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Pohle J, Signer J, Eccard JA, Dammhahn M, Schlägel UE. How to account for behavioral states in step-selection analysis: a model comparison. PeerJ 2024; 12:e16509. [PMID: 38426131 PMCID: PMC10903358 DOI: 10.7717/peerj.16509] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Accepted: 11/01/2023] [Indexed: 03/02/2024] Open
Abstract
Step-selection models are widely used to study animals' fine-scale habitat selection based on movement data. Resource preferences and movement patterns, however, often depend on the animal's unobserved behavioral states, such as resting or foraging. As this is ignored in standard (integrated) step-selection analyses (SSA, iSSA), different approaches have emerged to account for such states in the analysis. The performance of these approaches and the consequences of ignoring the states in step-selection analysis, however, have rarely been quantified. We evaluate the recent idea of combining iSSAs with hidden Markov models (HMMs), which allows for a joint estimation of the unobserved behavioral states and the associated state-dependent habitat selection. Besides theoretical considerations, we use an extensive simulation study and a case study on fine-scale interactions of simultaneously tracked bank voles (Myodes glareolus) to compare this HMM-iSSA empirically to both the standard and a widely used classification-based iSSA (i.e., a two-step approach based on a separate prior state classification). Moreover, to facilitate its use, we implemented the basic HMM-iSSA approach in the R package HMMiSSA available on GitHub.
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Affiliation(s)
- Jennifer Pohle
- Institute of Biochemistry and Biology, University of Potsdam, Potsdam, Germany
| | - Johannes Signer
- Wildlife Sciences, Faculty of Forest Sciences and Forest Ecology, University of Goettingen, Göttingen, Germany
| | - Jana A. Eccard
- Animal Ecology, Institute of Biochemistry and Biology, University of Potsdam, Potsdam, Germany
| | - Melanie Dammhahn
- Department of Behavioural Biology, University of Münster, Münster, Germany
| | - Ulrike E. Schlägel
- Institute of Biochemistry and Biology, University of Potsdam, Potsdam, Germany
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2
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Walker RH, Hutchinson MC, Becker JA, Daskin JH, Gaynor KM, Palmer MS, Gonçalves DD, Stalmans ME, Denlinger J, Bouley P, Angela M, Paulo A, Potter AB, Arumoogum N, Parrini F, Marshal JP, Pringle RM, Long RA. Trait-based sensitivity of large mammals to a catastrophic tropical cyclone. Nature 2023; 623:757-764. [PMID: 37968390 DOI: 10.1038/s41586-023-06722-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 10/06/2023] [Indexed: 11/17/2023]
Abstract
Extreme weather events perturb ecosystems and increasingly threaten biodiversity1. Ecologists emphasize the need to forecast and mitigate the impacts of these events, which requires knowledge of how risk is distributed among species and environments. However, the scale and unpredictability of extreme events complicate risk assessment1-4-especially for large animals (megafauna), which are ecologically important and disproportionately threatened but are wide-ranging and difficult to monitor5. Traits such as body size, dispersal ability and habitat affiliation are hypothesized to determine the vulnerability of animals to natural hazards1,6,7. Yet it has rarely been possible to test these hypotheses or, more generally, to link the short-term and long-term ecological effects of weather-related disturbance8,9. Here we show how large herbivores and carnivores in Mozambique responded to Intense Tropical Cyclone Idai, the deadliest storm on record in Africa, across scales ranging from individual decisions in the hours after landfall to changes in community composition nearly 2 years later. Animals responded behaviourally to rising floodwaters by moving upslope and shifting their diets. Body size and habitat association independently predicted population-level impacts: five of the smallest and most lowland-affiliated herbivore species declined by an average of 28% in the 20 months after landfall, while four of the largest and most upland-affiliated species increased by an average of 26%. We attribute the sensitivity of small-bodied species to their limited mobility and physiological constraints, which restricted their ability to avoid the flood and endure subsequent reductions in the quantity and quality of food. Our results identify general traits that govern animal responses to severe weather, which may help to inform wildlife conservation in a volatile climate.
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Affiliation(s)
- Reena H Walker
- Department of Fish and Wildlife Sciences, University of Idaho, Moscow, ID, USA
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA
| | - Matthew C Hutchinson
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA
- Department of Life and Environmental Sciences, University of California Merced, Merced, CA, USA
| | - Justine A Becker
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA
- Department of Ecology, Montana State University, Bozeman, MT, USA
| | - Joshua H Daskin
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT, USA
- Archbold Biological Station, Venus, FL, USA
| | - Kaitlyn M Gaynor
- Departments of Zoology and Botany, University of British Columbia, Vancouver, British Columbia, Canada
| | - Meredith S Palmer
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA
| | - Dominique D Gonçalves
- Department of Scientific Services, Gorongosa National Park, Sofala, Mozambique
- Durrell Institute of Conservation and Ecology, University of Kent, Canterbury, UK
| | - Marc E Stalmans
- Department of Scientific Services, Gorongosa National Park, Sofala, Mozambique
| | - Jason Denlinger
- Department of Scientific Services, Gorongosa National Park, Sofala, Mozambique
| | - Paola Bouley
- Department of Conservation, Gorongosa National Park, Sofala, Mozambique
- Associação Azul Moçambique, Maputo, Mozambique
| | - Mercia Angela
- Department of Conservation, Gorongosa National Park, Sofala, Mozambique
| | - Antonio Paulo
- Department of Conservation, Gorongosa National Park, Sofala, Mozambique
| | - Arjun B Potter
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA
- Wake Forest University, Winston-Salem, NC, USA
| | - Nikhail Arumoogum
- Centre for African Ecology, School of Animal, Plant and Environmental Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Francesca Parrini
- Centre for African Ecology, School of Animal, Plant and Environmental Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Jason P Marshal
- Centre for African Ecology, School of Animal, Plant and Environmental Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Robert M Pringle
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA.
| | - Ryan A Long
- Department of Fish and Wildlife Sciences, University of Idaho, Moscow, ID, USA.
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3
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Fagan WF, McBride F, Koralov L. Reinforced diffusions as models of memory-mediated animal movement. J R Soc Interface 2023; 20:20220700. [PMID: 36987616 PMCID: PMC10050924 DOI: 10.1098/rsif.2022.0700] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Accepted: 03/07/2023] [Indexed: 03/30/2023] Open
Abstract
How memory shapes animals' movement paths is a topic of growing interest in ecology, with connections to planning for conservation and climate change. Empirical studies suggest that memory has both temporal and spatial components, and can include both attractive and aversive elements. Here, we introduce reinforced diffusions (the continuous time counterpart of reinforced random walks) as a modelling framework for understanding the role that memory plays in determining animal movements. This framework includes reinforcement via functions of time before present and of distance away from a current location. Focusing on the interplay between memory and central place attraction (a component of home ranging behaviour), we explore patterns of space usage that result from the reinforced diffusion. Our efforts identify three qualitatively different behaviours: bounded wandering behaviour that does not collapse spatially, collapse to a very small area, and, most intriguingly, convergence to a cycle. Subsequent applications show how reinforced diffusion can create movement trajectories emulating the learning of movement routes by homing pigeons and consolidation of ant travel paths. The mathematically explicit manner with which assumptions about the structure of memory can be stated and subsequently explored provides linkages to biological concepts like an animal's 'immediate surroundings' and memory decay.
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Affiliation(s)
- William F. Fagan
- Department of Biology, University of Maryland, College Park, MD 20742, USA
| | - Frank McBride
- Graduate Program in Applied Mathematics and Scientific Computing, University of Maryland, College Park, MD 20742, USA
| | - Leonid Koralov
- Department of Mathematics, University of Maryland, College Park, MD 20742, USA
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4
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Kraft S, Gandra M, Lennox RJ, Mourier J, Winkler AC, Abecasis D. Residency and space use estimation methods based on passive acoustic telemetry data. MOVEMENT ECOLOGY 2023; 11:12. [PMID: 36859381 PMCID: PMC9976422 DOI: 10.1186/s40462-022-00364-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Accepted: 12/26/2022] [Indexed: 06/18/2023]
Abstract
Acoustic telemetry has helped overcome many of the challenges faced when studying the movement ecology of aquatic species, allowing to obtain unprecedented amounts of data. This has made it into one of the most widely used methods nowadays. Many ways to analyse acoustic telemetry data have been made available and deciding on how to analyse the data requires considering the type of research objectives, relevant properties of the data (e.g., resolution, study design, equipment), habits of the study species, researcher experience, among others. To ease this decision process, here we showcase (1) some of the methods used to estimate pseudo-positions and positions from raw acoustic telemetry data, (2) methods to estimate residency and (3) methods to estimate two-dimensional home and occurrence range using geometric or hull-based methods and density-distribution methods, a network-based approach, and three-dimensional methods. We provide examples of some of these were tested using a sample of real data. With this we intend to provide the necessary background for the selection of the method(s) that better fit specific research objectives when using acoustic telemetry.
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Affiliation(s)
- S Kraft
- Center of Marine Sciences (CCMAR), Universidade do Algarve, Faro, Portugal.
| | - M Gandra
- Center of Marine Sciences (CCMAR), Universidade do Algarve, Faro, Portugal
| | - R J Lennox
- Laboratory for Freshwater Ecology and Inland Fisheries at NORCE Norwegian Research Center, Bergen, Norway
- Norwegian Institute for Nature Research (NINA), Trondheim, Norway
| | - J Mourier
- MARBEC, Univ Montpellier, CNRS, Ifremer, IRD, Sète, France
| | - A C Winkler
- Center of Marine Sciences (CCMAR), Universidade do Algarve, Faro, Portugal
- Department of Ichthyology and Fisheries Science, Rhodes University, Makhanda, South Africa
| | - D Abecasis
- Center of Marine Sciences (CCMAR), Universidade do Algarve, Faro, Portugal
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5
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Pero EM, Palm EC, Chitwood MC, Hildreth AM, Keller BJ, Sumners JA, Hansen LP, Isabelle JL, Millspaugh JJ. Spatial acclimation of elk during population restoration to the Missouri Ozarks, USA. Anim Conserv 2023. [DOI: 10.1111/acv.12866] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/04/2023]
Affiliation(s)
- E. M. Pero
- Wildlife Biology Program University of Montana Missoula MT USA
| | - E. C. Palm
- Wildlife Biology Program University of Montana Missoula MT USA
| | - M. C. Chitwood
- Natural Resource Ecology & Management Oklahoma State University Stillwater OK USA
| | | | - B. J. Keller
- Minnesota Department of Natural Resources St. Paul MN USA
| | - J. A. Sumners
- Missouri Department of Conservation Jefferson City MO USA
| | - L. P. Hansen
- Missouri Department of Conservation Columbia MO USA
- Minnesota Department of Natural Resources St. Paul MN USA
| | - J. L. Isabelle
- Missouri Department of Conservation Columbia MO USA
- Minnesota Department of Natural Resources St. Paul MN USA
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6
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Potts JR, Börger L. How to scale up from animal movement decisions to spatiotemporal patterns: An approach via step selection. J Anim Ecol 2023; 92:16-29. [PMID: 36321473 PMCID: PMC10099581 DOI: 10.1111/1365-2656.13832] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Accepted: 10/16/2022] [Indexed: 11/17/2022]
Abstract
Uncovering the mechanisms behind animal space use patterns is of vital importance for predictive ecology, thus conservation and management of ecosystems. Movement is a core driver of those patterns so understanding how movement mechanisms give rise to space use patterns has become an increasingly active area of research. This study focuses on a particular strand of research in this area, based around step selection analysis (SSA). SSA is a popular way of inferring drivers of movement decisions, but, perhaps less well appreciated, it also parametrises a model of animal movement. Of key interest is that this model can be propagated forwards in time to predict the space use patterns over broader spatial and temporal scales than those that pertain to the proximate movement decisions of animals. Here, we provide a guide for understanding and using the various existing techniques for scaling up step selection models to predict broad-scale space use patterns. We give practical guidance on when to use which technique, as well as specific examples together with code in R and Python. By pulling together various disparate techniques into one place, and providing code and instructions in simple examples, we hope to highlight the importance of these techniques and make them accessible to a wider range of ecologists, ultimately helping expand the usefulness of SSA.
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Affiliation(s)
- Jonathan R Potts
- School of Mathematics and Statistics, University of Sheffield, Sheffield, UK
| | - Luca Börger
- Department of Biosciences, College of Science, Swansea University, Swansea, UK.,Centre for Biomathematics, College of Science, Swansea University, Swansea, UK
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7
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Drivers of habitat quality for a reintroduced elk herd. Sci Rep 2022; 12:20960. [PMID: 36470959 PMCID: PMC9723100 DOI: 10.1038/s41598-022-25058-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Accepted: 11/24/2022] [Indexed: 12/11/2022] Open
Abstract
Understanding spatiotemporal variation in habitat quality is essential for guiding wildlife reintroduction and restoration programs. The habitat productivity hypothesis posits that home range size is inversely related to habitat quality. Thus, home range size may be used as a proxy for habitat quality and can identify important land cover features for a recovering species. We sought to quantify variation in home range size across the biological cycle (seasons) for a reintroduced elk (Cervus canadensis) population in southwestern Virginia, USA and quantify habitat quality by linking home range sizes to the land cover types they contain using linear mixed-effects models. We found mean home range size was largest during late gestation for female elk. Additionally, throughout the year, smaller home ranges were associated with larger proportions of non-forested habitats whereas forested habitats were generally the opposite. However, both presumed poor- and high-quality habitats influenced female elk space use. Our approach revealed spatial variation in habitat quality for a recovering elk herd, demonstrated the importance of non-forested habitats to elk, can guide decisions regarding the location of future elk reintroduction programs, and serve as a model for evaluating habitat quality associated with wildlife reintroductions.
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8
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Butler MJ, Stewart DR, Harris GM, Bidwell MT, Pearse AT. Space use and site fidelity of wintering whooping cranes on the Texas Gulf Coast. J Wildl Manage 2022. [DOI: 10.1002/jwmg.22226] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
- Matthew J. Butler
- U.S. Fish and Wildlife Service, National Wildlife Refuge System Biological Services 500 Gold Avenue SW Albuquerque NM 87102 USA
| | - David R. Stewart
- U.S. Fish and Wildlife Service, National Wildlife Refuge System Biological Services 500 Gold Avenue SW Albuquerque NM 87102 USA
| | - Grant M. Harris
- U.S. Fish and Wildlife Service, National Wildlife Refuge System Biological Services 500 Gold Avenue SW Albuquerque NM 87102 USA
| | - Mark T. Bidwell
- Canadian Wildlife Service Environment and Climate Change Canada Saskatoon SK Canada
| | - Aaron T. Pearse
- U.S. Geological Survey Northern Prairie Wildlife Research Center Jamestown ND 58401 USA
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9
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Paxton KL, Baker KM, Crytser ZB, Guinto RMP, Brinck KW, Rogers HS, Paxton EH. Optimizing trilateration estimates for tracking fine‐scale movement of wildlife using automated radio telemetry networks. Ecol Evol 2022; 12:e8561. [PMID: 35169450 PMCID: PMC8831095 DOI: 10.1002/ece3.8561] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Revised: 12/13/2021] [Accepted: 12/22/2021] [Indexed: 11/11/2022] Open
Abstract
A major advancement in the use of radio telemetry has been the development of automated radio tracking systems (ARTS), which allow animal movements to be tracked continuously. A new ARTS approach is the use of a network of simple radio receivers (nodes) that collect radio signal strength (RSS) values from animal‐borne radio transmitters. However, the use of RSS‐based localization methods in wildlife tracking research is new, and analytical approaches critical for determining high‐quality location data have lagged behind technological developments. We present an analytical approach to optimize RSS‐based localization estimates for a node network designed to track fine‐scale animal movements in a localized area. Specifically, we test the application of analytical filters (signal strength, distance among nodes) to data from real and simulated node networks that differ in the density and configuration of nodes. We evaluate how different filters and network configurations (density and regularity of node spacing) may influence the accuracy of RSS‐based localization estimates. Overall, the use of signal strength and distance‐based filters resulted in a 3‐ to 9‐fold increase in median accuracy of location estimates over unfiltered estimates, with the most stringent filters providing location estimates with a median accuracy ranging from 28 to 73 m depending on the configuration and spacing of the node network. We found that distance filters performed significantly better than RSS filters for networks with evenly spaced nodes, but the advantage diminished when nodes were less uniformly spaced within a network. Our results not only provide analytical approaches to greatly increase the accuracy of RSS‐based localization estimates, as well as the computer code to do so, but also provide guidance on how to best configure node networks to maximize the accuracy and capabilities of such systems for wildlife tracking studies.
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Affiliation(s)
- Kristina L. Paxton
- Hawaiʻi Cooperative Studies Unit University of Hawaiʻi Hilo Hawaiʻi National Park Hawaii USA
| | - Kayla M. Baker
- Department of Ecology, Evolution, and Organismal Biology Iowa State University Ames Iowa USA
| | - Zia B. Crytser
- Department of Ecology, Evolution, and Organismal Biology Iowa State University Ames Iowa USA
| | - Ray Mark P. Guinto
- U.S. Geological Survey Pacific Island Ecosystems Research Center Hawaiʻi National Park Hawaii USA
| | - Kevin W. Brinck
- Hawaiʻi Cooperative Studies Unit University of Hawaiʻi Hilo Hawaiʻi National Park Hawaii USA
| | - Haldre S. Rogers
- Department of Ecology, Evolution, and Organismal Biology Iowa State University Ames Iowa USA
| | - Eben H. Paxton
- U.S. Geological Survey Pacific Island Ecosystems Research Center Hawaiʻi National Park Hawaii USA
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10
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Fleming CH, Deznabi I, Alavi S, Crofoot MC, Hirsch BT, Medici EP, Noonan MJ, Kays R, Fagan WF, Sheldon DR, Calabrese JM. Population‐level inference for home‐range areas. Methods Ecol Evol 2022. [DOI: 10.1111/2041-210x.13815] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- C. H. Fleming
- University of Maryland College Park College Park MD USA
- Smithsonian Conservation Biology Institute Front Royal VA USA
| | - I. Deznabi
- University of Massachusetts Amherst Amherst MA USA
| | - S. Alavi
- Max Planck Institute of Animal Behavior Konstanz Germany
| | - M. C. Crofoot
- Max Planck Institute of Animal Behavior Konstanz Germany
- University of Konstanz Konstanz Germany
| | | | - E. P. Medici
- Instituto de Pesquisas Ecológicas Nazaré Paulista Brazil
| | - M. J. Noonan
- The University of British Columbia Okanagan Kelowna BC Canada
| | - R. Kays
- North Carolina State University Raleigh NC USA
- North Carolina Museum of Natural Sciences Raleigh NC USA
| | - W. F. Fagan
- University of Maryland College Park College Park MD USA
| | - D. R. Sheldon
- University of Massachusetts Amherst Amherst MA USA
- Mount Holyoke College South Hadley MA USA
| | - J. M. Calabrese
- University of Maryland College Park College Park MD USA
- Smithsonian Conservation Biology Institute Front Royal VA USA
- Center for Advanced Systems Understanding (CASUS), Görlitz Germany
- Helmholtz Centre for Environmental Research (HZDR), Leipzig Germany
- Department of Ecological Modelling, Helmholtz Centre for Environmental Research (UFZ), Leipzig Germany
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11
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Fisher KE, Bradbury SP. Influence of habitat quality and resource density on breeding‐season female monarch butterfly
Danaus plexippus
movement and space use in north‐central USA agroecosystem landscapes. J Appl Ecol 2021. [DOI: 10.1111/1365-2664.14061] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
| | - Steven P. Bradbury
- Department of Entomology Iowa State University Ames IA USA
- Department of Natural Resource Ecology and Management Iowa State University Ames IA USA
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12
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Smetzer JR, Paxton KL, Paxton EH. Individual and seasonal variation in the movement behavior of two tropical nectarivorous birds. MOVEMENT ECOLOGY 2021; 9:36. [PMID: 34233764 PMCID: PMC8264974 DOI: 10.1186/s40462-021-00275-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Accepted: 06/29/2021] [Indexed: 06/13/2023]
Abstract
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 'apapane (Himatione sanguinea) and 'i'iwi (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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Affiliation(s)
- Jennifer R Smetzer
- Hawai'i Cooperative Studies Unit, University of Hawai'i at Hilo, PO Box 44, Hawai'i National Park, HI, 96718, USA.
| | - Kristina L Paxton
- Hawai'i Cooperative Studies Unit, University of Hawai'i at Hilo, PO Box 44, Hawai'i National Park, HI, 96718, USA
| | - Eben H Paxton
- U.S. Geological Survey Pacific Island Ecosystems Research Center, PO Box 44, Hawai'i National Park, HI, 96718, USA
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13
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Signer J, Fieberg JR. A fresh look at an old concept: home-range estimation in a tidy world. PeerJ 2021; 9:e11031. [PMID: 33954027 PMCID: PMC8048401 DOI: 10.7717/peerj.11031] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Accepted: 02/09/2021] [Indexed: 11/27/2022] Open
Abstract
A rich set of statistical techniques has been developed over the last several decades to estimate the spatial extent of animal home ranges from telemetry data, and new methods to estimate home ranges continue to be developed. Here we investigate home-range estimation from a computational point of view and aim to provide a general framework for computing home ranges, independent of specific estimators. We show how such a workflow can help to make home-range estimation easier and more intuitive, and we provide a series of examples illustrating how different estimators can be compared easily. This allows one to perform a sensitivity analysis to determine the degree to which the choice of estimator influences qualitative and quantitative conclusions. By providing a standardized implementation of home-range estimators, we hope to equip researchers with the tools needed to explore how estimator choice influences answers to biologically meaningful questions.
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Affiliation(s)
- Johannes Signer
- Wildlife Sciences, Faculty of Forestry and Forest Ecology, University of Goettingen, Göttingen, Germany
| | - John R Fieberg
- Department of Fisheries, Wildlife, and Conservation Biology, University of Minnesota, St. Paul, MN, USA
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14
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The Use of Animal-Borne Biologging and Telemetry Data to Quantify Spatial Overlap of Wildlife with Marine Renewables. JOURNAL OF MARINE SCIENCE AND ENGINEERING 2021. [DOI: 10.3390/jmse9030263] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The growth of the marine renewable energy sector requires the potential effects on marine wildlife to be considered carefully. For this purpose, utilization distributions derived from animal-borne biologging and telemetry data provide accurate information on individual space use. The degree of spatial overlap between potentially vulnerable wildlife such as seabirds and development areas can subsequently be quantified and incorporated into impact assessments and siting decisions. While rich in information, processing and analyses of animal-borne tracking data are often not trivial. There is therefore a need for straightforward and reproducible workflows for this technique to be useful to marine renewables stakeholders. The aim of this study was to develop an analysis workflow to extract utilization distributions from animal-borne biologging and telemetry data explicitly for use in assessment of animal spatial overlap with marine renewable energy development areas. We applied the method to European shags (Phalacrocorax aristotelis) in relation to tidal stream turbines. While shag occurrence in the tidal development area was high (99.4%), there was no overlap (0.14%) with the smaller tidal lease sites within the development area. The method can be applied to any animal-borne bio-tracking datasets and is relevant to stakeholders aiming to quantify environmental effects of marine renewables.
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15
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Calabrese JM, Fleming CH, Noonan MJ, Dong X. ctmmweb: A Graphical User Interface for Autocorrelation‐Informed Home Range Estimation. WILDLIFE SOC B 2021. [DOI: 10.1002/wsb.1154] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Affiliation(s)
- Justin M. Calabrese
- Center for Advanced Systems Understanding (CASUS) Untermarkt 20 02826 Görlitz Germany
| | - Christen H. Fleming
- Smithsonian Conservation Biology Institute 1500 Remount Rd Front Royal VA 22630 USA
| | - Michael J. Noonan
- The Irving K. Barber School of Arts and Sciences The University of British Columbia, Okanagan campus 1177 Research Road Kelowna BC V1V 1V7 Canada
| | - Xianghui Dong
- Department of Biology University of Maryland College Park MD 20742 USA
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16
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Cohen BS, Marquardt DD, Bakner NW, Perez RM, Collier BA. Daily Movements, Space Use, and Habitat Selection of GPS‐tagged Northern Bobwhite in Texas. WILDLIFE SOC B 2020. [DOI: 10.1002/wsb.1137] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Affiliation(s)
- Bradley S. Cohen
- School of Arts and Sciences Tennessee Technological University Cookeville TN 38505 USA
| | | | - Nicholas W. Bakner
- School of Renewable Natural Resources Louisiana State University Baton Rouge LA 70803 USA
| | | | - Bret A. Collier
- School of Renewable Natural Resources Louisiana State University Agricultural Center Baton Rouge LA 70803 USA
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17
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Michelot T, Gloaguen P, Blackwell PG, Étienne M. The Langevin diffusion as a continuous‐time model of animal movement and habitat selection. Methods Ecol Evol 2019. [DOI: 10.1111/2041-210x.13275] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Théo Michelot
- School of Mathematics and Statistics University of Sheffield Sheffield UK
- School of Mathematics and Statistics, Centre for Research into Ecological and Environmental Modelling University of St Andrews St Andrews UK
| | | | - Paul G. Blackwell
- School of Mathematics and Statistics University of Sheffield Sheffield UK
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18
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Péron G. The time frame of home-range studies: from function to utilization. Biol Rev Camb Philos Soc 2019; 94:1974-1982. [PMID: 31347250 DOI: 10.1111/brv.12545] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2019] [Revised: 06/18/2019] [Accepted: 06/21/2019] [Indexed: 12/23/2022]
Abstract
As technological and statistical innovations open new avenues in movement ecology, I review the fundamental implications of the time frame of home-range studies, with the aim of associating terminologies consistently with research objectives and methodologies. There is a fundamental distinction between (a) extrapolations of stationary distributions, associated with long time scales and aiming at asymptotic consistency, and (b) period-specific techniques, aiming at specificity but typically sensitive to the sampling design. I then review the difference between function and utilization in home-range studies. Most home-range studies are based on phenomenological descriptions of the time budgets of the study animals, not the function of the visited areas. I highlight emerging trends in automated pattern-recognition techniques for inference about function rather than utilization.
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Affiliation(s)
- Guillaume Péron
- University of Lyon, Laboratoire de Biométrie et Biologie Evolutive, CNRS, Université Lyon 1, UMR5558, F-69622, Villeurbanne, France
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19
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Schlägel UE, Signer J, Herde A, Eden S, Jeltsch F, Eccard JA, Dammhahn M. Estimating interactions between individuals from concurrent animal movements. Methods Ecol Evol 2019. [DOI: 10.1111/2041-210x.13235] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Ulrike E. Schlägel
- Department of Plant Ecology and Nature Conservation University of Potsdam Potsdam‐Golm Germany
| | - Johannes Signer
- Faculty of Forest Science and Forest Ecology University of Goettingen Göttingen Germany
| | - Antje Herde
- Department of Plant Ecology and Nature Conservation University of Potsdam Potsdam‐Golm Germany
| | - Sophie Eden
- Animal Ecology University of Potsdam Potsdam Germany
| | - Florian Jeltsch
- Department of Plant Ecology and Nature Conservation University of Potsdam Potsdam‐Golm Germany
- Berlin‐Brandenburg Institute of Advanced Biodiversity Research (BBIB) Berlin Germany
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20
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Noonan MJ, Tucker MA, Fleming CH, Akre TS, Alberts SC, Ali AH, Altmann J, Antunes PC, Belant JL, Beyer D, Blaum N, Böhning‐Gaese K, Cullen L, Paula RC, Dekker J, Drescher‐Lehman J, Farwig N, Fichtel C, Fischer C, Ford AT, Goheen JR, Janssen R, Jeltsch F, Kauffman M, Kappeler PM, Koch F, LaPoint S, Markham AC, Medici EP, Morato RG, Nathan R, Oliveira‐Santos LGR, Olson KA, Patterson BD, Paviolo A, Ramalho EE, Rösner S, Schabo DG, Selva N, Sergiel A, Xavier da Silva M, Spiegel O, Thompson P, Ullmann W, Zięba F, Zwijacz‐Kozica T, Fagan WF, Mueller T, Calabrese JM. A comprehensive analysis of autocorrelation and bias in home range estimation. ECOL MONOGR 2019. [DOI: 10.1002/ecm.1344] [Citation(s) in RCA: 80] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Michael J. Noonan
- Smithsonian Conservation Biology Institute National Zoological Park 1500 Remount Road Front Royal Virginia 22630 USA
- Department of Biology University of Maryland College Park Maryland 20742 USA
| | - Marlee A. Tucker
- 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
| | - Christen H. Fleming
- Smithsonian Conservation Biology Institute National Zoological Park 1500 Remount Road Front Royal Virginia 22630 USA
- Department of Biology University of Maryland College Park Maryland 20742 USA
| | - Thomas S. Akre
- Smithsonian Conservation Biology Institute National Zoological Park 1500 Remount Road Front Royal Virginia 22630 USA
| | - Susan C. Alberts
- Departments of Biology and Evolutionary Anthropology Duke University Durham North Carolina 27708 USA
| | | | - Jeanne Altmann
- Department of Ecology and Evolution Princeton University Princeton New Jersey 08544 USA
| | - Pamela Castro Antunes
- Department of Ecology Federal University of Mato Grosso do Sul Campo Grande MS 79070‐900 Brazil
| | - Jerrold L. Belant
- Camp Fire Program in Wildlife Conservation College of Environmental Science and Forestry State University of New York Syracuse New York 13210 USA
| | - Dean Beyer
- Conservation Ecology Faculty of Biology Philipps‐University Marburg Karl‐von‐Frisch Straße 8 Marburg D‐35043 Germany
| | - Niels Blaum
- Plant Ecology and Nature Conservation University of Potsdam Am Mühlenberg 3 14476 Potsdam Germany
| | - Katrin Böhning‐Gaese
- 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
| | - Laury Cullen
- Instituto de Pesquisas Ecológicas Nazare Paulista Rod. Dom Pedro I, km 47 Caixa Postal 47 ‐ 12960‐000 Nazaré Paulista SP Brazil
| | - Rogerio Cunha Paula
- National Research Center for Carnivores Conservation Chico Mendes Institute for the Conservation of Biodiversity Estrada Municipal Hisaichi Takebayashi 8600 Atibaia SP 12952‐011 Brazil
| | - Jasja Dekker
- Jasja Dekker Dierecologie Enkhuizenstraat 26 6843 WZ Arnhem The Netherlands
| | - Jonathan Drescher‐Lehman
- Smithsonian Conservation Biology Institute National Zoological Park 1500 Remount Road Front Royal Virginia 22630 USA
- Department of Biology George Mason University 4400 University Drive Fairfax Virginia 22030 USA
| | - Nina Farwig
- Michigan Department of Natural Resources 1990 U.S. 41 South Marquette Michigan 49855 USA
| | - Claudia Fichtel
- Behavioral Ecology & Sociobiology Unit German Primate Center Kellnerweg 4 37077 Göttingen Germany
| | - Christina Fischer
- Restoration Ecology Department of Ecology and Ecosystem Management Technische Universität München Emil‐Ramann‐Straße 6 85354 Freising Germany
| | - Adam T. Ford
- Department of Biology University of British Columbia 1177 Research Road Kelowna British Columbia V1V 1V7 Canada
| | - Jacob R. Goheen
- Department of Zoology and Physiology University of Wyoming Laramie Wyoming 82071 USA
| | - René Janssen
- Bionet Natuuronderzoek Valderstraat 39 6171EL Stein The Netherlands
| | - Florian Jeltsch
- Plant Ecology and Nature Conservation University of Potsdam Am Mühlenberg 3 14476 Potsdam Germany
| | - Matthew Kauffman
- U.S. Geological Survey Wyoming Cooperative Fish and Wildlife Research Unit Department of Zoology and Physiology University of Wyoming Laramie Wyoming 82071 USA
| | - Peter M. Kappeler
- Behavioral Ecology & Sociobiology Unit German Primate Center Kellnerweg 4 37077 Göttingen Germany
| | - Flávia Koch
- Behavioral Ecology & Sociobiology Unit German Primate Center Kellnerweg 4 37077 Göttingen Germany
| | - Scott LaPoint
- Max Planck Institute for Ornithology, Vogelwarte Radolfzell Am Obstberg 1 D‐78315 Radolfzell Germany
- Lamont‐Doherty Earth Observatory Columbia University Palisades New York 10964 USA
| | - A. Catherine Markham
- Department of Anthropology Stony Brook University Stony Brook New York 11794 USA
| | - Emilia Patricia Medici
- Lowland Tapir Conservation Initiative (LTCI) Instituto de Pesquisas Ecologicas (IPE) & IUCN SSC Tapir Specialist Group (TSG) Rua Licuala 622, Damha 1, CEP: 79046‐150 Campo Grande Mato Grosso do Sul Brazil
| | - Ronaldo G. Morato
- National Research Center for Carnivores Conservation Chico Mendes Institute for the Conservation of Biodiversity Estrada Municipal Hisaichi Takebayashi 8600 Atibaia SP 12952‐011 Brazil
- Institute for the Conservation of Neotropical Carnivores – Pro‐Carnívoros Atibaia SP 12945‐010 Brazil
| | - Ran Nathan
- Movement Ecology Laboratory Department of Ecology, Evolution and Behavior Alexander Silberman Institute of Life Sciences The Hebrew University of Jerusalem Edmond J. Safra Campus Jerusalem 91904 Israel
| | | | - Kirk A. Olson
- 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
| | - Bruce D. Patterson
- Integrative Research Center Field Museum of Natural History Chicago Illinois 60605 USA
| | - Agustin Paviolo
- Instituto de Biología Subtropical Universidad Nacional de Misiones and CONICET Bertoni 85 3370 Puerto Iguazú Misiones Argentina
| | - Emiliano Esterci Ramalho
- Institute for the Conservation of Neotropical Carnivores – Pro‐Carnívoros Atibaia SP 12945‐010 Brazil
- Instituto de Desenvolvimento Sustentável Mamirauá Estrada do Bexiga, 2.584 Bairro Fonte Boa Caixa Postal 38 69.553‐225 Tefé Amazonas Brazil
| | - Sascha Rösner
- Michigan Department of Natural Resources 1990 U.S. 41 South Marquette Michigan 49855 USA
| | - Dana G. Schabo
- Michigan Department of Natural Resources 1990 U.S. 41 South Marquette Michigan 49855 USA
| | - Nuria Selva
- Institute of Nature Conservation Polish Academy of Sciences Mickiewicza 33 31‐120 Krakow Poland
| | - Agnieszka Sergiel
- Institute of Nature Conservation Polish Academy of Sciences Mickiewicza 33 31‐120 Krakow Poland
| | - Marina Xavier da Silva
- Projeto Carnívoros do Iguaçu Parque Nacional do Iguaçu BR‐469, Km 22.5, CEP 85851‐970 Foz do Iguaçu PR Brazil
| | - Orr Spiegel
- School of Zoology Faculty of Life Sciences Tel Aviv University Tel Aviv 69978 Israel
| | - Peter Thompson
- Department of Biology University of Maryland College Park Maryland 20742 USA
| | - Wiebke Ullmann
- Plant Ecology and Nature Conservation University of Potsdam Am Mühlenberg 3 14476 Potsdam Germany
| | - Filip Zięba
- Tatra National Park Kuźnice 1 34‐500 Zakopane Poland
| | | | - William F. Fagan
- Department of Biology University of Maryland College Park Maryland 20742 USA
| | - Thomas Mueller
- 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
| | - Justin M. Calabrese
- Smithsonian Conservation Biology Institute National Zoological Park 1500 Remount Road Front Royal Virginia 22630 USA
- Department of Biology University of Maryland College Park Maryland 20742 USA
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21
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Fleming CH, Sheldon D, Fagan WF, Leimgruber P, Mueller T, Nandintsetseg D, Noonan MJ, Olson KA, Setyawan E, Sianipar A, Calabrese JM. Correcting for missing and irregular data in home-range estimation. ECOLOGICAL APPLICATIONS : A PUBLICATION OF THE ECOLOGICAL SOCIETY OF AMERICA 2018; 28:1003-1010. [PMID: 29450936 DOI: 10.1002/eap.1704] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/24/2017] [Revised: 11/13/2017] [Accepted: 01/02/2018] [Indexed: 06/08/2023]
Abstract
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.
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Affiliation(s)
- C H Fleming
- 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
| | - D Sheldon
- 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
| | - W F Fagan
- Department of Biology, University of Maryland College Park, College Park, Maryland, 20742, USA
| | - P Leimgruber
- Smithsonian Conservation Biology Institute, National Zoological Park, 1500 Remount Road, Front Royal, Virginia, 22630, USA
| | - T Mueller
- 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
| | - D Nandintsetseg
- 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
| | - M J Noonan
- Smithsonian Conservation Biology Institute, National Zoological Park, 1500 Remount Road, Front Royal, Virginia, 22630, USA
| | - K A Olson
- 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
| | - E Setyawan
- Manta Trust-Indonesian Manta Project, Badung, Bali, 80361, Indonesia
- Institute for Marine and Antarctic Studies, University of Tasmania, Launceston, Tasmania, 7250, Australia
| | - A Sianipar
- Conservation International Indonesia, Marine Program, Jalan Pejaten Barat 16A, Kemang, Jakarta, DKI Jakarta, 12550, Indonesia
| | - J M Calabrese
- 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
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22
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Scharf H, Hooten MB, Johnson DS. Imputation Approaches for Animal Movement Modeling. JOURNAL OF AGRICULTURAL, BIOLOGICAL AND ENVIRONMENTAL STATISTICS 2017. [DOI: 10.1007/s13253-017-0294-5] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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23
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Sennhenn-Reulen H, Diedhiou L, Klapproth M, Zinner D. Estimation of baboon daily travel distances by means of point sampling - the magnitude of underestimation. Primate Biol 2017; 4:143-151. [PMID: 32110702 PMCID: PMC7041532 DOI: 10.5194/pb-4-143-2017] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2017] [Accepted: 06/02/2017] [Indexed: 01/18/2023] Open
Abstract
Daily travel distance (DTD), the distance an animal moves over the
course of the day, is an important metric in movement ecology. It provides
data with which to test hypotheses related to energetics and behaviour, e.g. impact of
group size or food distribution on DTDs. The automated tracking of movements
by applying GPS technology has become widely available and easy to implement. However, due to
battery duration constraints, it is necessary to select a tracking-time
resolution, which inevitably introduces an underestimation of the true
underlying path distance. Here we give a quantification of this inherent
systematic underestimation of DTDs for a terrestrial primate, the Guinea
baboon. We show that sampling protocols with interval lengths from 1 to
120 min underestimate DTDs on average by 7 to 35 %. For longer time
intervals (i.e. 60, 90, 120 min), the relative increase of deviation from
the “true” trajectory is less pronounced than for shorter intervals. Our
study provides first hints on the magnitude of error, which can be applied as
a corrective when estimating absolute DTDs in calculations on travelling
costs in terrestrial primates.
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Affiliation(s)
- Holger Sennhenn-Reulen
- Cognitive Ethology Laboratory, German Primate Center, Leibniz-Institute for Primate Research, Kellnerweg 4, 37077 Göttingen, Germany.,Leibniz ScienceCampus "Primate Cognition", German Primate Center/Leibniz Institute for Primate Research, Kellnerweg 4, 37077 Göttingen, Germany
| | | | - Matthias Klapproth
- Cognitive Ethology Laboratory, German Primate Center, Leibniz-Institute for Primate Research, Kellnerweg 4, 37077 Göttingen, Germany
| | - Dietmar Zinner
- Cognitive Ethology Laboratory, German Primate Center, Leibniz-Institute for Primate Research, Kellnerweg 4, 37077 Göttingen, Germany
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24
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Fleming CH, Sheldon D, Gurarie E, Fagan WF, LaPoint S, Calabrese JM. Kálmán filters for continuous-time movement models. ECOL INFORM 2017. [DOI: 10.1016/j.ecoinf.2017.04.008] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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25
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Signer J, Fieberg J, Avgar T. Estimating utilization distributions from fitted step‐selection functions. Ecosphere 2017. [DOI: 10.1002/ecs2.1771] [Citation(s) in RCA: 45] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
Affiliation(s)
- Johannes Signer
- Department of Wildlife Sciences University of Goettingen Büsgenweg 3 37077 Göttingen Germany
| | - John Fieberg
- Department of Fisheries, Wildlife and Conservation Biology University of Minnesota 2003 Upper Buford Circle, Suite 135 St. Paul Minnesota 55108 USA
| | - Tal Avgar
- Department of Biological Sciences University of Alberta Edmonton Alberta T6G 2R3 Canada
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26
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McClintock BT, London JM, Cameron MF, Boveng PL. Bridging the gaps in animal movement: hidden behaviors and ecological relationships revealed by integrated data streams. Ecosphere 2017. [DOI: 10.1002/ecs2.1751] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Affiliation(s)
- Brett T. McClintock
- Marine Mammal Laboratory; Alaska Fisheries Science Center; NOAA-NMFS; 7600 Sand Point Way NE Seattle Washington 98115 USA
| | - Joshua M. London
- Marine Mammal Laboratory; Alaska Fisheries Science Center; NOAA-NMFS; 7600 Sand Point Way NE Seattle Washington 98115 USA
| | - Michael F. Cameron
- Marine Mammal Laboratory; Alaska Fisheries Science Center; NOAA-NMFS; 7600 Sand Point Way NE Seattle Washington 98115 USA
| | - Peter L. Boveng
- Marine Mammal Laboratory; Alaska Fisheries Science Center; NOAA-NMFS; 7600 Sand Point Way NE Seattle Washington 98115 USA
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27
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Calabrese JM, Fleming CH, Gurarie E. ctmm: an
r
package for analyzing animal relocation data as a continuous‐time stochastic process. Methods Ecol Evol 2016. [DOI: 10.1111/2041-210x.12559] [Citation(s) in RCA: 238] [Impact Index Per Article: 29.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Justin M. Calabrese
- Smithsonian Conservation Biology Institute National Zoological Park 1500 Remount Rd. Front Royal VA 22630 USA
- Department of Biology University of Maryland College Park MD 20742 USA
| | - Chris H. Fleming
- Smithsonian Conservation Biology Institute National Zoological Park 1500 Remount Rd. Front Royal VA 22630 USA
- Department of Biology University of Maryland College Park MD 20742 USA
| | - Eliezer Gurarie
- Department of Biology University of Maryland College Park MD 20742 USA
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