Context-dependent variability in the predicted daily energetic costs of disturbance for blue whales

Bayesian Estimation of Individual Gray Whale Space Use Reveals Differential Exposure to Stressors

This study quantifies the individual space use patterns of Pacific Coast Feeding Group gray whales (Eschrichtius robustus) from photographic capture-recapture data, collected in central Oregon, U.S.A., within a Bayesian framework. We evaluate the potential exposure of individuals to six anthropogenic stressors given their space use patterns. We used an 8-year dataset of spatially explicit encounter histories collected via photo-identification during continuous boat surveys to inform a Bayesian spatially explicit capture-recapture model and estimate space use of individual whales. Space use estimates were combined with exposure values of four static (distance from two ports, distance from an effluent discharge site, area of whale watching) and two dynamic (commercial Dungeness crab pots, recreational fishing) anthropogenic stressors or their proxies to estimate relative individual stressor exposure. The influence of age and sex on space use patterns and stressor exposure was assessed post hoc. Space use, and thereby stressor exposure, was highly variable among individuals, both within and between years. Some individuals displayed remarkable long-term and fine-spatial-scale site fidelity, not typically documented for large baleen whales. Juveniles concentrate their space use in a distinct area that is proximal to a port and center of whale watch activity. Exposure to stressors is highly variable across individuals and years given the heterogeneity of individual space use within the population and of stressor distribution, underscoring the complexity of managing wildlife populations. While population management plans need to be implemented at a population level, the recognition and incorporation of intraspecific variation can improve regulation efficacy since individual performance has relevant consequences on population health.

Intermediate Habitat Fragmentation Buffers Droughts: How Individual Energy Dynamics Mediate Mammal Community Response to Stressors

Biodiversity is threatened by land-use and climate change. Although these processes are known to influence species survival and diversity, predicting their combined effects on communities remains challenging. We here aim to disentangle the combined effects of drought-induced resource shortage and habitat fragmentation on species coexistence. To understand how both fragmentation and droughts affect individual movement and physiology, and ultimately influence population and community dynamics, we use an individual-based metabolic modelling approach to simulate a community of small mammals. Individuals forage in the landscape to ingest energy, which they then allocate to basal maintenance, digestion, locomotion, growth, reproduction, and storage. If individuals of several species are able to balance their energy intake and needs, and additionally store energy as fat reserves, they may overcome stress periods and coexist. We find that species recover best after a drought when they live in moderately fragmented landscapes compared to those with low or high fragmentation. In low fragmented landscapes, high local competition during resource shortages is problematic, while in highly fragmented landscapes, low energy balance and storage often lead to high mortality during drought. Intermediately fragmented landscapes balance these effects and show the least impact of droughts on species richness, a pattern that holds also when integrating observed drought time series from monitoring data in the model simulations. Due to the interacting negative impacts, we suggest that with ongoing global change, it is increasingly important to understand stressors simultaneously to identify measures that support species coexistence and biodiversity. Including individual energy dynamics allowed us to conflate the different global change effects through energy storage and energy allocation to different processes. Our presented community model, which integrates metabolic and behavioural reactions of individuals to different stressors and scales them to the community level, offers valuable insights with great potential to support nature conservation.

Assessing variation in faecal glucocorticoid concentrations in gray whales exposed to anthropogenic stressors

Understanding how individual animals respond to stressors behaviourally and physiologically is a critical step towards quantifying long-term population consequences and informing management efforts. Glucocorticoid (GC) metabolite accumulation in various matrices provides an integrated measure of adrenal activation in baleen whales and could thus be used to investigate physiological changes following exposure to stressors. In this study, we measured GC concentrations in faecal samples of Pacific Coast Feeding Group (PCFG) gray whales (Eschrichtius robustus) collected over seven consecutive years to assess the association between GC content and metrics of exposure to sound levels and vessel traffic at different temporal scales, while controlling for contextual variables such as sex, reproductive status, age, body condition, year, time of year and location. We develop a Bayesian Generalized Additive Modelling approach that accommodates the many complexities of these data, including non-linear variation in hormone concentrations, missing covariate values, repeated samples, sampling variability and some hormone concentrations below the limit of detection. Estimated relationships showed large variability, but emerging patterns indicate a strong context-dependency of physiological variation, depending on sex, body condition and proximity to a port. Our results highlight the need to control for baseline hormone variation related to context, which otherwise can obscure the functional relationship between faecal GCs and stressor exposure. Therefore, extensive data collection to determine sources of baseline variation in well-studied populations, such as PCFG gray whales, could shed light on cetacean stress physiology and be used to extend applicability to less-well-studied taxa. GC analyses may offer greatest utility when employed as part of a suite of markers that, in aggregate, provide a multivariate measure of physiological status, better informing estimates of individuals' health and ultimately the consequences of anthropogenic stressors on populations.

Using individual-based bioenergetic models to predict the aggregate effects of disturbance on populations: A case study with beaked whales and Navy sonar

Anthropogenic activities can lead to changes in animal behavior. Predicting population consequences of these behavioral changes requires integrating short-term individual responses into models that forecast population dynamics across multiple generations. This is especially challenging for long-lived animals, because of the different time scales involved. Beaked whales are a group of deep-diving odontocete whales that respond behaviorally when exposed to military mid-frequency active sonar (MFAS), but the effect of these nonlethal responses on beaked whale populations is unknown. Population consequences of aggregate exposure to MFAS was assessed for two beaked whale populations that are regularly present on U.S. Navy training ranges where MFAS is frequently used. Our approach integrates a wide range of data sources, including telemetry data, information on spatial variation in habitat quality, passive acoustic data on the temporal pattern of sonar use and its relationship to beaked whale foraging activity, into an individual-based model with a dynamic bioenergetic module that governs individual life history. The predicted effect of disturbance from MFAS on population abundance ranged between population extinction to a slight increase in population abundance. These effects were driven by the interaction between the temporal pattern of MFAS use, baseline movement patterns, the spatial distribution of prey, the nature of beaked whale behavioral response to MFAS and the top-down impact of whale foraging on prey abundance. Based on these findings, we provide recommendations for monitoring of marine mammal populations and highlight key uncertainties to help guide future directions for assessing population impacts of nonlethal disturbance for these and other long-lived animals.

Estimating energetic intake for marine mammal bioenergetic models

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 support effective conservation and management.

Gray whale density during seismic surveys near their Sakhalin feeding ground

Oil and gas development off northeastern Sakhalin Island, Russia, has exposed the western gray whale population on their summer-fall foraging grounds to a range of anthropogenic activities, such as pile driving, dredging, pipeline installation, and seismic surveys. In 2015, the number of seismic surveys within a feeding season surpassed the level of the number and duration of previous seismic survey activities known to have occurred close to the gray whales' feeding ground, with the potential to cause disturbance to their feeding activity. To examine the extent that gray whales were potentially avoiding areas when exposed to seismic and vessel sounds, shore-based teams monitored the abundance and distribution of gray whales from 13 stations that encompassed the known nearshore feeding area. Gray whale density was examined in relation to natural (spatial, temporal, and prey energy) and anthropogenic (cumulative sound exposure from vessel and seismic sounds) explanatory variables using Generalized Additive Models (GAM). Distance from shore, water depth, date, and northing explained a significant amount of variation in gray whale densities. Prey energy from crustaceans, specifically amphipods, isopods, and cumaceans also significantly influenced gray whale densities in the nearshore feeding area. Increasing cumulative exposure to vessel and seismic sounds resulted in both a short- and longer-term decline in gray whale density in an area. This study provides further insights about western gray whale responses to anthropogenic activity in proximity to and within the nearshore feeding area. As the frequency of seismic surveys and other non-oil and gas anthropogenic activity are expected to increase off Sakhalin Island, it is critical to continue to monitor and assess potential impacts on this endangered population of gray whales.

A sampling, exposure and receptor framework for identifying factors that modulate behavioural responses to disturbance in cetaceans

The assessment of behavioural disturbance in cetacean species (e.g. resulting from exposure to anthropogenic sources such as military sonar, seismic surveys, or pile driving) is important for effective conservation and management. Disturbance effects can be informed by Behavioural Response Studies (BRSs), involving either controlled exposure experiments (CEEs) where noise exposure conditions are presented deliberately to meet experimental objectives or in opportunistic contexts where ongoing activities are monitored in a strategic manner. In either context, animal-borne sensors or in situ observations can provide information on individual exposure and disturbance responses. The past 15 years of research have greatly expanded our understanding of behavioural responses to noise, including hundreds of experiments in nearly a dozen cetacean species. Many papers note limited sample sizes, required knowledge of baseline behaviour prior to exposure and the importance of contextual factors modulating behavioural responses, all of which in combination can lead to sampling biases, even for well-designed research programs. It is critical to understand these biases to robustly identify responses. This ensures outcomes of BRSs help inform predictions of how anthropogenic disturbance impacts individuals and populations. Our approach leverages concepts from the animal behaviour literature focused on helping to avoid sampling bias by considering what shapes an animal's response. These factors include social, experience, genetic and natural changes in responsiveness. We developed and applied a modified version of this framework to synthesise current knowledge on cetacean response in the context of effects observed across marine and terrestrial taxa. This new 'Sampling, Exposure, Receptor' framework (SERF) identifies 43 modulating factors, highlights potential biases, and assesses how these vary across selected focal species. In contrast to studies that identified variation in 'Exposure' factors as a key concern, our analysis indicated that factors relating to 'Sampling' (e.g. deploying tags on less evasive individuals, which biases selection of subjects), and 'Receptor' (e.g. health status or coping style) have the greatest potential for weakening the desired broad representativeness of BRSs. Our assessment also highlights how potential biases could be addressed with existing datasets or future developments.

Shaken, not stirred: blue whales show no acoustic response to earthquake events

Quantifying how animals respond to disturbance events bears relevance for understanding consequences to population health. We investigate whether blue whales respond acoustically to naturally occurring episodic noise by examining calling before and after earthquakes (27 040 calls, 32 earthquakes; 27 January-29 June 2016). Two vocalization types were evaluated: New Zealand blue whale song and downswept vocalizations ('D calls'). Blue whales did not alter the number of D calls, D call received level or song intensity following earthquakes (paired t-tests, p > 0.7 for all). Linear models accounting for earthquake strength and proximity revealed significant relationships between change in calling activity surrounding earthquakes and prior calling activity (D calls: R ² = 0.277, p < 0.0001; song: R ² = 0.080, p = 0.028); however, these same relationships were true for 'null' periods without earthquakes (D calls: R ² = 0.262, p < 0.0001; song: R ² = 0.149, p = 0.0002), indicating that the pattern is driven by blue whale calling context regardless of earthquake presence. Our findings that blue whales do not respond to episodic natural noise provide context for interpreting documented acoustic responses to anthropogenic noise sources, including shipping traffic and petroleum development, indicating that they potentially evolved tolerance for natural noise sources but not novel noise from anthropogenic origins.

A review of bioenergetic modelling for marine mammal populations

Bioenergetic models describe the processes through which animals acquire energy from resources in the environment and allocate it to different life history functions. They capture some of the fundamental mechanisms regulating individuals, populations and ecosystems and have thus been used in a wide variety of theoretical and applied contexts. Here, I review the development of bioenergetic models for marine mammals and their application to management and conservation. For these long-lived, wide-ranging species, bioenergetic approaches were initially used to assess the energy requirements and prey consumption of individuals and populations. Increasingly, models are developed to describe the dynamics of energy intake and allocation and predict how resulting body reserves, vital rates and population dynamics might change as external conditions vary. The building blocks required to develop such models include estimates of intake rate, maintenance costs, growth patterns, energy storage and the dynamics of gestation and lactation, as well as rules for prioritizing allocation. I describe how these components have been parameterized for marine mammals and highlight critical research gaps. Large variation exists among available analytical approaches, reflecting the large range of life histories, management needs and data availability across studies. Flexibility in modelling strategy has supported tailored applications to specific case studies but has resulted in limited generality. Despite the many empirical and theoretical uncertainties that remain, bioenergetic models can be used to predict individual and population responses to environmental change and other anthropogenic impacts, thus providing powerful tools to inform effective management and conservation.

Integrating remote sensing methods during controlled exposure experiments to quantify group responses of dolphins to navy sonar

Human noise can be harmful to sound-centric marine mammals. Significant research has focused on characterizing behavioral responses of protected cetacean species to navy mid-frequency active sonar (MFAS). Controlled exposure experiments (CEE) using animal-borne tags have proved valuable, but smaller dolphins are not amenable to tagging and groups of interacting individuals are more relevant behavioral units for these social species. To fill key data gaps on group responses of social delphinids that are exposed to navy MFAS in large numbers, we describe novel approaches for the coordinated collection and integrated analysis of multiple remotely-sensed datasets during CEEs. This involves real-time coordination of a sonar source, shore-based group tracking, aerial photogrammetry to measure fine-scale movements and passive acoustics to quantify vocal activity. Using an example CEE involving long-beaked common dolphins (Delphinus delphis bairdii), we demonstrate how resultant quantitative metrics can be used to estimate behavioral changes and noise exposure-response relationships.

Emerging themes in Population Consequences of Disturbance models

Assessing the non-lethal effects of disturbance from human activities is necessary for wildlife conservation and management. However, linking short-term responses to long-term impacts on individuals and populations is a significant hurdle for evaluating the risks of a proposed activity. The Population Consequences of Disturbance (PCoD) framework conceptually describes how disturbance can lead to changes in population dynamics, and its real-world application has led to a suite of quantitative models that can inform risk assessments. Here, we review PCoD models that forecast the possible consequences of a range of disturbance scenarios for marine mammals. In so doing, we identify common themes and highlight general principles to consider when assessing risk. We find that, when considered holistically, these models provide valuable insights into which contextual factors influence a population's degree of exposure and sensitivity to disturbance. We also discuss model assumptions and limitations, identify data gaps and suggest future research directions to enable PCoD models to better inform risk assessments and conservation and management decisions. The general principles explored can help wildlife managers and practitioners identify and prioritize the populations most vulnerable to disturbance and guide industry in planning activities that avoid or mitigate population-level effects.