Developing state and transition models of floodplain vegetation dynamics as a tool for conservation decision‐making: a case study of the Macquarie Marshes Ramsar wetland. Issue 3 (1st March 2015)

• Record Type: Journal Article
• Authors: Bino, Gilad; Sisson, Scott A.; Kingsford, Richard T.; Thomas, Rachael F.; Bowen, Sharon; Kardol, Paul
• Is Part Of: Journal of applied ecology. Volume 52:Issue 3(2015)
• Page Start: 654
• Page End: 664
• Publication Date: 2015-03-01
• Subjects: Agriculture -- Periodicals; Biology, Economic -- Periodicals; Agricultural ecology -- Periodicals; Applied ecology -- Periodicals; 577
• DOI: 10.1111/1365-2664.12410
• Languages: English
• ISSNs: 0021-8901

Abstract

<abstract abstract-type="main" id="jpe12410-abs-0001"> <title>Summary</title> <p> <list id="jpe12410-list-0001" list-type="order"> <list-item> <p>Floodplain vegetation states (communities) exhibit spatiotemporal dynamics in vegetation structure and composition, which reflect unique hydrological and connectivity patterns. Shifts in inundation regimes can drive succession and establish new stable states, determined by the magnitude and duration of the hydrological perturbation.</p> </list-item> <list-item> <p>We aimed to develop a modelling approach that is able to capture ecosystem dynamics, identify and quantify the main drivers of change, and provide a tool for conservation decision‐making. We developed state and transition models for floodplain vegetation states based on surveys in 1991 and 2008 in the Macquarie Marshes (Australia), a Ramsar wetland of international importance. We used a Bayesian logistic regression approach to model state and transitions between vegetation states and investigated how flood frequency, distance to stream and fire frequency were associated with vegetation dynamics during this period.</p> </list-item> <list-item> <p>During 1991–2008, significant transitions have occurred towards drier states. Semi‐permanent wetland vegetation had the lowest persistence probability (<italic>p</italic><sub><italic>psis </italic></sub>= 0·456) and a significant threshold response of transitioning to terrestrial vegetation (<italic>p</italic><sub><italic>tran </italic></sub>= 0·505). Transition to drier states was driven by lower inundation probabilities followed by increased fire probability, and distance to nearest stream.</p> </list-item> <list-item> <p>Using developed models, we predicted persistence probabilities of vegetation states under an unregulated (i.e. no dams or diversions) and regulated water availability system. Under a regulated system, semi‐permanent wetland vegetation had an average persistence of <italic>p</italic><sub><italic>psis </italic></sub>= 0. 67 and 0·08 in the northern and southern sections of the nature reserve, respectively. Under an unregulated system, the predicted persistence of semi‐permanent wetland vegetation was considerably higher: <italic>p</italic><sub><italic>psis </italic></sub>= 0·87 and 0·38, respectively.</p> </list-item> <list-item> <p> <italic>Synthesis and applications</italic>. Developing quantitative models of state transitions significantly improved our understanding of ecosystem dynamics, identifying sensitive indicators for monitoring and thus supporting conservation decision‐making. This helps managers understand potential trajectories of change in ecosystems in response to management options. For example, increasing environmental flows in the Macquarie Marshes is predicted to shift the community towards more of a wetland than the terrestrial state, resulting from river regulation. State and transition models identified how key ecological assets respond to drivers of change, particularly where these can be managed. This is critical for ensuring that all ecosystem components are managed and that these do not shift into undesirable states.</p> </list-item> </list> </p> </abstract>