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

1. 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. 2. 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. 3. During 1991–2008, significant trans...

1. 泛滥平原植被状态（Floodplain vegetation states，即群落）在植被结构与组成上呈现时空动态特征，该特征反映了其独特的水文与连通性格局。淹水节律的改变可驱动群落演替并形成新的稳定状态，而该过程由水文扰动的强度与持续时长决定。
2. 本研究旨在开发一种能够捕捉生态系统动态、识别并量化主要变化驱动因子，并为保护决策提供支持工具的建模方法。研究基于1991年与2008年对国际重要拉姆萨尔湿地（Ramsar wetland）——澳大利亚麦夸里沼泽（Macquarie Marshes）的野外调查数据，构建了泛滥平原植被状态的状态与转移模型（state and transition models）。本研究采用贝叶斯逻辑回归（Bayesian logistic regression）方法对植被状态及其间的转移过程进行建模，并探究了该时段内洪水频率、距河道距离与火灾频率如何影响植被动态。
3. 在1991年至2008年期间，显著的[原文内容未完整呈现]