Impacts of marine heatwaves on top predator distributions are variable but predictable.

Marine heatwaves cause widespread environmental, biological, and socio-economic impacts, placing them at the forefront of 21st-century management challenges. However, heatwaves vary in intensity and evolution, and a paucity of information on how this variability impacts marine species limits our ability to proactively manage for these extreme events. Here, we model the effects of four recent heatwaves (2014, 2015, 2019, 2020) in the Northeastern Pacific on the distributions of 14 top predator species of ecological, cultural, and commercial importance. Predicted responses were highly variable across species and heatwaves, ranging from near total loss of habitat to a two-fold increase. Heatwaves rapidly altered political bio-geographies, with up to 10% of predicted habitat across all species shifting jurisdictions during individual heatwaves. The variability in predicted responses across species and heatwaves portends the need for novel management solutions that can rapidly respond to extreme climate events. As proof-of-concept, we developed an operational dynamic ocean management tool that predicts predator distributions and responses to extreme conditions in near real-time.

Assessing the accuracy of altitude estimates in avian biologging devices.

Advances in animal biologging technologies have greatly improved our understanding of animal movement and distribution, particularly for highly mobile species that travel across vast spatial scales. Assessing the accuracy of these devices is critical to drawing appropriate conclusions from resulting data. While understanding the vertical dimension of movements is key to assessing habitat use and behavior in aerial species, previous studies have primarily focused on assessing the accuracy of biologging devices in the horizontal plane with far less emphasis placed on the vertical plane. Here we use an Unaccompanied Aircraft System (UAS) outfitted with a laser altimeter to broadly assess the accuracy of altitude estimates of three commonly used avian biologging devices during three field trials: stationary flights, continuous horizontal movements, and continuous vertical movements. We found that the device measuring barometric pressure consistently provided the most accurate altitude estimates (mean error of 1.57m) and effectively captured finer-scale vertical movements. Conversely, devices that relied upon GPS triangulation to estimate altitude typically overestimated altitude during horizontal movements (mean error of 6.5m or 40.96m) and underestimated amplitude during vertical movements. Additional factors thought to impact device accuracy, including Horizontal- and Position- Dilution of Precision and the time intervals over which altitude estimates were assessed, did not have notable effects on results in our analyses. Reported accuracy values for different devices may be useful in future studies of aerial species' behavior relative to vertical obstacles such as wind turbines. Our results suggest that studies seeking to quantify altitude of aerial species should prioritize pressure-based measurements, which provide sufficient resolution for examining broad and some fine-scale behaviors. This work highlights the importance of considering and accounting for error in altitude measurements during avian studies relative to the scale of data needed to address particular scientific questions.

Potential impacts of floating wind turbine technology for marine species and habitats.

Offshore wind energy is expanding globally and new floating wind turbine technology now allows wind energy developments in areas previously too deep for fixed-platform turbines. Floating offshore wind has the potential to greatly expand our renewable energy portfolio, but with rapid expansion planned globally, concerns exist regarding impacts to marine species and habitats. Floating turbines currently exist in three countries but large-scale and rapid expansion is planned in over a dozen. This technology comes with unique potential ecological impacts. Here, we outline the various floating wind turbine configurations, and consider the potential impacts on marine mammals, seabirds, fishes and benthic ecosystems. We focus on the unique risks floating turbines may pose with respect to: primary and secondary entanglement of marine life in debris ensnared on mooring lines used to stabilize floating turbines or dynamic inter-array cables; behavioral modification and displacement, such as seabird attraction to perching opportunities; turbine and vessel collision; and benthic habitat degradation from turbine infrastructure, for example from scour from anchors and inter-array cables. We highlight mitigation techniques that can be applied by managers or mandated through policy, such as entanglement deterrents or the use of cable and mooring line monitoring technologies to monitor for and reduce entanglement potential, or smart siting to reduce impacts to critical habitats. We recommend turbine configurations that are likely to have the lower ecological impacts, particularly taut or semi-taut mooring configurations, and we recommend studies and technologies still needed that will allow for floating turbines to be applied with limited ecological impacts, for example entanglement monitoring and deterrent technologies. Our review underscores additional research and mitigation techniques are required for floating technology, beyond those needed for pile-driven offshore or inshore turbines, and that understanding and mitigating the unique impacts from this technology is critical to sustainability of marine ecosystems.

Hidden Markov models identify major movement modes in accelerometer and magnetometer data from four albatross species.

BACKGROUND: Inertial measurement units (IMUs) with high-resolution sensors such as accelerometers are now used extensively to study fine-scale behavior in a wide range of marine and terrestrial animals. Robust and practical methods are required for the computationally-demanding analysis of the resulting large datasets, particularly for automating classification routines that construct behavioral time series and time-activity budgets. Magnetometers are used increasingly to study behavior, but it is not clear how these sensors contribute to the accuracy of behavioral classification methods. Development of effective  classification methodology is key to understanding energetic and life-history implications of foraging and other behaviors. METHODS: We deployed accelerometers and magnetometers on four species of free-ranging albatrosses and evaluated the ability of unsupervised hidden Markov models (HMMs) to identify three major modalities in their behavior: 'flapping flight', 'soaring flight', and 'on-water'. The relative contribution of each sensor to classification accuracy was measured by comparing HMM-inferred states with expert classifications identified from stereotypic patterns observed in sensor data. RESULTS: HMMs provided a flexible and easily interpretable means of classifying behavior from sensor data. Model accuracy was high overall (92%), but varied across behavioral states (87.6, 93.1 and 91.7% for 'flapping flight', 'soaring flight' and 'on-water', respectively). Models built on accelerometer data alone were as accurate as those that also included magnetometer data; however, the latter were useful for investigating slow and periodic behaviors such as dynamic soaring at a fine scale. CONCLUSIONS: The use of IMUs in behavioral studies produces large data sets, necessitating the development of computationally-efficient methods to automate behavioral classification in order to synthesize and interpret underlying patterns. HMMs provide an accessible and robust framework for analyzing complex IMU datasets and comparing behavioral variation among taxa across habitats, time and space.

Linking stress and immunity: Immunoglobulin A as a non-invasive physiological biomarker in animal welfare studies.

As the animal welfare community strives to empirically assess how care and management practices can help maintain or even enhance welfare, the development of tools for non-invasively measuring physiological biomarkers is essential. Of the suite of physiological biomarkers, Immunoglobulin A (IgA), particularly the secretory form (Secretory IgA or SIgA), is at the forefront because of its crucial role in mucosal immunity and links to physical health, stress, and overall psychological well-being. While interpretation of changes in SIgA concentrations on short time scales is complex, long-term SIgA patterns are consistent: conditions that create chronic stress lead to suppression of SIgA. In contrast, when welfare is enhanced, SIgA is predicted to stabilize at higher concentrations. In this review, we examine how SIgA concentrations are reflective of both physiological stress and immune function. We then review the literature associating SIgA concentrations with various metrics of animal welfare and provide detailed methodological considerations for SIgA monitoring. Overall, our aim is to provide an in-depth discussion regarding the value of SIgA as physiological biomarker to studies aiming to understand the links between stress and immunity.

Foraging behavior links climate variability and reproduction in North Pacific albatrosses.

BACKGROUND: Climate-driven environmental change in the North Pacific has been well documented, with marked effects on the habitat and foraging behavior of marine predators. However, the mechanistic linkages connecting climate-driven changes in behavior to predator populations are not well understood. We evaluated the effects of climate-driven environmental variability on the reproductive success and foraging behavior of Laysan and Black-footed albatrosses breeding in the Northwest Hawaiian Islands during both brooding and incubating periods. We assessed foraging trip metrics and reproductive success using data collected from 2002-2012 and 1981-2012, respectively, relative to variability in the location of the Transition Zone Chlorophyll Front (TZCF, an important foraging region for albatrosses), sea surface temperature (SST), Multivariate ENSO Index (MEI), and the North Pacific Gyre Oscillation index (NPGO). RESULTS: Foraging behavior for both species was influenced by climatic and oceanographic factors. While brooding chicks, both species traveled farther during La Niña conditions, when NPGO was high and when the TZCF was farther north (farther from the breeding site). Models showed that reproductive success for both species showed similar trends, correlating negatively with conditions observed during La Niña events (low MEI, high SST, high NPGO, increased distance to TZCF), but models for Laysan albatrosses explained a higher proportion of the variation. Spatial correlations of Laysan albatross reproductive success and SST anomalies highlighted strong negative correlations (>95 %) between habitat use and SST. Higher trip distance and/or duration during brooding were associated with decreased reproductive success. CONCLUSIONS: Our findings suggest that during adverse conditions (La Niña conditions, high NPGO, northward displacement of the TZCF), both Laysan and Black-footed albatrosses took longer foraging trips and/or traveled farther during brooding, likely resulting in a lower reproductive success due to increased energetic costs. Our results link climate variability with both albatross behavior and reproductive success, information that is critical for predicting how albatross populations will respond to future climate change.

Shadowed by scale: subtle behavioral niche partitioning in two sympatric, tropical breeding albatross species.

BACKGROUND: To meet the minimum energetic requirements needed to support parents and their provisioned offspring, the timing of breeding in birds typically coincides with periods of high food abundance. Seasonality and synchrony of the reproductive cycle is especially important for marine species that breed in high latitudes with seasonal booms in ocean productivity. Laysan and black-footed albatrosses breeding in the northwestern Hawaiian Islands have a dual reliance on both seasonally productive waters of high latitudes and on nutrient-poor waters of low latitudes, because their foraging ranges contract during the short but critical brood-guard stage. Therefore, these species face an additional constraint of having to negotiate nutrient-poor waters during the most energetically-demanding stage of the breeding cycle. This constriction of foraging range likely results in a higher density of foraging competitors. Thus, our aim was to understand how Hawaiian albatross partition resources both between and within species in this highly constrained breeding stage while foraging in less productive waters and simultaneously experiencing increased competition. High-precision GPS dataloggers were deployed on black-footed (Phoebastria nigripes, n=20) and Laysan (Phoebastria immutabilis, n=18) albatrosses during the brood-guard stage of the breeding season in 2006 (n=8), 2009 (n=13), 2010 (n=16) and 2012 (n=1). We used GPS data and movement analyses to identify six different behavioral states in foraging albatrosses that we then used to characterize foraging trips across individuals and species. We examined whether variations in behavior were correlated with both intrinsic factors (sex, body size, body condition) and extrinsic factors (lunar phase, wind speed, year). RESULTS: Behavioral partitioning was revealed both between and within species in Hawaiian albatrosses. Both species were highly active during chick-brooding trips and foraged across day and night; however, Laysan albatrosses relied on foraging at night to a greater extent than black-footed albatrosses and exhibited different foraging patterns at night. For both species, foraging along direct flight paths and foraging on the water in a "sit-and-wait" strategy were just as prevalent as foraging in a searching flight mode, indicating flexibility in foraging strategies in Hawaiian albatross. Both species strongly increased drift forage at night when the lunar phase was the darkest, suggesting Hawaiian albatross feed on diel vertically-migrating prey to some extent. Black-footed albatrosses showed greater variation in foraging behavior between individuals which suggests a higher level of intra-specific competition. This behavioral variability in black-footed albatrosses was not correlated with sex or body size, but differences in body condition suggested varying efficiencies among foraging patterns. Behavioral variability in Laysan albatrosses was correlated with sex, such that females exhibited greater flight foraging than drift foraging, had longer trip durations and flew farther maximum distances from the breeding colony, but with no difference in body condition. CONCLUSION: Fine-scale movement data and an analysis of multiple behavioral states identified behavioral mechanisms that facilitate coexistence within a community of albatross during a critical life-history period when energetic demands are high, resources are limited, and competition for food is greatest.