Central place foragers and moving stimuli: A hidden-state model to discriminate the processes affecting movement

Bottlenose dolphin distribution in a Mediterranean area exposed to intensive trawling

The Adriatic Sea is one of the areas most exposed to trawling, worldwide. We used four years (2018-2021) and 19,887 km of survey data to investigate factors influencing daylight dolphin distribution in its north-western sector, where common bottlenose dolphins Tursiops truncatus routinely follow fishing trawlers. We validated Automatic Identification System information on the position, type and activity of three types of trawlers based on observations from boats, and incorporated this information in a GAM-GEE modelling framework, together with physiographic, biological and anthropogenic variables. Along with bottom depth, trawlers (particularly otter and midwater trawlers) appeared to be important drivers of dolphin distribution, with dolphins foraging and scavenging behind trawlers during 39.3% of total observation time in trawling days. The spatial dimension of dolphin adaptations to intensive trawling, including distribution shifts between days with and without trawling, sheds light on the magnitude of ecological change driven by the trawl fishery.

Sleeping sites provide new insight into multiple central place foraging strategies of Tibetan macaques (Macaca thibetana)

Food resources, including food types, quantity, and quality, are the key factors that determine the survival and reproduction of wild animals. However, the most basic requirement is access to food. The choice of sleeping sites plays a crucial role in efficiently acquiring food and provides a useful starting point for studying foraging strategies. We collected data on sleeping site and foraging patch uses of wild Tibetan macaques (Macaca thibetana) in Huangshan, Anhui, China, from September 2020 to August 2021. We found that Tibetan macaques used 50 different sleeping sites, mostly located on cliffs, some of which they reused. Sleeping site altitude differed significantly according to season, with higher altitudes recorded in summer and winter. Tibetan macaques did not sleep as much as expected in the peripheral regions of their home range. The sleeping sites were often distributed in proximity to foraging patches, and there was a positive correlation between the use of sleeping sites and surrounding foraging patches. The utilization of foraging patches by Tibetan macaques is inclined towards the multiple central place foraging strategy. Our results provide supportive evidence for the proximity to food resource hypothesis and indicate the important role of sleeping sites in food resource utilization in Tibetan macaques.

An integrated path for spatial capture-recapture and animal movement modeling

Ecologists and conservation biologists increasingly rely on spatial capture-recapture (SCR) and movement modeling to study animal populations. Historically, SCR has focused on population-level processes (e.g., vital rates, abundance, density, and distribution), whereas animal movement modeling has focused on the behavior of individuals (e.g., activity budgets, resource selection, migration). Even though animal movement is clearly a driver of population-level patterns and dynamics, technical and conceptual developments to date have not forged a firm link between the two fields. Instead, movement modeling has typically focused on the individual level without providing a coherent scaling from individual- to population-level processes, whereas SCR has typically focused on the population level while greatly simplifying the movement processes that give rise to the observations underlying these models. In our view, the integration of SCR and animal movement modeling has tremendous potential for allowing ecologists to scale up from individuals to populations and advancing the types of inferences that can be made at the intersection of population, movement, and landscape ecology. Properly accounting for complex animal movement processes can also potentially reduce bias in estimators of population-level parameters, thereby improving inferences that are critical for species conservation and management. This introductory article to the Special Feature reviews recent advances in SCR and animal movement modeling, establishes a common notation, highlights potential advantages of linking individual-level (Lagrangian) movements to population-level (Eulerian) processes, and outlines a general conceptual framework for the integration of movement and SCR models. We then identify important avenues for future research, including key challenges and potential pitfalls in the developments and applications that lie ahead.

Underwater visibility constrains the foraging behaviour of a diving pelagic seabird

Understanding the sensory ecology of species is vital if we are to predict how they will function in a changing environment. Visual cues are fundamentally important for many predators when detecting and capturing prey. However, many marine areas have become more turbid through processes influenced by climate change, potentially affecting the ability of marine predators to detect prey. We performed the first study that directly relates a pelagic seabird species's foraging behaviour to oceanic turbidity. We collected biologging data from 79 foraging trips and 5472 dives of a visually dependent, pursuit-diving seabird, the Manx shearwater (Puffinus puffinus). Foraging behaviour was modelled against environmental variables affecting underwater visibility, including water turbidity, cloud cover and solar angle. Shearwaters were more likely to initiate area-restricted search and foraging dives in clearer waters. Underwater visibility also strongly predicted dive rate and depth, suggesting that fine-scale prey capture was constrained by the detectability of prey underwater. Our novel use of dynamic descriptors of underwater visibility suggests that visual cues are vital for underwater foraging. Our data indicate that climate change could negatively impact seabird populations by making prey more difficult to detect, compounded by the widely reported effects of reduced prey populations.

Diving deeper into the underlying white shark behaviors at Guadalupe Island, Mexico

Fine-scale movement patterns are driven by both biotic (hunting, physiological needs) and abiotic (environmental conditions) factors. The energy balance governs all movement-related strategic decisions.Marine environments can be better understood by considering the vertical component. From 24 acoustic trackings of 10 white sharks in Guadalupe Island, this study linked, for the first time, horizontal and vertical movement data and inferred six different behavioral states along with movement states, through the use of hidden Markov models, which allowed to draw a comprehensive picture of white shark behavior.Traveling was the most frequent state of behavior for white sharks, carried out mainly at night and twilight. In contrast, area-restricted searching was the least used, occurring primarily in daylight hours.Time of day, distance to shore, total shark length, and, to a lesser extent, tide phase affected behavioral states. Chumming activity reversed, in the short term and in a nonpermanent way, the behavioral pattern to a general diel vertical pattern.

What you see is where you go: visibility influences movement decisions of a forest bird navigating a three-dimensional-structured matrix

Animal spatial behaviour is often presumed to reflect responses to visual cues. However, inference of behaviour in relation to the environment is challenged by the lack of objective methods to identify the information that effectively is available to an animal from a given location. In general, animals are assumed to have unconstrained information on the environment within a detection circle of a certain radius (the perceptual range; PR). However, visual cues are only available up to the first physical obstruction within an animal's PR, making information availability a function of an animal's location within the physical environment (the effective visual perceptual range; EVPR). By using LiDAR data and viewshed analysis, we modelled forest birds' EVPRs at each step along a movement path. We found that the EVPR was on average 0.063% that of an unconstrained PR and, by applying a step-selection analysis, that individuals are 1.55 times more likely to move to a tree within their EVPR than to an equivalent tree outside it. This demonstrates that behavioural choices can be substantially impacted by the characteristics of an individual's EVPR and highlights that inferences made from movement data may be improved by accounting for the EVPR.

Movement patterns of large juvenile loggerhead turtles in the Mediterranean Sea: Ontogenetic space use in a small ocean basin

Mechanisms that determine how, where, and when ontogenetic habitat shifts occur are mostly unknown in wild populations. Differences in size and environmental characteristics of ontogenetic habitats can lead to differences in movement patterns, behavior, habitat use, and spatial distributions across individuals of the same species. Knowledge of juvenile loggerhead turtles' dispersal, movements, and habitat use is largely unknown, especially in the Mediterranean Sea. Satellite relay data loggers were used to monitor movements, diving behavior, and water temperature of eleven large juvenile loggerhead turtles (Caretta caretta) deliberately caught in an oceanic habitat in the Mediterranean Sea. Hidden Markov models were used over 4,430 spatial locations to quantify the different activities performed by each individual: transit, low-, and high-intensity diving. Model results were then analyzed in relation to water temperature, bathymetry, and distance to the coast. The hidden Markov model differentiated between bouts of area-restricted search as low- and high-intensity diving, and transit movements. The turtles foraged in deep oceanic waters within 60 km from the coast as well as above 140 km from the coast. They used an average area of 194,802 km2, where most individuals used the deepest part of the Southern Tyrrhenian Sea with the highest seamounts, while only two switched to neritic foraging showing plasticity in foraging strategies among turtles of similar age classes. The foraging distribution of large juvenile loggerhead turtles, including some which were of the minimum size of adults, in the Tyrrhenian Sea is mainly concentrated in a relatively small oceanic area with predictable mesoscale oceanographic features, despite the proximity of suitable neritic foraging habitats. Our study highlights the importance of collecting high-resolution data about species distribution and behavior across different spatio-temporal scales and life stages for implementing conservation and dynamic ocean management actions.

Resource distribution and internal factors interact to govern movement of a freshwater snail

Movement enables mobile organisms to respond to local environmental conditions and is driven by a combination of external and internal factors operating at multiple scales. Here, we explored how resource distribution interacted with the internal state of organisms to drive patterns of movement. Specifically, we tracked snail movements on experimental landscapes where resource (algal biofilm) distribution varied from 0 to 100% coverage and quantified how that movement changed over a 24 h period. Resource distribution strongly affected snail movement. Trajectories were tortuous (i.e. Brownian-like) within resource patches but straighter (i.e. Lévy) in resource-free (bare) patches. The average snail speed was slower in resource patches, where snails spent most of their time. Different patterns of movement between resource and bare patches explained movement at larger spatial scales; movement was ballistic-like Lévy in resource-free landscapes, Lévy in landscapes with intermediate resource coverage and approximated Brownian in landscapes covered in resources. Our temporal analysis revealed that movement patterns changed predictably for snails that satiated their hunger and then performed other behaviours. These changes in movement patterns through time were similar across all treatments that contained resources. Thus, external and internal factors interacted to shape the inherently flexible movement of these snails.