Running on empty: recharge dynamics from animal movement data

Hooten, Mevin B.; Scharf, Henry R.; Morales, Juan Manuel

doi:10.1111/ele.13198

Cited by 30 publications

(40 citation statements)

References 86 publications

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“…An interesting development in that direction is by Hooten, Scharf, and Morales (2018), who present a new approach to analyse movement data, including explicit mechanistic links to physiological dynamics, to better model decision-making and movement in heterogeneous environments. Notably, this approach can be extended to accommodate additional data such as those provided by biologgers.…”

Section: Movement Analyses In the Biologging Eramentioning

confidence: 99%

Optimizing the use of biologgers for movement ecology research

Williams

Taylor

Benhamou

et al. 2019

Journal of Animal Ecology

225

233

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1. The paradigm-changing opportunities of biologging sensors for ecological research, especially movement ecology, are vast, but the crucial questions of how best to match the most appropriate sensors and sensor combinations to specific biological questions and how to analyse complex biologging data, are mostly ignored.2. Here, we fill this gap by reviewing how to optimize the use of biologging techniques to answer questions in movement ecology and synthesize this into an Integrated Biologging Framework (IBF).3. We highlight that multisensor approaches are a new frontier in biologging, while identifying current limitations and avenues for future development in sensor technology.4. We focus on the importance of efficient data exploration, and more advanced multidimensional visualization methods, combined with appropriate archiving and sharing approaches, to tackle the big data issues presented by biologging. We also discuss the challenges and opportunities in matching the peculiarities of specific sensor data to the statistical models used, highlighting at the same time the large advances which will be required in the latter to properly analyse biologging data.

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Section: Movement Analyses In the Biologging Eramentioning

confidence: 99%

Optimizing the use of biologgers for movement ecology research

Williams

Taylor

Benhamou

et al. 2019

Journal of Animal Ecology

225

233

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“…its lethality) prey Brown et al 2016). This variation can range from being highly dynamic, as when predator hunger elicits increased foraging activity (Hooten et al 2019), to persistent, as when aggressive behavioural types are more likely to attack prey given an encounter (e.g. Michalko & Re zucha 2018).…”

Section: Properties Of the Predatormentioning

confidence: 99%

The context dependence of non‐consumptive predator effects

et al. 2020

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Non-consumptive predator effects (NCEs) are now widely recognised for their capacity to shape ecosystem structure and function. Yet, forecasting the propagation of these predator-induced trait changes through particular communities remains a challenge. Accordingly, focusing on plasticity in prey anti-predator behaviours, we conceptualise the multi-stage process by which predators trigger direct and indirect NCEs, review and distil potential drivers of contingencies into three key categories (properties of the prey, predator and setting), and then provide a general framework for predicting both the nature and strength of direct NCEs. Our review underscores the myriad factors that can generate NCE contingencies while guiding how research might better anticipate and account for them. Moreover, our synthesis highlights the value of mapping both habitat domains and prey-specific patterns of evasion success ('evasion landscapes') as the basis for predicting how direct NCEs are likely to manifest in any particular community. Looking ahead, we highlight two key knowledge gaps that continue to impede a comprehensive understanding of non-consumptive predator-prey interactions and their ecosystem consequences; namely, insufficient empirical exploration of (1) context-dependent indirect NCEs and (2) the ways in which direct and indirect NCEs are shaped interactively by multiple drivers of context dependence.

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“…In this study, we demonstrated that the interplay between memory and resource preferences is sufficient to explain the formation of animal home ranges following reintroduction to a novel environment, and thus contributing to our understanding of the space-use implications of movement behaviour. The approach utilised here could be expanded to model the interconnections between movement behaviour and energy acquisition and consumption 56 , providing a framework to quantitatively characterize the fitness, and demographic consequences of animal movement patterns, and space-use 57 .…”

Section: For a Cognitive Model Including Perception And Memory)mentioning

confidence: 99%

Memory drives the formation of animal home ranges: evidence from a reintroduction

Ranc

Cagnacci

Moorcroft

2020

Preprint

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Most animals live in a characteristic home range, a space-use pattern thought to emerge from the benefits of memory-based movements; however, a general model for characterizing and predicting their formation in the absence of territoriality has been lacking. Here, we use a mechanistic movement model to quantify the role of memory in the movements of a large mammal reintroduced into a novel environment, and to predict observed patterns of home range emergence. We show that an interplay between memory and resource preferences is the primary process influencing the movements of reintroduced roe deer (Capreolus capreolus). Our memory-based model fitted with empirical data successfully predicts the formation of home ranges, as well as emerging properties of movement and revisits observed in the reintroduced animals. These results provide a quantitative framework for combining memory-based movements, resource preference and the emergence of home ranges in nature.

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Running on empty: recharge dynamics from animal movement data

Cited by 30 publications

References 86 publications

Optimizing the use of biologgers for movement ecology research

Optimizing the use of biologgers for movement ecology research

The context dependence of non‐consumptive predator effects

Memory drives the formation of animal home ranges: evidence from a reintroduction

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