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Publication - Professor Jane Memmott

    A method for the objective selection of landscape-scale study regions and sites at the national level

    Citation

    Gillespie, MA, Baude, M, Biesmeijer, J, Boatman, N, Budge, GE, Crowe, A, Memmott, J, Morton, RD, Pietravalle, S, Potts, SG, Senapathi, D, Smart, SM & Kunin, WE, 2017, ‘A method for the objective selection of landscape-scale study regions and sites at the national level’. Methods in Ecology and Evolution.

    Abstract

    Ecological processes operating on large
    spatio-temporal scales are difficult to disentangle with traditional empirical
    approaches. Alternatively, researchers can take advantage of ‘natural’
    experiments, where experimental control is exercised by careful site selection.
    Recent advances in developing protocols for designing these
    ‘pseudo-experiments’ commonly do not consider the selection of the focal region
    and predictor variables are usually restricted to two. Here, we advance this
    type of site selection protocol to study the impact of multiple landscape scale
    factors on pollinator abundance and diversity across multiple regions.



    Using datasets of geographic and
    ecological variables with national coverage, we applied a novel hierarchical
    computation approach to select study sites that contrast as much as possible in
    four key variables, while attempting to maintain regional comparability and
    national representativeness. There were three main steps to the protocol: (i)
    selection of six 100 × 100 km2 regions that collectively
    provided land cover representative of the national land average, (ii) mapping
    of potential sites into a multivariate space with axes representing four key
    factors potentially influencing insect pollinator abundance, and (iii) applying
    a selection algorithm which maximized differences between the four key
    variables, while controlling for a set of external constraints.



     



    Validation data for the site selection metrics were
    recorded alongside the collection of data on pollinator populations during two
    field campaigns. While the accuracy of the metric estimates varied, the site
    selection succeeded in objectively identifying field sites that differed
    significantly in values for each of the four key variables. Between-variable
    correlations were also reduced or eliminated, thus facilitating analysis of
    their separate effects.



    This study has shown that national datasets can be
    used to select randomized and replicated field sites objectively within
    multiple regions and along multiple interacting gradients. Similar protocols
    could be used for studying a range of alternative research questions related to
    land use or other spatially explicit environmental variables, and to identify
    networks of field sites for other countries, regions, drivers and response taxa
    in a wide range of scenarios.

    Full details in the University publications repository