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Critical transitions in disturbance-driven ecosystems: identifying Windows of Opportunity for recovery
Balke, T.; Herman, P.M.J.; Bouma, T.J. (2014). Critical transitions in disturbance-driven ecosystems: identifying Windows of Opportunity for recovery. J. Ecol. 102(3): 700-708.
In: Journal of Ecology. British Ecological Society: Oxford. ISSN 0022-0477, more
Peer reviewed article  

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Author keywords
    saltmarsh; biogeomorphology; critical transitions; stable state;mangrove; riparian; plant population and community dynamics

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    Vegetation recovery in disturbance-driven ecosystems is difficult to predict. We demonstrate a concept to analyse time series for short-term variability in external forcing that can identify potential events for sudden vegetation recovery in biogeomorphic ecosystems such as saltmarshes, mangroves, dunes or floodplains.
    Time series of external forcing (i.e. water level and wind speed) were analysed for 'Windows of Opportunity' (WoO), defined as disturbance-free periods of a critical minimal duration directly following potential diaspore dispersal, which allow seedling establishment and can induce a sudden shift to a new persistent vegetation cover.
    Across different ecosystems, the minimal required WoO duration determines how many WoO events are available for seedling establishment. The distribution of WoO along an elevation gradient on riverbanks and in tidal systems, for example, is defined by the combination of the overall disturbance regime (e.g. seasonal vs. tidal flooding cycles) and the stochastic deviations from that regime (e.g. changes in weather conditions). Standardizing the WoO for the frequency of the regular disturbance regime shows that tidal and river systems have a similar relation between the required WoO length and the elevation suitable for establishment. WoO analysis correctly predicted a sudden vegetation recovery event in a saltmarsh case study.
    Synthesis. Time-series analysis for 'WoO' offers an important tool towards predicting the establishment of vegetation cover in disturbance-driven ecosystems and may have broader implications for understanding critical transitions in general. Quantifying the effects of stochastic external forcing on critical transitions in ecosystems is crucial for restoration efforts and to assess the effects of anthropogenic and global change.

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