Intrinsic traits, social context, and local environment shape home range size and fidelity of sleepy lizards

Active crocodiles are less sociable

How animals move and associate with conspecifics is rarely random, with a population's spatial structure forming the foundation on which the social behaviours of individuals form. Studies examining the spatial-social interface typically measure averaged behavioural differences between individuals; however, this neglects the inherent variation present within individuals and how it may impact the spatial-social interface. Here, we investigated differences in among-individual (co)variance in sociability, activity and site fidelity in a population of wild estuarine crocodiles, Crocodylus porosus, across a 10-year period. By monitoring 118 crocodiles using coded acoustic transmitters and an array of fixed underwater receivers, we discovered that not only did individual crocodiles repeatably differ (among-individual variation) in each behaviour measured but also in how consistently they expressed these behaviours through time (within-individual variation). As expected, crocodile activity and sociability formed a behavioural syndrome, with more active individuals being less sociable. Interestingly, we also found that individuals that were either more sociable or displayed greater site fidelity were also more specialized (lower within-individual variation) in these behaviours. Together, our results provide important empirical evidence for the interplay between spatial, temporal and social individual-level behavioural variation and how these contribute to forming behavioural niches. This article is part of the theme issue 'The spatial-social interface: a theoretical and empirical integration'.

The statistical building blocks of animal movement simulations

Animal movement plays a key role in many ecological processes and has a direct influence on an individual's fitness at several scales of analysis (i.e., next-step, subdiel, day-by-day, seasonal). This highlights the need to dissect movement behavior at different spatio-temporal scales and develop hierarchical movement tools for generating realistic tracks to supplement existing single-temporal-scale simulators. In reality, animal movement paths are a concatenation of fundamental movement elements (FuMEs: e.g., a step or wing flap), but these are not generally extractable from a relocation time-series track (e.g., sequential GPS fixes) from which step-length (SL, aka velocity) and turning-angle (TA) time series can be extracted. For short, fixed-length segments of track, we generate their SL and TA statistics (e.g., means, standard deviations, correlations) to obtain segment-specific vectors that can be cluster into different types. We use the centroids of these clusters to obtain a set of statistical movement elements (StaMEs; e.g.,directed fast movement versus random slow movement elements) that we use as a basis for analyzing and simulating movement tracks. Our novel concept is that sequences of StaMEs provide a basis for constructing and fitting step-selection kernels at the scale of fixed-length canonical activity modes: short fixed-length sequences of interpretable activity such as dithering, ambling, directed walking, or running. Beyond this, variable length pure or characteristic mixtures of CAMs can be interpreted as behavioral activity modes (BAMs), such as gathering resources (a sequence of dithering and walking StaMEs) or beelining (a sequence of fast directed-walk StaMEs interspersed with vigilance and navigation stops). Here we formulate a multi-modal, step-selection kernel simulation framework, and construct a 2-mode movement simulator (Numerus ANIMOVER_1), using Numerus RAMP technology. These RAMPs run as stand alone applications: they require no coding but only the input of selected parameter values. They can also be used in R programming environments as virtual R packages. We illustrate our methods for extracting StaMEs from both ANIMOVER_1 simulated data and empirical data from two barn owls (Tyto alba) in the Harod Valley, Israel. Overall, our new bottom-up approach to path segmentation allows us to both dissect real movement tracks and generate realistic synthetic ones, thereby providing a general tool for testing hypothesis in movement ecology and simulating animal movement in diverse contexts such as evaluating an individual's response to landscape changes, release of an individual into a novel environment, or identifying when individuals are sick or unusually stressed.

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.

Predator-mediated interactions through changes in predator home range size can lead to local prey exclusion

The strength of indirect biotic interactions is difficult to quantify in the wild and can alter community composition. To investigate whether the presence of a prey species affects the population growth rate of another prey species, we quantified predator-mediated interaction strength using a multi-prey mechanistic model of predation and a population matrix model. Models were parametrized using behavioural, demographic and experimental data from a vertebrate community that includes the arctic fox (Vulpes lagopus), a predator feeding on lemmings and eggs of various species such as sandpipers and geese. We show that the positive effects of the goose colony on sandpiper nesting success (due to reduction of search time for sandpiper nests) were outweighed by the negative effect of an increase in fox density. The fox numerical response was driven by changes in home range size. As a result, the net interaction from the presence of geese was negative and could lead to local exclusion of sandpipers. Our study provides a rare empirically based model that integrates mechanistic multi-species functional responses and behavioural processes underlying the predator numerical response. This is an important step forward in our ability to quantify the consequences of predation for community structure and dynamics.

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.

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.