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首页> 外文期刊>Hydrology and Earth System Sciences Discussions >Coupled local facilitation and global hydrologic inhibition drive landscape geometry in a patterned peatland
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Coupled local facilitation and global hydrologic inhibition drive landscape geometry in a patterned peatland

机译:局部便利化和整体水文抑制相结合,驱动了格局化泥炭地的景观几何

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pstrongAbstract./strong Self-organized landscape patterning can arise in response to multiple processes. Discriminating among alternative patterning mechanisms, particularly where experimental manipulations are untenable, requires process-based models. Previous modeling studies have attributed patterning in the Everglades (Florida, USA) to sediment redistribution and anisotropic soil hydraulic properties. In this work, we tested an alternate theory, the self-organizing-canal (SOC) hypothesis, by developing a cellular automata model that simulates pattern evolution via local positive feedbacks (i.e., facilitation) coupled with a global negative feedback based on hydrology. The model is forced by global hydroperiod that drives stochastic transitions between two patch types ridge (higher elevation) and slough (lower elevation). We evaluated model performance using multiple criteria based on six statistical and geostatistical properties observed in reference portions of the Everglades landscape patch density, patch anisotropy, semivariogram ranges, power-law scaling of ridge areas, perimeter area fractal dimension, and characteristic pattern wavelength. Model results showed strong statistical agreement with reference landscapes, but only when anisotropically acting local facilitation was coupled with hydrologic global feedback, for which several plausible mechanisms exist. Critically, the model correctly generated fractal landscapes that had no characteristic pattern wavelength, supporting the invocation of global rather than scale-specific negative feedbacks./p.
机译:> >摘要。自组织景观模式可响应多个过程而出现。区分其他图案形成机制,尤其是在无法进行实验操作的情况下,需要基于过程的模型。先前的建模研究已将大沼泽地(美国佛罗里达)的模式归因于沉积物的重新分布和各向异性的土壤水力学特性。在这项工作中,我们通过开发一种细胞自动机模型来测试另一种理论,即自组织运河(SOC)假设,该模型通过局部正反馈(即促进)与基于水文学的全局负反馈相结合来模拟模式演变。该模型受整体水文周期的驱使,该周期驱动两种斑块类型的脊(高海拔)和泥沼(低海拔)之间的随机过渡。我们基于在大沼泽地景观斑块密度,斑块各向异性,半变异函数范围,山脊区域的幂律定标,周长区域分形维数和特征图案波长的参考部分中观察到的六个统计和地统计学特性,使用多种标准评估了模型性能。模型结果显示出与参考景观的强烈统计一致性,但仅当各向异性作用的局部促进与水文全局反馈结合时,存在一些合理的机制。至关重要的是,该模型可以正确生成不具有特征图案波长的分形景观,从而支持调用全局而不是特定于比例的负反馈。

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