Long-term ecological trends of flow-dependent ecosystems in a major regulated river basin

Matthew J. Colloff*, Peter Caley, Neil Saintilan, Carmel A. Pollino, Neville D. Crossman

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    43 Citations (Scopus)


    The case for restoring water to the environment in the Murray-Darling Basin, Australia, is based mainly on condition assessments, although time series provide valuable information on trends. We assessed trends of 301 ecological time series (mean 23 years, range 1905-2013) in two categories: (1) 'population' (abundance, biomass, extent) and (2) 'non-population' (condition, occurrence, composition). We analysed trends using log-linear regression, accounting for observation error only, and a state-space model that accounts for observation error and environmental 'noise'. Of the log-linear series (n=239), 50 (22%) showed statistically significant decline, but 180 (78%) showed no trend. For state-space series (n=197) one increased, but others were stable. Distribution of median exponential rates of increase (r) indicated a small but statistically significant declining trend, though 35-39% of the series were positive. Our analysis only partly supports, though does not refute, prevailing assumptions of recent ecological decline in the Murray-Darling Basin. The pattern is of fluctuating stability, with declines during droughts and recovery after flood. The overall trend from our meta-analysis is consistent with a pattern of historical decline to a hybrid ecosystem followed by slow, recent decline for some components and stability for others, with considerable variation in trends of specific ecological components: in short, there are ecological 'winners' and 'losers'.

    Original languageEnglish
    Pages (from-to)957-969
    Number of pages13
    JournalMarine and Freshwater Research
    Issue number11
    Publication statusPublished - 2015


    • ecosystem resilience
    • environmental condition
    • environmental flow
    • freshwater
    • historical data
    • meta-analysis
    • monitoring
    • population dynamics
    • state-space model


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