Markov-modulated marked Poisson processes for modeling disease dynamics based on medical claims data.

We explore Markov-modulated marked Poisson processes (MMMPPs) as a natural framework for modeling patients' disease dynamics over time based on medical claims data. In claims data, observations do not only occur at random points in time but are also informative, that is, driven by unobserved disease levels, as poor health conditions usually lead to more frequent interactions with the health care system. Therefore, we model the observation process as a Markov-modulated Poisson process, where the rate of health care interactions is governed by a continuous-time Markov chain. Its states serve as proxies for the patients' latent disease levels and further determine the distribution of additional data collected at each observation time, the so-called marks. Overall, MMMPPs jointly model observations and their informative time points by comprising two state-dependent processes: the observation process (corresponding to the event times) and the mark process (corresponding to event-specific information), which both depend on the underlying states. The approach is illustrated using claims data from patients diagnosed with chronic obstructive pulmonary disease by modeling their drug use and the interval lengths between consecutive physician consultations. The results indicate that MMMPPs are able to detect distinct patterns of health care utilization related to disease processes and reveal interindividual differences in the state-switching dynamics.

Individuality counts: A new comprehensive approach to foraging strategies of a tropical marine predator.

Foraging strategies are of great ecological interest, as they have a strong impact on the fitness of an individual and can affect its ability to cope with a changing environment. Recent studies on foraging strategies show a higher complexity than previously thought due to intraspecific variability. To reliably identify foraging strategies and describe the different foraging niches they allow individual animals to realize, high-resolution multivariate approaches which consider individual variation are required. Here we dive into the foraging strategies of Galápagos sea lions (Zalophus wollebaeki), a tropical predator confronted with substantial annual variation in sea surface temperature. This affects prey abundance, and El Niño events, expected to become more frequent and severe with climate change, are known to have dramatic effects on sea lions. This study used high-resolution measures of depth, GPS position and acceleration collected from 39 lactating sea lion females to analyze their foraging strategies at an unprecedented level of detail using a novel combination of automated broken stick algorithm, hierarchical cluster analysis and individually fitted multivariate hidden Markov models. We found three distinct foraging strategies (pelagic, benthic, and night divers), which differed in their horizontal, vertical and temporal distribution, most likely corresponding to different prey species, and allowed us to formulate hypotheses with regard to adaptive values under different environmental scenarios. We demonstrate the advantages of our multivariate approach and inclusion of individual variation to reliably gain a deeper understanding of the adaptive value and ecological relevance of foraging strategies of marine predators in dynamic environments.

A stable foraging polymorphism buffers Galápagos sea lions against environmental change.

Understanding the ability of animals to cope with a changing environment is critical in a world affected by anthropogenic disturbance.1 Individual foraging strategies may influence the coping ability of entire populations, as these strategies can be adapted to contrasting conditions, allowing populations with foraging polymorphisms to be more resilient toward environmental change.2,3 However, environmentally dependent fitness consequences of individual foraging strategies and their effects on population dynamics have not been conclusively documented.4,5 Here, we use biologging data from endangered Galápagos sea lion females (Zalophus wollebaeki) to show that benthically foraging individuals dig after sand-dwelling prey species while pelagic foragers hunt in more open waters. These specialized foraging behaviors result in distinct and temporally stable patterns of vibrissae abrasion. Using vibrissae length as a visual marker for the benthic versus pelagic foraging strategies, we furthermore uncovered an environment-dependent fitness trade-off between benthic and pelagic foragers, suggesting that the foraging polymorphism could help to buffer the population against the negative effects of climate change. However, demographic projections suggest that this buffering effect is unlikely to be sufficient to reverse the ongoing population decline of the past four decades.6 Our study shows how crucial a deeper understanding of behavioral polymorphisms can be for predicting how populations cope within a rapidly changing world. VIDEO ABSTRACT.

Reducing vessel noise increases foraging in endangered killer whales.

Disturbance from underwater noise is one of the primary threats to the critically endangered southern resident killer whales (SRKWs). Previous studies have demonstrated that SRKWs spend less time feeding when vessels are present. In 2018, we measured the effects of a voluntary vessel slowdown action in SRKW critical habitat to assess whether ship speed (and related source level) affects foraging behaviour. Observations of SRKWs and ships were collected from land-based sites on San Juan Island, WA, USA, overlooking the Haro Strait slow-down area. Exploratory analyses found little support for a linear relationship between ship speed and SRKW behaviour, but strong support between received noise level from ships and the probability of SRKWs engaging in foraging activity. Reducing ship speed, and therefore ship noise amplitude will help decrease the probability of ship noise disrupting SRKW foraging activity and may help to increase the proportion of accessible salmon.

Movement patterns and activity levels are shaped by the neonatal environment in Antarctic fur seal pups.

Tracking studies of juveniles are rare compared to those of adults, and consequently little is known about the influence of intrinsic and extrinsic factors on activity during this critical life stage. We used hourly GPS data, collected from 66 Antarctic fur seal pups from birth until moulting, to investigate the explanatory power of multiple individual-based and environmental variables on activity levels. Pups were sampled from two nearby breeding colonies of contrasting density during two subsequent years, and a two-state hidden Markov model was used to identify modalities in their movement behaviour, specifically 'active' and 'inactive' states. We found that movement was typified by central place exploration, with active movement away from and subsequent return to a location of inactivity. The probability of such directed exploration was unaffected by several factors known to influence marine mammal movement including sex, body condition, and temperature. Compared to pups born at the high-density colony, pups at low-density were more active, increased their activity with age, and transitioned earlier into the tussock grass, which offers protection from predators and extreme weather. Our study illustrates the importance of extrinsic factors, such as colony of birth, to early-life activity patterns and highlights the adaptive potential of movement.

Classifying grey seal behaviour in relation to environmental variability and commercial fishing activity - a multivariate hidden Markov model.

Classifying movement behaviour of marine predators in relation to anthropogenic activity and environmental conditions is important to guide marine conservation. We studied the relationship between grey seal (Halichoerus grypus) behaviour and environmental variability in the southwestern Baltic Sea where seal-fishery conflicts are increasing. We used multiple environmental covariates and proximity to active fishing nets within a multivariate hidden Markov model (HMM) to quantify changes in movement behaviour of grey seals while at sea. Dive depth, dive duration, surface duration, horizontal displacement, and turning angle were used to identify travelling, resting and foraging states. The likelihood of seals foraging increased in deeper, colder, more saline waters, which are sites with increased primary productivity and possibly prey densities. Proximity to active fishing net also had a pronounced effect on state occupancy. The probability of seals foraging was highest <5 km from active fishing nets (51%) and decreased as distance to nets increased. However, seals used sites <5 km from active fishing nets only 3% of their time at sea highlighting an important temporal dimension in seal-fishery interactions. By coupling high-resolution oceanographic, fisheries, and grey seal movement data, our study provides a scientific basis for designing management strategies that satisfy ecological and socioeconomic demands on marine ecosystems.