Is beach scenic quality a function of habitat diversity?

R.W. Duck, M. R. Phillips, A. T. Williams, T. Wadham

    Research output: Contribution to journalArticlepeer-review

    12 Citations (Scopus)

    Abstract

    Recently there has been an increasing trend towards coastal scenery quantification and a novel method first introduced a few years ago is finding wide applicability within Europe as an effective classification and management tool. Beaches are assessed using a checklist comprising IS physical and eight human parameters, selected on the basis of literature searches and a questionnaire survey of experts and beach users, which best delineate coastal scenery. To overcome subjectivity and quantify uncertainty, results are subsequently Subjected to a Fuzzy Logic systems approach. In this way, the method calculates a site Evaluation Index (D) which enables beaches to be ranked according to a five-fold classification: Class 1 (D > 0.85, an extremely attractive natural site in terms of scenic quality); Class 2 (0.85 > D > 0.65); Class 3 (0.65 > 1) > 0.4); Class 4 (0.4 > D > 0) and Class 5 (D < 0, a very unattractive, developed urban site). Results from scenically diverse UK regions; eastern Scotland, southwest Wales and southwest England, indicate that beach D Values show no statistically significant correlation (R-2 = 0.0065) with diversity of habitats present. Most important to beach users are litter Free sediment and clean seawater; far more so than richness and diversity of coastal habitats. Furthermore, the award of beach Blue Flag status, so coveted by local authorities, typically does not equate with a naturally attractive, scenic site.

    Original languageEnglish
    Pages (from-to)415-418
    Number of pages4
    JournalJournal of Coastal Research
    Issue numberSI 56
    Publication statusPublished - 2009

    Keywords

    • Coastal
    • Management
    • Fuzzy logic

    Fingerprint

    Dive into the research topics of 'Is beach scenic quality a function of habitat diversity?'. Together they form a unique fingerprint.

    Cite this