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.

A telemetry study shows that an endangered nocturnal avian species roosts in extremely dry habitats to avoid predation

Describing animal space use is essential for understanding their ecological needs and for planning effective conservation schemes. Notably, certain biomes and life histories are understudied due to methodological challenges in tracking animals in their natural habitats. Specifically, both arid environments and nocturnal species are not sufficiently researched compared to diurnal species and to other biomes. This knowledge gap hinders our ability to properly prioritize habitats for species protection in areas undergoing human-related development. Here, we investigate the movement ecology of the Egyptian Nightjar (Caprimulgus aegyptius) in the arid Dead-sea region of Israel, the Palestinian Authority (the West Bank) and Jordan. This nocturnal insectivore is a cryptic desert-dweller and was considered locally extinct until it was rediscovered in 2016. For this work we tracked twelve individuals using GPS tags to determine how this resource-poor environment affects their home range, (predicting large areas), habitat use, and day-roost ecology. We found that the tracked Egyptian Nightjars had a much larger home range area than other Nightjar species, commuting nightly between foraging grounds and day-roosts. We found, as expected, intensive foraging activity at agricultural fields, where artificial irrigation likely supports higher resource (insect) density. Additionally, we found that individuals showed very high roosting site fidelity, often returning to the same specific site, located in extremely dry and exposed habitats, presumably for predator avoidance. This finding highlights the ecological value of these barren habitats that are often considered "lifeless" and therefore of lower priority for conservation. Consequently, our research demonstrates the importance of describing the space-use of nocturnal animals in arid habitats for conservation efforts.

Plasma cholinesterase activity: A benchmark for rapid detection of pesticide poisoning in an avian scavenger

Poisoning due to exposure to organophosphate and carbamate pesticides is a common threat for many wildlife species, especially for scavengers such as vultures. The Griffon vulture population (Gyps fulvus), for instance, is deteriorating in the Eastern Mediterranean, and is considered to be critically endangered in Israel, where 48 out of 107 (45 %) known injury/mortality cases in 2010-2021 were caused by poisoning. Lack of specific clinical indications, together with levels of organophosphate or carbamate pesticides too low to detect, challenge the ability to diagnose and treat such poisoning events. The activity of cholinesterase (ChE) in plasma has the potential to serve as an effective biomarker for monitoring exposure to anticholinesterase pesticides in live vultures. Yet, the applicability of this approach has been limited by intra- and inter-species variations in ChE basal levels. The present study aims to provide a benchmark for ChE activity levels in healthy Griffons and their intra-species variation. Blood samples from free-roaming (n = 231) and captive (n = 63) Griffons were collected during routine monitoring, and ChE levels were determined using a colorimetric method. We established that the ChE in the plasma of Griffons reflects mostly acetylcholinesterase as the dominant form. ChE levels in healthy Griffons are 0.601 ± 0.011 U/ml (mean ± SE), while Griffons with suspected or confirmed pesticide poisoning display much lower levels of ChE activity (typically <0.3 U/ml). We also characterized the age dependence of ChE activity, as well as differences among groups from different locations or origins. Our study provides a rapid diagnostic tool for the detection of exposure to organophosphate and carbamate pesticides that should facilitate the lifesaving treatment and the conservation of this species. Moreover, our protocols can be adapted to other species and geographical areas, addressing pesticide poisoning worldwide and contributing to the protection of endangered species and their ecological functions (e.g. sanitation by scavengers).

Behavioral responses of terrestrial mammals to COVID-19 lockdowns

COVID-19 lockdowns in early 2020 reduced human mobility, providing an opportunity to disentangle its effects on animals from those of landscape modifications. Using GPS data, we compared movements and road avoidance of 2300 terrestrial mammals (43 species) during the lockdowns to the same period in 2019. Individual responses were variable with no change in average movements or road avoidance behavior, likely due to variable lockdown conditions. However, under strict lockdowns 10-day 95th percentile displacements increased by 73%, suggesting increased landscape permeability. Animals' 1-hour 95th percentile displacements declined by 12% and animals were 36% closer to roads in areas of high human footprint, indicating reduced avoidance during lockdowns. Overall, lockdowns rapidly altered some spatial behaviors, highlighting variable but substantial impacts of human mobility on wildlife worldwide.

Social situations differ in their contribution to population-level social structure in griffon vultures

Social relationships among animals emerge from interactions in multiple ecological and social situations. However, we seldom ask how each situation contributes to the global structure of a population, and whether different situations contribute different information about social relationships and the position of individuals within the social fabric. Griffon vultures (Gyps fulvus) interact socially in multiple situations, including communal roosting, joint flights, and co-feeding. These social interactions can influence population-level outcomes, such as disease transmission and information sharing that determine survival and response to changes. We examined the unique contribution of each social and ecological situation to the social structure of the population and individuals' positions within the overall social network using high-resolution GPS tracking. We found that the number of individuals each vulture interacted with (degree) was best predicted by diurnal interactions-both during flights and on the ground (such as when feeding). However, the strength of social bonds, that is, the number of interactions an individual had (strength), was best predicted by interactions on the ground-both during the day (e.g., while feeding) and at night (e.g., while roosting) but not by interactions while flying. Thus, social situations differ in their impact on the relationships that individuals form. By incorporating the ecological situations in which social interactions occur we gain a more complete view of how social relationships are formed and which situations are important for different types of interactions.

ViewShedR: a new open-source tool for cumulative, subtractive and elevated line-of-sight analysis

Many environmental and ecological studies require line of sight (LOS) and/or viewshed analyses. While tools for performing these analyses from digital elevation models (DEMs) are widespread, they are either too restrictive, inaccessible or pricey and difficult to use. This methodological gap is potentially imperative for scholars using solutions like telemetry tracking systems or spatial ecology landscape mapping. Here we present ViewShedR-a free, open-source and intuitive graphical user-interface application for performing LOS calculations, including cumulative, subtractive (areas covered by towers A + B or by A but not by B, respectively), and elevated-target analyses. ViewShedR is implemented in the widely used R environment, thus facilitating usage and further modification by end-users. We provide two working examples for ViewShedR in the context of permanent animal-tracking systems requiring simultaneous tag-detection by multiple towers (receivers): first, the ATLAS system for terrestrial animals in the Harod Valley, Israel; and second, an acoustic telemetry array for marine animals in the Dry Tortugas, Florida. ViewShedR allowed effective tower deployment and finding partially detected tagged animals in the ATLAS system. Similarly, it allowed us to identify reception shadows cast by islands in the marine array. We hope ViewShedR will facilitate deployment of tower arrays for tracking, communication networks and other ecological applications.

Categorizing the geometry of animal diel movement patterns with examples from high-resolution barn owl tracking

BACKGROUND

Movement is central to understanding the ecology of animals. The most robustly definable segments of an individual's lifetime track are its diel activity routines (DARs). This robustness is due to fixed start and end points set by a 24-h clock that depends on the individual's quotidian schedule. An analysis of day-to-day variation in the DARs of individuals, their comparisons among individuals, and the questions that can be asked, particularly in the context of lunar and annual cycles, depends on the relocation frequency and spatial accuracy of movement data. Here we present methods for categorizing the geometry of DARs for high frequency (seconds to minutes) movement data.

METHODS

Our method involves an initial categorization of DARs using data pooled across all individuals. We approached this categorization using a Ward clustering algorithm that employs four scalar "whole-path metrics" of trajectory geometry: 1. net displacement (distance between start and end points), 2. maximum displacement from start point, 3. maximum diameter, and 4. maximum width. We illustrate the general approach using reverse-GPS data obtained from 44 barn owls, Tyto alba, in north-eastern Israel. We conducted a principle components analysis (PCA) to obtain a factor, PC1, that essentially captures the scale of movement. We then used a generalized linear mixed model with PC1 as the dependent variable to assess the effects of age and sex on movement.

RESULTS

We clustered 6230 individual DARs into 7 categories representing different shapes and scale of the owls nightly routines. Five categories based on size and elongation were classified as closed (i.e. returning to the same roost), one as partially open (returning to a nearby roost) and one as fully open (leaving for another region). Our PCA revealed that the DAR scale factor, PC1, accounted for 86.5% of the existing variation. It also showed that PC2 captures the openness of the DAR and accounted for another 8.4% of the variation. We also constructed spatio-temporal distributions of DAR types for individuals and groups of individuals aggregated by age, sex, and seasonal quadrimester, as well as identify some idiosyncratic behavior of individuals within family groups in relation to location. Finally, we showed in two ways that DARs were significantly larger in young than adults and in males than females.

CONCLUSION

Our study offers a new method for using high-frequency movement data to classify animal diel movement routines. Insights into the types and distributions of the geometric shape and size of DARs in populations may well prove to be more invaluable for predicting the space-use response of individuals and populations to climate and land-use changes than other currently used movement track methods of analysis.

Movement predictability of individual barn owls facilitates estimation of home range size and survival

BACKGROUND

There is growing attention to individuality in movement, its causes and consequences. Similarly to other well-established personality traits (e.g., boldness or sociability), conspecifics also differ repeatedly in their spatial behaviors, forming behavioral types ("spatial-BTs"). These spatial-BTs are typically described as the difference in the mean-level among individuals, and the intra-individual variation (IIV, i.e., predictability) is only rarely considered. Furthermore, the factors determining predictability or its ecological consequences for broader space-use patterns are largely unknown, in part because predictability was mostly tested in captivity (e.g., with repeated boldness assays). Here we test if (i) individuals differ in their movement and specifically in their predictability. We then investigate (ii) the consequences of this variation for home-range size and survival estimates, and (iii) the factors that affect individual predictability.

METHODS

We tracked 92 barn owls (Tyto alba) with an ATLAS system and monitored their survival. From these high-resolution (every few seconds) and extensive trajectories (115.2 ± 112.1 nights; X̅ ± SD) we calculated movement and space-use indices (e.g., max-displacement and home-range size, respectively). We then used double-hierarchical and generalized linear mix-models to assess spatial-BTs, individual predictability in nightly max-displacement, and its consistency across time. Finally, we explored if predictability levels were associated with home-range size and survival, as well as the seasonal, geographical, and demographic factors affecting it (e.g., age, sex, and owls' density).

RESULTS

Our dataset (with 74 individuals after filtering) revealed clear patterns of individualism in owls' movement. Individuals differed consistently both in their mean movement (e.g., max-displacement) and their IIV around it (i.e., predictability). More predictable individuals had smaller home-ranges and lower survival rates, on top and beyond the expected effects of their spatial-BT (max-displacement), sex, age and ecological environments. Juveniles were less predictable than adults, but the sexes did not differ in their predictability.

CONCLUSION

These results demonstrate that individual predictability may act as an overlooked axis of spatial-BT with potential implications for relevant ecological processes at the population level and individual fitness. Considering how individuals differ in their IIV of movement beyond the mean-effect can facilitate understanding the intraspecific diversity, predicting their responses to changing ecological conditions and their population management.

Beyond simple habituation: Anthropogenic habitats influence the escape behaviour of spur-winged lapwings in response to both human and non-human threats

Habitat development may affect wildlife behaviour, favouring individuals or behaviours that cope better with perceived threats (predators). Bolder behaviours in human-dominated habitats (HDH; e.g. urban and rural settlements) may represent habituation specifically to humans, or a general reduction in predator-avoidance response. However, such carry-over effects across threat types (i.e. beyond humans) and phases of the escape sequence have not been well studied to date. Here we investigated escape behaviours of a locally common wader species, the spur-winged lapwing Vanellus spinosus. We assayed their flight initiation distance (FID) and subsequent escape behaviours in agricultural areas and in HDH. We found that lapwings in HDH were bolder, and that the difference was manifested in several phases of the predator-avoidance sequence (shorter FIDs, shorter distances fled, and a higher probability of escape by running vs. flying). When re-approached (by an observer) after landing, lapwings in HDH were also more repetitive in their FID than those in other habitats. To determine whether this apparent bolder behaviour in HDH areas is merely a consequence of habituation to humans or represents a broader behavioural change, we introduced an additional threat type-a remotely-operated taxidermic jackal ('Jack-Truck'). Finding bolder responses in the HDH to the human threat alone (and not to the Jack-Truck) could have supported the habituation hypothesis. In contrast, however, we found a bolder response in the HDH to both threat types, as well as a correlation between their FIDs across different sites. These bolder behaviours suggest that HDH impose a broader behavioural change on lapwings, rather than just simple habituation. Overall, our findings demonstrate how FID trials can reveal strong behavioural carry-over effects of HDH following human and non-human threats, including effects on the subsequent phases of escaping the predator. Further, FID assays may reveal consistent behavioural types when assessed under field conditions, and offer a direct way to differentiate among the various poorly understood and non-mutually exclusive mechanisms that lead to behavioural differences among organisms in HDH. The mechanistic perspective is essential for understanding how rapid urbanization impacts wildlife behaviour, populations, and the range of behaviours within them, even in species apparently resilient to such environmental changes.

Behavioural ecology at the spatial-social interface

Spatial and social behaviour are fundamental aspects of an animal's biology, and their social and spatial environments are indelibly linked through mutual causes and shared consequences. We define the 'spatial-social interface' as intersection of social and spatial aspects of individuals' phenotypes and environments. Behavioural variation at the spatial-social interface has implications for ecological and evolutionary processes including pathogen transmission, population dynamics, and the evolution of social systems. We link spatial and social processes through a foundation of shared theory, vocabulary, and methods. We provide examples and future directions for the integration of spatial and social behaviour and environments. We introduce key concepts and approaches that either implicitly or explicitly integrate social and spatial processes, for example, graph theory, density-dependent habitat selection, and niche specialization. Finally, we discuss how movement ecology helps link the spatial-social interface. Our review integrates social and spatial behavioural ecology and identifies testable hypotheses at the spatial-social interface.

Personality, spatiotemporal ecological variation and resident/explorer movement syndromes in the sleepy lizard

Individual variation in movement is profoundly important for fitness and offers key insights into the spatial and temporal dynamics of populations and communities. Nonetheless, individual variation in fine-scale movement behaviours is rarely examined even though animal tracking devices offer the long-term, high-resolution, repeatable data in natural conditions that are ideal for studying this variation. Furthermore, of the few studies that consider individual variation in movement, even fewer also consider the internal traits and environmental factors that drive movement behaviour which are necessary for contextualising individual differences in movement patterns. In this study, we GPS tracked a free-ranging population of sleepy lizards Tiliqua rugosa, each Austral spring over 5 years to examine consistent among-individual variation in movement patterns, as well as how these differences were mediated by key internal and ecological factors. We found that individuals consistently differed in a suite of weekly movement traits, and that these traits strongly covaried among-individuals, forming movement syndromes. Lizards fell on a primary movement continuum, from 'residents' that spent extended periods of time residing within smaller core areas of their home range, to 'explorers' that moved greater distances and explored vaster areas of the environment. Importantly, we also found that these consistent differences in lizard movement were related to two ecologically important animal personality traits (boldness and aggression), their sex, key features of the environment (including food availability, and a key water resource), habitat type and seasonal variation (cool/moist vs. hot/drier) in environmental conditions. Broadly, these movement specialisations likely reflect variation in life-history tactics including foraging and mating tactics that ultimately underlie key differences in space use. Such information can be used to connect phenotypic population structure to key ecological and evolutionary processes, for example social networks and disease-transmission pathways, further highlighting the value of examining individual variation in movement behaviour.

A guide to pre-processing high-throughput animal tracking data

Modern, high‐throughput animal tracking increasingly yields ‘big data’ at very fine temporal scales. At these scales, location error can exceed the animal's step size, leading to mis‐estimation of behaviours inferred from movement. ‘Cleaning’ the data to reduce location errors is one of the main ways to deal with position uncertainty. Although data cleaning is widely recommended, inclusive, uniform guidance on this crucial step, and on how to organise the cleaning of massive datasets, is relatively scarce.

A pipeline for cleaning massive high‐throughput datasets must balance ease of use and computationally efficiency, in which location errors are rejected while preserving valid animal movements. Another useful feature of a pre‐processing pipeline is efficiently segmenting and clustering location data for statistical methods while also being scalable to large datasets and robust to imperfect sampling. Manual methods being prohibitively time‐consuming, and to boost reproducibility, pre‐processing pipelines must be automated.

We provide guidance on building pipelines for pre‐processing high‐throughput animal tracking data to prepare it for subsequent analyses. We apply our proposed pipeline to simulated movement data with location errors, and also show how large volumes of cleaned data can be transformed into biologically meaningful ‘residence patches’, for exploratory inference on animal space use. We use tracking data from the Wadden Sea ATLAS system (WATLAS) to show how pre‐processing improves its quality, and to verify the usefulness of the residence patch method. Finally, with tracks from Egyptian fruit bats Rousettus aegyptiacus, we demonstrate the pre‐processing pipeline and residence patch method in a fully worked out example.

To help with fast implementation of standardised methods, we developed the R package atlastools, which we also introduce here. Our pre‐processing pipeline and atlastools can be used with any high‐throughput animal movement data in which the high data‐volume combined with knowledge of the tracked individuals' movement capacity can be used to reduce location errors. atlastools is easy to use for beginners while providing a template for further development. The common use of simple yet robust pre‐processing steps promotes standardised methods in the field of movement ecology and leads to better inferences from data.

Settling in: Reintroduced Persian Fallow Deer Adjust the Borders and Habitats of Their Home-Range During the First 5 Years Post Release

Translocated animals typically find themselves in a novel environment in which they must establish a home range in a manner that will maximize their fitness. We hypothesized that the initial establishment of a home range is followed by adjustments expressed as home range shifting, and occurs as familiarity with the landscape increases, until the home range is stabilized. We studied the process of home range shifting in 42 female Persian fallow deer (Dama mesopotamica) reintroduced into the Galilee, Israel over a period of 2–5 years. We used changes in the degree of home range overlap between consecutive years as an indicator of stabilization. We then compared how the mean percent cover of the key vegetation types (woodland, scrubland and open pastures) differed between the areas abandoned in the first year's home range and the areas added to the last year's home range relative to the first (using a weighted paired t-test). We also compared the distribution (using χ2 test of independence and Levene's test for homogeneity of variance) of %cover of the 3 vegetation types between the first and last year's home range. The average home range overlap increased over the 5 years following the first release. During the first-year post release, deer avoided open pastures and preferred woodland. In later years deer increase in the % open pastures (weighted t-test: p &lt; 0.001) and decreased the % woodland cover (weighted t-test: p = 0.07) by abandoning areas with little open pasture and steeper terrain and moving into areas with more open pasture and moderate terrain. Variance of the cover types across individuals increased with time. We conclude that the home ranges of the reintroduced deer stabilized with time. The changes in vegetation and slope are driven by time-dependent changing needs reflecting a tradeoff between safety (refuge) and foraging. Our findings suggest that using the initially established home range to determine species preferences can create a misleading picture of what the optimal home range of the species really is. Individual variation in term of preferences can take a few years to be expressed due to the initial high-risk perceived by individuals in a novel environment.

Gulls foraging in landfills: Does atmospheric exposure to halogenated flame retardants result in bioaccumulation?

Several bird species have adapted to foraging in landfills, although these sites are known to represent significant sources of emissions of toxic semi-volatile chemicals including the halogenated flame retardants (HFRs) (e.g., polybrominated diphenyl ethers (PBDEs) and emerging compounds). The objective of this study was to investigate the association between atmospheric exposure to PBDEs and selected emerging HFRs and their bioaccumulation in landfill-foraging birds. We determined HFR concentrations in liver of 58 GPS-tagged ring-billed gulls (Larus delawarensis) breeding in a colony near Montreal (Canada) as well as their atmospheric exposure determined using a miniature bird-borne passive air sampler. PBDE mixtures were the most abundant HFRs determined in passive air samplers (daily exposure rates of ∑₉PentaBDE: 47.4 ± 6.5 pg/day; DecaBDE: 36.0 ± 6.3 pg/day, and ∑₃OctaBDE: 3.4 ± 0.5 pg/day) and liver (∑₉PentaBDE: 68.1 ± 8.9 ng/g ww; DecaBDE: 52.3 ± 8.1 ng/g ww, and ∑₃OctaBDE: 12.8 ± 2.1 ng/g ww), and their concentrations increased with the presence probability of gulls in landfills. We found a spatial relationship between the local sources of atmospheric exposure to PBDEs and the sites associated with greatest PBDE concentrations in liver. Specifically, the atmospheric exposure index was correlated with the bioaccumulation index (Pearson r for ∑₉PentaBDE: r = 0.63, p < 0.001; DecaBDE: r = 0.66, p < 0.001, and ∑₃OctaBDE: r = 0.42, p < 0.001). However, we found no correlation at the individual level between daily exposure rates of HFRs in passive air samplers and their liver concentrations. This suggests that complex exposure pathways combined with toxicokinetic factors shaped HFR profiles in gull liver, potentially confounding the relationships with atmospheric exposure.

Social interactions in striped hyena inferred from camera trap data: is it more social than previously thought?

Understanding the drivers promoting sociality over solitariness in animal species is imperative for predicting future population trends and informing conservation and management. In this study we investigate the social structure of a desert dwelling population of striped hyena Hyaena hyaena. This species is historically regarded as strictly solitary albeit being the least studied of the extant Hyaenids. Accumulating evidence regarding the frequency of social interactions suggests a revision of striped hyena social structure is required. We hypothesized that striped hyena has a social structure that is more complex than expected for a strictly solitary species. For that end, we deployed an array of camera-traps in a remote desert region in Israel, and compared observed frequencies of striped hyena co-occurrence against null models to test whether hyena co-occurred more than expected by chance. Seven adults were (re)captured by our camera-traps in 49 different instances over 83 tracking days. Of these, 6 exhibited shared space-use around a scarce, isolated perennial water source. Five of them, co-occurred with other hyena (in 3 instances) significantly more frequent than expected by chance (and that timing suggests reproduction is unlikely to be the driving factor). Our findings substantiate evidence of complex social structure in striped hyena, highlight the importance of a scarce resource in space-use and sociality, and provide a baseline for future research of striped hyena social structure. We suggest that similar methods be employed to evaluate social structure in other “solitary species” to better understand their social dynamics.

Disturbance modifies payoffs in the explore-exploit trade-off

Decision-making agents face a fundamental trade-off between exploring new opportunities with risky outcomes versus exploiting familiar options with more certain but potentially suboptimal outcomes. Although mediation of this trade-off is essential to adaptive behavior and has for decades been assumed to modulate performance, the empirical consequences of human exploratory strategies are unknown beyond laboratory or theoretical settings. Leveraging 540,000 vessel position records from 2494 commercial fishing trips along with corresponding revenues, here we find that during undisturbed conditions, there was no relationship between exploration and performance, contrary to theoretical predictions. However, during a major disturbance event which closed the most-utilized fishing grounds, explorers benefited significantly from less-impacted revenues and were also more likely to continue fishing. We conclude that in stochastic natural systems characterized by non-stationary rewards, the role of exploration in buffering against disturbance may be greater than previously thought in humans.

The empirical consequences of human explorative strategies are not fully understood. Here the authors find that during undisturbed conditions, more-explorative vessels gained no performance advantage while during a major disturbance event, explorers benefited significantly from less-impacted revenues and were also more likely to continue fishing.

Endure your parasites: Sleepy Lizard (Tiliqua rugosa) movement is not affected by their ectoparasites

Movement is often used to indicate host vigour, as it has various ecological and evolutionary implications, and has been shown to be affected by parasites. We investigate the relationship between tick load and movement in the Australian Sleepy Lizard (Tiliqua rugosa (Gray, 1825)) using high resolution GPS tracking. This allowed us to track individuals across the entire activity season. We hypothesized that tick load negatively affects host movement (mean distance moved per day). We used a multivariate statistical model informed by the ecology and biology of the host and parasite, their host–parasite relationship, and known host movement patterns. This allowed us to quantify the effects of ticks on lizard movement above and beyond effects of other factors such as time in the activity season, lizard body condition, and stress. We did not find any support for our hypothesis. Instead, our results provide evidence that lizard movement is strongly driven by internal state (sex and body condition independent of tick load) and by external factors (environmental conditions). We suggest that the Sleepy Lizard has largely adapted to natural levels of tick infection in this system. Our results conform to host–parasite arms race theory, which predicts varying impacts of parasites on hosts in natural systems.

Moving in the Anthropocene: Global reductions in terrestrial mammalian movements

Animal movement is fundamental for ecosystem functioning and species survival, yet the effects of the anthropogenic footprint on animal movements have not been estimated across species. Using a unique GPS-tracking database of 803 individuals across 57 species, we found that movements of mammals in areas with a comparatively high human footprint were on average one-half to one-third the extent of their movements in areas with a low human footprint. We attribute this reduction to behavioral changes of individual animals and to the exclusion of species with long-range movements from areas with higher human impact. Global loss of vagility alters a key ecological trait of animals that affects not only population persistence but also ecosystem processes such as predator-prey interactions, nutrient cycling, and disease transmission.

Going through the motions: incorporating movement analyses into disease research

Though epidemiology dates back to the 1700s, most mathematical representations of epidemics still use transmission rates averaged at the population scale, especially for wildlife diseases. In simplifying the contact process, we ignore the heterogeneities in host movements that complicate the real world, and overlook their impact on spatiotemporal patterns of disease burden. Movement ecology offers a set of tools that help unpack the transmission process, letting researchers more accurately model how animals within a population interact and spread pathogens. Analytical techniques from this growing field can also help expose the reverse process: how infection impacts movement behaviours, and therefore other ecological processes like feeding, reproduction, and dispersal. Here, we synthesise the contributions of movement ecology in disease research, with a particular focus on studies that have successfully used movement-based methods to quantify individual heterogeneity in exposure and transmission risk. Throughout, we highlight the rapid growth of both disease and movement ecology and comment on promising but unexplored avenues for research at their overlap. Ultimately, we suggest, including movement empowers ecologists to pose new questions, expanding our understanding of host-pathogen dynamics and improving our predictive capacity for wildlife and even human diseases.

Decision-making by a soaring bird: time, energy and risk considerations at different spatio-temporal scales

Natural selection theory suggests that mobile animals trade off time, energy and risk costs with food, safety and other pay-offs obtained by movement. We examined how birds make movement decisions by integrating aspects of flight biomechanics, movement ecology and behaviour in a hierarchical framework investigating flight track variation across several spatio-temporal scales. Using extensive global positioning system and accelerometer data from Eurasian griffon vultures (Gyps fulvus) in Israel and France, we examined soaring-gliding decision-making by comparing inbound versus outbound flights (to or from a central roost, respectively), and these (and other) home-range foraging movements (up to 300 km) versus long-range movements (longer than 300 km). We found that long-range movements and inbound flights have similar features compared with their counterparts: individuals reduced journey time by performing more efficient soaring-gliding flight, reduced energy expenditure by flapping less and were more risk-prone by gliding more steeply between thermals. Age, breeding status, wind conditions and flight altitude (but not sex) affected time and energy prioritization during flights. We therefore suggest that individuals facing time, energy and risk trade-offs during movements make similar decisions across a broad range of ecological contexts and spatial scales, presumably owing to similarity in the uncertainty about movement outcomes.This article is part of the themed issue 'Moving in a moving medium: new perspectives on flight'.

Social foraging and individual consistency in following behaviour: testing the information centre hypothesis in free-ranging vultures

Uncertainties regarding food location and quality are among the greatest challenges faced by foragers and communal roosting may facilitate success through social foraging. The information centre hypothesis (ICH) suggests that uninformed individuals at shared roosts benefit from following informed individuals to previously visited resources. We tested several key prerequisites of the ICH in a social obligate scavenger, the Eurasian griffon vulture (Gyps fulvus), by tracking movements and behaviour of sympatric individuals over extended periods and across relatively large spatial scales, thereby precluding alternative explanations such as local enhancement. In agreement with the ICH, we found that 'informed' individuals returning to previously visited carcasses were followed by 'uninformed' vultures that consequently got access to these resources. When a dyad (two individuals that depart from the same roost within 2 min of each other) included an informed individual, they spent a higher proportion of the flight time close to each other at a shorter distance between them than otherwise. Although all individuals occasionally profited from following others, they differed in their tendencies to be informed or uninformed. This study provides evidence for 'following behaviour' in natural conditions and demonstrates differential roles and information states among foragers within a population. Moreover, demonstrating the possible reliance of vultures on following behaviour emphasizes that individuals in declining populations may suffer from reduced foraging efficiency.

When the going gets tough: behavioural type-dependent space use in the sleepy lizard changes as the season dries

Understanding space use remains a major challenge for animal ecology, with implications for species interactions, disease spread, and conservation. Behavioural type (BT) may shape the space use of individuals within animal populations. Bolder or more aggressive individuals tend to be more exploratory and disperse further. Yet, to date we have limited knowledge on how space use other than dispersal depends on BT. To address this question we studied BT-dependent space-use patterns of sleepy lizards (Tiliqua rugosa) in southern Australia. We combined high-resolution global positioning system (GPS) tracking of 72 free-ranging lizards with repeated behavioural assays, and with a survey of the spatial distributions of their food and refuge resources. Bayesian generalized linear mixed models (GLMM) showed that lizards responded to the spatial distribution of resources at the neighbourhood scale and to the intensity of space use by other conspecifics (showing apparent conspecific avoidance). BT (especially aggressiveness) affected space use by lizards and their response to ecological and social factors, in a seasonally dependent manner. Many of these effects and interactions were stronger later in the season when food became scarce and environmental conditions got tougher. For example, refuge and food availability became more important later in the season and unaggressive lizards were more responsive to these predictors. These findings highlight a commonly overlooked source of heterogeneity in animal space use and improve our mechanistic understanding of processes leading to behaviourally driven disease dynamics and social structure.

From Individuals to Groups and Back: The Evolutionary Implications of Group Phenotypic Composition

There is increasing interest in understanding the processes that maintain phenotypic variation in groups, populations, or communities. Recent studies have investigated how the phenotypic composition of groups or aggregations (e.g., its average phenotype or phenotypic variance) affects ecological and social processes, and how multi-level selection can drive phenotypic covariance among interacting individuals. However, we argue that these questions are rarely studied together. We present a unified framework to address this gap, and discuss how group phenotypic composition (GPC) can impact on processes ranging from individual fitness to population demography. By emphasising the breadth of topics affected, we hope to motivate more integrated empirical studies of the ecological and evolutionary implications of GPC.

AcceleRater: a web application for supervised learning of behavioral modes from acceleration measurements

BACKGROUND

The study of animal movement is experiencing rapid progress in recent years, forcefully driven by technological advancement. Biologgers with Acceleration (ACC) recordings are becoming increasingly popular in the fields of animal behavior and movement ecology, for estimating energy expenditure and identifying behavior, with prospects for other potential uses as well. Supervised learning of behavioral modes from acceleration data has shown promising results in many species, and for a diverse range of behaviors. However, broad implementation of this technique in movement ecology research has been limited due to technical difficulties and complicated analysis, deterring many practitioners from applying this approach. This highlights the need to develop a broadly applicable tool for classifying behavior from acceleration data.

DESCRIPTION

Here we present a free-access python-based web application called AcceleRater, for rapidly training, visualizing and using models for supervised learning of behavioral modes from ACC measurements. We introduce AcceleRater, and illustrate its successful application for classifying vulture behavioral modes from acceleration data obtained from free-ranging vultures. The seven models offered in the AcceleRater application achieved overall accuracy of between 77.68% (Decision Tree) and 84.84% (Artificial Neural Network), with a mean overall accuracy of 81.51% and standard deviation of 3.95%. Notably, variation in performance was larger between behavioral modes than between models.

CONCLUSIONS

AcceleRater provides the means to identify animal behavior, offering a user-friendly tool for ACC-based behavioral annotation, which will be dynamically upgraded and maintained.

Mixed strategies of griffon vultures' (Gyps fulvus) response to food deprivation lead to a hump-shaped movement pattern

BACKGROUND

The need to obtain food is a critical proximate driver of an organism's movement that shapes the foraging and survival of individual animals. Consequently, the relationship between hunger and foraging has received considerable attention, leading to the common conception that hunger primarily enhances a "food-intake maximization" (FIMax) strategy and intensive search. A complementary explanation, however, suggests a trade-off with precautions taken to reduce the risk of physiological collapse from starvation, under a strategy we denote as "energy-expenditure minimization" (EEMin). The FImax-EEmin trade-off may interact with the forager's hunger level to shape a complex (non-monotonic) response pattern to increasing hunger. Yet, this important trade-off has rarely been investigated, particularly in free-ranging wild animals. We explored how hunger affects the movements of adult griffon vultures (Gyps fulvus) in southern Israel. Transmitters combining GPS and accelerometers provided high-resolution data on vultures' movements and behavior, enabling the identification of feeding events and the estimation of food deprivation periods (FDPs, measured in days), which is used as a proxy for hunger.

RESULTS

Data from 47 vultures, tracked for 339 ± 36 days, reveal high variability in FDPs. While flight speed, flight straightness and the proportion of active flights were invariant in relation to food deprivation, a clear hump-shaped response was found for daily flight distances, maximal displacements and flight elevation. These movement characteristics increased during the first five days of the FDP sequence and decreased during the following five days. These characteristics also differed between short FDPs of up to four days, and the first four days of longer FDP sequences. These results suggest a switch from FIMax to EEMin strategies along the FDP sequence. They also indicate that vultures' response to hunger affected the eventual duration of the FDP. During winter (the vultures' incubation period characterized by unfavorable soaring meteorological conditions), the vultures' FIMax response was less intensive and resulted in longer starvation periods, while, in summer, more intensive FIMax response to hunger resulted in shorter FDPs.

CONCLUSIONS

Our results show a flexible, non-monotonic response of free-ranging wild animals to increasing hunger levels, reflecting a trade-off between increasing motivation to find food and the risk of starvation. The proposed trade-off offers a unifying perspective to apparently contradictory or case-specific empirical findings.

Using tri-axial acceleration data to identify behavioral modes of free-ranging animals: general concepts and tools illustrated for griffon vultures

Integrating biomechanics, behavior and ecology requires a mechanistic understanding of the processes producing the movement of animals. This calls for contemporaneous biomechanical, behavioral and environmental data along movement pathways. A recently formulated unifying movement ecology paradigm facilitates the integration of existing biomechanics, optimality, cognitive and random paradigms for studying movement. We focus on the use of tri-axial acceleration (ACC) data to identify behavioral modes of GPS-tracked free-ranging wild animals and demonstrate its application to study the movements of griffon vultures (Gyps fulvus, Hablizl 1783). In particular, we explore a selection of nonlinear and decision tree methods that include support vector machines, classification and regression trees, random forest methods and artificial neural networks and compare them with linear discriminant analysis (LDA) as a baseline for classifying behavioral modes. Using a dataset of 1035 ground-truthed ACC segments, we found that all methods can accurately classify behavior (80-90%) and, as expected, all nonlinear methods outperformed LDA. We also illustrate how ACC-identified behavioral modes provide the means to examine how vulture flight is affected by environmental factors, hence facilitating the integration of behavioral, biomechanical and ecological data. Our analysis of just over three-quarters of a million GPS and ACC measurements obtained from 43 free-ranging vultures across 9783 vulture-days suggests that their annual breeding schedule might be selected primarily in response to seasonal conditions favoring rising-air columns (thermals) and that rare long-range forays of up to 1750 km from the home range are performed despite potentially heavy energetic costs and a low rate of food intake, presumably to explore new breeding, social and long-term resource location opportunities.

Context-dependent flight speed: evidence for energetically optimal flight speed in the bat Pipistrellus kuhlii?

1. Understanding the causes and consequences of animal flight speed has long been a challenge in biology. Aerodynamic theory is used to predict the most economical flight speeds, minimizing energy expenditure either per distance (maximal range speed, Vmr) or per time (minimal power speed, Vmp). When foraging in flight, flight speed also affects prey encounter and energy intake rates. According to optimal flight speed theory, such effects may shift the energetically optimal foraging speed to above Vmp. 2. Therefore, we predicted that if energetic considerations indeed have a substantial effect on flight speed of aerial-hawking bats, they will use high speed (close to Vmr) to commute from their daily roost to the foraging sites, while a slower speed (but still above Vmp) will be preferred during foraging. To test these predictions, echolocation calls of commuting and foraging Pipistrellus kuhlii were recorded and their flight tracks were reconstructed using an acoustic flight path tracking system. 3. Confirming our qualitative prediction, commuting flight was found to be significantly faster than foraging flight (9.3 vs. 6.7 m s(-1)), even when controlling for its lower tortuosity. 4. In order to examine our quantitative prediction, we compared observed flight speeds with Vmp and Vmr values generated for the study population using two alternative aerodynamic models, based on mass and wing morphology variables measured from bats we captured while commuting. The Vmp and Vmr values generated by one of the models were much lower than our measured flight speed. According to the other model used, however, measured foraging flight was faster than Vmp and commuting flight slightly slower than Vmr, which is in agreement with the predictions of optimal flight speed theory. 5. Thus, the second aerodynamic model we used seems to be a reasonable predictor of the different flight speeds used by the bats while foraging and while commuting. This supports the hypothesis that bats fly at a context-dependent, energetically optimal flight speed.

Mechanisms of long-distance seed dispersal

Growing recognition of the importance of long-distance dispersal (LDD) of plant seeds for various ecological and evolutionary processes has led to an upsurge of research into the mechanisms underlying LDD. We summarize these findings by formulating six generalizations stating that LDD is generally more common in open terrestrial landscapes, and is typically driven by large and migratory animals, extreme meteorological phenomena, ocean currents and human transportation, each transporting a variety of seed morphologies. LDD is often associated with unusual behavior of the standard vector inferred from plant dispersal morphology, or mediated by nonstandard vectors. To advance our understanding of LDD, we advocate a vector-based research approach that identifies the significant LDD vectors and quantifies how environmental conditions modify their actions.

Incorporating dispersal distance into the disperser effectiveness framework: frugivorous birds provide complementary dispersal to plants in a patchy environment

Fleshy-fruited plants are usually dispersed by an array of frugivores, differing in the effectiveness of the dispersal service they provide to the plant. Body size differences among frugivores are hypothesized to affect seed dispersal distances and consequently their effectiveness as dispersers. We tested this hypothesis by comparing the effectiveness of two passerine birds, grackles (Onychognathus tristramii) and bulbuls (Pycnonotus xanthopygos), dispersing the desert shrub Ochradenus baccatus. Laboratory experiments, quantifying gut retention time and the effect on germination, were combined with field observations quantifying bird movements and fruit consumption rates. An empirically parameterized mechanistic model showed that the two dispersers switch roles as a function of spatial-scale: while most seeds within the local habitat were dispersed by bulbuls, the larger grackles were exclusively responsible for between-patches, long-distance dispersal. We suggest that distance-related differences are common and important to plant fitness, and thus should explicitly be considered in studies of disperser effectiveness.