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Modeling of hydroecological feedbacks predicts distinct classes of landscape pattern, process, and restoration potential in shallow aquatic ecosystems

机译:对水生态反馈的建模预测了浅水生态系统中不同类型的景观格局,过程和恢复潜力

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It is widely recognized that interactions between vegetation and flow cause the emergence of channel patterns that are distinct from the standard Schumm classification of river channels. Although landscape pattern is known to be linked to ecosystem services such as habitat provision, pollutant removal, and sustaining biodiversity, the mechanisms responsible for the development and stability of different landscape patterns in shallow, vegetated flows have remained poorly understood. Fortunately, recent advances have made possible large-scale models of flow through vegetated environments that can be run over a range of environmental variables and over timescales of millennia. We describe a new, quasi-3D cellular automata model that couples simulations of shallow-water flow, bed shear stresses, sediment transport, and vegetation dynamics in an efficient manner. That efficiency allowed us to apply the model widely in order to determine how different hydroecological feedbacks control landscape pattern and process in various types of wetlands and floodplains. Distinct classes of landscape pattern were uniquely associated with specific types of allogenic and autogenic drivers in wetland flows. Regular, anisotropically patterned wetlands were dominated by allogenic processes (i.e., processes driven by periodic high water levels and flow velocities that redistribute sediment), relative to autogenic processes (e.g., vegetation production, peat accretion, and gravitational erosion). These anistropically patterned wetlands are therefore particularly prone to hydrologic disturbance. Other classes of wetlands that emerged from simulated interactions included maze-patterned, amorphous, and topographically noisy marshes, open marsh with islands, banded string-pool sequences perpendicular to flow, parallel deep and narrow channels flanked by marsh, and ridge-and-slough patterned marsh oriented parallel to flow. Because vegetation both affects and responds to the balance between the transport capacity of the flow and sediment supply, these vegetated systems exhibit a feedback that is not dominant in most rivers. Consequently, unlike in most rivers, it is not possible to predict the "channel pattern" of a vegetated landscape based only on discharge characteristics and sediment supply; the antecedent vegetation pattern and vegetation dynamics must also be known. In general, the stability of different wetland pattern types is most strongly related to factors controlling the erosion and deposition of sediment at vegetation patch edges, the magnitude of sediment redistribution by flow, patch elevation relative to water level, and the variability of erosion rates in vegetation patches with low flow-resistance. As we exemplify in our case-study of the Everglades ridge and slough landscape, feedback between flow and vegetation also causes hysteresis in landscape evolution trajectories that will affect the potential for landscape restoration. Namely, even if the hydrologic conditions that historically produced higher flows are restored, degraded portions of the ridge and slough landscape are unlikely to revert to their former patterning. As wetlands and floodplains worldwide become increasingly threatened by climate change and urbanization, the greater mechanistic understanding of landscape pattern and process that our analysis provides will improve our ability to forecast and manage the behavior of these ecosystems.
机译:人们普遍认识到,植被与水流之间的相互作用会导致河床模式的出现,这与标准的河道Schumm分类不同。尽管已知景观格局与生态系统服务(例如栖息地提供,污染物去除和维持生物多样性)相关联,但对于浅层植被流中不同景观格局的发展和稳定性的机制仍知之甚少。幸运的是,最近的进展使在植被环境中流动的大规模模型成为可能,该模型可以在一系列环境变量和几千年的时间尺度上运行。我们描述了一种新的准3D元胞自动机模型,该模型以有效的方式结合了浅水流动,河床切应力,泥沙输送和植被动力学的模拟。这种效率使我们能够广泛应用该模型,以确定不同的水生态反馈如何控制各种类型的湿地和洪泛区的景观格局和过程。不同类型的景观格局与湿地流中的特定类型的异源和自生驱动因子独特相关。相对于自生过程(例如植被的产生,泥炭的堆积和重力侵蚀),常规的,各向异性模式的湿地主要由同种异体过程(即由周期性的高水位和重新分配沉积物的流速驱动的过程)主导。因此,这些具有各向异性图案的湿地特别容易受到水文干扰。通过模拟的相互作用产生的其他类型的湿地包括迷宫状,无定形和地形嘈杂的沼泽,开阔的沼泽和岛屿,垂直于水流的带状串池序列,平行的深窄通道,沼泽两侧以及山脊和泥沼。与水流平行的带图案的沼泽。由于植被既影响着流量又影响着沉积物供应量之间的平衡,因此这些植被系统表现出的反馈作用在大多数河流中都不占主导地位。因此,与大多数河流不同,不可能仅根据流量特征和沉积物供应量来预测植被景观的“通道模式”。还必须知道先前的植被格局和植被动态。通常,不同湿地类型类型的稳定性与控制植被斑块边缘的沉积物的侵蚀和沉积,通过流量的沉积物再分布的大小,斑块相对于水位的升高以及水土流失速率的变化之间的关系最密切。流动阻力低的植被斑块。正如我们在对大沼泽地和低洼地貌的案例研究中所举例说明的那样,水流和植被之间的反馈也会引起景观演变轨迹的滞后现象,这将影响景观恢复的潜力。即,即使恢复了历史上产生较高流量的水文条件,山脊和洼地景观的退化部分也不大可能恢复到以前的模式。随着全球湿地和洪泛区日益受到气候变化和城市化的威胁,我们的分析提供的对景观格局和过程的更多机械理解将提高我们预测和管理这些生态系统行为的能力。

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