A Methodological Framework to Estimate the Site Fidelity of Tagged Animals Using Passive Acoustic Telemetry

The rapid expansion of the use of passive acoustic telemetry technologies has facilitated unprecedented opportunities for studying the behavior of marine organisms in their natural environment. This technological advance would greatly benefit from the parallel development of dedicated methodologies accounting for the variety of timescales involved in the remote detection of tagged animals related to instrumental, environmental and behavioral events. In this paper we propose a methodological framework for estimating the site fidelity (“residence times”) of acoustic tagged animals at different timescales, based on the survival analysis of continuous residence times recorded at multiple receivers. Our approach is validated through modeling and applied on two distinct datasets obtained from a small coastal pelagic species (bigeye scad, Selar crumenophthalmus) and a large, offshore pelagic species (yellowfin tuna, Thunnus albacares), which show very distinct spatial scales of behavior. The methodological framework proposed herein allows estimating the most appropriate temporal scale for processing passive acoustic telemetry data depending on the scientific question of interest. Our method provides residence times free of the bias inherent to environmental and instrumental noise that can be used to study the small scale behavior of acoustic tagged animals. At larger timescales, it can effectively identify residence times that encompass the diel behavioral excursions of fish out of the acoustic detection range. This study provides a systematic framework for the analysis of passive acoustic telemetry data that can be employed for the comparative study of different species and study sites. The same methodology can be used each time discrete records of animal detections of any nature are employed for estimating the site fidelity of an animal at different timescales.     

Territory surveillance and prey management: Wolves keep track of space and time

Identifying behavioral mechanisms that underlie observed movement patterns is difficult when animals employ sophisticated cognitive‐based strategies. Such strategies may arise when timing of return visits is important, for instance to allow for resource renewal or territorial patrolling. We fitted spatially explicit random‐walk models to GPS movement data of six wolves (Canis lupus; Linnaeus, 1758) from Alberta, Canada to investigate the importance of the following: (1) territorial surveillance likely related to renewal of scent marks along territorial edges, to reduce intraspecific risk among packs, and (2) delay in return to recently hunted areas, which may be related to anti‐predator responses of prey under varying prey densities. The movement models incorporated the spatiotemporal variable “time since last visit,” which acts as a wolf's memory index of its travel history and is integrated into the movement decision along with its position in relation to territory boundaries and information on local prey densities. We used a model selection framework to test hypotheses about the combined importance of these variables in wolf movement strategies. Time‐dependent movement for territory surveillance was supported by all wolf movement tracks. Wolves generally avoided territory edges, but this avoidance was reduced as time since last visit increased. Time‐dependent prey management was weak except in one wolf. This wolf selected locations with longer time since last visit and lower prey density, which led to a longer delay in revisiting high prey density sites. Our study shows that we can use spatially explicit random walks to identify behavioral strategies that merge environmental information and explicit spatiotemporal information on past movements (i.e., “when” and “where”) to make movement decisions. The approach allows us to better understand cognition‐based movement in relation to dynamic environments and resources.     

How area restricted search of a pelagic seabird changes while performing a dual foraging strategy

Movements and foraging strategies of marine predators should cope with the hierarchical spatial distribution of resources. Therefore, in order to predict the at‐sea distribution of aerial predators, it is crucial to understand the factors governing trajectory decisions at different scales. Using first passage time (FPT) analysis on precision tracking information (GPS‐loggers data) we were able to examine the foraging strategy of Cory's shearwaters Calonectris diomedea and to detect the adoption of area‐restricted search (ARS), measuring the scale and duration of this behaviour. Data were collected from three different populations foraging in different oceanographic conditions. During long excursions birds only commuted between their colony and prey patches, while on their short movements birds increased the amount of looping movements. On short trips, birds addopted ARS behaviour at an average scale of 18 km and at a second nested scale of around 2 km. When engaging in long trips, first scale of ARS occurred on average at about 67 km of radii and than a second nested scale at a radii of 24 km. Overall, the different populations showed foraging patterns matching the habitats exploited: a) at smaller scales of ARS, sea‐surface temperature, chlorophyll‐a concentration and depth influenced the time of residence (i.e. FPT) of birds (with variations at a population level); b) at larger scales of ARS, FPT increased within regions of higher gradients of sea‐surface temperature, chlorophyl‐a concentration and depth. This study demonstrates that Cory's shearwaters adopt scale‐dependent adjustments of movement in relation to the hierarchical distribution of the environment they exploit, matching the scale and duration of ARS with the hierarchical distribution of the environmental features.     

A framework for testing assumptions about foraging scales,body mass,and niche separation using telemetry data

Ecological theory predicts that if animals with very similar dietary requirements inhabit the same landscape, then they should avoid niche overlap by either exploiting food resources at different times or foraging at different spatial scales. Similarly, it is often assumed that animals that fall in different body mass modes and share the same body plan will use landscapes at different spatial scales. We developed a new methodological framework for understanding the scaling of foraging (i.e. the range and distribution of scales at which animals use their landscapes) by applying a combination of three well‐established methods to satellite telemetry data to quantify foraging patch size distributions: (1) first‐passage time analysis; (2) a movement‐based kernel density estimator; and (3) statistical comparison of resulting histograms and tests for multimodality. We demonstrate our approach using two sympatric, ecologically similar species of African ducks with quite different body masses: Egyptian Geese (actually a shelduck), and Red‐billed Teal. Contrary to theoretical predictions, the two species, which are sympatric throughout the year, foraged at almost identical spatial scales. Our results show how ecologists can use GPS tracking data to explicitly quantify and compare the scales of foraging by different organisms within an animal community. Our analysis demonstrates both a novel approach to foraging data analysis and the need for caution when making assumptions about the relationships among niche separation, diet, and foraging scale.     

Spatial memory shapes migration and its benefits: evidence from a large herbivore

From fine‐scale foraging to broad‐scale migration, animal movement is shaped by the distribution of resources. There is mounting evidence, however, that learning and memory also guide movement. Although migratory mammals commonly track resource waves, how resource tracking and memory guide long‐distance migration has not been reconciled. We examined these hypotheses using movement data from four populations of migratory mule deer (n = 91). Spatial memory had an extraordinary influence on migration, affecting movement 2–28 times more strongly than tracking spring green‐up or autumn snow depth. Importantly, with only an ability to track resources, simulated deer were unable to recreate empirical migratory routes. In contrast, simulated deer with memory of empirical routes used those routes and obtained higher foraging benefits. For migratory terrestrial mammals, spatial memory provides knowledge of where seasonal ranges and migratory routes exist, whereas resource tracking determines when to beneficially move within those areas.     

Large‐scale movement behavior in a reintroduced predator population

Understanding movement behavior and identifying areas of landscape connectivity is critical for the conservation of many species. However, collecting fine‐scale movement data can be prohibitively time consuming and costly, especially for rare or endangered species, whereas existing data sets may provide the best available information on animal movement. Contemporary movement models may not be an option for modeling existing data due to low temporal resolution and large or unusual error structures, but inference can still be obtained using a functional movement modeling approach. We use a functional movement model to perform a population‐level analysis of telemetry data collected during the reintroduction of Canada lynx to Colorado. Little is known about southern lynx populations compared to those in Canada and Alaska, and inference is often limited to a few individuals due to their low densities. Our analysis of a population of Canada lynx fills significant gaps in the knowledge of Canada lynx behavior at the southern edge of its historical range. We analyzed functions of individual‐level movement paths, such as speed, residence time, and tortuosity, and identified a region of connectivity that extended north from the San Juan Mountains, along the continental divide, and terminated in Wyoming at the northern edge of the Southern Rocky Mountains. Individuals were able to traverse large distances across non‐boreal habitat, including exploratory movements to the Greater Yellowstone area and beyond. We found evidence for an effect of seasonality and breeding status on many of the movement quantities and documented a potential reintroduction effect. Our findings provide the first analysis of Canada lynx movement in Colorado and substantially augment the information available for conservation and management decisions. The functional movement framework can be extended to other species and demonstrates that information on movement behavior can be obtained using existing data sets.     

Animal movement in the absence of predation: environmental drivers of movement strategies in a partial migration system

Animal movement strategies including migration, dispersal, nomadism, and residency are shaped by broad‐scale spatial‐temporal structuring of the environment, including factors such as the degrees of spatial variation, seasonality and inter‐annual predictability. Animal movement strategies, in turn, interact with the characteristics of individuals and the local distribution of resources to determine local patterns of resource selection with complex and poorly understood implications for animal fitness. Here we present a multi‐scale investigation of animal movement strategies and resource selection. We consider the degree to which spatial variation, seasonality, and inter‐annual predictability in resources drive migration patterns among different taxa and how movement strategies in turn shape local resource selection patterns. We focus on adult Galapagos giant tortoises Chelonoidis spp. as a model system since they display many movement strategies and evolved in the absence of predators of adults. Specifically, our analysis is based on 63 individuals among four taxa tracked on three islands over six years and almost 10⁶ tortoise re‐locations. Tortoises displayed a continuum of movement strategies from migration to sedentarism that were linked to the spatio‐temporal scale and predictability of resource distributions. Movement strategies shaped patterns of resource selection. Specifically, migratory individuals displayed stronger selection toward areas where resources were more predictable among years than did non‐migratory individuals, which indicates a selective advantage for migrants in seasonally structured, more predictable environments. Our analytical framework combines large‐scale predictions for movement strategies, based on environmental structuring, with finer‐scale analysis of space‐use. Integrating different organizational levels of analysis provides a deeper understanding of the eco‐evolutionary dynamics at play in the emergence and maintenance of migration and the critical role of resource predictability. Our results highlight that assessing the potential benefits of differential behavioral responses first requires an understanding of the interactions among movement strategies, resource selection and individual characteristics.     

Context dependency of animal resource subsidies

The transport of resource subsidies by animals has been documented across a range of species and ecosystems. Although many of these studies have shown that animal resource subsidies can have significant effects on nutrient cycling, ecosystem productivity, and food‐web structure, there is a great deal of variability in the occurrence and strength of these effects. Here we propose a conceptual framework for understanding the context dependency of animal resource subsidies, and for developing and testing predictions about the effects of animal subsidies over space and time. We propose a general framework, in which abiotic characteristics and animal vector characteristics from the donor ecosystem interact to determine the quantity, quality, timing, and duration (QQTD) of an animal input. The animal input is translated through the lens of recipient ecosystem characteristics, which include both abiotic and consumer characteristics, to yield the QQTD of the subsidy. The translated subsidy influences recipient ecosystem dynamics through effects on both trophic structure and ecosystem function, which may both influence the recipient ecosystem's response to further inputs and feed back to influence the donor ecosystem. We present a review of research on animal resource subsidies across ecosystem boundaries, placed within the context of this framework, and we discuss how the QQTD of resource subsidies can influence trophic structure and ecosystem function in recipient ecosystems. We explore the importance of understanding context dependency of animal resource subsidies in increasingly altered ecosystems, in which the characteristics of both animal vectors and donor and recipient ecosystems may be changing rapidly. Finally, we make recommendations for future research on animal resource subsidies, and resource subsidies in general, that will increase our understanding and predictive capacity about their ecosystem effects.     

State‐space modeling reveals habitat perception of a small terrestrial mammal in a fragmented landscape

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Modelling large herbivore movement decisions: Beyond food availability as a predictor of ranging patterns

The ability of animals to adapt to their changing environment will depend in part on shifts in their ranging patterns, but when and why individuals choose to move requires detailed understanding of their decision‐making processes. We develop a simple decision‐making model accounting for resource availability in habitually used ranges. We suggest that disparities between model predictions and animal tracking data indicate additional factors influencing movement decisions, which may be identified given detailed system‐specific knowledge. The model was evaluated using movement data from satellite‐tracked elephants (Loxodonta africana) inhabiting the Amboseli basin in Kenya, moving from savannah areas with low quality but constant resource availability, to areas with temporally constrained higher nutrient availability. Overall, the model fits the data well: There was a good correlation between predicted and observed locations for the combined data from all elephants, but variation between individuals in how well the model fits. For those elephants where model predictions were less successful, additional factors likely to affect movement decisions, including reproduction, anthropogenic threats, memory and perception are suggested. This protocol for building and testing decision‐making models should contribute to success in attempts to preserve sufficient space for large herbivores in their increasingly human‐dominated ecosystems.     

Animal movement in dynamic landscapes: interaction between behavioural strategies and resource distributions

Most ecological and evolutionary processes are thought to critically depend on dispersal and individual movement but there is little empirical information on the movement strategies used by animals to find resources. In particular, it is unclear whether behavioural variation exists at all scales, or whether behavioural decisions are primarily made at small spatial scales and thus broad-scale patterns of movement simply reflect underlying resource distributions. We evaluated animal movement responses to variable resource distributions using the grey teal (Anas gracilis) in agricultural and desert landscapes in Australia as a model system. Birds in the two landscapes differed in the fractal dimension of their movement paths, with teal in the desert landscape moving less tortuously overall than their counterparts in the agricultural landscape. However, the most striking result was the high levels of individual variability in movement strategies, with different animals exhibiting different responses to the same resources. Teal in the agricultural basin moved with both high and low tortuosity, while teal in the desert basin primarily moved using low levels of tortuosity. These results call into question the idea that broad-scale movement patterns simply reflect underlying resource distributions, and suggest that movement responses in some animals may be behaviourally complex regardless of the spatial scale over which movement occurs.     

From random walks to informed movement

The analysis of animal movement is a large and continuously growing field of research. Detailed knowledge about movement strategies is of crucial importance for understanding eco‐evolutionary dynamics at all scales – from individuals to (meta‐)populations. This and the availability of detailed movement and dispersal data motivated Nathan and colleagues to published their much appreciated call to base movement ecology on a more thorough mechanistic basis. So far, most movement models are based on random walks. However, even if a random walk might describe real movement patterns acceptably well, there is no reason to assume that animals move randomly. Therefore, mechanistic models of foraging strategies should be based on information use and memory in order to increase our understanding of the processes that lead to animal movement decisions. We present a mechanistic movement model of an animal with a limited perceptual range and basic information storage capacities. This ‘spatially informed forager’ constructs an internal map of its environment by using perception, memory and learned or evolutionarily acquired assumptions about landscape attributes. We analyse resulting movement patterns and search efficiencies and compare them to area restricted search strategies (ARS) and biased correlated random walks (BCRW) of omniscient individuals. We show that, in spite of their limited perceptual range, spatially informed individuals boost their foraging success and may perform much better than the best ARS. The construction of an internal map and the use of spatial information results in the emergence of a highly correlated walk between patches and a rather systematic search within resource clusters. Furthermore, the resulting movement patterns may include foray search behaviour. Our work highlights the strength of mechanistic modelling approaches and sets the stage for the development of more sophisticated models of memory use for movement decisions and dispersal.     

Scale-dependent hierarchical adjustments of movement patterns in a long-range foraging seabird

Foraging animals are expected to adjust their path according to the hierarchical spatial distribution of food resources and environmental factors. Studying such behaviour requires methods that allow for the detection of changes in pathways' characteristics across scales, i.e. a definition of scale boundaries and techniques to continuously monitor the precise movement of the animal over a sufficiently long period. We used a recently developed application of fractals, the changes in fractal dimension within a path and applied it to foraging trips over scales ranging across five orders of magnitude (10 m to 1000 km), using locations of wandering albatrosses (Diomedea exulans) recorded at 1 s intervals with a miniaturized global positioning system. Remarkably, all animals consistently showed the same pattern: the use of three scale-dependent nested domains where they adjust tortuosity to different environmental and behavioural constraints. At a small scale (ca. 100 m) they use a zigzag movement as they continuously adjust for optimal use of wind; at a medium scale (1-10 km), the movement shows changes in tortuosity consistent with food-searching behaviour; and at a large scale (greater than 10 km) the movement corresponds to commuting between patches and is probably influenced by large-scale weather systems. Our results demonstrate the possibility of identifying the hierarchical spatial scales at which long-ranging animals adjust their foraging behaviour, even in featureless environments such as oceans, and hence how to relate their movement patterns to environmental factors using an objective mathematical approach.     

Using animal movement paths to measure response to spatial scale

Animals live in an environment that is patchy and hierarchical. I present a method of detecting the scales at which animals perceive their world. The hierarchical nature of habitat causes movement path structure to vary with spatial scale, and the patchy nature of habitat causes movement path structure to vary throughout space. These responses can be measured by a combination of path tortuousity (measured with fractal dimension) versus spatial scale, the variation in tortuousity of small path segments along the movement path, and the correlation between tortuousities of adjacent path segments. These statistics were tested using simulated animal movements. When movement paths contained no spatial heterogeneity, then fractal D and variance continuously increased with scale, and correlation was zero at all scales. When movement paths contained spatial heterogeneity, then fractal D sometimes showed a discontinuity at transitions between domains of scale, variation showed peaks at transitions, and correlations showed a statistically significant positive value at scales smaller than patch size, decreasing to below zero at scales greater than patch size. I illustrated these techniques with movement paths from deer mice and red-backed voles. These new analyses should help understand how animals perceive and react to their landscape structure at various spatial scales, and to answer questions about how habitat structure affects animal movement patterns.     

Running on empty: recharge dynamics from animal movement data

Vital rates such as survival and recruitment have always been important in the study of population and community ecology. At the individual level, physiological processes such as energetics are critical in understanding biomechanics and movement ecology and also scale up to influence food webs and trophic cascades. Although vital rates and population‐level characteristics are tied with individual‐level animal movement, most statistical models for telemetry data are not equipped to provide inference about these relationships because they lack the explicit, mechanistic connection to physiological dynamics. We present a framework for modelling telemetry data that explicitly includes an aggregated physiological process associated with decision making and movement in heterogeneous environments. Our framework accommodates a wide range of movement and physiological process specifications. We illustrate a specific model formulation in continuous‐time to provide direct inference about gains and losses associated with physiological processes based on movement. Our approach can also be extended to accommodate auxiliary data when available. We demonstrate our model to infer mountain lion (Puma concolor; in Colorado, USA) and African buffalo (Syncerus caffer; in Kruger National Park, South Africa) recharge dynamics.     

Combining animal movements and behavioural data to detect behavioural states

Animal movement paths show variation in space caused by qualitative shifts in behaviours. I present a method that (1) uses both movement path data and ancillary sensor data to detect natural breakpoints in animal behaviour and (2) groups these segments into different behavioural states. The method can also combine analyses of different path segments or paths from different individuals. It does not assume any underlying movement mechanism. I give an example with simulated data. I also show the effects of random variation, # of states and # of segments on this method. I present a case study of a fisher movement path spanning 8 days, which shows four distinct behavioural states divided into 28 path segments when only turning angles and speed were considered. When accelerometer data were added, the analysis shows seven distinct behavioural states divided into 41 path segments.     

First Passage Time Analysis of Animal Movement and Insights into the Functional Response

Movement plays a role in structuring the interactions between individuals, their environment, and other species. Although movement models coupled with empirical data are widely used to study animal distribution, they have seldom been used to study search time. This paper proposes first passage time as a novel approach for understanding the effect of the landscape on animal movement and search time. In the context of animal movement, first passage time is the time taken for an animal to reach a specified site for the first time. We synthesize current first passage time theory and derive a general first passage time equation for animal movement. This equation is related to the Fokker–Planck equation, which is used to describe the distribution of animals in the landscape. We illustrate the first passage time method by analyzing the effect of territorial behavior on the time required for a red fox to locate prey throughout its home range. Using first passage time to compute search times, we consider the effect of two different searching modes on a functional response. We show that random searching leads to a Holling type III functional response. First passage time analysis provides a new tool for studying how animal movement may influence ecological processes.     

Does prey capture induce area-restricted search? A fine-scale study using GPS in a marine predator, the wandering albatross

In a patchy environment, predators are expected to increase turning rate and start an area-restricted search (ARS) when prey have been encountered, but few empirical data exist for large predators. By using GPS loggers with devices measuring prey capture, we studied how a marine predator adjusts foraging movements at various scales in relation to prey capture. Wandering albatrosses use two tactics, sit and wait and foraging in flight, the former tactic being three times less efficient than the latter. During flight foraging, birds caught large isolated prey and used ARS at scales varying from 5 to 90 km, with large-scale ARS being used only by young animals. Birds did not show strong responses to prey capture at a large scale, few ARS events occurred after prey capture, and birds did not have high rates of prey capture in ARS. Only at small scales did birds increase sinuosity after prey captures for a limited time period, and this occurred only after they had caught a large prey item within an ARS zone. When this species searches over a large scale, the most effective search rule was to follow a nearly straight path. ARS may be used to restrict search to a particular environment where prey capture is more predictable and profitable.     

A dynamic Brownian bridge movement model to estimate utilization distributions for heterogeneous animal movement

1.?The recently developed Brownian bridge movement model (BBMM) has advantages over traditional methods because it quantifies the utilization distribution of an animal based on its movement path rather than individual points and accounts for temporal autocorrelation and high data volumes. However, the BBMM assumes unrealistic homogeneous movement behaviour across all data. 2.?Accurate quantification of the utilization distribution is important for identifying the way animals use the landscape. 3.?We improve the BBMM by allowing for changes in behaviour, using likelihood statistics to determine change points along the animal's movement path. 4.?This novel extension, outperforms the current BBMM as indicated by simulations and examples of a territorial mammal and a migratory bird. The unique ability of our model to work with tracks that are not sampled regularly is especially important for GPS tags that have frequent failed fixes or dynamic sampling schedules. Moreover, our model extension provides a useful one-dimensional measure of behavioural change along animal tracks. 5.?This new method provides a more accurate utilization distribution that better describes the space use of realistic, behaviourally heterogeneous tracks.     

The Debate About Bait: A Red Herring in Wildlife Research

The use of bait (or attractants) to lure animals to a sampling site is common in wildlife research and important for optimizing species detection rates. The effect of bait on animal movement and space-use, however, is contested, fueled by concerns bait may affect animal movement and increase residency time. If founded, bait may bias parameter estimates from density, species distribution, resource selection, or behavioral models, produce spurious ecological inferences, and skew resulting management recommendations. To test whether animal movement varies with proximity to bait, we used high-resolution global positioning system telemetry data of 10 fishers (Pekania pennanti), temporally paired with 64 baited wildlife camera traps, to quantify the effect of bait on individual and population movement metrics. Although bait appeared to have a significant correlative effect on 1-hour movement segments, landscape characteristics had an effect 1.7 times greater, where the proportion of mixed forest and cultivation explained the majority of variability in animal movements. We contend that maximizing probability of detection and controlling or modeling local-scale landscape variability that could affect the probability of detection is a more important consideration in wildlife research than the effect of bait, which is eclipsed by differences incurred by natural habitat heterogeneity. Failing to maximize the probability of detection may obscure the modest bias potentially presented by the use of bait, or attractants, on ecological inference. © 2019 The Wildlife Society