figshare
Browse
Hassall & Thompson (2012) J Ins Cons.pdf (1.12 MB)

Study design and mark-recapture estimates of dispersal: a case study with the endangered damselfly Coenagrion mercuriale

Download (0 kB)
journal contribution
posted on 2014-03-24, 18:45 authored by Christopher HassallChristopher Hassall, David Thompson

Accurate data on dispersal ability are vital to the understanding of how species are affected by fragmented landscapes. However, three factors may limit the ability of field studies to detect a representative sample of dispersal events: (1) the number of individuals monitored, (2) the area over which the study is conducted and (3) the time over which the study is conducted. Using sub-sampling of mark-release-recapture data from a study on the endangered damselfly Coenagrion mercuriale (Charpentier), we show that maximum dispersal distance is strongly related to the number of recaptured individuals in the mark-release-recapture study and the length of time over which the study is conducted. Median dispersal distance is only related significantly to the length of the study. Spatial extent is not associated with either dispersal measure in our analysis. Previously consideration has been given to the spatial scale of dispersal experiments but we demonstrated conclusively that temporal scale and the number of marked individuals also have the potential to affect the measurement of dispersal. Based on quadratic relationships between the maximum dispersal distance, recapture number and length of study, we conclude that a previous study was of sufficient scale to characterise the dispersal kernel of C. mercuriale. Our method of analysis could be used to ensure that the results of mark-release-recapture studies are independent of levels of spatial and temporal investment. Improved confidence in dispersal estimates will enable better management decisions to be made for endangered species.

History

Usage metrics

    Licence

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC