Inferring detailed space use from movement paths: A unifying, residence time‐based framework

Kapota, Dror; Dolev, Amit; Saltz, David

doi:10.1002/ece3.3321

Cited by 5 publications

(7 citation statements)

References 31 publications

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“…This was met with several criticisms by Barraquand and Benhamou (2008). Nonetheless, Kapota, Dolev, and Saltz (2017) revisited the variance-scale curve method and improved on it in several ways, specifically addressing the concerns of Barraquand and Benhamou (2008). In principle, these techniques could be used in combination with our usage-time algorithm if the user is particularly concerned in identifying sizes of the sites of interest.…”

Section: Discussionmentioning

confidence: 99%

Making sense of ultrahigh‐resolution movement data: A new algorithm for inferring sites of interest

Munden

Börger

Wilson

et al. 2018

Ecology and Evolution

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Decomposing the life track of an animal into behavioral segments is a fundamental challenge for movement ecology. The proliferation of high‐resolution data, often collected many times per second, offers much opportunity for understanding animal movement. However, the sheer size of modern data sets means there is an increasing need for rapid, novel computational techniques to make sense of these data. Most existing methods were designed with smaller data sets in mind and can thus be prohibitively slow. Here, we introduce a method for segmenting high‐resolution movement trajectories into sites of interest and transitions between these sites. This builds on a previous algorithm of Benhamou and Riotte‐Lambert (2012). Adapting it for use with high‐resolution data. The data’s resolution removed the need to interpolate between successive locations, allowing us to increase the algorithm’s speed by approximately two orders of magnitude with essentially no drop in accuracy. Furthermore, we incorporate a color scheme for testing the level of confidence in the algorithm's inference (high = green, medium = amber, low = red). We demonstrate the speed and accuracy of our algorithm with application to both simulated and real data (Alpine cattle at 1 Hz resolution). On simulated data, our algorithm correctly identified the sites of interest for 99% of “high confidence” paths. For the cattle data, the algorithm identified the two known sites of interest: a watering hole and a milking station. It also identified several other sites which can be related to hypothesized environmental drivers (e.g., food). Our algorithm gives an efficient method for turning a long, high‐resolution movement path into a schematic representation of broadscale decisions, allowing a direct link to existing point‐to‐point analysis techniques such as optimal foraging theory. It is encoded into an package called , so should serve as a valuable tool for making sense of these increasingly large data streams.

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Section: Discussionmentioning

confidence: 99%

Making sense of ultrahigh‐resolution movement data: A new algorithm for inferring sites of interest

Munden

Börger

Wilson

et al. 2018

Ecology and Evolution

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“…We also calculated three recursion metrics useful for characterizing movement [ 7 , 77 ]. Over each bird’s full tracking period we calculated 1) the total number of revisits within a defined distance radius of locations, 2) residence time , the total time spent inside the radius, and 3) return time , the time between revisits [ 78 ].…”

Section: Methodsmentioning

confidence: 99%

Individual and seasonal variation in the movement behavior of two tropical nectarivorous birds

Smetzer

Paxton

2021

Mov Ecol

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Background Movement of animals directly affects individual fitness, yet fine spatial and temporal resolution movement behavior has been studied in relatively few small species, particularly in the tropics. Nectarivorous Hawaiian honeycreepers are believed to be highly mobile throughout the year, but their fine-scale movement patterns remain unknown. The movement behavior of these crucial pollinators has important implications for forest ecology, and for mortality from avian malaria (Plasmodium relictum), an introduced disease that does not occur in high-elevation forests where Hawaiian honeycreepers primarily breed. Methods We used an automated radio telemetry network to track the movement of two Hawaiian honeycreeper species, the ʻapapane (Himatione sanguinea) and ʻiʻiwi (Drepanis coccinea). We collected high temporal and spatial resolution data across the annual cycle. We identified movement strategies using a multivariate analysis of movement metrics and assessed seasonal changes in movement behavior. Results Both species exhibited multiple movement strategies including sedentary, central place foraging, commuting, and nomadism , and these movement strategies occurred simultaneously across the population. We observed a high degree of intraspecific variability at the individual and population level. The timing of the movement strategies corresponded well with regional bloom patterns of ‘ōhi‘a (Metrosideros polymorpha) the primary nectar source for the focal species. Birds made long-distance flights, including multi-day forays outside the tracking array, but exhibited a high degree of fidelity to a core use area, even in the non-breeding period. Both species visited elevations where avian malaria can occur but exhibited little seasonal change in elevation (< 150 m) and regularly returned to high-elevation roosts at night. Conclusions This study demonstrates the power of automated telemetry to study complex and fine-scale movement behaviors in rugged tropical environments. Our work reveals a system in which birds can track shifting resources using a diverse set of movement behaviors and can facultatively respond to environmental change. Importantly, fidelity to high-elevation roosting sites minimizes nocturnal exposure to avian malaria for far-ranging individuals and is thus a beneficial behavior that may be under high selection pressure.

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“…Second, our method draws attention to a neglected temporal metric, namely the persistence of movement recursions. Previous studies focused on inferring latent processes from recursive movement patterns use residence time [4], presence [23], time-to-return [70], mean visit duration [39], periodicity [57], or repeatability of visitation sequences [58] as temporal metrics, but not the persistence of movement recursions. We introduced a probabilistic approach to quantify the persistence of recursions to a central location (nest site) and to estimate the cessation of a latent behavior (administering parental care to nestlings) using a survival analysis in a Bayesian hierarchical modeling framework.…”

Section: Innovations In the Analysis Of Movement Recursionsmentioning

confidence: 99%

“…Similar to residence time, the concept of presence [23] quantifies cumulative attendance within a spatial cluster with the exclusion of absence periods, accounting not only for the number of locations within a cluster but also their temporal consecutiveness. The frequency of visits has also been used to quantify the intensity of use of different areas within animals' home ranges, with individuals visiting profitable patches more often [6,39]. Conversely, shorter times between visits (or time-to-return) characterize preferred areas within an animal's home range [70], as do lower speeds [49].…”

Section: Introductionmentioning

confidence: 99%

“…Conversely, shorter times between visits (or time-to-return) characterize preferred areas within an animal's home range [70], as do lower speeds [49]. The mean visit duration provides information on responses to resource depletion as predicted by optimal foraging theory [39]. The periodicity of movement recursions, that is, the temporal repeatability of visits to a certain location, detected using Fourier-and waveletbased methodologies, has been used to quantify responses of animals to cyclical variation in resource availability and/or predation risk [57].…”

Section: Introductionmentioning

confidence: 99%

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Analysis of movement recursions to detect reproductive events and estimate their fate in central place foragers

et al. 2020

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Background: Recursive movement patterns have been used to detect behavioral structure within individual movement trajectories in the context of foraging ecology, home-ranging behavior, and predator avoidance. Some animals exhibit movement recursions to locations that are tied to reproductive functions, including nests and dens; while existing literature recognizes that, no method is currently available to explicitly target different types of revisited locations. Moreover, the temporal persistence of recursive movements to a breeding location can carry information regarding the fate of breeding attempts, but it has never been used as a metric to quantify recursive movement patterns. Here, we introduce a method to locate breeding attempts and estimate their fate from GPStracking data of central place foragers. We tested the performance of our method in three bird species differing in breeding ecology (wood stork (Mycteria americana), lesser kestrel (Falco naumanni), Mediterranean gull (Ichthyaetus melanocephalus)) and implemented it in the R package 'nestR'. Methods: We identified breeding sites based on the analysis of recursive movements within individual tracks. Using trajectories with known breeding attempts, we estimated a set of species-specific criteria for the identification of nest sites, which we further validated using non-reproductive individuals as controls. We then estimated individual nest survival as a binary measure of reproductive fate (success, corresponding to fledging of at least one chick, or failure) from nest-site revisitation histories during breeding attempts, using a Bayesian hierarchical modeling approach that accounted for temporally variable revisitation patterns, probability of visit detection, and missing data. Results: Across the three species, positive predictive value of the nest-site detection algorithm varied between 87 and 100% and sensitivity between 88 and 92%, and we correctly estimated the fate of 86-100% breeding attempts.

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Inferring detailed space use from movement paths: A unifying, residence time‐based framework

Cited by 5 publications

References 31 publications

Making sense of ultrahigh‐resolution movement data: A new algorithm for inferring sites of interest

Making sense of ultrahigh‐resolution movement data: A new algorithm for inferring sites of interest

Individual and seasonal variation in the movement behavior of two tropical nectarivorous birds

Analysis of movement recursions to detect reproductive events and estimate their fate in central place foragers

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