Contact Information
Continuous-Time Movement Modeling
- An overview of the ctmm R package. [1]
- An overview of the ctmmweb R Shiny package. [2]
- How important is autocorrelation in home-range estimation? [3,4]
- How do we properly estimate the home range of an animal, given that tracking data are necessarily autocorrelated? [5]
- How do we correct for bias in the kernel-density area estimates? [6]
- How do we correct for sampling bias/irregularity? [7]
- How do we estimate home-range overlap, correcting for bias and accounting for uncertainty? [8]
- How do we estimate where an animal has been from a sparse set of tracking data? [9]
- How do we estimate how fast and how far the animal was traveling? [10]
- What is the general framework to estimating autocorrelation in animal tracking data? [11]
- How do we estimate efficiently with large datasets? [12]
- How do we correct for bias in these estimates? [13]
- What is the best way to visualize the autocorrelation structure in animal tracking data? [14]
- What is the best way to visualize periodicities in animal tracking data? [15]
- What is the best way to fit periodicities to animal tracking data? [16]
- What justifies our class of movement models? [17]
- J. M. Calabrese, C. H. Fleming, E. Gurarie, "ctmm: An R package for analyzing animal relocation data as a continuous-time stochastic process",
Methods in Ecology and Evolution 7:9, 1124-1132 (2016)
- J. M. Calabrese, C. H. Fleming, M. J. Noonan, X. Dong, "ctmmweb: A graphical user interface for autocorrelation-informed home range estimation",
Wildlife Society Bulletin, doi:10.1002/wsb.1154 (2021)
- M. J. Noonan, M. A. Tucker, C. H. Fleming, et al, "A comprehensive analysis of autocorrelation and bias in home range estimation",
Ecological Monographs, 89:2, e01344 (2019)
- M. J. Noonan, C. H. Fleming, et al, "Bodysize-dependent underestimation of mammalian area requirements",
Conservation Biology, 34:4 1017-1028 (2020)
- C. H. Fleming, W. F. Fagan, T. Mueller, K. A. Olson, P. Leimgruber, J. M. Calabrese, "Rigorous home-range estimation with movement data: A new autocorrelated kernel-density estimator",
Ecology 96:5, 1182-1188 (2015)
- C. H. Fleming, J. M. Calabrese, "A new kernel-density estimator for accurate home-range and species-range area estimation",
Methods in Ecology and Evolution 8, 571-579 (2016)
- C. H. Fleming, D. Sheldon, W. F. Fagan, P. Leimgruber, T. Mueller, D. Nandintsetseg, M. J. Noonan, K. A. Olson, E. Setyawan, A. Sianipar, J. M. Calabrese, "Correcting for missing and irregular data in home-range estimation",
Ecological Applications 28:4, 1003-1010 (2018)
- K. Winner, M. J. Noonan, C. H. Fleming, K. Olson, T. Mueller, D. Sheldon, J. M. Calabrese, "Statistical inference for home range overlap",
Methods in Ecology and Evolution, 9:7, 1679-1691 (2018)
- C. H. Fleming, W. F. Fagan, T. Mueller, K. A. Olson, P. Leimgruber, J. M. Calabrese, "Estimating where and how animals travel: An optimal framework for path reconstruction from autocorrelated tracking data",
Ecology 97:3, 576-582 (2016)
- M. J. Noonan, C. H. Fleming, T. S. Akre, J. Dresher-Lehman, E. Gurarie, A.-L. Harrison, R. Kays, J. M. Calabrese, "Scale-insensitive estimation of speed and distance traveled from animal tracking data",
Movement Ecology, 7:35 (2019)
- C. H. Fleming, J. M. Calabrese, T. Mueller, K. A. Olson, P. Leimgruber, W. F. Fagan, "Non-Markovian maximum likelihood estimation of autocorrelated movement processes",
Methods in Ecology and Evolution 5:5, 462-472 (2014)
- C. H. Fleming, D. Sheldon, E. Gurarie, W. F. Fagan. S. LaPoint, J. M. Calabrese, "Kalman filters for continuous-time movement models",
Ecological Informatics 40, 8-21 (2017)
- C. H. Fleming, M. J. Noonan, E. P. Medici, J. M. Calabrese, "Overcoming the challenge of small effective sample sizes in home-range estimation",
Methods in Ecology and Evolution 10:10, 1679-1689 (2019)
- C. H. Fleming, J. M. Calabrese, T. Mueller, K. A. Olson, P. Leimgruber, W. F. Fagan, "From fine-scale foraging to home ranges: A semi-variance approach to identifying movement modes across spatiotemporal scales",
The American Naturalist 183:5, E154-E167 (2014)
- G. Péron, C. H. Fleming, R. C. de Paula, J. M. Calabrese, "Uncovering periodic patterns of space use in animal tracking data with periodograms, including a new algorithm for the Lomb-Scargle periodogram and improved randomization tests",
Movement Ecology 4:19 10.1186/s40462-016-0084-7 (2016)
- G. Péron, C. H. Fleming, R. C. de Paula, N. Mitchell, M. Stronbach, P. Leimgruber, J. M. Calabrese, "Periodic continuous-time movement models uncover behavioral changes of wild canids along anthropization gradients",
Ecological Monographs 87:3, 442-456 (2017)
- C. H. Fleming, Y. Subasi, J. M. Calabrese, "A maximum-entropy description of animal movement",
Physical Review E 91, 032107 (2015)
ctmm R package
This CRAN package has most everything you need to estimate animal home ranges: including variogram movement-model visualization, peturbative-REML based movement-model estimation, autocorrelated kernel-density home-range estimation, optimal kernel weighting, location-error model selection, and home-range area meta-analysis. Additional analyses are continuously being rolled in.