A Quantitative Framework for Identifying Patterns of Route-Use in Animal Movement Data

Animal movement along repeatedly used, “habitual” routes could emerge from a variety of cognitive mechanisms, as well as in response to a diverse set of environmental features. Because of the high conservation value of identifying wildlife movement corridors, there has been extensive work focusing on environmental factors that contribute to the emergence of habitual routes between protected habitats. In parallel, significant work has focused on disentangling the cognitive mechanisms underlying animal route use, as such movement patterns are of fundamental interest to the study of decision making and navigation. We reviewed the types of processes that can generate routine patterns of animal movement, suggested a new methodological workflow for classifying one of these patterns—high fidelity path reuse—in animal tracking data, and compared the prevalence of this pattern across four sympatric species of frugivorous mammals in Panama. We found the highest prevalence of route-use in kinkajous, the only nocturnal species in our study, and propose that further development of this method could help to distinguish the processes underlying the presence of specific routes in animal movement data.

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A Guide to Pre-Processing High-Throughput Animal Tracking Data

10.1101/2020.12.15.422876 ◽

2020 ◽

Author(s):

Pratik Rajan Gupte ◽

Christine E Beardsworth ◽

Orr Spiegel ◽

Emmanuel Lourie ◽

Sivan Toledo ◽

...

Keyword(s):

High Throughput ◽

Animal Movement ◽

Calibration Data ◽

Tracking Data ◽

Location Error ◽

Step Size ◽

Animal Tracking ◽

Location Errors ◽

Processing Pipeline ◽

Movement Data

Modern, high-throughput animal tracking studies collect increasingly large volumes of data at very fine temporal scales. At these scales, location error can exceed the animal step size, confounding inferences from tracking data. Cleaning the data to exclude positions with large location errors prior to analyses is one of the main ways movement ecologists deal with location errors. Cleaning data to reduce location error before making biological inferences is widely recommended, and ecologists routinely consider cleaned data to be the ground-truth. Nonetheless, uniform guidance on this crucial step is scarce. Cleaning high-throughput data must strike a balance between rejecting location errors without discarding valid animal movements. Additionally, users of high-throughput systems face challenges resulting from the high volume of data itself, since processing large data volumes is computationally intensive and difficult without a common set of efficient tools. Furthermore, many methods that cluster movement tracks for ecological inference are based on statistical phenomena, and may not be intuitive to understand in terms of the tracked animal biology. In this article we introduce a pipeline to pre-process high-throughput animal tracking data in order to prepare it for subsequent analysis. We demonstrate this pipeline on simulated movement data to which we have randomly added location errors. We further suggest how large volumes of cleaned data may be synthesized into biologically meaningful residence patches. We then use calibration data to show how the pipeline improves its quality, and to verify that the residence patch synthesis accurately captures animal space-use. Finally, turning to real tracking data from Egyptian fruit bats (Rousettus aegyptiacus), we demonstrate the pre-processing pipeline and residence patch method in a fully worked out example. To help with fast implementations of our pipeline, and to help standardise methods, we developed the R package atlastools, which we introduce here. Our pre-processing pipeline and atlastools can be used with any high-throughput animal movement data in which the high data volume combined with knowledge of the tracked individuals biology can be used to reduce location errors. The use of common pre-processing steps that are simple yet robust promotes standardised methods in the field of movement ecology and better inferences from data.

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Mobilizing Animal Movement Data: API use and the Movebank platform

Biodiversity Information Science and Standards ◽

10.3897/biss.5.74312 ◽

2021 ◽

Vol 5 ◽

Author(s):

Sarah Davidson ◽

Gil Bohrer ◽

Andrea Kölzsch ◽

Candace Vinciguerra ◽

Roland Kays

Keyword(s):

Data Acquisition ◽

Large Scale ◽

Animal Movement ◽

Mobile Apps ◽

Environmental Parameters ◽

Data Access ◽

Environmental Data ◽

Sensor Data ◽

Animal Tracking ◽

Movement Data

Movebank, a global platform for animal tracking and other animal-borne sensor data, is used by over 3,000 researchers globally to harmonize, archive and share nearly 3 billion animal occurrence records and more than 3 billion other animal-borne sensor measurements that document the movements and behavior of over 1,000 species. Movebank’s publicly described data model (Kranstauber et al. 2011), vocabulary and application programming interfaces (APIs) provide services for users to automate data import and retrieval. Near-live data feeds are maintained in cooperation with over 20 manufacturers of animal-borne sensors, who provide data in agreed-upon formats for accurate data import. Data acquisition by API complies with public or controlled-access sharing settings, defined within the database by data owners. The Environmental Data Automated Track Annotation System (EnvDATA, Dodge et al. 2013) allows users to link animal tracking data with hundreds of environmental parameters from remote sensing and weather reanalysis products through the Movebank website, and offers an API for advanced users to automate the submission of annotation requests. Movebank's mobile apps, the Animal Tracker and Animal Tagger, use APIs to support reporting and monitoring while in the field, as well as communication with citizen scientists. The recently-launched MoveApps platform connects with Movebank data using an API to allow users to build, execute and share repeatable workflows for data exploration and analysis through a user-friendly interface. A new API, currently under development, will allow calls to retrieve data from Movebank reduced according to criteria defined by "reduction profiles", which can greatly reduce the volume of data transferred for many use cases. In addition to making this core set of Movebank services possible, Movebank's APIs enable the development of external applications, including the widely used R programming packages 'move' (Kranstauber et al. 2012) and 'ctmm' (Calabrese et al. 2016), and user-specific workflows to efficiently execute collaborative analyses and automate tasks such as syncing with local organizational and governmental websites and archives. The APIs also support large-scale data acquisition, including for projects under development to visualize, map and analyze bird migrations led by the British Trust for Ornithology, the coordinating organisation for European bird ringing (banding) schemes (EURING), Georgetown University, National Audubon Society, Smithsonian Institution and United Nations Convention on Migratory Species. Our API development is constrained by a lack of standardization in data reporting across animal-borne sensors and a need to ensure adequate communication with data users (e.g., how to properly interpret data; expectations for use and attribution) and data owners (e.g., who is using publicly-available data and how) when allowing automated data access. As interest in data linking, harvesting, mirroring and integration grows, we recognize needs to coordinate API development across animal tracking and biodiversity databases, and to develop a shared system for unique organism identifiers. Such a system would allow linking of information about individual animals within and across repositories and publications in order to recognize data for the same individuals across platforms, retain provenance and attribution information, and ensure beneficial and biologically meaningful data use.

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Movement syndromes of a Neotropical frugivorous bat inhabiting heterogeneous landscapes in Brazil

Movement Ecology ◽

10.1186/s40462-021-00266-6 ◽

2021 ◽

Vol 9 (1) ◽

Author(s):

Patricia Kerches-Rogeri ◽

Danielle Leal Ramos ◽

Jukka Siren ◽

Beatriz de Oliveira Teles ◽

Rafael Souza Cruz Alves ◽

...

Keyword(s):

Site Fidelity ◽

Animal Movement ◽

Radio Telemetry ◽

Food Resource ◽

Movement Behavior ◽

Movement Activity ◽

Landscape Features ◽

Heterogeneous Landscapes ◽

Movement Data ◽

High Site

Abstract Background There is growing evidence that individuals within populations can vary in both habitat use and movement behavior, but it is still not clear how these two relate to each other. The aim of this study was to test if and how individual bats in a Stunira lilium population differ in their movement activity and preferences for landscape features in a correlated manner. Methods We collected data on movements of 27 individuals using radio telemetry. We fitted a heterogeneous-space diffusion model to the movement data in order to evaluate signals of movement variation among individuals. Results S. lilium individuals generally preferred open habitat with Solanum fruits, regularly switched between forest and open areas, and showed high site fidelity. Movement variation among individuals could be summarized in four movement syndromes: (1) average individuals, (2) forest specialists, (3) explorers which prefer Piper, and (4) open area specialists which prefer Solanum and Cecropia. Conclusions Individual preferences for landscape features plus food resource and movement activity were correlated, resulting in different movement syndromes. Individual variation in preferences for landscape elements and food resources highlight the importance of incorporating explicitly the interaction between landscape structure and individual heterogeneity in descriptions of animal movement.

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Joint estimation over multiple individuals improves behavioural state inference from animal movement data

Scientific Reports ◽

10.1038/srep20625 ◽

2016 ◽

Vol 6 (1) ◽

Cited By ~ 69

Author(s):

Ian Jonsen

Keyword(s):

Animal Movement ◽

Joint Estimation ◽

Behavioural State ◽

Movement Data ◽

State Inference

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Running on empty: recharge dynamics from animal movement data

Ecology Letters ◽

10.1111/ele.13198 ◽

2018 ◽

Cited By ~ 2

Author(s):

Mevin B. Hooten ◽

Henry R. Scharf ◽

Juan M. Morales

Keyword(s):

Animal Movement ◽

Movement Data

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Cattle trade between and within biomes in the state of Mato Grosso, Brazil

Pesquisa Veterinária Brasileira ◽

10.1590/1678-5150-pvb-5661 ◽

2018 ◽

Vol 38 (11) ◽

pp. 2023-2028

Author(s):

Rísia L. Negreiros ◽

José H.H. Grisi-Filho ◽

Ricardo A. Dias ◽

Fernando Ferreira ◽

Valéria S.F. Homem ◽

...

Keyword(s):

Infectious Diseases ◽

Animal Movement ◽

Control Strategies ◽

The State ◽

Disease Spread ◽

Mato Grosso ◽

Movement Data ◽

Cattle Movements ◽

Increased Risk ◽

And Control

ABSTRACT: The analysis of animal movement patterns may help identify farm premises with a potentially high risk of infectious disease introduction. Farm herd sizes and bovine movement data from 2007 in the state of Mato Grosso, Brazil, were analyzed. There are three different biomes in Mato Grosso: the Amazon, Cerrado, and Pantanal. The analysis of the animal trade between and within biomes would enable characterization of the connections between the biomes and the intensity of the internal trade within each biome. We conducted the following analyses: 1) the concentration of cattle on farm premises in the state and in each biome, 2) the number and relative frequency of cattle moved between biomes, and 3) the most frequent purposes for cattle movements. Twenty percent (20%) of the farm premises had 81.15% of the herd population. Those premises may be important not only for the spread of infectious diseases, but also for the implementation of surveillance and control strategies. Most of the cattle movement was intrastate (97.1%), and internal movements within each biome were predominant (88.6%). A high percentage of movement from the Pantanal was to the Cerrado (48.6%), the biome that received the most cattle for slaughter, fattening and reproduction (62.4%, 56.8%, and 49.1% of all movements for slaughter, fattening, and reproduction, respectively). The primary purposes for cattle trade were fattening (43.5%), slaughter (31.5%), and reproduction (22.7%). Presumably, movements for slaughter has a low risk of disease spread. In contrast, movements for fattening and reproduction purposes (66.2% of all movements) may contribute to an increased risk of the spread of infectious diseases.

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Generalizing the first-difference correlated random walk for marine animal movement data

Scientific Reports ◽

10.1038/s41598-019-40405-z ◽

2019 ◽

Vol 9 (1) ◽

Cited By ~ 2

Author(s):

Christoffer Moesgaard Albertsen

Keyword(s):

Random Walk ◽

Animal Movement ◽

Marine Animal ◽

Correlated Random Walk ◽

Movement Data

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Distinguishing technology from biology: a critical review of the use of GPS telemetry data in ecology

Philosophical Transactions of the Royal Society B Biological Sciences ◽

10.1098/rstb.2010.0087 ◽

2010 ◽

Vol 365 (1550) ◽

pp. 2303-2312 ◽

Cited By ~ 316

Author(s):

Mark Hebblewhite ◽

Daniel T. Haydon

Keyword(s):

Animal Ecology ◽

Animal Movement ◽

Gps Telemetry ◽

Long Distance ◽

Location Data ◽

The Past ◽

Movement Data ◽

Migratory Songbirds ◽

Spatio Temporal ◽

Gps Devices

In the past decade, ecologists have witnessed vast improvements in our ability to collect animal movement data through animal-borne technology, such as through GPS or ARGOS systems. However, more data does not necessarily yield greater knowledge in understanding animal ecology and conservation. In this paper, we provide a review of the major benefits, problems and potential misuses of GPS/Argos technology to animal ecology and conservation. Benefits are obvious, and include the ability to collect fine-scale spatio-temporal location data on many previously impossible to study animals, such as ocean-going fish, migratory songbirds and long-distance migratory mammals. These benefits come with significant problems, however, imposed by frequent collar failures and high cost, which often results in weaker study design, reduced sample sizes and poorer statistical inference. In addition, we see the divorcing of biologists from a field-based understanding of animal ecology to be a growing problem. Despite these difficulties, GPS devices have provided significant benefits, particularly in the conservation and ecology of wide-ranging species. We conclude by offering suggestions for ecologists on which kinds of ecological questions would currently benefit the most from GPS/Argos technology, and where the technology has been potentially misused. Significant conceptual challenges remain, however, including the links between movement and behaviour, and movement and population dynamics.

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