Big-data approaches lead to an increased understanding of the ecology of animal movement

Freshwater megafauna shape ecosystems and facilitate restoration

Freshwater megafauna, such as sturgeons, giant catfishes, river dolphins, hippopotami, crocodylians, large turtles, and giant salamanders, have experienced severe population declines and range contractions worldwide. Although there is an increasing number of studies investigating the causes of megafauna losses in fresh waters, little attention has been paid to synthesising the impacts of megafauna on the abiotic environment and other organisms in freshwater ecosystems, and hence the consequences of losing these species. This limited understanding may impede the development of policies and actions for their conservation and restoration. In this review, we synthesise how megafauna shape ecological processes in freshwater ecosystems and discuss their potential for enhancing ecosystem restoration. Through activities such as movement, burrowing, and dam and nest building, megafauna have a profound influence on the extent of water bodies, flow dynamics, and the physical structure of shorelines and substrata, increasing habitat heterogeneity. They enhance nutrient cycling within fresh waters, and cross-ecosystem flows of material, through foraging and reproduction activities. Freshwater megafauna are highly connected to other freshwater organisms via direct consumption of species at different trophic levels, indirect trophic cascades, and through their influence on habitat structure. The literature documenting the ecological impacts of freshwater megafauna is not evenly distributed among species, regions, and types of ecological impacts, with a lack of quantitative evidence for large fish, crocodylians, and turtles in the Global South and their impacts on nutrient flows and food-web structure. In addition, population decline, range contraction, and the loss of large individuals have reduced the extent and magnitude of megafaunal impacts in freshwater ecosystems, rendering a posteriori evaluation more difficult. We propose that reinstating freshwater megafauna populations holds the potential for restoring key ecological processes such as disturbances, trophic cascades, and species dispersal, which will, in turn, promote overall biodiversity and enhance nature's contributions to people. Challenges for restoration actions include the shifting baseline syndrome, potential human-megafauna competition for habitats and resources, damage to property, and risk to human life. The current lack of historical baselines for natural distributions and population sizes of freshwater megafauna, their life history, trophic interactions with other freshwater species, and interactions with humans necessitates further investigation. Addressing these knowledge gaps will improve our understanding of the ecological roles of freshwater megafauna and support their full potential for facilitating the development of effective conservation and restoration strategies to achieve the coexistence of humans and megafauna.

ExMove: An open-source toolkit for processing and exploring animal-tracking data in R

Ongoing technological advances have led to a rapid increase in the number, type and scope of animal-tracking studies. In response, many software tools have been developed to analyse animal movement data. These tools generally focus on movement modelling, but the steps required to clean raw data files from different tracking devices have been largely ignored. Such pre-processing steps are often time-consuming and involve a steep learning curve but are crucial for the creation of high-quality, standardised and shareable data. Moreover, decisions made at this early stage can substantially influence subsequent analyses, and in the current age of reproducibility crisis, the transparency of this process is vital. Here we present an open-access, reproducible toolkit written in the programming language R for processing raw data files into a single cleaned data set for analyses and upload to online tracking databases (found here: https://github.com/ExMove/ExMove). The toolkit comprises well-documented and flexible code to facilitate data processing and user understanding, both of which can increase user confidence and improve the uptake of sharing open and reproducible code. Additionally, we provide an overview website (found here: https://exmove.github.io/) and a Shiny app to help users visualise tracking data and assist with parameter determination during data cleaning. The toolkit is generalisable to different data formats and device types, uses modern 'tidy coding' practices, and relies on a few well-maintained packages. Among these, we perform spatial manipulations using the package sf. Overall, by collating all required steps from data collection to archiving on open access databases into a single, robust pipeline, our toolkit provides a valuable resource for anyone conducting animal movement analyses and represents an important step towards increased standardisation and reproducibility in animal movement ecology.

Temperature and body size affect movement of juvenile Atlantic cod (Gadus morhua) and saithe (Pollachius virens) at nearshore nurseries

Seasonal migrations of marine fish between shallow summer feeding habitats and deep overwintering grounds are driven by fluctuations in the biotic and abiotic environment as well as by changes in the internal state. Ontogenetic shifts in physiology and metabolism affect the response to environmental drivers and may lead to changes in migration timing and propensity. In this study, we investigated the effect of temperature and body size on migration timing and depth distribution in acoustically tagged Atlantic cod, Gadus morhua, and saithe, Pollachius virens, during the period of seasonal migration from shallow summer habitats. The results from our study revealed a wide range of horizontal and vertical distribution of age 1 and 2 G. morhua within the fjord. Larger G. morhua inhabited deeper, cooler waters than smaller juveniles, likely reflecting size-dependent thermal preferences and predation pressure. Conversely, juvenile P. virens occupied primarily shallow waters close to land. The variation in depth distribution of G. morhua was mainly explained by body size and not, against our predictions, by water temperature. Conversely, the dispersal from the in-fjord habitats occurred when water temperatures were high, suggesting that seasonal temperature fluctuations can trigger the migration timing of P. virens and larger G. morhua from summer habitats. Partial migration of small juvenile G. morhua from in-fjord foraging grounds, likely influenced by individual body condition, suggested seasonal migration as a flexible strategy that individuals may use to reduce predation and energetic expenditure. Predation mortality rates of tagged juveniles were higher than previously suggested and are the first robust predation mortality rates for juvenile G. morhua and P. virens estimated based on acoustic transmitters with acidity sensors. The results have relevance for climate-informed marine spatial planning as under the scenario of increasing ocean temperatures, increasing summer temperatures may reduce the juveniles' resource utilization in the shallow summer nurseries, resulting in lower growth rates, increased predation pressure, and lower chances of juvenile winter survival.

Resource manipulation reveals interactive phenotype-dependent foraging in free-ranging lizards

Recent evidence suggests that individuals differ in foraging tactics and this variation is often linked to an individual's behavioural type (BT). Yet, while foraging typically comprises a series of search and handling steps, empirical investigations have rarely considered BT-dependent effects across multiple stages of the foraging process, particularly in natural settings. In our long-term sleepy lizard (Tiliqua rugosa) study system, individuals exhibit behavioural consistency in boldness (measured as an individual's willingness to approach a novel food item in the presence of a threat) and aggressiveness (measured as an individual's response to an 'attack' by a conspecific dummy). These BTs are only weakly correlated and have previously been shown to have interactive effects on lizard space use and movement, suggesting that they could also affect lizard foraging performance, particularly in their search behaviour for food. To investigate how lizards' BTs affect their foraging process in the wild, we supplemented food in 123 patches across a 120-ha study site with three food abundance treatments (high, low and no-food controls). Patches were replenished twice a week over the species' entire spring activity season and feeding behaviours were quantified with camera traps at these patches. We tracked lizards using GPS to determine their home range (HR) size and repeatedly assayed their aggressiveness and boldness in designated assays. We hypothesised that bolder lizards would be more efficient foragers while aggressive ones would be less attentive to the quality of foraging patches. We found an interactive BT effect on overall foraging performance. Individuals that were both bold and aggressive ate the highest number of food items from the foraging array. Further dissection of the foraging process showed that aggressive lizards in general ate the fewest food items in part because they visited foraging patches less regularly, and because they discriminated less between high and low-quality patches when revisiting them. Bolder lizards, in contrast, ate more tomatoes because they visited foraging patches more regularly, and ate a higher proportion of the available tomatoes at patches during visits. Our study demonstrates that BTs can interact to affect different search and handling components of the foraging process, leading to within-population variation in foraging success. Given that individual differences in foraging and movement will influence social and ecological interactions, our results highlight the potential role of BT's in shaping individual fitness strategies and population dynamics.

How to treat mixed behavior segments in supervised machine learning of behavioural modes from inertial measurement data

The application of supervised machine learning methods to identify behavioural modes from inertial measurements of bio-loggers has become a standard tool in behavioural ecology. Several design choices can affect the accuracy of identifying the behavioural modes. One such choice is the inclusion or exclusion of segments consisting of more than a single behaviour (mixed segments) in the machine learning model training data. Currently, the common practice is to ignore such segments during model training. In this paper we tested the hypothesis that including mixed segments in model training will improve accuracy, as the model would perform better in identifying them in the test data. We test this hypothesis using a series of data simulations on four datasets of accelerometer data coupled with behaviour observations, obtained from four study species (Damaraland mole-rats, meerkats, olive baboons, polar bears). Results show that when a substantial proportion of the test data are mixed behaviour segments (above ~ 10%), including mixed segments in machine learning model training improves the accuracy of classification. These results were consistent across the four study species, and robust to changes in segment length, sample size, and degree of mixture within the mixed segments. However, we also find that in some cases (particularly in baboons) models trained with mixed segments show reduced accuracy in classifying test data containing only single behaviour (pure) segments, compared to models trained without mixed segments. Based on these results, we recommend that when the classification model is expected to deal with a substantial proportion of mixed behaviour segments (> 10%), it is beneficial to include them in model training, otherwise, it is unnecessary but also not harmful. The exception is when there is a basis to assume that the training data contains a higher rate of mixed segments than the actual (unobserved) data to be classified-such a situation may occur particularly when training data are collected in captivity and used to classify data from the wild. In this case, excess inclusion of mixed segments in training data should probably be avoided.

A century of statistical Ecology

As data and computing power have surged in recent decades, statistical modeling has become an important tool for understanding ecological patterns and processes. Statistical modeling in ecology faces two major challenges. First, ecological data may not conform to traditional methods, and second, professional ecologists often do not receive extensive statistical training. In response to these challenges, the journal Ecology has published many innovative statistical ecology papers that introduced novel modeling methods and provided accessible guides to statistical best practices. In this paper, we reflect on Ecology's history and its role in the emergence of the subdiscipline of statistical ecology, which we define as the study of ecological systems using mathematical equations, probability, and empirical data. We showcase 36 influential statistical ecology papers that have been published in Ecology over the last century and, in so doing, comment on the evolution of the field. As data and computing power continue to increase, we anticipate continued growth in statistical ecology to tackle complex analyses and an expanding role for Ecology to publish innovative and influential papers, advancing the discipline and guiding practicing ecologists.

African dryland antelope trade-off behaviours in response to heat extremes

Climate change is predicted to narrow the prescriptive zone of dryland species, potentially leading to behavioural modifications with fitness consequences. This study explores the behavioural responses of three widespread African antelope species-springbok, kudu and eland-to extreme heat in a dryland savanna. We classified the behaviour of 29 individuals during the hot, dry season on the basis of accelerometer data using supervised machine learning and analysed the impact of afternoon heat on behaviour-specific time allocation and overall dynamic body acceleration (ODBA), a proxy for energy expenditure, along with compensatory changes over the 24-hour cycle. Extreme afternoon heat reduced feeding time in all three antelope species, increased ruminating and resting time, while only minimally affecting walking time. With rising heat, all three species reduced ODBA on feeding, while eland reduced and kudu increased ODBA on walking. Diel responses in behaviour differed between species, but were generally characterised by daytime reductions in feeding and increases in ruminating or resting on hot days compared to cool days. While antelope compensated for heat-driven behavioural change over the 24-hour cycle in some cases, significant differences persisted in others, including reduced feeding and increased rumination and resting. The impact of heat on antelope behaviour reveals trade-offs between feeding and thermoregulation, as well as between feeding and rumination, the latter suggesting a strategy to enhance nutrient uptake through increased digestive efficiency, while the walking response suggests narrow constraints between cost and necessity. Our findings suggest that heat influences both behaviour-specific time allocation and energy expenditure. Altered diel behaviour patterns and incomplete compensation over the 24-hour cycle point to fitness consequences. The need to prioritise thermoregulation over feeding is likely to narrow the prescriptive zone of these dryland antelope.

Biology's transformation: from observation through experiment to computation

Summary

We explore the nuanced temporal and epistemological distinctions among natural sciences, particularly the contrasting treatment of time and the interplay between theory and experimentation. Physics, an exemplar of mature science, relies on theoretical models for predictability and simulations. In contrast, biology, traditionally experimental, is witnessing a computational surge, with data analytics and simulations reshaping its research paradigms. Despite these strides, a unified theoretical framework in biology remains elusive. We propose that contemporary global challenges might usher in a renewed emphasis, presenting an opportunity for the establishment of a novel theoretical underpinning for the life sciences.

Availability and implementation

https://github.com/ouzounis/CLS-emerges Data in Json format, Images in PNG format.

Methods for implementing integrated step-selection functions with incomplete data

Integrated step-selection analyses (iSSAs) are versatile and powerful frameworks for studying habitat and movement preferences of tracked animals. iSSAs utilize integrated step-selection functions (iSSFs) to model movements in discrete time, and thus, require animal location data that are regularly spaced in time. However, many real-world datasets are incomplete due to tracking devices failing to locate an individual at one or more scheduled times, leading to slight irregularities in the duration between consecutive animal locations. To address this issue, researchers typically only consider bursts of regular data (i.e., sequences of locations that are equally spaced in time), thereby reducing the number of observations used to model movement and habitat selection. We reassess this practice and explore four alternative approaches that account for temporal irregularity resulting from missing data. Using a simulation study, we compare these alternatives to a baseline approach where temporal irregularity is ignored and demonstrate the potential improvements in model performance that can be gained by leveraging these additional data. We also showcase these benefits using a case study on a spotted hyena (Crocuta crocuta).

Effects of tag mass on the physiology and behaviour of common noctule bats

BACKGROUND

External tags, such as transmitters and loggers, are often used to study bat movements. However, physiological and behavioural effects on bats carrying tags have rarely been investigated, and recommendations on the maximum acceptable tag mass are rather based on rules of thumb than on rigorous scientific assessment.

METHODS

We conducted a comprehensive three-step assessment of the potential physiological and behavioural effects of tagging bats, using common noctules Nyctalus noctula as a model. First, we examined seasonal changes in body mass. Second, we predicted and then measured potential changes in flight metabolic rate in a wind tunnel. Third, we conducted a meta-analysis of published data to assess effects of different tag masses on the weight and behaviour of bats.

RESULTS

Individual body mass of common noctules varied seasonally by 7.0 ± 2.6 g (range: 0.5-11.5 g). Aerodynamic theory predicted a 26% increase in flight metabolic rate for a common noctule equipped with a 3.8 g tag, equating to 14% of body mass. In a wind tunnel experiment, we could not confirm the predicted increase for tagged bats. Our meta-analysis revealed a weak correlation between tag mass and emergence time and flight duration in wild bats. Interestingly, relative tag mass (3-19% of bat body mass) was not related to body mass loss, but bats lost more body mass the longer tags were attached. Notably, relatively heavy bats lost more mass than conspecifics with a more average body mass index.

CONCLUSION

Because heavy tags (> 3 g) were generally used for shorter periods of time than lighter tags (~ 1 g), the long-term effects of heavy tags on bats cannot be assessed at this time. Furthermore, the effects of disturbance and resource distribution in the landscape cannot be separated from those of tagging. We recommend that tags weighing 5-10% of a bat's mass should only be applied for a few days. For longer studies, tags weighing less than 5% of a bat's body mass should be used. To avoid adverse effects on bats, researchers should target individuals with average, rather than peak, body mass indices.

Visual social information use in collective foraging

Collective dynamics emerge from individual-level decisions, yet we still poorly understand the link between individual-level decision-making processes and collective outcomes in realistic physical systems. Using collective foraging to study the key trade-off between personal and social information use, we present a mechanistic, spatially-explicit agent-based model that combines individual-level evidence accumulation of personal and (visual) social cues with particle-based movement. Under idealized conditions without physical constraints, our mechanistic framework reproduces findings from established probabilistic models, but explains how individual-level decision processes generate collective outcomes in a bottom-up way. In clustered environments, groups performed best if agents reacted strongly to social information, while in uniform environments, individualistic search was most beneficial. Incorporating different real-world physical and perceptual constraints profoundly shaped collective performance, and could even buffer maladaptive herding by facilitating self-organized exploration. Our study uncovers the mechanisms linking individual cognition to collective outcomes in human and animal foraging and paves the way for decentralized robotic applications.

Leakage of plastics and other debris from landfills to a highly protected lake by wintering gulls

GENERAL CONTEXT

Gulls ingest plastic and other litter while foraging in open landfills, because organic matter is mixed with other debris. Therefore, gulls are potential biovectors of plastic pollution into natural habitats, especially when they concentrate in wetlands for roosting.

NOVELTY

We quantified, for the first time, the flow of plastic and other anthropogenic debris from open landfills to a natural lake via the movement of gulls. We focused on Fuente de Piedra, an inland closed-basin lake in Spain that is internationally important for biodiversity.

METHODOLOGY

In 2022, we sampled gull pellets regurgitated in the lake by lesser black-backed gulls Larus fuscus that feed on landfills, as well as their faeces, then characterized and quantified debris particles of ≥0.5 mm. By combining GPS and census data from 2010 to 2022, together with plastic quantification based on FTIR-ATR analysis, we estimated the average annual deposition of plastic and other debris by the wintering gull population into the lake.

MAIN RESULTS

86 % of pellets contained plastics, and 94 % contained other debris such as glass and textiles. Polyethylene (54 %), polypropylene (11.5 %) and polystyrene (11.5 %) were the main plastic polymers. An estimated annual mean of 400 kg of plastics were moved by gulls into the lake. Only 1 % of plastic mass was imported in faeces.

DISCUSSION

Incorporating the biovectoring role of birds can provide a more holistic view of the plastic cycle and waste management. Biovectoring is predictable in sites worldwide where gulls and other waterbirds feed in landfills and roost in wetlands. We discuss bird deterrence and other ways of mitigating debris leakage into aquatic ecosystems.

ORTEGA v1.0: an open-source Python package for context-aware interaction analysis using movement data

BACKGROUND

Interaction analysis via movement in space and time contributes to understanding social relationships among individuals and their dynamics in ecological systems. While there is an exciting growth in research in computational methods for interaction analysis using movement data, there remain challenges regarding reproducibility and replicability of the existing approaches. The current movement interaction analysis tools are often less accessible or tested for broader use in ecological research.

RESULTS

To address these challenges, this paper presents ORTEGA, an Object-oRiented TimE-Geographic Analytical tool, as an open-source Python package for analyzing potential interactions between pairs of moving entities based on the observation of their movement. ORTEGA is developed based on one of the newly emerged time-geographic approaches for quantifying space-time interaction patterns among animals. A case study is presented to demonstrate and evaluate the functionalities of ORTEGA in tracing dynamic interaction patterns in animal movement data. Besides making the analytical code and data freely available to the community, the developed package also offers an extension of the existing theoretical development of ORTEGA for incorporating a context-aware ability to inform interaction analysis.

CONCLUSIONS

ORTEGA contributes two significant capabilities: (1) the functions to identify potential interactions (e.g., encounters, concurrent interactions, delayed interactions) from movement data of two or more entities using a time-geographic-based approach; and (2) the capacity to compute attributes of potential interaction events including start time, end time, interaction duration, and difference in movement parameters such as speed and moving direction, and also contextualize the identified potential interaction events.

Spatial-temporal shifting patterns and in situ conservation of spotted seal (Phoca largha) populations in the Yellow Sea ecoregion

Understanding the habitat shifting pattern is a prerequisite for implementing in situ conservation of migratory species. Spotted seals (Phoca largha) inhabiting the Yellow Sea ecoregion (YSE) comprise a small population with independent genes and represent a charismatic flagship species in this region. However, this population has declined by 80% since the 1940s, and increased support from the countries around the YSE is urgently needed to address the potential local extinction risk. A time-series niche model and life-history weighted systematic conservation planning were designed on the basis of a satellite beacon tracking survey (2010-2020) of the YSE population. The results showed clustering and spreading shifting patterns during the breeding and migratory seasons, respectively. The closed-loop migration route formed in the YSE indicated that this population might be geographically isolated from populations in other breeding areas around the world. The conservation priority area (CPA), with an area of 19 632 km2 (3.58% of the total YSE area), was the most effective response to the potential in situ risk. However, nearly 80% of the CPA was exposed outside the existing marine protected areas (MPAs). Future establishment of MPAs in China should strategically consider the conservation gap identified herein, and it is recommended for Korea's closed fishing season to be spatially set in the western Korean Peninsula from May to August. This study also exemplified that the lack of temporal information would lead to the dislocation of niche modeling for migratory species represented by spotted seals. Attention should be paid to protecting small and migratory populations in marine biodiversity conservation planning.

Foray movements are common and vary with natal habitat for a highly mobile bird

Understanding dispersal is central to interpreting the effects of climate change, habitat loss and habitat fragmentation, and species invasions. Prior to dispersal, animals may gather information about the surrounding landscape via forays, or systematic, short-duration looping movements away from and back to the original location. Despite theory emphasizing that forays can be beneficial for dispersing organisms and that such behaviors are predicted to be common, relatively little is known about forays in wild populations. Theory predicts that individuals that use forays may delay dispersal and such behaviors should increase survival, yet empirical tests of these predictions remain scarce. We tested these predictions in a natural system using the critically endangered snail kite (Rostrhaumus sociabilis), a wetland-dependent raptor. We GPS tracked 104 snail kites from fledging through emigration from the natal site across their breeding range to understand the demographic consequences of movement. We found that forays were common (82.7% of individuals tracked), and natal habitat played an important role in the initiation, execution, and outcome of foray behavior. The effect of foraying on survival was indirect, where forayers emigrated later than non-forayers, and individuals that emigrated later had the highest survival. Poor hydrological conditions in the natal environment were especially important for eliciting forays. Finally, females responded more strongly to natal hydrology than males, making more forays and significantly longer, more distant trips. These results emphasize the fundamental role of natal habitat for determining behavioral patterns, strengthen links between individual movement decisions and their demographic consequences, and provide an important behavioral focal point for interpreting movement tracks that would not otherwise be captured by conventional movement models.

Heterogeneous dispersal networks to improve biodiversity science

Dispersal has a key role in shaping spatial patterns of biodiversity, yet its spatial heterogeneity is often overlooked in biodiversity analyses and management strategies. Properly parameterised heterogeneous dispersal networks capture the complex interplay between landscape structure and species-specific dispersal capacities. However, this heterogeneity is recurrently neglected when studying the processes underlying biodiversity variation. To address this gap, we introduce a conceptual framework detailing the fundamental processes driving dispersal heterogeneity and its effects on biodiversity dynamics. We propose methods to parameterise heterogeneous dispersal networks, facilitating their integration into commonly used quantitative frameworks for biodiversity analyses. By considering the architecture of heterogeneous dispersal networks, we demonstrate their critical role in guiding biodiversity management strategies.

Experimental evidence that competition strength scales with ecological similarity: a case study using Anolis lizards

Interspecific competition is widely considered a powerful process underlying species coexistence and ecological community structure. Although coexistence theory predicts stronger competition between more ecologically similar species, empirical support has largely relied on inferring competition from patterns of species co-occurrence. Coexistence theory also posits that species can only coexist when individuals compete more with conspecifics than with other species, however, few field studies-particularly in reptiles-have simultaneously estimated the strength of both intra- and interspecific competition among co-occurring species. Using an array of 12 experimental plots, we manipulated species presence and population size by plot of three native Anolis lizard species to empirically estimate the strength of competition on one anole species driven by two other species of varying ecological similarity. We observed that the strength of competition-as determined by relative growth rates and gravidity-was highly predictable and correlated to ecological similarity. Interspecific competition was strongest among species of highest ecological similarity, and intraspecific competition-induced by the addition or removal of conspecifics-was consistently the most intense. By employing direct experimental manipulations, our study provides an empirical investigation of the strength of competition as it relates to ecological similarity.

Environmental factors influencing red knot (Calidris canutus islandica) departure times of relocation flights within the non-breeding period

Deciding when to depart on long-distance, sometimes global, movements can be especially important for flying species. Adverse weather conditions can affect energetic flight costs and navigational ability. While departure timings and conditions have been well-studied for migratory flights to and from the breeding range, few studies have focussed on flights within the non-breeding season. Yet in some cases, overwintering ranges can be large enough that ecological barriers, and a lack of resting sites en route, may resist movement, especially in unfavorable environmental conditions. Understanding the conditions that will enable or prohibit flights within an overwintering range is particularly relevant in light of climate change, whereby increases in extreme weather events may reduce the connectivity of sites. We tracked 495 (n = 251 in 2019; n = 244 in 2020) overwintering red knots (Calidris canutus islandica) in the Dutch Wadden Sea and investigated how many departed towards the UK (on westward relocation flights), which requires flying over the North Sea. For those that departed, we used a resource selection model to determine the effect of environmental conditions on the timing of relocation flights. Specifically, we investigated the effects of wind, rain, atmospheric pressure, cloud cover, and migratory timing relative to sunset and tidal cycle, which have all been shown to be crucial to migratory departure conditions. Approximately 37% (2019) and 36% (2020) of tagged red knots departed on westward relocation flights, indicating differences between individuals' space use within the overwintering range. Red knots selected for departures between 1 and 2.5 h after sunset, approximately 4 h before high tide, with tailwinds and little cloud cover. However, rainfall and changes in atmospheric pressure appear unimportant. Our study reveals environmental conditions that are important for relocation flights across an ecological barrier, indicating potential consequences of climate change on connectivity.

Herbivorous fish feeding dynamics and energy expenditure on a coral reef: Insights from stereo-video and AI-driven 3D tracking

Unveiling the intricate relationships between animal movement ecology, feeding behavior, and internal energy budgeting is crucial for a comprehensive understanding of ecosystem functioning, especially on coral reefs under significant anthropogenic stress. Here, herbivorous fishes play a vital role as mediators between algae growth and coral recruitment. Our research examines the feeding preferences, bite rates, inter-bite distances, and foraging energy expenditure of the Brown surgeonfish (Acanthurus nigrofuscus) and the Yellowtail tang (Zebrasoma xanthurum) within the fish community on a Red Sea coral reef. To this end, we used advanced methods such as remote underwater stereo-video, AI-driven object recognition, species classification, and 3D tracking. Despite their comparatively low biomass, the two surgeonfish species significantly influence grazing pressure on the studied coral reef. A. nigrofuscus exhibits specialized feeding preferences and Z. xanthurum a more generalist approach, highlighting niche differentiation and their importance in maintaining reef ecosystem balance. Despite these differences in their foraging strategies, on a population level, both species achieve a similar level of energy efficiency. This study highlights the transformative potential of cutting-edge technologies in revealing the functional feeding traits and energy utilization of keystone species. It facilitates the detailed mapping of energy seascapes, guiding targeted conservation efforts to enhance ecosystem health and biodiversity.

Deep learning-based efficient drone-borne sensing of cyanobacterial blooms using a clique-based feature extraction approach

Recent advances in remote sensing techniques provide a new horizon for monitoring the spatiotemporal variations of harmful algal blooms (HABs) using hyperspectral data in inland water. In this study, a hierarchical concatenated variational autoencoder (HCVAE) is proposed as an efficient and accurate deep learning (DL) based bio-optical model. To demonstrate its usefulness in retrieving algal pigments, the HCVAE is applied to bloom-prone regions in Daecheong Lake, South Korea. By abstracting the similarity between highly related features using layer-wise clique-based latent-feature extraction, HCVAE reduces the computational loads in deriving outputs while preventing performance degradation. Graph-based clique-detection uses information theory-based criteria to group the related reflectance spectra. Consequently, six latent features were extracted from 79 spectral bands to consist of a multilevel hierarchy of HCVAE that can simultaneously estimate concentrations of chlorophyll-a (Chl-a) and phycocyanin (PC). Despite the parsimonious model architecture, the Chl-a and PC concentrations estimated by HCVAE closely agree with the measured concentrations, with test R2 values of 0.76 and 0.82, respectively. In addition, spatial distribution maps of algal pigments obtained from HCVAE using drone-borne reflectance successfully capture the blooming spots. Based on its multilevel hierarchical architecture, HCVAE can provide the importance of latent features along with their individual wavelengths using Shapley additive explanations. The most important latent features covered the spectral regions associated with both Chl-a and PC. The lightweight neural network DNNsel, which uses only the spectral bands of highest importance in latent-feature extraction, performed comparably to HCVAE. The study results demonstrate the utility of the multilevel hierarchical architecture as a comprehensive assessment model for near-real-time drone-borne sensing of HABs. Moreover, HCVAE is applicable to a wide range of environmental big data, as it can handle numerous sets of features.

Capturing wild animal welfare: a physiological perspective

Affective states, such as emotions, are presumably widespread across the animal kingdom because of the adaptive advantages they are supposed to confer. However, the study of the affective states of animals has thus far been largely restricted to enhancing the welfare of animals managed by humans in non-natural contexts. Given the diversity of wild animals and the variable conditions they can experience, extending studies on animal affective states to the natural conditions that most animals experience will allow us to broaden and deepen our general understanding of animal welfare. Yet, this same diversity makes examining animal welfare in the wild highly challenging. There is therefore a need for unifying theoretical frameworks and methodological approaches that can guide researchers keen to engage in this promising research area. The aim of this article is to help advance this important research area by highlighting the central relationship between physiology and animal welfare and rectify its apparent oversight, as revealed by the current scientific literature on wild animals. Moreover, this article emphasises the advantages of including physiological markers to assess animal welfare in the wild (e.g. objectivity, comparability, condition range, temporality), as well as their concomitant limitations (e.g. only access to peripheral physiological markers with complex relationships with affective states). Best-practice recommendations (e.g. replication and multifactorial approaches) are also provided to allow physiological markers to be used most effectively and appropriately when assessing the welfare of animals in their natural habitat. This review seeks to provide the foundation for a new and distinct research area with a vast theoretical and applied potential: wild animal welfare physiology.

Edge computing in wildlife behavior and ecology

Modern sensor technologies increasingly enrich studies in wildlife behavior and ecology. However, constraints on weight, connectivity, energy and memory availability limit their implementation. With the advent of edge computing, there is increasing potential to mitigate these constraints, and drive major advancements in wildlife studies.

Finding navigation cues near fishways

Many fish species depend on migration for various parts of their life cycle. Well-known examples include diadromous fish such as salmon and eels that need both fresh water and salt water to complete their life cycle. Migration also occurs within species that depend only on fresh water. In recent decades, anthropogenic pressures on freshwater systems have increased greatly, and have resulted, among other effects, in drastic habitat fragmentation. Fishways have been developed to mitigate the resulting habitat fragmentation, but these are not always effective. To improve fishway efficiency, the variety of navigation cues used by fish must be better understood: fish use a multitude of sensory inputs ranging from flow variables to olfactory cues. The reaction of a fish is highly dependent on the intensity of the cue, the fish species involved, and individual traits. Recently developed monitoring technologies allow us to gain insights into different combinations of environmental and physiological conditions. By combining fish behavioural models with environmental models, interactions among these components can be investigated. Several methods can be used to analyse fish migration, with state-space models, hidden Markov models, and individual-based models potentially being the most relevant since they can use individual data and can tie them to explicit spatial locations within the considered system. The aim of this review is to analyse the navigational cues used by fish and the models that can be applied to gather knowledge on these processes. Such knowledge could greatly improve the design and operation of fishways for a wider range of fish species and conditions.

Advances in biologging can identify nuanced energetic costs and gains in predators

Foraging is a key driver of animal movement patterns, with specific challenges for predators which must search for mobile prey. These patterns are increasingly impacted by global changes, principally in land use and climate. Understanding the degree of flexibility in predator foraging and social strategies is pertinent to wildlife conservation under global change, including potential top-down effects on wider ecosystems. Here we propose key future research directions to better understand foraging strategies and social flexibility in predators. In particular, rapid continued advances in biologging technology are helping to record and understand dynamic behavioural and movement responses of animals to environmental changes, and their energetic consequences. Data collection can be optimised by calibrating behavioural interpretation methods in captive settings and strategic tagging decisions within and between social groups. Importantly, many species' social systems are increasingly being found to be more flexible than originally described in the literature, which may be more readily detectable through biologging approaches than behavioural observation. Integrating the effects of the physical landscape and biotic interactions will be key to explaining and predicting animal movements and energetic balance in a changing world.

Movement ecology of an endangered mesopredator in a mining landscape

BACKGROUND

Efficient movement and energy expenditure are vital for animal survival. Human disturbance can alter animal movement due to changes in resource availability and threats. Some animals can exploit anthropogenic disturbances for more efficient movement, while others face restricted or inefficient movement due to fragmentation of high-resource habitats, and risks associated with disturbed habitats. Mining, a major anthropogenic disturbance, removes natural habitats, introduces new landscape features, and alters resource distribution in the landscape. This study investigates the effect of mining on the movement of an endangered mesopredator, the northern quoll (Dasyurus hallucatus). Using GPS collars and accelerometers, we investigate their habitat selection and energy expenditure in an active mining landscape, to determine the effects of this disturbance on northern quolls.

METHODS

We fit northern quolls with GPS collars and accelerometers during breeding and non-breeding season at an active mine site in the Pilbara region of Western Australia. We investigated broad-scale movement by calculating the movement ranges of quolls using utilisation distributions at the 95% isopleth, and compared habitat types and environmental characteristics within observed movement ranges to the available landscape. We investigated fine-scale movement by quolls with integrated step selection functions, assessing the relative selection strength for each habitat covariate. Finally, we used piecewise structural equation modelling to analyse the influence of each habitat covariate on northern quoll energy expenditure.

RESULTS

At the broad scale, northern quolls predominantly used rugged, rocky habitats, and used mining habitats in proportion to their availability. However, at the fine scale, habitat use varied between breeding and non-breeding seasons. During the breeding season, quolls notably avoided mining habitats, whereas in the non-breeding season, they frequented mining habitats equally to rocky and riparian habitats, albeit at a higher energetic cost.

CONCLUSION

Mining impacts northern quolls by fragmenting favoured rocky habitats, increasing energy expenditure, and potentially impacting breeding dispersal. While mining habitats might offer limited resource opportunities in the non-breeding season, conservation efforts during active mining, including the creation of movement corridors and progressive habitat restoration would likely be useful. However, prioritising the preservation of natural rocky and riparian habitats in mining landscapes is vital for northern quoll conservation.

Over 300 km Dispersion of Wild Boar during Hot Summer, from Central Poland to Ukraine

The movement of wild boars is a complex process influenced by both internal conditions and external factors. Despite their typically sedentary lifestyle, dispersion constitutes an integral element of the wild boar's behavior. This report documents the longest observed wild boar dispersal, involving a collared two-year-old male near Warsaw, Poland. The aim of this study was to present the characteristics of movement during the "nomadic phase", drawing comparisons with the "sedentary phase". The other aim was to evaluate the influence of meteorological factors on the minimum daily travel distance of the wild boar. We collected data from two-year-old males. The first exhibited long-distance dispersal and the second only demonstrated local movements. We calculated the minimum daily distance of both wild boars based on collar locations and calculated basic statistics of movement. We used a generalized linear model with a gamma distribution and log link function to assess the potential impact of weather conditions on the minimum daily distance of wild boars. We tested maximum daily temperature, average daily temperature, and the sum of daily precipitation. The wild boar during a "nomadic phase" covered a total of 922 km with a mean minimum daily movement of 6 km. The dispersion distance was 307 km. The highest value of the minimum daily distance reached 31.8 km/day. The second wild boar (near Warsaw) covered a mean minimum daily distance of 1.4 km; the highest value of the minimum daily distance was 3.9 km. Both wild boars exhibited no dependence of minimum daily distance on weather conditions. However, when intensive and non-intensive dispersion were analyzed separately, it was demonstrated that the maximum daily temperature positively influenced the minimum daily distance. We speculate that the wild boar was forced to search for water sources after dark on hot days, which induced a longer traveling distance in an unfamiliar environment. This study highlights the significant spatial capabilities of wild boar in the transmission of genes or pathogens. We speculate that extended daily distances during the initial "nomadic phase" might suggest a panicked escape from a perceived threat. It is plausible that the wild boar found improved shelter within tall cereal crops in July and August, which resulted in lower daily distances.

Time is of the essence: The importance of considering biological rhythms in an increasingly polluted world

Biological rhythms have a crucial role in shaping the biology and ecology of organisms. Light pollution is known to disrupt these rhythms, and evidence is emerging that chemical pollutants can cause similar disruption. Conversely, biological rhythms can influence the effects and toxicity of chemicals. Thus, by drawing insights from the extensive study of biological rhythms in biomedical and light pollution research, we can greatly improve our understanding of chemical pollution. This Essay advocates for the integration of biological rhythmicity into chemical pollution research to gain a more comprehensive understanding of how chemical pollutants affect wildlife and ecosystems. Despite historical barriers, recent experimental and technological advancements now facilitate the integration of biological rhythms into ecotoxicology, offering unprecedented, high-resolution data across spatiotemporal scales. Recognizing the importance of biological rhythms will be essential for understanding, predicting, and mitigating the complex ecological repercussions of chemical pollution.

Conserve the open media ecosystem! Legal and ethical considerations when using online repositories for AI training in ecological research

Ecological researchers who train Artificial Intelligence models using digital media have to be cognizant of legal and ethical implications when sourcing such content from online repositories. The way forward? Complying with Creative Commons licensing requirements, obtaining consent from media creators and adhering to FAIR data principles. Collective action from researchers, repositories, licence providers, and legislators is needed to conserve this complex open media ecosystem. This way, we can continue to develop innovative applications to address pressing ecological issues while maintaining the trust of content creators and respecting the legal and ethical framework of online media use.

Extensive behavioral data contained within existing ecological datasets

Long-term ecological datasets contain vast behavioral data, enabling the quantification of among-individual behavioral variation at unprecedented spatiotemporal scales. We detail how behaviors can be extracted and describe how such data can be used to test new hypotheses, inform population and community ecology, and address pressing conservation needs.

Predator home range size mediates indirect interactions between prey species in an arctic vertebrate community

Indirect interactions are widespread among prey species that share a common predator, but the underlying mechanisms driving these interactions are often unclear, and our ability to predict their outcome is limited. Changes in behavioural traits that impact predator space use could be a key proximal mechanism mediating indirect interactions, but there is little empirical evidence of the causes and consequences of such behavioural-numerical response in multispecies systems. Here, we investigate the complex ecological relationships between seven prey species sharing a common predator. We used a path analysis approach on a comprehensive 9-year data set simultaneously tracking predator space use, prey densities and prey mortality rate on key species of a simplified Arctic food web. We show that high availability of a clumped and spatially predictable prey (goose eggs) leads to a twofold reduction in predator (arctic fox) home range size, which increases local predator density and strongly decreases nest survival of an incidental prey (American golden plover). On the contrary, a scattered cyclic prey with potentially lower spatial predictability (lemming) had a weaker effect on fox space use and an overall positive impact on the survival of incidental prey. These contrasting effects underline the importance of studying behavioural responses of predators in multiprey systems and to explicitly integrate behavioural-numerical responses in multispecies predator-prey models.

Atlantic cod individual spatial behaviour and stable isotope associations in a no-take marine reserve

Foraging is a behavioural process and, therefore, individual behaviour and diet are theorized to covary. However, few comparisons of individual behaviour type and diet exist in the wild. We tested whether behaviour type and diet covary in a protected population of Atlantic cod, Gadus morhua. Working in a no-take marine reserve, we could collect data on natural behavioural variation and diet choice with minimal anthropogenic disturbance. We inferred behaviour using acoustic telemetry and diet from stable isotope compositions (expressed as δ13 C and δ15 N values). We further investigated whether behaviour and diet could have survival costs. We found cod with shorter diel vertical migration distances fed at higher trophic levels. Cod δ13 C and δ15 N values scaled positively with body size. Neither behaviour nor diet predicted survival, indicating phenotypic diversity is maintained without survival costs for cod in a protected ecosystem. The links between diet and diel vertical migration highlight that future work is needed to understand whether the shifts in this behaviour during environmental change (e.g. fishing or climate), could lead to trophic cascades.

Tracking technologies: advances driving new insights into monarch migration

Understanding the rules of how monarch butterflies complete their annual North American migration will be clarified by studying them within a movement ecology framework. Insect movement ecology is growing at a rapid pace due to the development of novel monitoring systems that allow ever-smaller animals to be tracked at higher spatiotemporal resolution for longer periods of time. New innovations in tracking hardware and associated software, including miniaturization, energy autonomy, data management, and wireless communication, are reducing the size and increasing the capability of next-generation tracking technologies, bringing the goal of tracking monarchs over their entire migration closer within reach. These tools are beginning to be leveraged to provide insight into different aspects of monarch biology and ecology, and to contribute to a growing capacity to understand insect movement ecology more broadly and its impact on human life.

The biological invasion of an apex predator (Silurus glanis) amplifies PCB transfer in a large lake food web

Invasive species can affect food web structure possibly modifying the transfer of pollutants in ecosystems but this facet of biological invasion remains largely unexplored. We examined how trophic and ontogenetic characteristics of the invasive European catfish could differ from its native counterpart, the Northern pike, possibly resulting in the amplification of PCB transfer to the higher trophic levels in a large lake food web. The PCB contents of catfish and pike were on average low (Ʃ7 PCBi 42.4 ± 38.6 ng g-1 ww and 37.9 ± 49.4 ng g-1 ww respectively) and dominated by PCB153 (~35 % of the PCB contamination). Only the largest pike (126 cm) slightly exceeded the European sanitary threshold of 125 ng g-1 ww Ʃ6 PCBi-NDL. Both species increased in trophic position with body size while catfish had clearly higher littoral reliance than pike indicating they exploited complementary trophic niches. PCB biomagnification was identified only for catfish (PCB153, Ʃ7 PCBi) leading to trophic magnification factor of ~5. PCB ontogenetic bioaccumulation was pervasive for catfish (PCB101, PCB118, PCB153, PCB138 and Ʃ7 PCBi) and identified for pike only regarding PCB101. The derived size accumulation factors (~1.02) indicated a size-doubling PCB contamination of ~40 cm for catfish. This finding suggested that catfish would exceed the European sanitary threshold at body size larger than 168 cm possibly constraining their commercial exploitation. Our results highlighted that the invasive catfish was a littoral-oriented apex predator occupying an alternative trophic niche as compared to pike thereby modifying the lake food web structure that resulted in an enhancement of PCB transfer to higher trophic levels. The biomagnification and ontogenetic bioaccumulation of catfish underlined the impact of this biological invasion on the fate of PCB in the ecosystem. Finally, the remarkable inter-individual PCB contamination suggested variable inter-individual PCB exposure likely associated to localized hotspots of PCB contamination in the lake.

Robust Time-of-Arrival Location Estimation Algorithms for Wildlife Tracking

Time-of-arrival transmitter localization systems, which use measurements from an array of sensors to estimate the location of a radio or acoustic emitter, are now widely used for tracking wildlife. Outlier measurements can severely corrupt estimated locations. This article describes a new suite of location estimation algorithms for such systems. The new algorithms detect and discard outlier time-of-arrival observations, which can be caused by non-line-of-sight propagation, radio interference, clock glitches, or an overestimation of the signal-to-noise ratio. The new algorithms also detect cases in which two locations are equally consistent with measurements and can usually select the correct one. The new algorithms can also infer approximate altitude information from a digital elevation map to improve location estimates close to one of the sensors. Finally, the new algorithms approximate the covariance matrix of location estimates in a simpler and more reliable way than the baseline algorithm. Extensive testing on real-world data involving mobile transmitters attached to wild animals demonstrates the efficacy of the new algorithms. Performance testing also shows that the new algorithms are fast and that they can easily cope with high-throughput real-time loads.

AIMS for wildlife: Developing an automated interactive monitoring system to integrate real-time movement and environmental data for true adaptive management

To effectively manage species and habitats at multiple scales, population and land managers require rapid information on wildlife use of managed areas and responses to landscape conditions and management actions. GPS tracking studies of wildlife are particularly informative to species ecology, habitat use, and conservation. Combining GPS data with administrative data and a diverse suite of remotely sensed, geo-referenced environmental (e.g., climatic) data, would more comprehensively inform how animals interact with and utilize habitats and ecosystems and our goal was to create a conceptual model for a system that would accomplish this - the 'Automated Interactive Monitoring System (AIMS) for Wildlife'. Our objective for this study was to develop a Customized Wildlife Report (CWR) - the first AIMS for Wildlife deliverable product. CWRs collate and summarize our 8-year GPS tracking dataset of ∼11 million locations from 1338 individual (16 species) avifauna and make actionable, real-time data on animal movements and trends in a specific area of interest available to managers and stakeholders for rapid application in day-to-day management. The CWR exemplar presented in this paper was developed to address needs identified by habitat managers of Sacramento National Wildlife Refuge and illustrates the highly specific, information offered and how it contributes to assessing the efficacy of conservation actions while allowing for near real-time adaptive management. The report can be easily customized for any of the thousands of wildlife refuges or regional areas of interest in the United States, emphasizing the broad application of an animal movement data stream. Utilizing diverse, extensive telemetry data streams through scientific collaboration can aid managers and conservation stakeholders with short and long-term research and conservation planning and help address a cadre of issues from local-scale habitat management to improving the understanding of landscape level impacts like drought, wildfire, and climate change on wildlife populations.

A global systematic review of frugivorous animal tracking studies and the estimation of seed dispersal distances

Seed dispersal is one of the most important ecosystem functions globally. It shapes plant populations, enhances forest succession, and has multiple, indirect benefits for humans, yet it is one of the most threatened processes in plant regeneration, worldwide. Seed dispersal distances are determined by the diets, seed retention times and movements of frugivorous animals. Hence, understanding how we can most effectively describe frugivore movement and behaviour with rapidly developing animal tracking technology is key to quantifying seed dispersal. To assess the current use of animal tracking in frugivory studies and to provide a baseline for future studies, we provide a comprehensive review and synthesis on the existing primary literature of global tracking studies that monitor movement of frugivorous animals. Specifically, we identify studies that estimate dispersal distances and how they vary with body mass and environmental traits. We show that over the last two decades there has been a large increase in frugivore tracking studies that determine seed dispersal distances. However, some taxa (e.g. reptiles) and geographic locations (e.g. Africa and Central Asia) are poorly studied. Furthermore, we found that certain morphological and environmental traits can be used to predict seed dispersal distances. We demonstrate that flight ability and increased body mass both significantly increase estimated seed dispersal mean and maximum distances. Our results also suggest that protected areas have a positive effect on mean seed dispersal distances when compared to unprotected areas. We anticipate that this review will act as a reference for future frugivore tracking studies, specifically to target current taxonomic and geographic data gaps, and to further explore how seed dispersal relates to key frugivore and fruit traits.

Ponds as experimental arenas for studying animal movement: current research and future prospects

Animal movement is a multifaceted process that occurs for multiple reasons with powerful consequences for food web and ecosystem dynamics. New paradigms and technical innovations have recently pervaded the field, providing increasingly powerful means to deliver fine-scale movement data, attracting renewed interest. Specifically in the aquatic environment, tracking with acoustic telemetry now provides integral spatiotemporal information to follow individual movements in the wild. Yet, this technology also holds great promise for experimental studies, enhancing our ability to truly establish cause-and-effect relationships. Here, we argue that ponds with well-defined borders (i.e. "islands in a sea of land") are particularly well suited for this purpose. To support our argument, we also discuss recent experiences from studies conducted in an innovative experimental infrastructure, composed of replicated ponds equipped with modern aquatic telemetry systems that allow for unparalleled insights into the movement patterns of individual animals.

Uniting Experiments and Big Data to advance ecology and conservation

Many ecologists increasingly advocate for research frameworks centered on the use of 'big data' to address anthropogenic impacts on ecosystems. Yet, experiments are often considered essential for identifying mechanisms and informing conservation interventions. We highlight the complementarity of these research frameworks and expose largely untapped opportunities for combining them to speed advancements in ecology and conservation. With nascent but increasing application of model integration, we argue that there is an urgent need to unite experimental and big data frameworks throughout the scientific process. Such an integrated framework offers potential for capitalizing on the benefits of both frameworks to gain rapid and reliable answers to ecological challenges.

Chromosome-level assembly and annotation of the Xyrichtys novacula (Linnaeus, 1758) genome

The pearly razorfish (Xyrichtys novacula), commonly known as raor in the Balearic Islands, is a wrasse within the family Labridae. This fish species has particular biological and socio-cultural characteristics making it an ideal model organism in the fields of behavioural ecology, molecular ecology and conservation biology. In this study, we present the first annotated chromosome-level assembly for this species. Sequencing involved a combination of long reads with Oxford Nanopore Technologies, Illumina paired-end short reads (2 × 151 bp), Hi-C and RNA-seq from different tissues. The nuclear genome assembly has a scaffold N50 of 34.33 Mb, a total assembly span of 775.53 Mb and 99.63% of the sequence assembled into 24 superscaffolds, consistent with its known karyotype. Quality metrics revealed a consensus accuracy (QV) of 42.92 and gene completeness > 98%. The genome annotation resulted in 26,690 protein-coding genes and 12,737 non-coding transcripts. The coding regions encoded 39,613 unique protein products, 93% of them with assigned function. Overall, the publication of the X. novacula's reference genome will broaden the scope and impact of genomic research conducted on this iconic and colourful species.

Movement diversity and partial sympatry of coastal and Northeast Arctic cod ecotypes at high latitudes

Movement diversity within species represent an important but often neglected, component of biodiversity that affects ecological and genetic interactions, as well as the productivity of exploited systems. By combining individual tracking data from acoustic telemetry with novel genetic analyses, we describe the movement diversity of two Atlantic cod Gadus morhua ecotypes in two high-latitude fjord systems: the highly migratory Northeast Arctic cod (NEA cod) that supports the largest cod fishery in the world, and the more sedentary Norwegian coastal cod, which is currently in a depleted state. As predicted, coastal cod displayed a higher level of fjord residency than NEA cod. Of the cod tagged during the spawning season, NEA cod left the fjords permanently to a greater extent and earlier compared to coastal cod, which to a greater extent remained resident and left the fjords temporarily. Despite this overall pattern, horizontal movements atypical for the ecotypes were common with some NEA cod remaining within the fjords year-round and some coastal cod displaying a low fjord fidelity. Fjord residency and exit timing also differed with spawning status and body size, with spawning cod and large individuals tagged during the feeding season more prone to leave the fjords and earlier than non-spawning and smaller individuals. While our results confirm a lower fjord dependency for NEA cod, they highlight a movement diversity within each ecotype and sympatric residency between ecotypes, previously undetected by population-level monitoring. This new knowledge is relevant for the management, which should base their fisheries advice for these interacting ecotypes on their habitat use and seasonal movements.

Rhythm of relationships in a social fish over the course of a full year in the wild

BACKGROUND

Animals are expected to adjust their social behaviour to cope with challenges in their environment. Therefore, for fish populations in temperate regions with seasonal and daily environmental oscillations, characteristic rhythms of social relationships should be pronounced. To date, most research concerning fish social networks and biorhythms has occurred in artificial laboratory environments or over confined temporal scales of days to weeks. Little is known about the social networks of wild, freely roaming fish, including how seasonal and diurnal rhythms modulate social networks over the course of a full year. The advent of high-resolution acoustic telemetry enables us to quantify detailed social interactions in the wild over time-scales sufficient to examine seasonal rhythms at whole-ecosystems scales. Our objective was to explore the rhythms of social interactions in a social fish population at various time-scales over one full year in the wild by examining high-resolution snapshots of a dynamic social network.

METHODS

To that end, we tracked the behaviour of 36 adult common carp, Cyprinus carpio, in a 25 ha lake and constructed temporal social networks among individuals across various time-scales, where social interactions were defined by proximity. We compared the network structure to a temporally shuffled null model to examine the importance of social attraction, and checked for persistent characteristic groups over time.

RESULTS

The clustering within the carp social network tended to be more pronounced during daytime than nighttime throughout the year. Social attraction, particularly during daytime, was a key driver for interactions. Shoaling behavior substantially increased during daytime in the wintertime, whereas in summer carp interacted less frequently, but the interaction duration increased. Therefore, smaller, characteristic groups were more common in the summer months and during nighttime, where the social memory of carp lasted up to two weeks.

CONCLUSIONS

We conclude that social relationships of carp change diurnally and seasonally. These patterns were likely driven by predator avoidance, seasonal shifts in lake temperature, visibility, forage availability and the presence of anoxic zones. The techniques we employed can be applied generally to high-resolution biotelemetry data to reveal social structures across other fish species at ecologically realistic scales.

Bibliometric analysis of the global scientific production on machine learning applied to different cancer types

Cancer disease is one of the main causes of death in the world, with million annual cases in the last decades. The need to find a cure has stimulated the search for efficient treatments and diagnostic procedures. One of the most promising tools that has emerged against cancer in recent years is machine learning (ML), which has raised a huge number of scientific papers published in a relatively short period of time. The present study analyzes global scientific production on ML applied to the most relevant cancer types through various bibliometric indicators. We find that over 30,000 studies have been published so far and observe that cancers with the highest number of published studies using ML (breast, lung, and colon cancer) are those with the highest incidence, being the USA and China the main scientific producers on the subject. Interestingly, the role of China and Japan in stomach cancer is correlated with the number of cases of this cancer type in Asia (78% of the worldwide cases). Knowing the countries and institutions that most study each area can be of great help for improving international collaborations between research groups and countries. Our analysis shows that medical and computer science journals lead the number of publications on the subject and could be useful for researchers in the field. Finally, keyword co-occurrence analysis suggests that ML-cancer research trends are focused not only on the use of ML as an effective diagnostic method, but also for the improvement of radiotherapy- and chemotherapy-based treatments.

The Internet of Animals: what it is, what it could be

One of the biggest trends in ecology over the past decade has been the creation of standardized databases. Recently, this has included live data, formal linkages between disparate databases, and automated analytics, a synergy that we recognize as the Internet of Animals (IoA). Early IoA systems relate animal locations to remote-sensing data to predict species distributions and detect disease outbreaks, and use live data to inform management of endangered species. However, meeting the future potential of the IoA concept will require solving challenges of taxonomy, data security, and data sharing. By linking data sets, integrating live data, and automating workflows, the IoA has the potential to enable discoveries and predictions relevant to human societies and the conservation of animals.

A gradual migratory divide determines not only the direction of migration but also migration strategy of a social migrant bird

Migratory divides separate populations of migratory animals, facilitating the evolution of intraspecific differences in migration strategies. Migration strategies are expected to be different for birds using different flyways and environments, but the knowledge regarding the impact of the flyway on individual migration strategies is scarce. By using satellite tracking and neckband resightings, we reveal the existence and structure of a gradual migratory divide between two European flyway populations of greylag geese Anser anser. Birds breeding at the far end of the Gulf of Bothnia in the Baltic Sea coast use the Western Flyway, those breeding in the Gulf of Finland the Central Flyway and those breeding between these extremes scatter to the two flyways. By using Gaussian process modelling, we show that migration strategies differed between the flyways. The birds using the Western Flyway migrated earlier in autumn, performed longer annual migration and made a clear stopover during migration, whereas the birds using the Central Flyway flew directly to their wintering sites. The gradual migratory divide that also divides migration strategies provides insights into migratory divides on birds with learned migration. Distinct migration strategies in different flyways provide exciting possibilities to further study the factors driving migration strategies.

Novel pathogen introduction triggers rapid evolution in animal social movement strategies

Animal sociality emerges from individual decisions on how to balance the costs and benefits of being sociable. Novel pathogens introduced into wildlife populations should increase the costs of sociality, selecting against gregariousness. Using an individual-based model that captures essential features of pathogen transmission among social hosts, we show how novel pathogen introduction provokes the rapid evolutionary emergence and coexistence of distinct social movement strategies. These strategies differ in how they trade the benefits of social information against the risk of infection. Overall, pathogen-risk-adapted populations move more and have fewer associations with other individuals than their pathogen-risk-naive ancestors, reducing disease spread. Host evolution to be less social can be sufficient to cause a pathogen to be eliminated from a population, which is followed by a rapid recovery in social tendency. Our conceptual model is broadly applicable to a wide range of potential host-pathogen introductions and offers initial predictions for the eco-evolutionary consequences of wildlife pathogen spillover scenarios and a template for the development of theory in the ecology and evolution of animals' movement decisions.

Linking fine-scale behaviour to the hydraulic environment shows behavioural responses in riverine fish

BACKGROUND

Fish migration has severely been impacted by dam construction. Through the disruption of fish migration routes, freshwater fish communities have seen an incredible decline. Fishways, which have been constructed to mitigate the problem, have been shown to underperform. This is in part due to fish navigation still being largely misunderstood. Recent developments in tracking technology and modelling make it possible today to track (aquatic) animals at very fine spatial (down to one meter) and temporal (down to every second) scales. Hidden Markov models are appropriate models to analyse behavioural states at these fine scales. In this study we link fine-scale tracking data of barbel (Barbus barbus) and grayling (Thymallus thymallus) to a fine-scale hydrodynamic model. With a HMM we analyse the fish's behavioural switches to understand their movement and navigation behaviour near a barrier and fishway outflow in the Iller river in Southern Germany.

METHODS

Fish were tracked with acoustic telemetry as they approached a hydropower facility and were presented with a fishway. Tracking resulted in fish tracks with variable intervals between subsequent fish positions. This variability stems from both a variable interval between tag emissions and missing detections within a track. After track regularisation hidden Markov models were fitted using different parameters. The tested parameters are step length, straightness index calculated over a 3-min moving window, and straightness index calculated over a 10-min window. The best performing model (based on a selection by AIC) was then expanded by allowing flow velocity and spatial velocity gradient to affect the transition matrix between behavioural states.

RESULTS

In this study it was found that using step length to identify behavioural states with hidden Markov models underperformed when compared to models constructed using straightness index. Of the two different straightness indices assessed, the index calculated over a 10-min moving window performed better. Linking behavioural states to the ecohydraulic environment showed an effect of the spatial velocity gradient on behavioural switches. On the contrary, flow velocity did not show an effect on the behavioural transition matrix.

CONCLUSIONS

We found that behavioural switches were affected by the spatial velocity gradient caused by the attraction flow coming from the fishway. Insight into fish navigation and fish reactions to the ecohydraulic environment can aid in the construction of fishways and improve overall fishway efficiencies, thereby helping to mitigate the effects migration barriers have on the aquatic ecosystem.

Individual variation in the habitat selection of upstream migrating fish near a barrier

BACKGROUND

Migration is a vital element of the life cycle of many freshwater fish species but is increasingly hampered globally by riverine barriers. Fish passes are a common approach to enable migration past barriers but are often ineffective. More knowledge is required on fish behaviour as they approach barriers such as habitat preferences.

METHODS

We evaluate the habitat selection of two upstream migrating fish species, barbel Barbus barbus and grayling Thymallus thymallus, at a hydropower plant in southern Germany, considering individual variation and population trends. Fish were tracked via fine-scale 2D acoustic telemetry in 2018 during their spawning migration. Step selection functions were used to evaluate selection of hydraulic parameters by the fish for a time step of 20 s. Exploratory models were built via model selection for each individual fish, to evaluate the extent of individual variation in model structure. A population model was developed for each species by averaging coefficients from individual models to describe general trends. The extent of individual variation was determined and confidence intervals for the population model coefficients were calculated.

RESULTS

Fish varied greatly in individual model structure though common terms were apparent in both species, such as depth, flow velocity, the angular difference between fish and velocity, and the logarithm of the step length. Final population models for barbel included several parameters describing habitat selection and displacement. Barbel selected for faster flows, deeper water, and higher spatial velocity gradients. In addition, they selected to move more with the flow than against. Interactions were also present between habitat parameters, suggesting selection is context dependent. Barbel movement speed also changed with depth, flow velocity and spatial velocity gradient. With grayling, terms often had contrasting effects among individuals and thus general trends could not be distinguished for most terms.

CONCLUSION

Our findings demonstrate habitat selection by upstream migrating fish approaching a fish pass and differences in individual selection which may have an impact on barrier management. Step selection functions are a promising approach and can provide useful insight into habitat selection and movement by migrating freshwater fish in an altered river system.