Defining null expectations for animal site fidelity

Picardi, Simona; Abrahms, Briana; Gelzer, Emily; Morrison, Thomas A.; Verzuh, Tana L.; Merkle, Jerod A.

doi:10.1111/ele.14148

Cited by 8 publications

(12 citation statements)

References 76 publications

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“…On the one hand, we might expect mild to moderate collinearity between familiarity covariates and other important environmental drivers, which can make it challenging to quantify their unique contributions (Picardi et al, 2023). On the other hand, accounting for familiarity and memory effects should reduce bias associated with estimators of habitat-selection strength.…”

Section: Discussionmentioning

confidence: 99%

“…A notable limitation of this approach is the risk of overestimating the importance of familiarity due to unaccounted-for habitat attributes (e.g. if the OD reflects the distribution of an unobserved resource; see Picardi et al 2023). The OD approach further necessitates that users choose an appropriate time window in the past for calculating the OD (Figure 1).…”

Section: Exploring How Memory Influences Animal Movements Using Ssasmentioning

confidence: 99%

“…For example, we used berries as a seasonal resource covariate. However, the importance of the memory covariate (TSLV) might change if additional environmental covariates are added to the model (Picardi et al, 2023). Similar to Merkle et al (2019), Thompson et al (2022b) compared their models with memory to “resource-only” models without memory, finding that the former models better fit the data.…”

Section: Brown Bear – Time Since Last Visit (Tslv)mentioning

confidence: 99%

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Identifying signals of memory from observations of animal movements

Kim,

Thompson,

Wolfson

et al. 2023

Preprint

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Incorporating memory (i.e., some notion of familiarity or experience with the landscape) into models of animal movement is a rising challenge in the field of movement ecology. The recent proliferation of new methods offers new opportunities to understand how memory influences movement. However, there are no clear guidelines for practitioners wishing to parameterize the effects of memory on moving animals. We review approaches for incorporating memory into Step-Selection Analyses (SSAs), a frequently used movement modeling framework. Memory-informed SSAs can be constructed by including spatial-temporal covariates (or maps) that define some aspect of familiarity (e.g., whether, how often, or how long ago the animal visited different spatial locations) derived from long-term telemetry data. We demonstrate how various familiarity covariates can be included in SSAs using a series of coded examples in which we fit models to wildlife tracking data from a wide range of taxa. We discuss how these different approaches can be used to address questions related to whether and how animals use information from past experiences to inform their future movements. By reviewing different approaches and providing code templates for their implementation, we hope to inspire practitioners to further investigate the importance of memory in animal movements using wildlife tracking data.

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Section: Discussionmentioning

confidence: 99%

Section: Exploring How Memory Influences Animal Movements Using Ssasmentioning

confidence: 99%

Section: Brown Bear – Time Since Last Visit (Tslv)mentioning

confidence: 99%

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Identifying signals of memory from observations of animal movements

Kim,

Thompson,

Wolfson

et al. 2023

Preprint

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“…Similar to our case study, one can evaluate whether the observed and simulated paths exhibit similar behaviour near roads, rivers, or other prominent environmental features. Second, our simulator can be used as a way to develop a null distribution to test for evidence of site fidelity and/or memory (Picardi et al., 2023). One can, for example, simulate movement in the absence of home‐ranging behaviour and/or absence of habitat selection and contrast emerging patterns with more complex models.…”

Section: Discussionmentioning

confidence: 99%

Simulating animal space use from fitted integrated Step‐Selection Functions (iSSF)

Signer,

Fieberg,

Reineking

et al. 2023

Methods Ecol Evol

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A standing challenge in the study of animal movement ecology is the capacity to predict where and when an individual animal might occur on the landscape, the so‐called, utilisation distribution (UD). Under certain assumptions, the steady‐state UD can be predicted from a fitted exponential habitat selection function. However, these assumptions are rarely met. Furthermore, there are many applications that require the estimation of transient dynamics rather than steady‐state UDs (e.g. when modelling migration or dispersal). Thus, there is a clear need for computational tools capable of predicting UDs based on observed animal movement data. Integrated Step‐Selection Analyses (iSSAs), which integrates movement of the animal into habitat selection analyses, are widely used to study habitat selection and movement of wild animals, and result in a fully parametrised individual‐based model of animal movement, which we refer to as an integrated Step Selection Function (iSSF). An iSSF can be used to generate stochastic animal paths based on random draws from a series of Markovian redistribution kernels, each consisting of a selection‐free, but possibly habitat‐influenced, movement kernel and a movement‐free selection function. The UD can be approximated by a sufficiently large set of such stochastic paths. Here, we present a set of functions in R to facilitate the simulation of animal space use from fitted iSSFs. Our goal is to provide a general purpose simulator that is easy to use and is part of an existing workflow for iSSAs (within the amt R package). We demonstrate through a series of applications how the simulator can be used to address a variety of questions in applied movement ecology. By providing functions in amt and coded examples, we hope to encourage ecologists using iSSFs to explore their predictions and model goodness‐of‐fit using simulations, and to further explore mechanistic approaches to modelling landscape connectivity.

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“…The residuals for the final model were evaluated with the "DHARMa" package (Hartig & Hartig, 2017). We used the "fidelity" package in R (Picardi et al, 2023) to estimate site fidelity on the basis of the Blischke-Scheuer method-of-moments estimator, which calculates the step length parameters of shape and scale for a comparison with simulated toad movements according to a Correlated Random Walk (CRW). We included every toad with 3 or more relocations after the removal of the initial capture points in this analysis.…”

Section: Distance Movedmentioning

confidence: 99%

A Combination of Environmental and Landscape Variables Drive Movement and Habitat use in TwoAnaxyrussp. in the Eastern Coastal Plain

Ferentinos,

Check,

Windorf

et al. 2024

Preprint

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Amphibians are one of the most endangered taxa and are largely threatened by habitat loss. Little work has been conducted on the movement and habitat use of amphibians outside of the breeding season. In this study, we examined the movement patterns of two species of toads inhabiting the Eastern Coastal Plain of Virginia: the Eastern American Toad (Anaxyrus americanus americanus) and the Fowlers Toad (Anaxyrus fowleri). Based on three years of movement data, we estimated the median migration distance of toads from their breeding location and the propensity for site fidelity, related variation in distance traveled to environmental (e.g., rain, temperature, humidity) and landscape variables (e.g., coniferous forests, distance to trails, terrain ruggedness index), and compared microhabitat selection for daytime refugia between the two species. We found the median distance from breeding grounds to be similar between the two species, 63 m for the Eastern American Toad and 64 m for the Fowlers Toad, but Eastern American Toads had a greater range of moved distances (3rd quartiles were 122 m for Eastern American and 73 m for Fowlers Toads). We also found that both species exhibit site fidelity. Distance to trails, proportion of conifer forest, minimum temperature, and 3-day cumulative rainfall related positively with increased movements. Compared to Fowlers Toads, Eastern American Toads favored woody structures and leaf litter for daytime refugia. Our research provides crucial information for two toad species about the extent of their movements and habitat use during the nonbreeding season. To lessen the decline of amphibians, habitat occupied during the nonbreeding season needs to be included in conservation strategies at biologically relevant distances.

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Defining null expectations for animal site fidelity

Cited by 8 publications

References 76 publications

Identifying signals of memory from observations of animal movements

Identifying signals of memory from observations of animal movements

Simulating animal space use from fitted integrated Step‐Selection Functions (iSSF)

A Combination of Environmental and Landscape Variables Drive Movement and Habitat use in TwoAnaxyrussp. in the Eastern Coastal Plain

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