Literature DB >> 30631244

Ecological metrics and methods for GPS movement data.

Dana Paige Seidel1, Eric Dougherty1, Colin Carlson2,3, Wayne M Getz1,4.   

Abstract

The growing field of movement ecology uses high resolution movement data to analyze animal behavior across multiple scales: from individual foraging decisions to population-level space-use patterns. These analyses contribute to various subfields of ecology-inter alia behavioral, disease, landscape, resource, and wildlife-and facilitate facilitate novel exploration in fields ranging from conservation planning to public health. Despite the growing availability and general accessibility of animal movement data, much potential remains for the analytical methods of movement ecology to be incorporated in all types of geographic analyses. This review provides for the Geographical Information Sciences (GIS) community an overview of the most common movement metrics and methods of analysis employed by animal ecologists. Through illustrative applications, we emphasize the potential for movement analyses to promote transdisciplinary GIS/wildlife-ecology research.

Entities:  

Keywords:  Animal Movement; GPS telemetry; Movement Analysis; Movement Ecology; Tracking data

Year:  2018        PMID: 30631244      PMCID: PMC6322554          DOI: 10.1080/13658816.2018.1498097

Source DB:  PubMed          Journal:  Int J Geogr Inf Sci        ISSN: 1365-8816            Impact factor:   4.186


  10 in total

1.  How often should dead-reckoned animal movement paths be corrected for drift?

Authors:  Richard M Gunner; Mark D Holton; David M Scantlebury; Phil Hopkins; Emily L C Shepard; Adam J Fell; Baptiste Garde; Flavio Quintana; Agustina Gómez-Laich; Ken Yoda; Takashi Yamamoto; Holly English; Sam Ferreira; Danny Govender; Pauli Viljoen; Angela Bruns; O Louis van Schalkwyk; Nik C Cole; Vikash Tatayah; Luca Börger; James Redcliffe; Stephen H Bell; Nikki J Marks; Nigel C Bennett; Mariano H Tonini; Hannah J Williams; Carlos M Duarte; Martin C van Rooyen; Mads F Bertelsen; Craig J Tambling; Rory P Wilson
Journal:  Anim Biotelemetry       Date:  2021-10-16

2.  Inferring an animal's environment through biologging: quantifying the environmental influence on animal movement.

Authors:  J A J Eikelboom; H J de Knegt; M Klaver; F van Langevelde; T van der Wal; H H T Prins
Journal:  Mov Ecol       Date:  2020-10-19       Impact factor: 3.600

3.  Climate alters the movement ecology of a non-migratory bird.

Authors:  Landon K Neumann; Samuel D Fuhlendorf; Craig D Davis; Shawn M Wilder
Journal:  Ecol Evol       Date:  2022-04-23       Impact factor: 3.167

Review 4.  Recent trends in movement ecology of animals and human mobility.

Authors:  Rocío Joo; Simona Picardi; Matthew E Boone; Thomas A Clay; Samantha C Patrick; Vilma S Romero-Romero; Mathieu Basille
Journal:  Mov Ecol       Date:  2022-05-25       Impact factor: 5.253

5.  A guide to pre-processing high-throughput animal tracking data.

Authors:  Pratik Rajan Gupte; Christine E Beardsworth; Orr Spiegel; Emmanuel Lourie; Sivan Toledo; Ran Nathan; Allert I Bijleveld
Journal:  J Anim Ecol       Date:  2021-11-16       Impact factor: 5.606

6.  Landscape characteristics influence ranging behavior of Asian elephants at the human-wildlands interface in Myanmar.

Authors:  A N Chan; G Wittemyer; J McEvoy; A C Williams; N Cox; P Soe; M Grindley; N M Shwe; A M Chit; Z M Oo; P Leimgruber
Journal:  Mov Ecol       Date:  2022-02-05       Impact factor: 3.600

Review 7.  Non-Lethal Sampling Supports Integrative Movement Research in Freshwater Fish.

Authors:  Matt J Thorstensen; Carolyn A Vandervelde; William S Bugg; Sonya Michaleski; Linh Vo; Theresa E Mackey; Michael J Lawrence; Ken M Jeffries
Journal:  Front Genet       Date:  2022-04-25       Impact factor: 4.772

8.  pamlr: A toolbox for analysing animal behaviour using pressure, acceleration, temperature, magnetic or light data in R.

Authors:  Kiran L Dhanjal-Adams; Astrid S T Willener; Felix Liechti
Journal:  J Anim Ecol       Date:  2022-04-22       Impact factor: 5.606

9.  Time and energy costs of different foraging choices in an avian generalist species.

Authors:  Alejandro Sotillo; Jan M Baert; Wendt Müller; Eric W M Stienen; Amadeu M V M Soares; Luc Lens
Journal:  Mov Ecol       Date:  2019-12-30       Impact factor: 3.600

10.  Deep inference of seabird dives from GPS-only records: Performance and generalization properties.

Authors:  Amédée Roy; Sophie Lanco Bertrand; Ronan Fablet
Journal:  PLoS Comput Biol       Date:  2022-03-11       Impact factor: 4.475

  10 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.