Disentangling the biotic and abiotic drivers of emergent migratory behavior using individual-based models

Long-distance communication can enable collective migration in a dynamic seascape

Social information is predicted to enhance the quality of animals' migratory decisions in dynamic ecosystems, but the relative benefits of social information in the long-range movements of marine megafauna are unknown. In particular, whether and how migrants use nonlocal information gained through social communication at the large spatial scale of oceanic ecosystems remains unclear. Here we test hypotheses about the cues underlying timing of blue whales' breeding migration in the Northeast Pacific via individual-based models parameterized by empirical behavioral data. Comparing emergent patterns from individual-based models to individual and population-level empirical metrics of migration timing, we find that individual whales likely rely on both personal and social sources of information about forage availability in deciding when to depart from their vast and dynamic foraging habitat and initiate breeding migration. Empirical patterns of migratory phenology can only be reproduced by models in which individuals use long-distance social information about conspecifics' behavioral state, which is known to be encoded in the patterning of their widely propagating songs. Further, social communication improves pre-migration seasonal foraging performance by over 60% relative to asocial movement mechanisms. Our results suggest that long-range communication enhances the perceptual ranges of migrating whales beyond that of any individual, resulting in increased foraging performance and more collective migration timing. These findings indicate the value of nonlocal social information in an oceanic migrant and suggest the importance of long-distance acoustic communication in the collective migration of wide-ranging marine megafauna.

Combining potential and realized distribution modeling of telemetry data for a bycatch risk assessment

Establishing marine species distributions is essential for guiding management and can be estimated by identifying potential favorable habitat at a population level and incorporating individual-level information (e.g., movement constraints) to inform realized space use. In this research, we applied a combined modeling approach to tracking data of adult female and juvenile South American sea lions (Otaria flavescens; n = 9) from July to November 2011 to make habitat predictions for populations in northern Chile. We incorporated topographic and oceanographic predictors with sea lion locations and environmentally based pseudo-absences in a generalized linear model for estimating population-level distribution. For the individual approach, we used a generalized linear mixed-effects model with a negative exponential kernel variable to quantify distance-dependent movement from the colony. Spatial predictions from both approaches were combined in a bivariate color map to identify areas of agreement. We then used a GIS-based risk model to characterize bycatch risk in industrial and artisanal purse-seine fisheries based on fishing set data from scientific observers and artisanal fleet logs (2010-2015), the bivariate sea lion distribution map, and criteria ratings of interaction characteristics. Our results indicate population-level associations with productive, shallow, low slope waters, near to river-mouths, and with high eddy activity. Individual distribution was restricted to shallow slopes and cool waters. Variation between approaches may reflect intrinsic factors restricting use of otherwise favorable habitat; however, sample size was limited, and additional data are needed to establish the full range of individual-level distributions. Our bycatch risk outputs identified highest risk from industrial fisheries operating nearshore (within 5 NM) and risk was lower, overall, for the artisanal fleet. This research demonstrates the potential for integrating potential and realized distribution models within a spatial risk assessment and fills a gap in knowledge on this species' distribution, providing a basis for targeting bycatch mitigation outreach and interventions.

Avoidance, confusion or solitude? Modelling how noise pollution affects whale migration

Many baleen whales are renowned for their acoustic communication. Under pristine conditions, this communication can plausibly occur across hundreds of kilometres. Frequent vocalisations may allow a dispersed migrating group to maintain contact, and therefore benefit from improved navigation via the "wisdom of the crowd". Human activities have considerably inflated ocean noise levels. Here we develop a data-driven mathematical model to investigate how ambient noise levels may inhibit whale migration. Mathematical models allow us to simultaneously simulate collective whale migration behaviour, auditory cue detection, and noise propagation. Rising ambient noise levels are hypothesised to influence navigation through three mechanisms: (i) diminished communication space; (ii) reduced ability to hear external sound cues and; (iii) triggering noise avoidance behaviour. Comparing pristine and current soundscapes, we observe navigation impairment that ranges from mild (increased journey time) to extreme (failed navigation). Notably, the three mechanisms induce qualitatively different impacts on migration behaviour. We demonstrate the model's potential predictive power, exploring the extent to which migration may be altered under future shipping and construction scenarios.

Quantifying thermal cues that initiate mass emigrations in juvenile white sharks

While the function of migration varies among species, environmental temperature is known to be one of the most important abiotic variables that drive animal migration; however, quantifying the thresholds and timing of the cues that influence a mass emigration is difficult, often due to lack of monitoring resolution, particularly for large, highly mobile species. We used acoustic telemetry tracking and high-resolution water temperature data over a relatively large spatial scale (5.5 km²) to identify and quantify a thermal threshold for mass emigration of juvenile white sharks. Sixteen tagged sharks were observed to initiate a search for warmer water within 10-12 hours of an upwelling event where water temperatures dropped below 14 °C. Eleven sharks traveled ~ 35 km away where they experienced similar cold temperatures before returning to the aggregation site within 24 hours. Five days following the upwelling event, most sharks emigrated from the site for the season. Quantifying movement patterns across different spatial and temporal scales is necessary to understand cues and thresholds influencing animal migration, which may be greatly affected by climate anomalies and climate change, resulting in potential impacts on the dynamics of local prey species, management, and conservation policy and practice.