on marine ecosystems require a variety of approaches, such as empirical analyses, expert opinion, and model-based simulation. The goal is to identify a meaningful set of indicators that can be used to assist with the management of multiple types of human interactions with marine ecosystems.
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Weight-at-length and length-/weight-at-age were analysed for mature 3- to 8-year-old Northeast Atlantic mackerel (Scomber scombrus; n= 26 084) collected annually in autumn (September and October) at the end of the annual feeding season during 1984–2013 in the northern North Sea. The age range represented 92% of the mackerel stock size (age 3+). During the most recent decade, mackerel length- and weight-at-age continually declined. In 2013, the average mackerel was 3.7 cm shorter and weighed 175 g less than the average individual in 2002. Individual weight-at-length, demonstrating annual summer feeding success, continually declined during the most recent 5 years, whereas somatic growth of cohorts aged 3–8 continually declined for the last 11 of 25 cohorts investigated. Growth of the latest cohort was 34% of the maximum cohort growth recorded. Both weight-at-length and cohort growth were negatively affected by mackerel stock size and Norwegian spring-spawning herring (Clupea harengus) stock size (weight-at-length: r2 = 0.89; growth (length): r2 = 0.68; growth (weight): r2 = 0.78), while temperature was not significant. Conspecific density-dependence was most likely mediated via intensified competition associated with greater mackerel density. Negative effects of herring were likely mediated by exploitative competition for shared food resources rather than direct competition due to limited spatio-temporal overlap between mackerel and herring during the feeding season. Herring begin their seasonal feeding migration at least a month before mackerel; therefore, herring consumption influences prey availability for the later-arriving mackerel. Record low mackerel growth and negative effects of mackerel and herring stock size suggest that the carrying capacity of the Norwegian Sea and adjacent areas for plankton-feeding fish stocks have been reached. However, compounding effects of a less productive Norwegian Sea during the 30-year period cannot be excluded.
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Individual-based models simulate populations and communities by following individuals and their properties. They have been used in ecology for more than four decades, with their use and ubiquity in ecology growing rapidly in the last two decades. Individual-based models have been used for many applied or "pragmatic" issues, such as informing the protection and management of particular populations in specific locations, but their use in addressing theoretical questions has also grown rapidly, recently helping us to understand how the sets of traits of individual organisms influence the assembly of communities and food webs. Individual-based models will play an increasingly important role in questions posed by complex ecological systems.
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The dynamic nature of their internal states and the environment directly shape animals' spatial behaviours and give rise to emergent properties at broader scales in natural systems. However, integrating these dynamic features into habitat selection studies remains challenging, due to practically impossible field work to access internal states and the inability of current statistical models to produce dynamic outputs. To address these issues, we developed a robust method, which combines statistical and individual-based modelling. Using a statistical technique for forward modelling of the IBM has the advantage of being faster for parameterization than a pure inverse modelling technique and allows for robust selection of parameters. Using GPS locations from caribou monitored in Québec, caribou movements were modelled based on generative mechanisms accounting for dynamic variables at a low level of emergence. These variables were accessed by replicating real individuals' movements in parallel sub-models, and movement parameters were then empirically parameterized using Step Selection Functions. The final IBM model was validated using both k-fold cross-validation and emergent patterns validation and was tested for two different scenarios, with varying hardwood encroachment. Our results highlighted a functional response in habitat selection, which suggests that our method was able to capture the complexity of the natural system, and adequately provided projections on future possible states of the system in response to different management plans. This is especially relevant for testing the long-term impact of scenarios corresponding to environmental configurations that have yet to be observed in real systems.
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The behavior of wild, pelagic fish in response to sound playback was observed with a sonar/echo sounder. Schools of sprat Sprattus sprattus and mackerel Scomber scombrus were examined at a quiet coastal location. The fish were exposed to a short sequence of repeated impulsive sounds, simulating the strikes from a pile driver, at different sound pressure levels. The incidence of behavioral responses increased with increasing sound level. Sprat schools were more likely to disperse and mackerel schools more likely to change depth. The sound pressure levels to which the fish schools responded on 50% of presentations were 163.2 and 163.3 dB re 1 μPa peak-to-peak, and the single strike sound exposure levels were 135.0 and 142.0 dB re 1 μPa(2) s, for sprat and mackerel, respectively, estimated from dose response curves. For sounds leading to mackerel responses, particle velocity levels were also estimated. The method of observation by means of a sonar/echo sounder proved successful in examining the behavior of unrestrained fish exposed to different sound levels. The technique may allow further testing of the relationship between responsiveness, sound level, and sound characteristics for different types of man-made sound, for a variety of fish species under varied conditions.
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Marine species distribution modeling has seen explosive growth in recent years, and the Endangered Species Research Theme Section entitled ‘Beyond marine mammal habitat modeling: applications for ecology and conservation’ demonstrates that the field of marine mammalogy has been no exception. For the past decade, marine mammal ecologists have been developing habitat models with increasing proficiency and sophistication. However, these efforts have largely focused on correlative analyses of observed species-environment associations, which often have low explanatory power due to the absence of critical, but unaccounted for processes that are important drivers of animal distributions. Here we provide an overview of these processes, advocate for directed studies (e.g. tagging, prey sampling, focal follows, physiological assessment) to address how the processes influence species’ distributions, and challenge the modeling community to incorporate these results into their efforts. We also identify a progression of modeling stages from correlative to confirmatory to mechanistic that should lead us to formulate increasingly robust and accurate predictions of species distributions rooted in greater ecological understanding. Given the on-going risks to marine mammals from human activities and climate change, such models are needed for conservation and management now more than ever.
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Species distribution models (SDMs) are increasingly proposed to support conservation decision making. However, evidence of SDMs supporting solutions for on-ground conservation problems is still scarce in the scientific literature. Here, we show that successful examples exist but are still largely hidden in the grey literature, and thus less accessible for analysis and learning. Furthermore, the decision framework within which SDMs are used is rarely made explicit. Using case studies from biological invasions, identification of critical habitats, reserve selection and translocation of endangered species, we propose that SDMs may be tailored to suit a range of decision-making contexts when used within a structured and transparent decision-making process. To construct appropriate SDMs to more effectively guide conservation actions, modellers need to better understand the decision process, and decision makers need to provide feedback to modellers regarding the actual use of SDMs to support conservation decisions. This could be facilitated by individuals or institutions playing the role of 'translators' between modellers and decision makers. We encourage species distribution modellers to get involved in real decision-making processes that will benefit from their technical input; this strategy has the potential to better bridge theory and practice, and contribute to improve both scientific knowledge and conservation outcomes.
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The current knowledge on detection of, and reaction to, sound by fish is reviewed, with special emphasis on underwater noise from offshore wind farms. The detection distance to wind farms for 3 species of fish representing various hearing capabilities varies between 0.4 and 25 km at wind speeds of 8 to 13 m s -1. The detection distance depends on the size and number of windmills, the hearing abilities of the fish, background noise level, wind speed, water depth and type of sea bottom. The noise from windmills may decrease the effective range for sound communication of fish; however, it is not known to what extent this decrease affects the behaviour and fitness of fish. Windmill noise does not have any destructive effects upon the hearing abilities of fish, even within distances of a few metres. It is estimated that fish are consistently scared away from windmills only at ranges shorter than about 4 m, and only at high wind speeds (higher than 13 m s -1). Thus, the acoustic impact of windmills on fish is restricted to masking communication and orientation signals rather than causing physiological damage or consistent avoidance reactions. These conclusions must be viewed with great caution, however, as the existing data are prone to large uncertainties. Further studies on more detailed measurements of the sound-field and of fish behaviour around windmills are needed.
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To determine whether seismic exploration affected abundance or catch rates of cod (Gadus morhua) and haddock (Melanogrammus aeglefinus), acoustic mapping and fishing trials with trawls and longlines were conducted in the central Barents Sea 7 days before, 5 days during, and 5 days after seismic shooting with air guns. Seismic shooting severely affected fish distribution, local abundance, and catch rates in the entire investigation area of 40 × 40 nautical miles.Trawl catches of cod and haddock and longline catches of haddock declined on average by about 50% (by mass) after shooting started, which agreed with the acoustic abundance estimates; longline catches of cod were reduced by 21%. Reductions in catch rates were observed 18 nautical miles from the seismic shooting area (3 × 10 nautical miles), but the most pronounced reduction occurred within the shooting area, where trawl catches of both species and longline catches of haddock were reduced by about 70% and the longline catches of cod by 45%; a relatively greater reduction was found (in catches and acoustic estimates) for large (>60 cm) than for small fish. Abundance and catch rates did not return to preshooting levels during the 5-day period after seismic shooting ended.
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Behavior of rockfish (Sebastes spp.) exposed to air-gun sounds was examined to establish parameters in a subsequent fishing experiment to determine the effects of a geophysical survey device on fishing success. Rockfish observed in a field enclosure showed startle and alarm responses during 10-min exposures to sounds from a single 1639-cm3 air gun. For olive and black rockfish (S. serranoides and S. melanops), the threshold for the startle responses lay between 200 and 205 dB re 1 μPa. Under sound presentation, blue rockfish (S. mystinus) milled in increasingly tighter mills, and schools of black rockfish collapsed to the bottom. Vermilion (S. miniatus) and olive rockfish formed stationary schools near the bottom and, on sound presentation, either rose in the water column or moved to the bottom and became almost motionless. The general threshold for the alarm responses was about 180 dB re 1 μPa. Regression analyses of changes in depth distribution and shifts to active behaviors suggested that more subtle behavioral responses to sounds might become evident at 161 dB re 1 μPa. These initial responses were sustained only for a few minutes and may differ from those of unconfined fish.
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Previous studies found that sounds generated by seismic air guns led to pronounced reductions in commercial catches from trawls and longlines and the displacement of fish from fishing grounds. In contradiction to these findings and fishermen’s concerns, we demonstrate here that gillnet catches were doubled for redfish (Sebastes norvegicus) and Greenland halibut (Reinhardtius hippoglossoides) during seismic shooting on a Norwegian fishing ground (86% and 132% increase, respectively, compared to preshooting levels). However, longline catch rates fell (16% for Greenland halibut, 25% for haddock (Melanogrammus aeglefinus)). These contradictory results were explained by greater swimming activity versus lowered food search behaviour in fish exposed to air-gun sound emissions. Changes in catch rates of all species studied (including saithe (i.e., pollock, Pollachius virens) and ling (Molva molva)) were found, indicating that these species all responded to air-gun sounds. Except for saithe, acoustic mapping of fish abundance did not suggest displacement from fishing grounds. Less intense sound exposure compared with previous studies and strong habitat preference in some species may explain this finding.
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The most abundant pelagic fish species in the Norwegian Sea, Norwegian spring-spawning herring, Northeast Atlantic mackerel and Northeast Atlantic blue whiting have inter-annual variation in their summer feeding migrations. Knowledge about the spatial distribution and overlap is essential for understanding the species’ interactions and their impact on the ecosystem. Here we attempt to recreate the annual feeding migrations with individual-based modelling and use the results to estimate the daily horizontal overlap between the three species. Species-specific swimming velocities and direction, and the degree of random walk for each year 1995–2003 are found by using a genetic algorithm through calibration with survey observations. From the results it can be concluded that herring and mackerel have a very low horizontal overlap during the feeding season, while herring and blue whiting have a high horizontal overlap. Blue whiting and mackerel have some horizontal overlap in late summer, but a very limited vertical overlap. There is generally a high variability in the horizontal overlap between the species both seasonally and inter-annually. The species utilize many of the same feeding areas in the Norwegian Sea, but often at different times. The modelling approach developed can be useful for implementation of dynamic fish distribution in end to end ecosystem models.
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A kinesis model driven by high-resolution sea surface temperature maps is used to simulate Atlantic bluefin tuna movements in the Gulf of Maine during summer months. Simulations showed that individuals concentrated in areas of thermal preference. Results are compared to empirical distribution maps of bluefin tuna schools determined from aerial overflights of the stock during the same time periods. Simulations and empirical observations showed similar bluefin tuna distributions along fronts, although interannual variations in temperature ranges occupied suggest that additional foraging factors are involved. Performance of the model is further tested by simulating the relatively large-scale annual north–south migrations of bluefin tuna that followed a preferred thermal regime. Despite the model’s relatively simple structure, results suggest that kinesis is an effective mechanism for describing movements of large pelagic fish in the expansive ocean environment.
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The practical analysis of space use and habitat selection by animals is often a problem due to the lack of well-designed programs. I present here the “adehabitat” package for the R software, which offers basic GIS (Geographic Information System) functions, methods to analyze radio-tracking data and habitat selection by wildlife, and interfaces with other R packages. These tools can be downloaded freely on the internet. Because the functions of this package can be combined with other functions of R, “adehabitat” provides a powerful environment for the analysis of the space and habitat use.
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Modern ecology recognizes that modelling systems across scales and at multiple levels-especially to link population and ecosystem dynamics to individual adaptive behaviour-is essential for making the science predictive. 'Pattern-oriented modelling' (POM) is a strategy for doing just this. POM is the multi-criteria design, selection and calibration of models of complex systems. POM starts with identifying a set of patterns observed at multiple scales and levels that characterize a system with respect to the particular problem being modelled; a model from which the patterns emerge should contain the right mechanisms to address the problem. These patterns are then used to (i) determine what scales, entities, variables and processes the model needs, (ii) test and select submodels to represent key low-level processes such as adaptive behaviour, and (iii) find useful parameter values during calibration. Patterns are already often used in these ways, but a mini-review of applications of POM confirms that making the selection and use of patterns more explicit and rigorous can facilitate the development of models with the right level of complexity to understand ecological systems and predict their response to novel conditions.
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Marine petroleum exploration involves the repetitive use of high-energy noise sources, air-guns, that produce a short, sharp, low-frequency sound. Despite reports of behavioral responses of fishes and marine mammals to such noise, it is not known whether exposure to air-guns has the potential to damage the ears of aquatic vertebrates. It is shown here that the ears of fish exposed to an operating air-gun sustained extensive damage to their sensory epithelia that was apparent as ablated hair cells. The damage was regionally severe, with no evidence of repair or replacement of damaged sensory cells up to 58 days after air-gun exposure.
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Seismic airguns produce considerable amounts of acoustic energy that have the potential to affect marine life. This study investigates the effects of exposure to a 730 in.3 airgun array on hearing of three fish species in the Mackenzie River Delta, the northern pike (Esox lucius), broad whitefish (Coregonus nasus), and lake chub (Couesius plumbeus). Fish were placed in cages in the 1.9 m of water and exposed to five or 20 airgun shots, while controls were placed in the same cage but without airgun exposure. Hearing in both exposed and control fish were then tested using the auditory brainstem response (ABR). Threshold shifts were found for exposed fish as compared to controls in the northern pike and lake chub, with recovery within 24 hours of exposure, while there was no threshold shift in the broad whitefish. It is concluded that these three species are not likely to be substantially impacted by exposure to an airgun array used in a river seismic survey. Care must be taken, however, in extrapolation to other species and to fishes exposed to airguns in deeper water or where the animals are exposed to a larger number of airgun shots over a longer period of time.
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Understanding and forecasting species' geographic distributions in the face of global change is a central priority in biodiversity science. The existing view is that one must choose between correlative models for many species versus process-based models for few species. We suggest that opportunities exist to produce process-based range models for many species, by using hierarchical and inverse modeling to borrow strength across species, fill data gaps, fuse diverse data sets, and model across biological and spatial scales. We review the statistical ecology and population and range modeling literature, illustrating these modeling strategies in action. A variety of large, coordinated ecological datasets that can feed into these modeling solutions already exist, and we highlight organisms that seem ripe for the challenge.
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Movement in the context of species distribution models (SDMs) generally refers to a species’ ability to access suitable habitat. Movement ability can be determined by some combination of dispersal constraints or migration rates, landscape factors such as patch configuration, disturbance, and barriers, and demographic factors related to age at maturity, mortality, and fecundity. Including movement ability can result in more precise projections that help to distinguish suitable habitat that is or can be potentially occupied, from suitable habitat that is inaccessible. While most SDM studies have ignored movement or conceptualized it in overly simplistic ways (e.g. no dispersal versus unlimited dispersal), it is increasingly important to incorporate realistic information on movement ability, particularly for studies that aim to project future distributions such as climate change forecasting and invasive species applications. This progress report addresses the increasingly complex ways in which movement has been incorporated in SDM and outlines directions for further study.
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Studies of sound propagation in the shallow waters of the Bristol Channel were carried out between 1967 and 1969, with a systematic coverage of the seasons. Acoustic signals were transmitted and monitored by fixed bottom-laid transducers, the main path lengths being 17, 23 and 137 km. Transmissions consisted of a sequence of tone pulses, varying from 0·3 to 4·5 kHz. Both symmetrical and asymmetrical patterns of modal interference were seen, and it was deduced that at 23 km the number of effective modes was proportional to frequency. Seasonal changes were not marked at 17 and 23 km, but at 137 km there was about 30 dB extra loss in the summer. The latter is thought to be mainly due to fish attenuation, with a significant contribution from summer layering effects at the lower frequencies only. Five other types of amplitude fluctuation were seen, which it is hoped to report later.
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Energy flow and trophic regulation are often well understood in closed freshwater ecosystems. Such regulation is harder to understand in large marine ecosystems, as they extend over vast areas and are influenced by adjacent marine areas. Fully coupled biophysical models have increased in popularity during recent years, but these models are still in their infancy. Here we present a coupled model system of the Norwegian Sea, including an ocean model, a phytoplankton model and individual-based models of the copepod Calanus finmarchicus and planktivorous fish. The fish migration model is driven by survey observations, but the C. finmarchicus densities also affect the fish migrations. This leads to a realistic predation pressure on zooplankton by fish in time and space. The predation pressure of fish on zooplankton is calculated by modelling individual fish growth using bioenergetics models. We estimated that the major pelagic fish stocks in the Norwegian Sea, herring, mackerel and blue whiting, consumed a total of 82 million tonnes of zooplankton, including 35 million tonnes C. finmarchicus, in 1997. Furthermore, the interspecific competition has the greatest effect on blue whiting consumption, while herring consumption is unaffected by the other fish species in this one-year simulation. We also analysed the spatial distribution of C. finmarchicus in June and August and found the highest densities in the northern Norwegian Sea and around Iceland. The results give us a better understanding of the effect from fish predation on the Norwegian Sea ecosystem, and how it affects the C. finmarchicus stock.
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Conservation planning of critical habitats for wildlife species at risk is a priority topic that requires the knowledge of how animals select and use their habitat, and how they respond to future developmental changes in their environment. This paper explores the role of a habitat-modeling methodological approach, agent-based modeling, which we advocate as a promising approach for ecological research. Agent-based models (ABMs) are capable of simultaneously distinguishing animal densities from habitat quality, can explicitly represent the environment and its dynamism, can accommodate spatial patterns of inter- and intra-species mechanisms, and can explore feedbacks and adaptations inherent in these systems. ABMs comprise autonomous, individual entities; each with dynamic, adaptive behaviors and heterogeneous characteristics that interact with each other and with their environment. These interactions result in emergent outcomes that can be used to quantitatively examine critical habitats from the individual- to population-level. ABMs can also explore how wildlife will respond to potential changes in environmental conditions, since they can readily incorporate adaptive animal-movement ecology in a changing landscape. This paper describes the necessary elements of an ABM developed specifically for understanding wildlife habitat selection, reviews the current empirical literature on ABMs in wildlife ecology and management, and evaluates the current and future roles these ABMs can play, specifically with regards to scenario planning of designated critical habitats.
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The considerable extent of construction and operation of marine renewable energy developments (MRED) within U.K. and adjacent waters will lead, among other things, to the emission of electromagnetic fields (EMF) and subsea sounds into the marine environment. Migratory fishes that respond to natural environmental cues, such as the Earth's geomagnetic field or underwater sounds, move through the same waters that the MRED occupy, thereby raising the question of whether there are any effects of MRED on migratory fishes. Diadromous species, such as the Salmonidae and Anguillidae, which undertake large-scale migrations through coastal and offshore waters, are already significantly affected by other human activities leading to national and international conservation efforts to manage any existing threats and to minimize future concerns, including the potential effect of MRED. Here, the current state of knowledge with regard to the potential for diadromous fishes of U.K. conservation importance to be affected by MRED is reviewed. The information on which to base the review was found to be limited with respect to all aspects of these fishes' migratory behaviour and activity, especially with regards to MRED deployment, making it difficult to establish cause and effect relationships. The main findings, however, were that diadromous species can use the Earth's magnetic field for orientation and direction finding during migrations. Juveniles of anadromous brown trout (sea trout) Salmo trutta and close relatives of S. trutta respond to both the Earth's magnetic field and artificial magnetic fields. Current knowledge suggests that EMFs from subsea cables may interact with migrating Anguilla sp. (and possibly other diadromous fishes) if their movement routes take them over the cables, particularly in shallow water (<20 m). The only known effect is a temporary change in swimming direction. Whether this will represent a biologically significant effect, for example delayed migration, cannot yet be determined. Diadromous fishes are likely to encounter EMFs from subsea cables either during the adult movement phases of life or their early life stages during migration within shallow, coastal waters adjacent to natal rivers. The underwater sound from MRED devices has not been fully characterized to determine its acoustic properties and propagation through the coastal waters. MRED that require pile driving during construction appear to be the most relevant to consider. In the absence of a clear understanding of their response to underwater sound, the specific effects on migratory species of conservation concern remain very difficult to determine in relation to MRED. Based on the studies reviewed, it is suggested that fishes that receive high intensity sound in close proximity to construction may be physiologically affected to some degree, whereas those at farther distances, potentially up to several km, may exhibit behaviour responses; the effect of which is unknown and will be dependent on the properties of the received sound and receptor characteristics and condition. Whether there are behavioural effects on the fishes during operation is unknown but any change to the environment and subsequent response by the fishes would need to be considered over the lifetime of the MRED. It is not yet possible to determine if effects relating to sound exposure are biologically significant. The current assumptions of limited effects are built on an incomplete understanding of how the species move around their environment and interact with natural and anthropogenic EMFs and subsea sound. A number of important knowledge gaps exist, principally whether migratory fish species on the whole respond to the EMF and the sound associated with MRED. Future research should address the principal gaps before assuming that any effect on diadromous species results in a biological effect.
Article
Within the field of species distribution modelling an apparent dichotomy exists between process-based and correlative approaches, where the processes are explicit in the former and implicit in the latter. However, these intuitive distinctions can become blurred when comparing species distribution modelling approaches in more detail. In this review article, we contrast the extremes of the correlativeprocess spectrum of species distribution models with respect to core assumptions, model building and selection strategies, validation, uncertainties, common errors and the questions they are most suited to answer. The extremes of such approaches differ clearly in many aspects, such as model building approaches, parameter estimation strategies and transferability. However, they also share strengths and weaknesses. We show that claims of one approach being intrinsically superior to the other are misguided and that they ignore the processcorrelation continuum as well as the domains of questions that each approach is addressing. Nonetheless, the application of process-based approaches to species distribution modelling lags far behind more correlative (process-implicit) methods and more research is required to explore their potential benefits. Critical issues for the employment of species distribution modelling approaches are given, together with a guideline for appropriate usage. We close with challenges for future development of process-explicit species distribution models and how they may complement current approaches to study species distributions.
Article
Ecological Modelling j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / e c o l m o d e l a b s t r a c t The 'ODD' (Overview, Design concepts, and Details) protocol was published in 2006 to standardize the published descriptions of individual-based and agent-based models (ABMs). The primary objectives of ODD are to make model descriptions more understandable and complete, thereby making ABMs less subject to criticism for being irreproducible. We have systematically evaluated existing uses of the ODD protocol and identified, as expected, parts of ODD needing improvement and clarification. Accordingly, we revise the definition of ODD to clarify aspects of the original version and thereby facilitate future standardization of ABM descriptions. We discuss frequently raised critiques in ODD but also two emerg-ing, and unanticipated, benefits: ODD improves the rigorous formulation of models and helps make the theoretical foundations of large models more visible. Although the protocol was designed for ABMs, it can help with documenting any large, complex model, alleviating some general objections against such models.
Article
Each modeller who builds and analyses an individual-based model learns of course a great deal, but what has ecology as a whole learned from the individual-based models published during the last decade? Answering this question proves extremely difficult as there is no common motivation behind individual-based models. The distinction is introduced between ‘pragmatic’ motivation, which uses the individual-based approach as a tool without any reference to the theoretical issues which have emerged from the classical state variable approach and ‘paradigmatic’ motivation, which explicitly refers to theoretical ecology. A mini-review of 50 individual-based animal population models shows that the majority are driven by pragmatic motivation. Most models are very complex and special techniques to cope with this complexity during their analysis are only occasionally applied. It is suggested that in order to orient individual-based modelling more towards general theoretical issues, we need increased explicit reference to theoretical ecology and an advanced strategy for building and analysing individual-based models. To this end, a heuristic list of rules is presented which may help us to advance the practice of individual-based modelling and to learn more general lessons from individual-based modelling in the future than we have during the last decade. The main ideas behind these rules are as follows: (1) Individual-based models usually make more realistic assumptions than state variable models, but it should not be forgotten that the aim of individual-based modelling is not ‘realism’ but modelling. (2) The individual-based approach is a bottom-up approach which starts with the ‘parts’ (i.e. individuals) of a system (i.e. population) and then tries to understand how the system’s properties emerge from the interaction among these parts. However, bottom-up approaches alone will never lead to theories at the systems level. State variable or top-down approaches are needed to provide an appropriate integrated view, i.e. the relevant questions at the population level.
Article
Species distribution models (SDMs) are numerical tools that combine observations of species occurrence or abundance with environmental estimates. They are used to gain ecological and evolutionary insights and to predict distributions across landscapes, sometimes requiring extrapolation in space and time. SDMs are now widely used across terrestrial, freshwater, and marine realms. Differences in methods between disciplines reflect both differences in species mobility and in “established use. Model realism and robustness is influenced by selection of relevant predictors and modeling method, consideration of scale, how the interplay between environmental and geographic factors is handled, and the extent of extrapolation. Current linkages between SDM practice and ecological theory are often weak, hindering progress. Remaining challenges include: improvement of methods for modeling presence-only data and for model selection and evaluation; accounting for biotic interactions; and assessing model uncertainty.
Article
The distribution and demography of Calanus finmarchicus, C. glacialis and C. hyperboreus were studied throughout their growth season on a basin scale in the Norwegian Sea using ordination techniques and generalized additive models. The distribution and demographic data were related to the seasonal development of the phytoplankton bloom and physical characteristics of water masses. The resulting quantified relationships were related to knowledge on life cycle and adaptations of Calanus species. C. finmarchicus was the numerically dominant Calanus species in Coastal, Atlantic and Arctic waters, showing strong association with both Atlantic and Arctic waters. C. hyperboreus and C. glacialis were associated with Arctic water; however, C. glacialis was occasionally observed in the Norwegian Sea and is probably an expatriate advected into the area from various origins. Demography indicated one generation per year of C. finmarchicus, a two-year life cycle of C. hyperboreus, and both one- and two-year life cycles for C. glacialis in the water masses where they were most abundant. For the examined Calanus species, young copepodites of the new generation seemed to be tuned to the phytoplankton bloom in their main water mass. The development of C. finmarchicus was delayed in Arctic water, and mis-match between feeding stages and the phytoplankton bloom may reduce survival and reproductive success of C. finmarchicus in Arctic water. Based on low abundances of C. hyperboreus CI–III in Atlantic water and main recruitment to CI prior to the phytoplankton bloom, we suggest that reproduction of C. hyperboreus in Atlantic water is not successful.
Article
Studies on the effects of offshore wind farm construction on marine life have focused on behavioral reactions in porpoises and seals (Thomsen et al. 2006). The effects on fish have only very recently come into the focus of scientists, regulators, and stakeholders (Popper and Hastings 2009). Pile-driving noise during construction is of particular concern because the very high sound pressure levels (see Thomsen et al. 2006) could potentially prevent fish from reaching breeding or spawning sites, finding food, and acoustically locating mates that could result in long-term effects on reproduction and population parameters. There is also the possibility that avoidance reactions might displace fish away from potential fishing grounds that could lead to reduced catches (see, e.g., Engås et al. 1996). However, the nature and extent of behavioral reactions of marine fish due to pile driving have not been studied in controlled experiments. Therefore, the impacts of pile driving on marine fish remain unknown.
Article
The underwater environment is filled with biotic and abiotic sounds, many of which can be important for the survival and reproduction of fish. Over the last century, human activities in and near the water have increasingly added artificial sounds to this environment. Very loud sounds of relatively short exposure, such as those produced during pile driving, can harm nearby fish. However, more moderate underwater noises of longer duration, such as those produced by vessels, could potentially impact much larger areas, and involve much larger numbers of fish. Here we call attention to the urgent need to study the role of sound in the lives of fish and to develop a better understanding of the ecological impact of anthropogenic noise.
Article
An expert panel reviewed the expanding literature on marine mammal (cetacean and pinniped) auditory and behavioral responses to sound exposure to develop comprehensive, scientifically based noise exposure criteria [Aquatic Mammals 33(4)]. They used precautionary extrapolation procedures to predict exposure levels above which adverse effects (both physical and behavioral) could be expected. Due to the paucity of data on long-term exposures, criteria were developed for single exposure events only. Marine mammals were broken into functional hearing groups. Exposure types were lumped into three broad classes (single pulses, multiple pulses, and nonpulses). Levels estimated to induce permanent noise-induced hearing loss were determined for each of 15 sound typeanimal group combinations. For example, injury criteria for pinnipeds in water exposed to multiple pulses were 186 dB re 1 muPa(2) -s (weighted SEL) and 218 dB(pk) re 1 muPa (unweighted peak SPL). Discrete behavioral disturbance thresholds could only be determined for exposure to single pulses. For other exposures, available data on behavioral responses were ranked by severity and significance. This severity scaling and the resulting conclusions will be described. New research required to improve criteria and to assess cumulative and ecosystem-level effects will also be considered, along with current policy andor regulatory applications.
Report of the Working Group on Widely Distributed Stocks (WGWIDE)
ICES, 2016. Report of the Working Group on Widely Distributed Stocks (WGWIDE). 31
Interim Report of the Working Group on Integrated Ecosystem Assess-ments for the Norwegian Sea (WGINOR)
ICES, 2017. Interim Report of the Working Group on Integrated Ecosystem Assess-ments for the Norwegian Sea (WGINOR). 28 November -2 December 2016. ICES, Bergen, Norway CM 2016/SSGIEA:10. 28 pp.
Mackerel behaviour and seismic signals -a net pen pilot study
  • L D Sivle
  • R Hansen
  • H E Karlsen
  • N O Handegard
Sivle, L.D., Hansen, R., Karlsen, H.E., Handegard, N.O., 2016. Mackerel behaviour and seismic signals -a net pen pilot study. Rapport fra Havforskningen 19.
Behavioural effects of seismic dose escalation exposure on captive mackerel (Scomber scombrus)
  • L D Sivle
  • T N Forland
  • R R Hasen
  • M Andersson
  • M Linne
  • E Grimsbø
  • H E Karlsen
Sivle, L.D., Forland, T.N., Hasen, R.R., Andersson, M., Linne, M., Grimsbø, E., Karlsen, H.E., 2017. Behavioural effects of seismic dose escalation exposure on captive mackerel (Scomber scombrus). Rapport fra Havforskningen 34 (2017), 72.