%AFleming, C. [Smithsonian Conservation Biology Institute National Zoological Park 1500 Remount Road Front Royal Virginia 22630 USA, Department of Biology University of Maryland College Park College Park Maryland 20742 USA, Conservation International Indonesia Marine Program Jalan Pejaten Barat 16A, Kemang Jakarta DKI Jakarta 12550 Indonesia]%AFleming, C. [Smithsonian Conservation Biology Institute; National Zoological Park; 1500 Remount Road Front Royal Virginia 22630 USA; Department of Biology; University of Maryland College Park; College Park Maryland 20742 USA; Conservation International Indonesia; Marine Program; Jalan Pejaten Barat 16A, Kemang Jakarta DKI Jakarta 12550 Indonesia]%ASheldon, D. [College of Information and Computer Sciences University of Massachusetts Amherst Amherst Massachusetts 01003‐9264 USA, Department of Computer Science Mount Holyoke College South Hadley Massachusetts 01075 USA]%ASheldon, D. [College of Information and Computer Sciences; University of Massachusetts Amherst; Amherst Massachusetts 01003-9264 USA; Department of Computer Science; Mount Holyoke College; South Hadley Massachusetts 01075 USA]%AFagan, W. [Department of Biology University of Maryland College Park College Park Maryland 20742 USA]%AFagan, W. [Department of Biology; University of Maryland College Park; College Park Maryland 20742 USA]%ALeimgruber, P. [Smithsonian Conservation Biology Institute National Zoological Park 1500 Remount Road Front Royal Virginia 22630 USA]%ALeimgruber, P. [Smithsonian Conservation Biology Institute; National Zoological Park; 1500 Remount Road Front Royal Virginia 22630 USA]%AMueller, T. [Senckenberg Biodiversity and Climate Research Centre Senckenberg Gesellschaft für Naturforschung Senckenberganlage 25 60325 Frankfurt (Main) Germany, Department of Biological Sciences Goethe University Max‐von‐Laue‐Straße 9 60438 Frankfurt (Main) Germany]%AMueller, T. [Senckenberg Biodiversity and Climate Research Centre; Senckenberg Gesellschaft für Naturforschung; Senckenberganlage 25 60325 Frankfurt (Main) Germany; Department of Biological Sciences; Goethe University; Max-von-Laue-Straße 9 60438 Frankfurt (Main) Germany]%ANandintsetseg, D. [Senckenberg Biodiversity and Climate Research Centre; Senckenberg Gesellschaft für Naturforschung; Senckenberganlage 25 60325 Frankfurt (Main) Germany; Department of Biological Sciences; Goethe University; Max-von-Laue-Straße 9 60438 Frankfurt (Main) Germany]%ANandintsetseg, D. [Senckenberg Biodiversity and Climate Research Centre Senckenberg Gesellschaft für Naturforschung Senckenberganlage 25 60325 Frankfurt (Main) Germany, Department of Biological Sciences Goethe University Max‐von‐Laue‐Straße 9 60438 Frankfurt (Main) Germany]%ANoonan, M. [Smithsonian Conservation Biology Institute; National Zoological Park; 1500 Remount Road Front Royal Virginia 22630 USA]%ANoonan, M. [Smithsonian Conservation Biology Institute National Zoological Park 1500 Remount Road Front Royal Virginia 22630 USA]%AOlson, K. [Smithsonian Conservation Biology Institute National Zoological Park 1500 Remount Road Front Royal Virginia 22630 USA, Wildlife Conservation Society Mongolia Program 201 San Business Center, Amar Street 29, Small Ring Road, Sukhbaatar District Post 20A, Box‐21 Ulaanbaatar Mongolia]%AOlson, K. [Smithsonian Conservation Biology Institute; National Zoological Park; 1500 Remount Road Front Royal Virginia 22630 USA; Wildlife Conservation Society; Mongolia Program; 201 San Business Center, Amar Street 29, Small Ring Road, Sukhbaatar District Post 20A, Box-21 Ulaanbaatar Mongolia]%ASetyawan, E. [Manta Trust‐Indonesian Manta Project Badung Bali 80361 Indonesia, Institute for Marine and Antarctic Studies University of Tasmania Launceston Tasmania 7250 Australia]%ASetyawan, E. [Manta Trust-Indonesian Manta Project; Badung Bali 80361 Indonesia; Institute for Marine and Antarctic Studies; University of Tasmania; Launceston Tasmania 7250 Australia]%ASianipar, A. [Conservation International Indonesia Marine Program Jalan Pejaten Barat 16A, Kemang Jakarta DKI Jakarta 12550 Indonesia]%ASianipar, A. [Conservation International Indonesia; Marine Program; Jalan Pejaten Barat 16A, Kemang Jakarta DKI Jakarta 12550 Indonesia]%ACalabrese, J. [Smithsonian Conservation Biology Institute National Zoological Park 1500 Remount Road Front Royal Virginia 22630 USA, Department of Biology University of Maryland College Park College Park Maryland 20742 USA]%ACalabrese, J. [Smithsonian Conservation Biology Institute; National Zoological Park; 1500 Remount Road Front Royal Virginia 22630 USA; Department of Biology; University of Maryland College Park; College Park Maryland 20742 USA]%BJournal Name: Ecological Applications; Journal Volume: 28; Journal Issue: 4; Related Information: CHORUS Timestamp: 2023-09-16 05:56:19 %D2018%IWiley Blackwell (John Wiley & Sons) %JJournal Name: Ecological Applications; Journal Volume: 28; Journal Issue: 4; Related Information: CHORUS Timestamp: 2023-09-16 05:56:19 %K %MOSTI ID: 10061187 %PMedium: X %TCorrecting for missing and irregular data in home‐range estimation %XAbstract

Home‐range estimation is an important application of animal tracking data that is frequently complicated by autocorrelation, sampling irregularity, and small effective sample sizes. We introduce a novel, optimal weighting method that accounts for temporal sampling bias in autocorrelated tracking data. This method corrects for irregular and missing data, such that oversampled times are downweighted and undersampled times are upweighted to minimize error in the home‐range estimate. We also introduce computationally efficient algorithms that make this method feasible with large data sets. Generally speaking, there are three situations where weight optimization improves the accuracy of home‐range estimates: with marine data, where the sampling schedule is highly irregular, with duty cycled data, where the sampling schedule changes during the observation period, and when a small number of home‐range crossings are observed, making the beginning and end times more independent and informative than the intermediate times. Using both simulated data and empirical examples including reef manta ray, Mongolian gazelle, and African buffalo, optimal weighting is shown to reduce the error and increase the spatial resolution of home‐range estimates. With a conveniently packaged and computationally efficient software implementation, this method broadens the array of data sets with which accurate space‐use assessments can be made.

%0Journal Article