Literature DB >> 28369891

A framework for modelling range shifts and migrations: asking when, whither, whether and will it return.

Eliezer Gurarie1, Francesca Cagnacci2,3, Wibke Peters2,4, Christen H Fleming1,5, Justin M Calabrese1,5, Thomas Mueller6,7, William F Fagan1.   

Abstract

Many animals undertake movements that are longer scaled and more directed than their typical home ranging behaviour. These movements include seasonal migrations (e.g. between breeding and feeding grounds), natal dispersal, nomadic range shifts and responses to local environmental disruptions. While various heuristic tools exist for identifying range shifts and migrations, none explicitly model the movement of the animals within a statistical framework that facilitates quantitative comparisons. We present the mechanistic range shift analysis (MRSA), a method to estimate a suite of range shift parameters: times of initiation, duration of transitions, centroids and areas of respective ranges. The method can take the autocorrelation and irregular sampling that is characteristic of much movement data into account. The mechanistic parameters suggest an intuitive measure, the range shift index, for the extent of a range shift. The likelihood based estimation further allows for statistical tests of several relevant hypotheses, including a range shift test, a stopover test and a site fidelity test. The analysis tools are provided in an R package (marcher). We applied the MRSA to a population of GPS tracked roe deer (Capreolus capreolus) in the Italian Alps between 2005 and 2008. With respect to seasonal migration, this population is extremely variable and difficult to classify. Using the MRSA, we were able to quantify the behaviours across the population and among individuals across years, identifying extents, durations and locations of seasonal range shifts, including cases that would have been ambiguous to detect using existing tools. The strongest patterns were differences across years: many animals simply did not perform a seasonal migration to wintering grounds during the mild winter of 2006-2007, even though some of these same animals did move extensively in other, harsher winters. For seasonal migrants, however, site fidelity across years was extremely high, even after skipping an entire seasonal migration. These results suggest that for roe deer behavioural plasticity and tactical responses to immediate environmental cues are reflected in the decision of whether rather than where to migrate. The MRSA also revealed a trade-off between the probability of migrating and the size of a home range.
© 2017 The Authors. Journal of Animal Ecology © 2017 British Ecological Society.

Entities:  

Keywords:  zzm321990Capreolus capreoluszzm321990; OU process; OUF process; continuous time movement models; migratoriness; partial migration; roe deer

Mesh:

Year:  2017        PMID: 28369891     DOI: 10.1111/1365-2656.12674

Source DB:  PubMed          Journal:  J Anim Ecol        ISSN: 0021-8790            Impact factor:   5.091


  12 in total

1.  Truly sedentary? The multi-range tactic as a response to resource heterogeneity and unpredictability in a large herbivore.

Authors:  Ophélie Couriot; A J Mark Hewison; Sonia Saïd; Francesca Cagnacci; Simon Chamaillé-Jammes; John D C Linnell; Atle Mysterud; Wibke Peters; Ferdinando Urbano; Marco Heurich; Petter Kjellander; Sandro Nicoloso; Anne Berger; Pavel Sustr; Max Kroeschel; Leif Soennichsen; Robin Sandfort; Benedikt Gehr; Nicolas Morellet
Journal:  Oecologia       Date:  2018-04-02       Impact factor: 3.225

2.  Disentangling social interactions and environmental drivers in multi-individual wildlife tracking data.

Authors:  Justin M Calabrese; Christen H Fleming; William F Fagan; Martin Rimmler; Petra Kaczensky; Sharon Bewick; Peter Leimgruber; Thomas Mueller
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2018-05-19       Impact factor: 6.237

3.  Green-up selection by red deer in heterogeneous, human-dominated landscapes of Central Europe.

Authors:  Benjamin Sigrist; Claudio Signer; Sascha D Wellig; Arpat Ozgul; Flurin Filli; Hannes Jenny; Dominik Thiel; Sven Wirthner; Roland F Graf
Journal:  Ecol Evol       Date:  2022-07-04       Impact factor: 3.167

Review 4.  Rapid changes in seed dispersal traits may modify plant responses to global change.

Authors:  Jeremy S Johnson; Robert Stephen Cantrell; Chris Cosner; Florian Hartig; Alan Hastings; Haldre S Rogers; Eugene W Schupp; Katriona Shea; Brittany J Teller; Xiao Yu; Damaris Zurell; Gesine Pufal
Journal:  AoB Plants       Date:  2019-03-28       Impact factor: 3.276

Review 5.  Population and evolutionary dynamics in spatially structured seasonally varying environments.

Authors:  Jane M Reid; Justin M J Travis; Francis Daunt; Sarah J Burthe; Sarah Wanless; Calvin Dytham
Journal:  Biol Rev Camb Philos Soc       Date:  2018-03-25

6.  A hierarchical machine learning framework for the analysis of large scale animal movement data.

Authors:  Colin J Torney; Juan M Morales; Dirk Husmeier
Journal:  Mov Ecol       Date:  2021-02-18       Impact factor: 3.600

7.  Climate change and anthropogenic food manipulation interact in shifting the distribution of a large herbivore at its altitudinal range limit.

Authors:  Julius G Bright Ross; Wibke Peters; Federico Ossi; Paul R Moorcroft; Emanuele Cordano; Emanuele Eccel; Filippo Bianchini; Maurizio Ramanzin; Francesca Cagnacci
Journal:  Sci Rep       Date:  2021-04-07       Impact factor: 4.379

8.  The level of habitat patchiness influences movement strategy of moose in Eastern Poland.

Authors:  Tomasz Borowik; Mirosław Ratkiewicz; Weronika Maślanko; Norbert Duda; Rafał Kowalczyk
Journal:  PLoS One       Date:  2020-03-19       Impact factor: 3.240

9.  Scale-insensitive estimation of speed and distance traveled from animal tracking data.

Authors:  Michael J Noonan; Christen H Fleming; Thomas S Akre; Jonathan Drescher-Lehman; Eliezer Gurarie; Autumn-Lynn Harrison; Roland Kays; Justin M Calabrese
Journal:  Mov Ecol       Date:  2019-11-15       Impact factor: 3.600

10.  Longest terrestrial migrations and movements around the world.

Authors:  Kyle Joly; Eliezer Gurarie; Mathew S Sorum; Petra Kaczensky; Matthew D Cameron; Andrew F Jakes; Bridget L Borg; Dejid Nandintsetseg; J Grant C Hopcraft; Bayarbaatar Buuveibaatar; Paul F Jones; Thomas Mueller; Chris Walzer; Kirk A Olson; John C Payne; Adiya Yadamsuren; Mark Hebblewhite
Journal:  Sci Rep       Date:  2019-10-25       Impact factor: 4.379

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