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Bioenergetics is the study of how animals achieve energetic balance. Energetic balance results from the energetic expenditure of an individual and the energy they extract from their environment. Ingested energy depends on several extrinsic (e.g prey species, nutritional value and composition, prey density and availability) and intrinsic factors (e.g. foraging effort, success at catching prey, digestive processes and associated energy losses, and digestive capacity). While the focus in bioenergetic modelling is often on the energetic costs an animal incurs, the robust estimation of an individual’s energy intake is equally critical for producing meaningful predictions. Here, we review the components and processes that affect energy intake from ingested gross energy to biologically useful net energy (NE). The current state of knowledge of each parameter is reviewed, shedding light on research gaps to advance this field. The review highlighted that the foraging behaviour of many marine mammals is relatively well studied via biologging tags, with estimates of success rate typically assumed for most species. However, actual prey capture success rates are often only assumed, although we note studies that provide approaches for its estimation using current techniques. A comprehensive collation of the nutritional content of marine mammal prey species revealed a robust foundation from which prey quality (comprising prey species, size and energy density) can be assessed, though data remain unavailable for many prey species. Empirical information on various energy losses following ingestion of prey was unbalanced among marine mammal species, with considerably more literature available for pinnipeds. An increased understanding and accurate estimate of each of the components that comprise a species NE intake are an integral part of bioenergetics. Such models provide a key tool to investigate the effects of disturbance on marine mammals at an individual and population level and to

Bioenergetic approaches are increasingly used to understand how marine mammal populations could be affected by a changing and disturbed aquatic environment. There remain considerable gaps in our knowledge of marine mammal bioenergetics, which hinder the application of bioenergetic studies to inform policy decisions. We conducted a priority-setting exercise to identify high-priority unanswered questions in marine mammal bioenergetics, with an emphasis on questions relevant to conservation and management. Electronic communication and a virtual workshop were used to solicit and collate potential research questions from the marine mammal bioenergetic community. From a final list of 39 questions, 11 were identified as ‘key’ questions because they received votes from at least 50% of survey participants. Key questions included those related to energy intake (prey landscapes, exposure to human activities) and expenditure (field metabolic rate, exposure to human activities, lactation, time-activity budgets), energy allocation priorities, metrics of body condition and relationships with survival and reproductive success and extrapolation of data from one species to another. Existing tools to address key questions include labelled water, animal-borne sensors, mark-resight data from long-term research programs, environmental DNA and unmanned vehicles. Further validation of existing approaches and development of new methodologies are needed to comprehensively address some key questions, particularly for cetaceans. The identification of these key questions can provide a guiding framework to set research priorities, which ultimately may yield more accurate information to inform policies and better conserve marine mammal populations.

Understanding why animals move as they do when searching for resources is a central question in ecology, and a prerequisite for the development of predictive process-based models for conservation and management. Many species are central-place foragers (CPF). While several models for CPFs have been proposed, they often assume well-defined return rules to the focal point (like breeding). For some CPFs, however, the decisions to return to central sites are governed by multiple interactions between environmental and physiological factors.We present AgentSeal, a behaviour- and physiology-based, spatially explicit, agent-based model. We use harbour seals, a marine CPF, as a case study and focus on individuals outside their breeding and moulting seasons to capture general fine- and large-scale movements and drivers behind CPF. We model movement decisions based on optimal foraging strategy, cognitive and physiological processes in a realistic landscape, coupled with realistic prey distribution and tuned to a range of behavioural and physiological patterns observed at different scales and levels of organisation (pattern-orientated modelling, POM).The model can reproduce energetic, movement and other behavioural patterns such as net energy balance, at-sea and on land site fidelity, daily activity budgets and trip extents. The model reveals the crucial elements needed to model return-trips of CPFs including movement characteristics that vary as a function of local environmental conditions, cognitive mapping of foraging areas as points of attraction in subsequent foraging trips, and physiological requirements defining switches between resting and foraging.We discuss potential applications and extensions of the model, including investigations of fundamental questions in foraging ecology: how spatial distribution and aggregation of resources affect movement of marine CPFs; what are the main drivers behind their at-sea site-fidelity to foraging patches? We also discuss applied obj

In marine environments noise from human activities is increasing dramatically, causing animals to alter their behavior and forage less efficiently. These alterations incur energetic costs that can result in reproductive failure, death, and may ultimately influence population viability; yet the link between population dynamics and individual energetics is poorly understood. We present an energy budget model for simulating effects of acoustic disturbance on populations. It accounts for environmental variability and individual state, while incorporating realistic animal movements. Using harbor porpoises (Phocoena phocoena) as a case study, we evaluated population consequences of disturbance from seismic surveys and investigated underlying drivers of vulnerability. The framework reproduced empirical estimates of population structure and seasonal variations in energetics. The largest effects predicted for seismic surveys were in late summer and fall, and were unrelated to local abundance, but instead to lactation costs, water temperature, and body fat. Our results demonstrate that consideration of temporal variation in individual energetics and their link to costs associated with disturbances is imperative when predicting disturbance impacts. These mechanisms are general to animal species, and the framework presented here can be used for gaining new insights into the spatiotemporal variability of animal movements and energetics that control population dynamics.

Climate change is modifying the structure of marine ecosystems, including that of fish communities. Alterations in abiotic and biotic conditions can decrease fish size and change community spatial arrangement, ultimately impacting predator species which rely on these communities. To conserve predators and understand drivers of observed changes in their population dynamics, we must advance our understanding of how shifting environmental conditions can impact populations by limiting food available to individuals.To investigate impacts of changing fish size and spatial aggregation on a top predator population, we applied an existing agent-based model parameterized for harbor porpoises (Phocoena phocoena) which represents animal energetics and movements in high detail. We used this framework to quantify impacts of shifting prey size and spatial aggregation on porpoise movement, space use, energetics, and population dynamics.Simulated individuals were more likely to switch from area-restricted search to transit behavior with increasing prey size, particularly when starving, due to elevated resource competition. In simulations with highly aggregated prey, higher prey encounter rates counteracted resource competition, resulting in no impacts of prey size on movement behavior.Reduced energy intake with decreasing prey size and aggregation level caused population decline. A 15% decrease in fish length, for example, resulted in total population collapse. Increasing prey consumption rates by 42.8 ± 4.5% could offset population declines, however this increase was 21.3 ± 12.7% higher than needed to account for changes in total energy availability alone. This suggests that animals in realistic seascapes require additional energy to locate smaller prey which should be considered when assessing impacts of decreased energy availability.Changes in prey size and aggregation influenced movements and population dynamics of simulated harbor porpoises, revealing that climate-induced chang

The majority of variation in six traits critical to the growth, survival and reproduction of plant species is thought to be organised along just two dimensions, corresponding to strategies of plant size and resource acquisition. However, it is unknown whether global plant trait relationships extend to climatic extremes, and if these interspecific relationships are confounded by trait variation within species. We test whether trait relationships extend to the cold extremes of life on Earth using the largest database of tundra plant traits yet compiled. We show that tundra plants demonstrate remarkably similar resource economic traits, but not size traits, compared to global distributions, and exhibit the same two dimensions of trait variation. Three quarters of trait variation occurs among species, mirroring global estimates of interspecific trait variation. Plant trait relationships are thus generalizable to the edge of global trait-space, informing prediction of plant community change in a warming world.

The Overview, Design concepts and Details (ODD) protocol for describing Individual-and Agent-Based Models (ABMs) is now widely accepted and used to document such models in journal articles. As a standardized document for providing a consistent, logical and readable account of the structure and dynamics of ABMs, some research groups also find it useful as a workflow for model design. Even so, there are still limitations to ODD that obstruct its more widespread adoption. Such limitations are discussed and addressed in this paper: the limited availability of guidance on how to use ODD; the length of ODD documents; limitations of ODD for highly complex models; lack of sufficient details of many ODDs to enable reimplementation without access to the model code; and the lack of provision for sections in the document structure covering model design ratio-nale, the model’s underlying narrative, and the means by which the model’s fitness for purpose is evaluated. We document the steps we have taken to provide better guidance on: structuring complex ODDs and an ODD summary for inclusion in a journal article (with full details in supplementary material; Table 1); using ODD to point readers to relevant sections of the model code; update the document structure to include sections on model rationale and evaluation. We also further advocate the need for standard descriptions of simulation experiments and argue that ODD can in principle be used for any type of simulation model. Thereby ODD would provide a lingua franca for simulation modelling.

The majority of variation in six traits critical to the growth, survival and reproduction of plant species is thought to be organised along just two dimensions, corresponding to strategies of plant size and resource acquisition. However, it is unknown whether global plant trait relationships extend to climatic extremes, and if these interspecific relationships are confounded by trait variation within species. We test whether trait relationships extend to the cold extremes of life on Earth using the largest database of tundra plant traits yet compiled. We show that tundra plants demonstrate remarkably similar resource economic traits, but not size traits, compared to global distributions, and exhibit the same two dimensions of trait variation. Three quarters of trait variation occurs among species, mirroring global estimates of interspecific trait variation. Plant trait relationships are thus generalizable to the edge of global trait-space, informing prediction of plant community change in a warming world.

The Overview, Design concepts and Details (ODD) protocol for describing Individual- and Agent-Based Models (ABMs) is now widely accepted and used to document such models in journal articles. As a standardized document for providing a consistent, logical and readable account of the structure and dynamics of ABMs, some research groups also find it useful as a workflow for model design. Even so, there are still limitations to ODD that obstruct its more widespread adoption. Such limitations are discussed and addressed in this paper: the limited availability of guidance on how to use ODD; the length of ODD documents; limitations of ODD for highly complex models; lack of sufficient details of many ODDs to enable reimplementation without access to the model code; and the lack of provision for sections in the document structure covering model design rationale, the model’s underlying narrative, and the means by which the model’s fitness for purpose is evaluated. We document the steps we have taken to provide better guidance on: structuring complex ODDs and an ODD summary for inclusion in a journal article (with full details in supplementary material; Table 1); using ODD to point readers to relevant sections of the model code; update the document structure to include sections on model rationale and evaluation. We also further advocate the need for standard descriptions of simulation experiments and argue that ODD can in principle be used for any type of simulation model. Thereby ODD would provide a lingua franca for simulation modelling.

The acceptance and usefulness of simulation models are often limited by the efficiency, transparency, reproducibility, and reliability of the modelling process. We address these issues by suggesting that modellers (1) “trace” the iterative modelling process by keeping a modelling notebook corresponding to the laboratory notebooks used by empirical researchers, (2) use a standardized notebook structure and terminology based on the existing TRACE documentation framework, and (3) use their notebooks to compile TRACE documents that supplement publications and reports. These practices have benefits for model developers, users, and stakeholders: improved and efficient model design, analysis, testing, and application; increased model acceptance and reuse; and replicability and reproducibility of the model and the simulation experiments. Using TRACE terminology and structure in modelling notebooks facilitates production of TRACE documents. We explain the rationale of TRACE, provide example TRACE documents, and suggest strategies for keeping “TRACE Modelling Notebooks.”

The majority of variation in six traits critical to the growth, survival and reproduction of plant species is thought to be organised along just two dimensions, corresponding to strategies of plant size and resource acquisition. However, it is unknown whether global plant trait relationships extend to climatic extremes, and if these interspecific relationships are confounded by trait variation within species. We test whether trait relationships extend to the cold extremes of life on Earth using the largest database of tundra plant traits yet compiled. We show that tundra plants demonstrate remarkably similar resource economic traits, but not size traits, compared to global distributions, and exhibit the same two dimensions of trait variation. Three quarters of trait variation occurs among species, mirroring global estimates of interspecific trait variation. Plant trait relationships are thus generalizable to the edge of global trait-space, informing prediction of plant community change in a warming world.

Motivation: The Tundra Trait Team (TTT) database includes field‐based measurements of key traits related to plant form and function at multiple sites across the tundra biome. This dataset can be used to address theoretical questions about plant strategy and trade‐offs, trait–environment relationships and environmental filtering, and trait variation across spatial scales, to validate satellite data, and to inform Earth system model parameters. Main types of variable contained: The database contains 91,970 measurements of 18 plant traits. The most frequently measured traits (> 1,000 observations each) include plant height, leaf area, specific leaf area, leaf fresh and dry mass, leaf dry matter content, leaf nitrogen, carbon and phosphorus content, leaf C:N and N:P, seed mass, and stem specific density. Spatial location and grain: Measurements were collected in tundra habitats in both the Northern and Southern Hemispheres, including Arctic sites in Alaska, Canada, Greenland, Fennoscandia and Siberia, alpine sites in the European Alps, Colorado Rockies, Caucasus, Ural Mountains, Pyrenees, Australian Alps, and Central Otago Mountains (New Zealand), and sub‐Antarctic Marion Island. More than 99% of observations are georeferenced. Time period and grain: All data were collected between 1964 and 2018. A small number of sites have repeated trait measurements at two or more time periods. Major taxa and level of measurement: Trait measurements were made on 978 terrestrial vascular plant species growing in tundra habitats. Most observations are on individuals (86%), while the remainder represent plot or site means or maximums per species. Software format: csv file and GitHub repository with data cleaning scripts in R; contribution to TRY plant trait database (www.try-db.org) to be included in the next version release.

AimPlant functional groups are widely used in community ecology and earth system modelling to describe trait variation within and across plant communities. However, this approach rests on the assumption that functional groups explain a large proportion of trait variation among species. We test whether four commonly used plant functional groups represent variation in six ecologically important plant traits.LocationTundra biome.Time periodData collected between 1964 and 2016.Major taxa studied295 tundra vascular plant species.MethodsWe compiled a database of six plant traits (plant height, leaf area, specific leaf area, leaf dry matter content, leaf nitrogen, seed mass) for tundra species. We examined the variation in species‐level trait expression explained by four traditional functional groups (evergreen shrubs, deciduous shrubs, graminoids, forbs), and whether variation explained was dependent upon the traits included in analysis. We further compared the explanatory power and species composition of functional groups to alternative classifications generated using post hoc clustering of species‐level traits.ResultsTraditional functional groups explained significant differences in trait expression, particularly amongst traits associated with resource economics, which were consistent across sites and at the biome scale. However, functional groups explained 19% of overall trait variation and poorly represented differences in traits associated with plant size. Post hoc classification of species did not correspond well with traditional functional groups, and explained twice as much variation in species‐level trait expression.Main conclusionsTraditional functional groups only coarsely represent variation in well‐measured traits within tundra plant communities, and better explain resource economic traits than size‐related traits. We recommend caution when using functional group approaches to predict tundra vegetation change, or ecosystem functions relating to plant size, su

MotivationThe Tundra Trait Team (TTT) database includes field‐based measurements of key traits related to plant form and function at multiple sites across the tundra biome. This dataset can be used to address theoretical questions about plant strategy and trade‐offs, trait–environment relationships and environmental filtering, and trait variation across spatial scales, to validate satellite data, and to inform Earth system model parameters. Main types of variable containedThe database contains 91,970 measurements of 18 plant traits. The most frequently measured traits (> 1,000 observations each) include plant height, leaf area, specific leaf area, leaf fresh and dry mass, leaf dry matter content, leaf nitrogen, carbon and phosphorus content, leaf C:N and N:P, seed mass, and stem specific density. Spatial location and grainMeasurements were collected in tundra habitats in both the Northern and Southern Hemispheres, including Arctic sites in Alaska, Canada, Greenland, Fennoscandia and Siberia, alpine sites in the European Alps, Colorado Rockies, Caucasus, Ural Mountains, Pyrenees, Australian Alps, and Central Otago Mountains (New Zealand), and sub‐Antarctic Marion Island. More than 99% of observations are georeferenced. Time period and grainAll data were collected between 1964 and 2018. A small number of sites have repeated trait measurements at two or more time periods. Major taxa and level of measurementTrait measurements were made on 978 terrestrial vascular plant species growing in tundra habitats. Most observations are on individuals (86%), while the remainder represent plot or site means or maximums per species. Software formatcsv file and GitHub repository with data cleaning scripts in R; contribution to TRY plant trait database (www.try-db.org) to be included in the next version release.

The tundra is warming more rapidly than any other biome on Earth, and the potential ramifications are far-reaching because of global feedback effects between vegetation and climate. A better understanding of how environmental factors shape plant structure and function is crucial for predicting the consequences of environmental change for ecosystem functioning. Here we explore the biome-wide relationships between temperature, moisture and seven key plant functional traits both across space and over three decades of warming at 117 tundra locations. Spatial temperature–trait relationships were generally strong but soil moisture had a marked influence on the strength and direction of these relationships, highlighting the potentially important influence of changes in water availability on future trait shifts in tundra plant communities. Community height increased with warming across all sites over the past three decades, but other traits lagged far behind predicted rates of change. Our findings highlight the challenge of using space-for-time substitution to predict the functional consequences of future warming and suggest that functions that are tied closely to plant height will experience the most rapid change. They also reveal the strength with which environmental factors shape biotic communities at the coldest extremes of the planet and will help to improve projections of functional changes in tundra ecosystems with climate warming.

Marine ecosystems are increasingly exposed to anthropogenic disturbances that cause animals to change behavior and move away from potential foraging grounds. Here we present a process‐based modeling framework for assessing population consequences of such sub‐lethal behavioral effects. It builds directly on how disturbances influence animal movements, foraging and energetics, and is therefore applicable to a wide range of species. To demonstrate the model we assess the impact of wind farm construction noise on the North Sea harbor porpoise population. Subsequently, we demonstrate how the model can be used to minimize population impacts of disturbances through spatial planning. Population models that build on the fundamental processes that determine animal fitness have a high predictive power in novel environments, making them ideal for marine management.

Motivation: The Tundra Trait Team (TTT) database includes field-based measurements of key traits related to plant form and function at multiple sites across the tundra biome. This dataset can be used to address theoretical questions about plant strategy and trade-offs, trait–environment relationships and environmental filtering, and trait variation across spatial scales, to validate satellite data, and to inform Earth system model parameters. Main types of variable contained: The database contains 91,970 measurements of 18 plant traits. The most frequently measured traits (> 1,000 observations each) include plant height, leaf area, specific leaf area, leaf fresh and dry mass, leaf dry matter content, leaf nitrogen, carbon and phosphorus content, leaf C:N and N:P, seed mass, and stem specific density. Spatial location and grain: Measurements were collected in tundra habitats in both the Northern and Southern Hemispheres, including Arctic sites in Alaska, Canada, Greenland, Fennoscandia and Siberia, alpine sites in the European Alps, Colorado Rockies, Caucasus, Ural Mountains, Pyrenees, Australian Alps, and Central Otago Mountains (New Zealand), and sub-Antarctic Marion Island. More than 99% of observations are georeferenced. Time period and grain: All data were collected between 1964 and 2018. A small number of sites have repeated trait measurements at two or more time periods. Major taxa and level of measurement: Trait measurements were made on 978 terrestrial vascular plant species growing in tundra habitats. Most observations are on individuals (86%), while the remainder represent plot or site means or maximums per species. Software format: csv file and GitHub repository with data cleaning scripts in R; contribution to TRY plant trait database (www.try-db.org) to be included in the next version release.

Movement is a fundamental element of animal behaviour, and it is the primary way through which animals respond to environmental changes. Therefore, understanding the drivers of individual movement is essential for species conservation. The endangered Saimaa ringed seal (Phoca hispida saimensis) lives land-locked in Lake Saimaa and is affected by various anthropogenic factors. Telemetry studies provide critical information but are insufficient to identify the mechanisms responsible for particular movement patterns. To better understand these mechanisms and to predict how changed movement patterns could influence the subspecies’ spatial ecology, we developed an individual-based movement model. We divided the seals’ daily routines into foraging and resting and explored how well the model captured observed home ranges and other movement metrics. Here we present the model, its predictions of home ranges and its sensitivity to model assumptions and parameter uncertainty. We used movement data from one individual to calibrate the model, but this resulted in poor predictions of home range sizes of five seals used for validation. This suggests that differences in movement paths not only reflect different landscape configurations but also differences among the individuals’ state and personalities. Therefore, we separately re-calibrated the model to data from five individuals, reproducing their home ranges, habitat use and movement paths more accurately. Although ignoring many aspects of seal behaviour, the model can be applied as a tool to guide further data collection and analysis, study seal ecology, and evaluate the efficacy of various conservation measures.

The migration strategy of many capital breeders is to garner body stores along the flyway at distinct stopover sites. The rate at which they can fuel is likely to be strongly influenced by a range of factors, such as physiology, food availability, time available for foraging and perceived predation. We analysed the foraging behaviour and fuel accumulation of pink-footed geese, an Arctic capital breeder, at their mid- flyway spring stopover site and evaluated to what extent their behaviour and fuelling were related to physiological and external factors and how it differed from other stopovers along the flyway. We found that fuel accumulation rates of geese at the mid-flyway site were limited by habitat availability rather than by digestive constraints. However, as the time available for foraging increased over the stopover season, geese were able to keep constant fuelling rate. Putting this in perspective, geese increased their daily net energy intake along the flyway corresponding to the increase in time available for foraging. The net energy intake per hour of foraging remained the same. Geese showed differences in their reaction to predators/disturbance between the sites, taking higher risks particularly at the final stopover site. Hence, perceived predation along the flyway may force birds to postpone the final fuel accumulation to the last stopover along the flyway. Flexibility in behaviour appears to be an important trait to ensure fitness in this capital breeder. Our findings are based on a new, improved method for estimating fuel accumulation of animals foraging in heterogeneous landscapes based on data obtained from satellite telemetry and habitat specific intake rates.

Polar bears (Ursus maritimus) from East Greenland and Svalbard exhibited very high concentrations of polychlorinated biphenyls (PCBs) in the 1980s and 1990s. In Svalbard, slow population growth during that period was suspected to be linked to PCB contamination. In this case study, we explored how PCBs could have impacted polar bear population growth and/or male reproductive success in Svalbard during the mid-1990s by reducing the fertility of contaminated males. A dose–response relationship linking the effects of PCBs to male polar bear fertility was extrapolated from studies of the effects of PCBs on sperm quality in rodents. Based on this relationship, an individual-based model of bear interactions during the breeding season predicted fertilization success under alternative assumptions regarding male–male competition for females. Contamination reduced pregnancy rates by decreasing the availability of fertile males, thus triggering a mate-finding Allee effect, particularly when male–male competition for females was limited or when infertile males were able to compete with fertile males for females. Comparisons of our model predictions on age-dependent reproductive success of males with published empirical observations revealed that the low representation of 10–14-year-old males among breeding males documented in Svalbard in mid-1990s could have resulted from PCB contamination. We conclude that contamination-related male infertility may lead to a reduction in population growth via an Allee effect. The magnitude of the effect is largely dependent on the population-specific mating system. In eco-toxicological risk assessments, appropriate consideration should therefore be given to negative effects of contaminants on male fertility and male mating behaviour.

Effective species conservation and management requires information on species distribution patterns, which is challenging for highly mobile and cryptic species that may be subject to multiple anthropogenic stressors across international boundaries. Understanding species-habitat relationships can improve the assessment of trends and distribution by explicitly allowing high-resolution data on habitats to inform abundance estimation and the identification of protected areas. In this study, we aggregated an unprecedented set of survey data of a marine top predator, the harbor porpoise (Phocoena phocoena), collected in the UK (SCANS II, Dogger Bank), Belgium, the Netherlands, Germany, and Denmark, to develop seasonal habitat-based density models for the central and southern North Sea. Visual survey data were collected over 9 yr (2005-2013) by means of dedicated line-transect surveys, taking into account the proportion of missed sightings. Generalized additive models of porpoise density were fitted to 156,630 km of on-effort survey data with 14,356 sightings of porpoise groups. Selected predictors included static and dynamic variables, such as depth, distance to shore and to sandeel (Ammodytes spp.) grounds, sea surface temperature (SST), proxies for fronts, and day length. Day length and the spatial distribution of daily SST proved to be good proxies for "season," allowing predictions in both space and time. The density models captured seasonal distribution shifts of porpoises across international boundaries. By combining the large-scale international SCANS II survey with the more frequent, small-scale national surveys, it has been possible to provide seasonal maps that will be used to assist the EU Habitats and Marine Strategy Framework Directives in effectively assessing the conservation status of harbor porpoises. Moreover, our results can facilitate the identification of regions where human activities and disturbances are likely to impact the population and are espec

Airguns used in seismic surveys are among the most prevalent and powerful anthropogenic noise sources in marine habitats. They are designed to produce most energy below 100 Hz, but the pulses have also been reported to contain medium-to-high frequency components with the potential to affect small marine mammals, which have their best hearing sensitivity at higher frequencies. In shallow water environments, inhabited by many of such species, the impact of airgun noise may be particularly challenging to assess due to complex propagation conditions. To alleviate the current lack of knowledge on the characteristics and propagation of airgun pulses in shallow water with implications for effects on small marine mammals, we recorded pulses from a single airgun with three operating volumes (10 in3, 25 in3 and 40 in3) at six ranges (6, 120, 200, 400, 800 and 1300 m) in a uniform shallow water habitat using two calibrated Reson 4014 hydrophones and four DSG-Ocean acoustic data recorders. We show that airgun pulses in this shallow habitat propagated out to 1300 meters in a way that can be approximated by a 18log(r) geometric transmission loss model, but with a high pass filter effect from the shallow water depth. Source levels were back-calculated to 192 dB re µPa2s (sound exposure level) and 200 dB re 1 µPa dB Leq-fast (rms over 125 ms duration), and the pulses contained substantial energy up to 10 kHz, even at the furthest recording station at 1300 meters. We conclude that the risk of causing hearing damage when using single airguns in shallow waters is small for both pinnipeds and porpoises. However, there is substantial potential for significant behavioral responses out to several km from the airgun, well beyond the commonly used shut-down zone of 500 meters.

Foraging decisions and their energetic consequences are critical to capital Arctic-breeders migrating in steps, because there is only a narrow time window with optimal foraging conditions at each step. Optimal foraging theory predicts that such animals should spend more time in patches that enable them to maximise the net rate of energy and nutrient gain. The type of search strategy employed by animals is, however, expected to depend on the amount of information that is involved in the search process. In highly dynamic landscapes, animals are unlikely to have complete knowledge about the distribution of the resources, which makes them unable to forage on the patches that enable them to maximise their net energy intake. Random search may, however, be a good strategy in landscapes where patches with profitable resources are abundant. We present simulation experiments using an individual-based model (IBM) to test which foraging decision rule (FDR) best reproduces the population patterns observed in pink-footed geese during spring staging in an agricultural landscape in Mid-Norway. Our results suggested that while geese employed a random search strategy, they were also able to individually learn where the most profitable patches were located and return to the patches that resulted in highest energy intake. Such asocial learning is rarely reported for flock animals. The modelled geese did not benefit from group foraging, which contradicts the results reported by most studies on flocking birds. Geese also did not possess complete knowledge about the profitability of the available habitat. Most likely, there is no one single optimal foraging strategy for capital breeders but such strategy is site and species-specific. We discussed the potential use of the model as a valuable tool for making future risk assessments of human disturbance and changes in agricultural practices.

Polychlorinated biphenyls (PCBs) can cause endocrine disruption, cancer, immunosuppression, or reproductive failure in animals. We used an individual-based model to explore whether and how PCB-associated reproductive failure could affect the dynamics of a hypothetical polar bear (Ursus maritimus) population exposed to PCBs to the same degree as the East Greenland subpopulation. Dose–response data from experimental studies on a surrogate species, the mink (Mustela vision), were used in the absence of similar data for polar bears. Two alternative types of reproductive failure in relation to maternal sum-PCB concentrations were considered: increased abortion rate and increased cub mortality. We found that the quantitative impact of PCB-induced reproductive failure on population growth rate depended largely on the actual type of reproductive failure involved. Critical potencies of the dose–response relationship for decreasing the population growth rate were established for both modeled types of reproductive failure. Comparing the model predictions of the age-dependent trend of sum-PCBs concentrations in females with actual field measurements from East Greenland indicated that it was unlikely that PCB exposure caused a high incidence of abortions in the subpopulation. However, on the basis of this analysis, it could not be excluded that PCB exposure contributes to higher cub mortality. Our results highlight the necessity for further research on the possible influence of PCBs on polar bear reproduction regarding their physiological pathway. This includes determining the exact cause of reproductive failure, i.e., in utero exposure versus lactational exposure of offspring; the timing of offspring death; and establishing the most relevant reference metrics for the dose–response relationship.

Climate change will increasingly affect the natural habitat and diet of polar bears (Ursus maritimus). Understanding the energetic needs of polar bears is therefore important. We developed a theoretical method for estimating polar bear food consumption based on using the highly recalcitrant polychlorinated biphenyl (PCB) congener, 2,2′,4,4′,55-hexaCB (CB153) in bear adipose tissue as an indicator of food intake. By comparing the CB153 tissue concentrations in wild polar bears with estimates from a purposely designed individual-based model, we identified the possible combinations of field metabolic rates (FMR) and CB153 deposition efficiencies in East Greenland polar bears. Our simulations indicate that if 30% of the CB153 consumed by polar bear individuals were deposited into their adipose tissue, the corresponding FMR would be only two times the basal metabolic rate. In contrast, if the modelled CB153 deposition efficiency were 10%, adult polar bears would require six times more energy than that needed to cover basal metabolism. This is considerably higher than what has been assumed for polar bears in previous studies though it is similar to FMRs found in other marine mammals. An implication of this result is that even relatively small reductions in future feeding opportunities could impact the survival of East Greenland polar bears.

Agent-based models (ABMs) are widely used to predict how populations respond to changing environments. As the availability of food varies in space and time, individuals should have their own energy budgets, but there is no consensus as to how these should be modelled. Here, we use knowledge of physiological ecology to identify major issues confronting the modeller and to make recommendations about how energy budgets for use in ABMs should be constructed. Our proposal is that modelled animals forage as necessary to supply their energy needs for maintenance, growth and reproduction. If there is sufficient energy intake, an animal allocates the energy obtained in the order: maintenance, growth, reproduction, energy storage, until its energy stores reach an optimal level. If there is a shortfall, the priorities for maintenance and growth/reproduction remain the same until reserves fall to a critical threshold below which all are allocated to maintenance. Rates of ingestion and allocation depend on body mass and temperature. We make suggestions for how each of these processes should be modelled mathematically. Mortality rates vary with body mass and temperature according to known relationships, and these can be used to obtain estimates of background mortality rate. If parameter values cannot be obtained directly, then values may provisionally be obtained by parameter borrowing, pattern-oriented modelling, artificial evolution or from allometric equations. The development of ABMs incorporating individual energy budgets is essential for realistic modelling of populations affected by food availability. Such ABMs are already being used to guide conservation planning of nature reserves and shell fisheries, to assess environmental impacts of building proposals including wind farms and highways and to assess the effects on nontarget organisms of chemicals for the control of agricultural pests.

Animalsoften alternate between searching for food locally and moving over larger distances depending on the amount offood they find. This ability to switch between movement modes can have large implications on the fate of individuals andpopulations, and a mechanism that allows animals to find the optimal balance between alternative movement strategies istherefore selectively advantageous. Recent theory suggests that animals are capable of switching movement mode dependingon heterogeneities in the landscape, and that different modes may predominate at different temporal scales. Here wedevelop a conceptual model that enables animals to use either an area-concentrated food search behavior or undirectedrandom movements. The model builds on the animals’ ability to remember the profitability and location of previouslyvisited areas. In contrast to classical optimal foraging models, our model does not assume food to be distributed inlarge, well-defined patches, and our focus is on animal movement rather than on how animals choose between foragingpatches with known locations and value. After parameterizing the fine-scale movements to resemble those of the harborporpoise Phocoena phocoena we investigate whether the model is capable of producing emergent home ranges and usepattern-oriented modeling to evaluate whether it can reproduce the large-scale movement patterns observed for porpoisesin nature. Finally we investigate whether the model enables animals to forage optimally. We found that the model wasindeed able to produce either stable home ranges or movement patterns that resembled those of real porpoises. It enabledanimals to maximize their food intake when fine-tuning the memory parameters that controlled the relative contributionof area concentrated and random movements.