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Discrete choice modelling of natal dispersal: ‘Choosing’ where to breed from a finite set of available areas
Author(s) -
Vardakis Michalis,
Goos Peter,
Adriaensen Frank,
Matthysen Erik
Publication year - 2015
Publication title -
methods in ecology and evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.425
H-Index - 105
ISSN - 2041-210X
DOI - 10.1111/2041-210x.12404
Subject(s) - biological dispersal , ecology , habitat , settlement (finance) , set (abstract data type) , geography , econometrics , computer science , biology , mathematics , population , demography , sociology , world wide web , payment , programming language
SummaryClassic natal dispersal studies focus mainly on distance travelled. Although distances capture some of the main selective pressures related to dispersal, this approach cannot easily incorporate the properties of the actual destination vs. the available alternatives. Recently, movement ecology studies have addressed questions on movement decisions in relation to availability of resources and/or availability of suitable habitats through the use of discrete choice models ( DCM s), a widely used type of models within econometrics, which explains individual choices as a function of the properties of a finite number of alternatives. In this contribution, we show how the dispersal discrete choice model ( DDCM ) can be used for analysing natal dispersal data in patchy environments given that the natal and the breeding area of the disperser are observed. We test this method using a case study on Great Tits ( Parus major ) in an archipelago of small woodlots. Our results show that DDCM s are able to capture the results of classic distance‐based approaches and simultaneously allow testing hypotheses on how departure and settlement are affected by variables that characterize the disperser, the natal patch and the breeding area, as well as their interactions.DDCM s can be applied to any other species and system that uses some form of discrete breeding location or a certain degree of discretization can be applied.