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.

Rapid restructuring of the odontocete community in an ocean warming hotspot.

Cetaceans are important consumers in marine ecosystems, but few studies have quantified their climate responses. The rapid, directional warming occurring in the Northeast United States (NEUS) provides a unique opportunity to assess climate impacts on cetaceans. We used stranding data to examine changes to the distribution and relative abundance of odontocetes from 1996 to 2020 in both the NEUS and the Southeast United States (SEUS), which is not warming. We conducted simulations to determine the number of stranding events needed to detect a distributional shift for each species given the speed of the shift and the spatial variability in strandings. We compared observed shifts to climate velocity. Smaller sample sizes were needed to detect more rapid poleward shifts, particularly for species with low spatial variability. Poleward shifts were observed in all species with sufficient sample sizes, and shifts were faster than predicted by climate velocity. For species whose trailing edge of distribution occurred in the NEUS, the center of distribution approached the northern limit of the NEUS and relative abundance declined through time, suggesting shifts north out of US waters. The relative abundance of warm water species in the stranding record increased significantly in the NEUS while that of cool water species declined significantly as their distributions shifted north out of the NEUS. Changes in the odontocete community were less apparent in the SEUS, highlighting the importance of regional warming. Observed poleward shifts and changes in species composition suggest a reorganization of the odontocete community in the NEUS in response to rapid warming. We suggest that strandings provide a key dataset for understanding climate impacts on cetaceans given limitations of survey effort and modeling approaches for predicting distributions under rapidly changing conditions. Our findings portend marked changes to the distribution of highly mobile consumer species across international boundaries under continued warming.

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.

Effects of urbanization on the foraging ecology and microbiota of the generalist seabird Larus argentatus.

Larus gull species have proven adaptable to urbanization and due to their generalist feeding behaviors, they provide useful opportunities to study how urban environments impact foraging behavior and host-associated microbiota. We evaluated how urbanization influenced the foraging behavior and microbiome characteristics of breeding herring gulls (Larus argentatus) at three different colonies on the east coast of the United States. Study colonies represented high, medium and low degrees of urbanization, respectively. At all colonies, gulls frequently foraged at landfills and in other urban environments, but both the use of urban environments and gull foraging metrics differed with the degree of urbanization. Gulls at the more urban colonies used urban environments more frequently, showed higher rates of site fidelity and took shorter trips. Gulls at less urban colonies used a greater diversity of habitat types and foraged offshore. We observed high microbial diversity at all colonies, though microbial diversity was highest at the least urban colony where gulls used a wider variety of foraging habitats. This suggests that gulls may acquire a wider range of bacteria when visiting a higher variety of foraging sites. Our findings highlight the influence of urban habitats on gull movements and microbiome composition and diversity during the breeding season and represent the first application of amplicon sequence variants, an objective and repeatable method of bacterial classification, to study the microbiota of a seabird species.

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.

Predictive modeling of spinner dolphin (Stenella longirostris) resting habitat in the main Hawaiian Islands.

Predictive habitat models can provide critical information that is necessary in many conservation applications. Using Maximum Entropy modeling, we characterized habitat relationships and generated spatial predictions of spinner dolphin (Stenella longirostris) resting habitat in the main Hawaiian Islands. Spinner dolphins in Hawai'i exhibit predictable daily movements, using inshore bays as resting habitat during daylight hours and foraging in offshore waters at night. There are growing concerns regarding the effects of human activities on spinner dolphins resting in coastal areas. However, the environmental factors that define suitable resting habitat remain unclear and must be assessed and quantified in order to properly address interactions between humans and spinner dolphins. We used a series of dolphin sightings from recent surveys in the main Hawaiian Islands and a suite of environmental variables hypothesized as being important to resting habitat to model spinner dolphin resting habitat. The model performed well in predicting resting habitat and indicated that proximity to deep water foraging areas, depth, the proportion of bays with shallow depths, and rugosity were important predictors of spinner dolphin habitat. Predicted locations of suitable spinner dolphin resting habitat provided in this study indicate areas where future survey efforts should be focused and highlight potential areas of conflict with human activities. This study provides an example of a presence-only habitat model used to inform the management of a species for which patterns of habitat availability are poorly understood.