R-universe search: topic:animal-movement

Showing 7 of total 7 results (show query)

ianjonsen

aniMotum:Fit Continuous-Time State-Space and Latent Variable Models for Quality Control of Argos Satellite (and Other) Telemetry Data and for Estimating Changes in Animal Movement

Fits continuous-time random walk, correlated random walk and move persistence state-space models for location estimation and behavioural inference from animal tracking data ('Argos', processed light-level 'geolocation', 'GPS'). Template Model Builder ('TMB') is used for fast random-effects estimation. The 'Argos' data can be: (older) least squares-based locations; (newer) Kalman filter-based locations with error ellipse information; or a mixture of both. The models estimate two sets of location states corresponding to: 1) each observation, which are (usually) irregularly timed; and 2) user-specified time intervals (regular or irregular). A track re-routing function is provided to adjust location estimates for known movement barriers. Track simulation functions are provided. Latent variable models are also provided to estimate move persistence from track data not requiring state-space model filtering.

Maintained by Ian Jonsen. Last updated 11 hours ago.

animal-movement animal-tracking random-effects-model state-space-models tmb cpp

39 stars 7.11 score 59 scripts

ropensci

pathviewr:Wrangle, Analyze, and Visualize Animal Movement Data

Tools to import, clean, and visualize movement data, particularly from motion capture systems such as Optitrack's 'Motive', the Straw Lab's 'Flydra', or from other sources. We provide functions to remove artifacts, standardize tunnel position and tunnel axes, select a region of interest, isolate specific trajectories, fill gaps in trajectory data, and calculate 3D and per-axis velocity. For experiments of visual guidance, we also provide functions that use subject position to estimate perception of visual stimuli.

Maintained by Vikram B. Baliga. Last updated 2 years ago.

animal-movement flydra motion movement-data optitrack trajectories trajectory-analysis visual-guidance visual-perception

8 stars 6.56 score 102 scripts

miguel-porto

SiMRiv:Simulating Multistate Movements in River/Heterogeneous Landscapes

Provides functions to generate and analyze spatially-explicit individual-based multistate movements in rivers, heterogeneous and homogeneous spaces. This is done by incorporating landscape bias on local behaviour, based on resistance rasters. Although originally conceived and designed to simulate trajectories of species constrained to linear habitats/dendritic ecological networks (e.g. river networks), the simulation algorithm is built to be highly flexible and can be applied to any (aquatic, semi-aquatic or terrestrial) organism, independently on the landscape in which it moves. Thus, the user will be able to use the package to simulate movements either in homogeneous landscapes, heterogeneous landscapes (e.g. semi-aquatic animal moving mainly along rivers but also using the matrix), or even in highly contrasted landscapes (e.g. fish in a river network). The algorithm and its input parameters are the same for all cases, so that results are comparable. Simulated trajectories can then be used as mechanistic null models (Potts & Lewis 2014, <DOI:10.1098/rspb.2014.0231>) to test a variety of 'Movement Ecology' hypotheses (Nathan et al. 2008, <DOI:10.1073/pnas.0800375105>), including landscape effects (e.g. resources, infrastructures) on animal movement and species site fidelity, or for predictive purposes (e.g. road mortality risk, dispersal/connectivity). The package should be relevant to explore a broad spectrum of ecological phenomena, such as those at the interface of animal behaviour, management, landscape and movement ecology, disease and invasive species spread, and population dynamics.

Maintained by Miguel Porto. Last updated 7 months ago.

animal-movement heterogeneous-landscapes movement-ecology river-networks simulation

15 stars 6.08 score 27 scripts 1 dependents

roaldarbol

animovement:An R toolbox for analysing animal movement across space and time

An R toolbox for analysing animal movement across space and time.

Maintained by Mikkel Roald-Arbøl. Last updated 3 months ago.

animal-behaviour animal-movement neuroethology neuroscience

10 stars 4.81 score 8 scripts

chaoranhu

smam:Statistical Modeling of Animal Movements

Animal movement models including Moving-Resting Process with Embedded Brownian Motion (Yan et al., 2014, <doi:10.1007/s10144-013-0428-8>; Pozdnyakov et al., 2017, <doi:10.1007/s11009-017-9547-6>), Brownian Motion with Measurement Error (Pozdnyakov et al., 2014, <doi:10.1890/13-0532.1>), Moving-Resting-Handling Process with Embedded Brownian Motion (Pozdnyakov et al., 2020, <doi:10.1007/s11009-020-09774-1>), Moving-Resting Process with Measurement Error (Hu et al., 2021, <doi:10.1111/2041-210X.13694>), Moving-Moving Process with two Embedded Brownian Motions.

Maintained by Chaoran Hu. Last updated 1 years ago.

animal-movement brownian-motion hidden-markov-model hidden-states measurement-error telegraph-process gsl cpp

2 stars 4.34 score 11 scripts

inbo

etn:Access Data from the European Tracking Network

Package with functions to access and process data from the European Tracking Network hosted by VLIZ.

Maintained by Pieter Huybrechts. Last updated 2 months ago.

animal-movement animal-tracking biologging data-access fish lifewatch oscibio

8 stars 4.15 score 14 scripts

robitalec

preparelocs:Prepares Relocations For The WEEL

Prepares animal relocation datasets for the Wildlife Evolutionary Ecology Lab at Memorial University.

Maintained by Alec L. Robitaille. Last updated 1 years ago.

animal animal-movement gps targets

1.70 score