Albatross movement suggests sensitivity to infrasound cues at sea.

The ways in which seabirds navigate over very large spatial scales remain poorly understood. While olfactory and visual information can provide guidance over short distances, their range is often limited to 100s km, far below the navigational capacity of wide-ranging animals such as albatrosses. Infrasound is a form of low-frequency sound that propagates for 1,000s km in the atmosphere. In marine habitats, its association with storms and ocean surface waves could in effect make it a useful cue for anticipating environmental conditions that favor or hinder flight or be associated with profitable foraging patches. However, behavioral responses of wild birds to infrasound remain untested. Here, we explored whether wandering albatrosses, Diomedea exulans, respond to microbarom infrasound at sea. We used Global Positioning System tracks of 89 free-ranging albatrosses in combination with acoustic modeling to investigate whether albatrosses preferentially orientate toward areas of 'loud' microbarom infrasound on their foraging trips. We found that in addition to responding to winds encountered in situ, albatrosses moved toward source regions associated with higher sound pressure levels. These findings suggest that albatrosses may be responding to long-range infrasonic cues. As albatrosses depend on winds and waves for soaring flight, infrasonic cues may help albatrosses to identify environmental conditions that allow them to energetically optimize flight over long distances. Our results shed light on one of the great unresolved mysteries in nature, navigation in seemingly featureless ocean environments.

Boldness predicts plasticity in flight responses to winds.

Behavioural plasticity can allow populations to adjust to environmental change when genetic evolution is too slow to keep pace. However, its constraints are not well understood. Personality is known to shape individual behaviour, but its relationship to behavioural plasticity is unclear. We studied the relationship between boldness and behavioural plasticity in response to wind conditions in wandering albatrosses (Diomedea exulans). We fitted multivariate hidden Markov models to an 11-year GPS dataset collected from 294 birds to examine whether the probability of transitioning between behavioural states (rest, prey search and travel) varied in response to wind, boldness and their interaction. We found that movement decisions varied with boldness, with bolder birds showing preferences for travel, and shyer birds showing preferences for search. For females, these effects depended on wind speed. In strong winds, which are optimal for movement, females increased time spent in travel, while in weaker winds, shyer individuals showed a slight preference for search, while bolder individuals maintained preference for travel. Our findings suggest that individual variation in behavioural plasticity may limit the capacity of bolder females to adjust to variable conditions and highlight the important role of behavioural plasticity in population responses to climate change.

Graphlet correlation distance to compare small graphs.

Graph models are standard for representing mutual relationships between sets of entities. Often, graphs deal with a large number of entities with a small number of connections (e.g. social media relationships, infectious disease spread). The distances or similarities between such large graphs are known to be well established by the Graphlet Correlation Distance (GCD). This paper deals with small graphs (with potentially high densities of connections) that have been somewhat neglected in the literature but that concern important fora like sociology, ecology and fisheries, to mention some examples. First, based on numerical experiments, we study the conditions under which Erdos-Rényi, Fitness Scale-Free, Watts-Strogatz small-world and geometric graphs can be distinguished by a specific GCD measure based on 11 orbits, the GCD11. This is done with respect to the density and the order (i.e. the number of nodes) of the graphs when comparing graphs with the same and different orders. Second, we develop a randomization statistical test based on the GCD11 to compare empirical graphs to the four possible null models used in this analysis and apply it to a fishing case study where graphs represent pairwise proximity between fishing vessels. The statistical test rules out independent pairing within the fleet studied which is a standard assumption in fisheries. It also illustrates the difficulty to identify similarities between real-world small graphs and graph models.

Scaling of ear morphology across 127 bird species and its implications for hearing performance.

The dimensions of auditory structures among animals of varying body size can have implications for hearing performance. Larger animals often have a hearing range focused on lower frequencies than smaller animals, which may be explained by several anatomical mechanisms in the ear and their scaling relationships. While the effect of size on ear morphology and hearing performance has been explored in some mammals, anurans and lizards, much less is known about the scaling relationships for the single-ossicle, internally-coupled ears of birds. Using micro- and nano-CT scans of the tympanic middle and inner ears of 127 ecologically and phylogenetically diverse bird species, spanning more than 400-fold in head mass (2.3 to 950 g), we undertook phylogenetically-informed scaling analyses to test whether 12 morphological traits, of functional importance to hearing, maintain their relative proportions with increasing head mass. We then extended our analysis by regressing these morphological traits with measures of hearing sensitivity and range to better understand morphological underpinnings of hearing performance. We find that most auditory structures scale together in equal proportions, whereas columella length increases disproportionately. We also find that the size of several auditory structures is associated with increased hearing sensitivity and frequency hearing limits, while head mass did not explain these measures. Although both birds and mammals demonstrate proportional scaling between auditory structures, the consequences for hearing in each group may diverge due to unique morphological predictors of auditory performance.

Revealing the global longline fleet with satellite radar.

Because many vessels use the Automatic Identification System (AIS) to broadcast GPS positions, recent advances in satellite technology have enabled us to map global fishing activity. Understanding of human activity at sea, however, is limited because an unknown number of vessels do not broadcast AIS. Those vessels can be detected by satellite-based Synthetic Aperture Radar (SAR) imagery, but this technology has not yet been deployed at scale to estimate the size of fleets in the open ocean. Here we combine SAR and AIS for large-scale open ocean monitoring, developing methods to match vessels with AIS to vessels detected with SAR and estimate the number of non-broadcasting vessels. We reveal that, between September 2019 and January 2020, non-broadcasting vessels accounted for about 35% of the longline activity north of Madagascar and 10% of activity near French Polynesia and Kiribati's Line Islands. We further demonstrate that this method could monitor half of the global longline activity with about 70 SAR images per week, allowing us to track human activity across the oceans.

Seasonal variation and group size affect movement patterns of two pelagic dolphin species (Lagenorhynchus obscurus and Delphinus delphis).

Movement is a key factor in the survival and reproduction of most organisms with important links to bioenergetics and population dynamics. Animals use movement strategies that minimize the costs of locating resources, maximizing energy gains. Effectiveness of these strategies depends on the spatial distribution, variability and predictability of resources. The study of fine-scale movement of small cetaceans in the pelagic domain is limited, in part because of the logistical difficulties associated with tagging and tracking them. Here we describe and model the fine-scale movement patterns of two pelagic dolphin species using georeferenced movement and behavioral data obtained by tracking dolphin groups on board small vessels. Movement patterns differed by species, group sizes and seasons. Dusky dolphin groups moved shorter distances when feeding and longer distances when traveling whereas the common dolphin did the same only when they moved in large groups. In summer, both dolphins cover longer distances in a more linear path, while in winter the movement is more erratic and moving shorter distances. Both species of dolphins prey on small pelagic fishes, which are patchily distributed and show seasonal variability in school sizes and distribution. However, dusky dolphins rely on anchovy to a larger extent than common dolphins. In Nuevo Gulf, anchovy shoals are smaller and separated by shorter distances in winter and dusky dolphins´ movement pattern is consistent with this. Dusky and common dolphins are impacted by tourism and fisheries. Further modelling of movement could be inform spatial based management tools.

Ten simple rules to host an inclusive conference.

Conferences are spaces to meet and network within and across academic and technical fields, learn about new advances, and share our work. They can help define career paths and create long-lasting collaborations and opportunities. However, these opportunities are not equal for all. This article introduces 10 simple rules to host an inclusive conference based on the authors' recent experience organizing the 2021 edition of the useR! statistical computing conference, which attracted a broad range of participants from academia, industry, government, and the nonprofit sector. Coming from different backgrounds, career stages, and even continents, we embraced the challenge of organizing a high-quality virtual conference in the context of the Coronavirus Disease 2019 (COVID-19) pandemic and making it a kind, inclusive, and accessible experience for as many people as possible. The rules result from our lessons learned before, during, and after the organization of the conference. They have been written mainly for potential organizers and selection committees of conferences and contain multiple practical tips to help a variety of events become more accessible and inclusive. We see this as a starting point for conversations and efforts towards building more inclusive conferences across the world. * Translated versions of the English abstract and the list of rules are available in 10 languages in S1 Text: Arabic, French, German, Italian, Japanese, Korean, Portuguese, Spanish, Tamil, and Thai.

Recent trends in movement ecology of animals and human mobility.

Movement is fundamental to life, shaping population dynamics, biodiversity patterns, and ecosystem structure. In 2008, the movement ecology framework (MEF Nathan et al. in PNAS 105(49):19052-19059, 2008) introduced an integrative theory of organismal movement-linking internal state, motion capacity, and navigation capacity to external factors-which has been recognized as a milestone in the field. Since then, the study of movement experienced a technological boom, which provided massive quantities of tracking data of both animal and human movement globally and at ever finer spatio-temporal resolutions. In this work, we provide a quantitative assessment of the state of research within the MEF, focusing on animal movement, including humans and invertebrates, and excluding movement of plants and microorganisms. Using a text mining approach, we digitally scanned the contents of [Formula: see text] papers from 2009 to 2018 available online, identified tools and methods used, and assessed linkages between all components of the MEF. Over the past decade, the publication rate has increased considerably, along with major technological changes, such as an increased use of GPS devices and accelerometers and a majority of studies now using the R software environment for statistical computing. However, animal movement research still largely focuses on the effect of environmental factors on movement, with motion and navigation continuing to receive little attention. A search of topics based on words featured in abstracts revealed a clustering of papers among marine and terrestrial realms, as well as applications and methods across taxa. We discuss the potential for technological and methodological advances in the field to lead to more integrated and interdisciplinary research and an increased exploration of key movement processes such as navigation, as well as the evolutionary, physiological, and life-history consequences of movement.

Aquatic birds have middle ears adapted to amphibious lifestyles.

Birds exhibit wide variation in their use of aquatic environments, on a spectrum from entirely terrestrial, through amphibious, to highly aquatic. Although there are limited empirical data on hearing sensitivity of birds underwater, mounting evidence indicates that diving birds detect and respond to sound underwater, suggesting that some modifications of the ear may assist foraging or other behaviors below the surface. In air, the tympanic middle ear acts as an impedance matcher that increases sound pressure and decreases sound vibration velocity between the outside air and the inner ear. Underwater, the impedance-matching task is reversed and the ear is exposed to high hydrostatic pressures. Using micro- and nano-CT (computerized tomography) scans of bird ears in 127 species across 26 taxonomic orders, we measured a suite of morphological traits of importance to aerial and aquatic hearing to test predictions relating to impedance-matching in birds with distinct aquatic lifestyles, while accounting for allometry and phylogeny. Birds that engage in underwater pursuit and deep diving showed the greatest differences in ear structure relative to terrestrial species. In these heavily modified ears, the size of the input areas of both the tympanic membrane and the columella footplate of the middle ear were reduced. Underwater pursuit and diving birds also typically had a shorter extrastapedius, a reduced cranial air volume and connectivity and several modifications in line with reversals of low-to-high impedance-matching. The results confirm adaptations of the middle ear to aquatic lifestyles in multiple independent bird lineages, likely facilitating hearing underwater and baroprotection, while potentially constraining the sensitivity of aerial hearing.

Sex-specific effects of wind on the flight decisions of a sexually dimorphic soaring bird.

In a highly dynamic airspace, flying animals are predicted to adjust foraging behaviour to variable wind conditions to minimize movement costs. Sexual size dimorphism is widespread in wild animal populations, and for large soaring birds which rely on favourable winds for energy-efficient flight, differences in morphology, wing loading and associated flight capabilities may lead males and females to respond differently to wind. However, the interaction between wind and sex has not been comprehensively tested. We investigated, in a large sexually dimorphic seabird which predominantly uses dynamic soaring flight, whether flight decisions are modulated to variation in winds over extended foraging trips, and whether males and females differ. Using GPS loggers we tracked 385 incubation foraging trips of wandering albatrosses Diomedea exulans, for which males are c. 20% larger than females, from two major populations (Crozet and South Georgia). Hidden Markov models were used to characterize behavioural states-directed flight, area-restricted search (ARS) and resting-and model the probability of transitioning between states in response to wind speed and relative direction, and sex. Wind speed and relative direction were important predictors of state transitioning. Birds were much more likely to take off (i.e. switch from rest to flight) in stronger headwinds, and as wind speeds increased, to be in directed flight rather than ARS. Males from Crozet but not South Georgia experienced stronger winds than females, and males from both populations were more likely to take-off in windier conditions. Albatrosses appear to deploy an energy-saving strategy by modulating taking-off, their most energetically expensive behaviour, to favourable wind conditions. The behaviour of males, which have higher wing loading requiring faster speeds for gliding flight, was influenced to a greater degree by wind than females. As such, our results indicate that variation in flight performance drives sex differences in time-activity budgets and may lead the sexes to exploit regions with different wind regimes.

Navigating through the r packages for movement.

The advent of miniaturized biologging devices has provided ecologists with unprecedented opportunities to record animal movement across scales, and led to the collection of ever-increasing quantities of tracking data. In parallel, sophisticated tools have been developed to process, visualize and analyse tracking data; however, many of these tools have proliferated in isolation, making it challenging for users to select the most appropriate method for the question in hand. Indeed, within the r software alone, we listed 58 packages created to deal with tracking data or 'tracking packages'. Here, we reviewed and described each tracking package based on a workflow centred around tracking data (i.e. spatio-temporal locations (x, y, t)), broken down into three stages: pre-processing, post-processing and analysis, the latter consisting of data visualization, track description, path reconstruction, behavioural pattern identification, space use characterization, trajectory simulation and others. Supporting documentation is key to render a package accessible for users. Based on a user survey, we reviewed the quality of packages' documentation and identified 11 packages with good or excellent documentation. Links between packages were assessed through a network graph analysis. Although a large group of packages showed some degree of connectivity (either depending on functions or suggesting the use of another tracking package), one third of the packages worked in isolation, reflecting a fragmentation in the r movement-ecology programming community. Finally, we provide recommendations for users when choosing packages, and for developers to maximize the usefulness of their contribution and strengthen the links within the programming community.

Metrics for describing dyadic movement: a review.

In movement ecology, the few works that have taken collective behaviour into account are data-driven and rely on simplistic theoretical assumptions, relying in metrics that may or may not be measuring what is intended. In the present paper, we focus on pairwise joint-movement behaviour, where individuals move together during at least a segment of their path. We investigate the adequacy of twelve metrics introduced in previous works for assessing joint movement by analysing their theoretical properties and confronting them with contrasting case scenarios. Two criteria are taken into account for review of those metrics: 1) practical use, and 2) dependence on parameters and underlying assumptions. When analysing the similarities between the metrics as defined, we show how some of them can be expressed using general mathematical forms. In addition, we evaluate the ability of each metric to assess specific aspects of joint-movement behaviour: proximity (closeness in space-time) and coordination (synchrony) in direction and speed. We found that some metrics are better suited to assess proximity and others are more sensitive to coordination. To help readers choose metrics, we elaborate a graphical representation of the metrics in the coordination and proximity space based on our results, and give a few examples of proximity and coordination focus in different movement studies.

Tamaño óptimo de muestra del programa de observadores a bordo de la flota dirigida a la explotación de la anchoveta peruana (Engraulis ringens) / Optimum sample size for a program of observers on board fishing vessels targetting Peruvian anchovy (Engraulis ringens)

El monitoreo de la pesquería de anchoveta en el Perú es de suma importancia para la sostenibilidad del ecosistema de Humboldt. El Programa de observadores a bordo Bitácoras de Pesca constituye una rica plataforma de recolección de datos de las embarcaciones durante sus viajes de pesca, y donde se recopila información acerca de las capturas en cada lance, distribuciones de tallas, descartes, captura incidental, captura por unidad de esfuerzo, entre otros. Para que los indicadores obtenidos a partir de esta información tengan robustez es preciso contar con un método de solidez estadística para el cálculo del número necesario de viajes a muestrear. Este trabajo presenta un método con estas características, para calcular el número óptimo de viajes de manera independiente para cada una de las variables y a diferentes escalas de tiempo. Se muestra que, dependiendo del objetivo y de la escala temporal, la cantidad óptima de viajes a muestrear varía. A partir de estos resultados, se proporcionan recomendaciones prácticas sobre el tamaño de muestra para el Programa Bitácoras de Pesca. También se discute la aplicabilidad de esta metodología para otros recursos pelágicos.

Monitoring the anchovy fishery is of great importance for assuring the sustainability of the Humboldt ecosystem. The on-board observers program constitutes a rich platform for data collection for monitoring, as it consists of the collection of data from vessels during their fishing trips, regarding catches, size distribution, discards, catch per unit of effort, among others. To get robust indicators from these data, it is necessary to use a solid statistical procedure for computing the number of fishing trips to sample. This work presents a method with those characteristics, for computing each indicator independently and at different time scales. We show that the optimum size varies depending on the objective (indicator) and the time scale. Based on these results, practical recommendations for fixing the sample size are given. We finally discuss the aplicability of this methodology for other pelagic resources.

Generalized Pareto for Pattern-Oriented Random Walk Modelling of Organisms' Movements.

How organisms move and disperse is crucial to understand how population dynamics relates to the spatial heterogeneity of the environment. Random walk (RW) models are typical tools to describe movement patterns. Whether Lévy or alternative RW better describes forager movements is keenly debated. We get around this issue using the Generalized Pareto Distribution (GPD). GPD includes as specific cases Normal, exponential and power law distributions, which underlie Brownian, Poisson-like and Lévy walks respectively. Whereas previous studies typically confronted a limited set of candidate models, GPD lets the most likely RW model emerge from the data. We illustrate the wide applicability of the method using GPS-tracked seabird foraging movements and fishing vessel movements tracked by Vessel Monitoring System (VMS), both collected in the Peruvian pelagic ecosystem. The two parameters from the fitted GPD, a scale and a shape parameter, provide a synoptic characterization of the observed movement in terms of characteristic scale and diffusive property. They reveal and quantify the variability, among species and individuals, of the spatial strategies selected by predators foraging on a common prey field. The GPD parameters constitute relevant metrics for (1) providing a synthetic and pattern-oriented description of movement, (2) using top predators as ecosystem indicators and (3) studying the variability of spatial behaviour among species or among individuals with different personalities.

Large-Scale Examination of Spatio-Temporal Patterns of Drifting Fish Aggregating Devices (dFADs) from Tropical Tuna Fisheries of the Indian and Atlantic Oceans.

Since the 1990s, massive use of drifting Fish Aggregating Devices (dFADs) to aggregate tropical tunas has strongly modified global purse-seine fisheries. For the first time, a large data set of GPS positions from buoys deployed by French purse-seiners to monitor dFADs is analysed to provide information on spatio-temporal patterns of dFAD use in the Atlantic and Indian Oceans during 2007-2011. First, we select among four classification methods the model that best separates "at sea" from "on board" buoy positions. A random forest model had the best performance, both in terms of the rate of false "at sea" predictions and the amount of over-segmentation of "at sea" trajectories (i.e., artificial division of trajectories into multiple, shorter pieces due to misclassification). Performance is improved via post-processing removing unrealistically short "at sea" trajectories. Results derived from the selected model enable us to identify the main areas and seasons of dFAD deployment and the spatial extent of their drift. We find that dFADs drift at sea on average for 39.5 days, with time at sea being shorter and distance travelled longer in the Indian than in the Atlantic Ocean. 9.9% of all trajectories end with a beaching event, suggesting that 1,500-2,000 may be lost onshore each year, potentially impacting sensitive habitat areas, such as the coral reefs of the Maldives, the Chagos Archipelago, and the Seychelles.

Hidden Markov models: the best models for forager movements?

One major challenge in the emerging field of movement ecology is the inference of behavioural modes from movement patterns. This has been mainly addressed through Hidden Markov models (HMMs). We propose here to evaluate two sets of alternative and state-of-the-art modelling approaches. First, we consider hidden semi-Markov models (HSMMs). They may better represent the behavioural dynamics of foragers since they explicitly model the duration of the behavioural modes. Second, we consider discriminative models which state the inference of behavioural modes as a classification issue, and may take better advantage of multivariate and non linear combinations of movement pattern descriptors. For this work, we use a dataset of >200 trips from human foragers, Peruvian fishermen targeting anchovy. Their movements were recorded through a Vessel Monitoring System (∼1 record per hour), while their behavioural modes (fishing, searching and cruising) were reported by on-board observers. We compare the efficiency of hidden Markov, hidden semi-Markov, and three discriminative models (random forests, artificial neural networks and support vector machines) for inferring the fishermen behavioural modes, using a cross-validation procedure. HSMMs show the highest accuracy (80%), significantly outperforming HMMs and discriminative models. Simulations show that data with higher temporal resolution, HSMMs reach nearly 100% of accuracy. Our results demonstrate to what extent the sequential nature of movement is critical for accurately inferring behavioural modes from a trajectory and we strongly recommend the use of HSMMs for such purpose. In addition, this work opens perspectives on the use of hybrid HSMM-discriminative models, where a discriminative setting for the observation process of HSMMs could greatly improve inference performance.