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
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
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DOI：
10.1111/1365-2664.12410
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发表时间：
2015-06-01
影响因子：
5.7
通讯作者：
Bowen, Sharon
中科院分区：
文献类型：
--
作者：
Bino, Gilad;Sisson, Scott A.;Bowen, Sharon
漫滩植被状态（群落）表现出植被结构和组成的时空动态特征，反映了独特的水文和连通性模式。淹没状态的变化可以驱动演替并建立新的稳定状态，这取决于水文扰动的大小和持续时间。我们的目标是开发一种建模方法，能够捕捉生态系统动态，识别和量化变化的主要驱动因素，并为保护决策提供工具。我们基于1991年和2008年对澳大利亚麦夸里沼泽（一个国际重要的拉姆萨尔湿地）的调查，开发了洪泛区植被状态的状态和过渡模型。我们使用贝叶斯逻辑回归方法来模拟状态和植被状态之间的转换，并研究了这一时期洪水频率、与河流的距离和火灾频率与植被动态的关系。在1991-2008年期间，发生了向干旱州的重大转变。半永久性湿地植被的持续概率最低（p(psis)=0456），向陆生植被过渡的阈值响应显著（p(tran)=0505）。向干旱状态的过渡是由较低的淹没概率驱动的，其次是火灾概率的增加，以及距离最近的河流的距离。利用开发的模型，我们预测了在不受管制（即没有水坝或引水）和受管制的水可用性系统下植被状态的持续概率。在调控系统下，半永久性湿地植被的平均持久性p(psis)=0。在自然保护区的北段和南段分别有67条和008条。在非调节系统下，半永久性湿地植被的预测持久性显著提高，p（psis）分别为087和038。合成与应用。发展状态转变的定量模型显著提高了我们对生态系统动力学的理解，确定了监测的敏感指标，从而支持了保护决策。这有助于管理人员了解响应管理选择的生态系统变化的潜在轨迹。例如，据预测，由于河流管理，麦格理沼泽的环境流量增加，将使该社区更多地转向湿地而不是陆地状态。状态和过渡模型确定了关键生态资产如何响应变化驱动因素，特别是在哪些方面可以对其进行管理。这对于确保所有生态系统组成部分都得到管理，并且这些组成部分不会转移到不受欢迎的状态至关重要。发展状态转变的定量模型显著提高了我们对生态系统动力学的理解，确定了监测的敏感指标，从而支持了保护决策。这有助于管理人员了解响应管理选择的生态系统变化的潜在轨迹。例如，据预测，由于河流管理，麦格理沼泽的环境流量增加，将使该社区更多地转向湿地而不是陆地状态。状态和过渡模型确定了关键生态资产如何响应变化驱动因素，特别是在哪些方面可以对其进行管理。这对于确保所有生态系统组成部分都得到管理，并且这些组成部分不会转移到不受欢迎的状态至关重要。
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. 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. During 1991-2008, significant transitions have occurred towards drier states. Semi-permanent wetland vegetation had the lowest persistence probability (p(psis)=0456) and a significant threshold response of transitioning to terrestrial vegetation (p(tran)=0505). Transition to drier states was driven by lower inundation probabilities followed by increased fire probability, and distance to nearest stream. 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 p(psis)=0. 67 and 008 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: p(psis)=087 and 038, respectively.Synthesis and applications. 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.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.