Integrated modelling of geomorphological and ecological landscape evolution

景观是一个复杂的动态系统，在地貌和生态上都是如此。此外，地貌过程受景观植被覆盖的影响，反之亦然。鉴于这些相互关系，可以预期，实际上已经表明，地貌和生态过程相互作用，共同决定景观的演变。然而，在目前的景观模拟研究中，这些相互作用往往被忽视。地貌景观演化模型通常将植被视为次要因素，要么将其视为静态因素，要么将其完全忽略。相反，生态景观演化模型通常将景观形态视为植被竞争和演替的静态阶段。本研究旨在通过一种综合的景观演化建模方法，加深对景观演化中生态和地貌过程之间的相互作用和反馈的理解。将开发两个新的计算模型来系统地研究：1)河段和流域尺度上地貌和生态过程相互作用的内部动力学；2)这些相互作用对景观演变的重要性；3)植被动态对地貌过程速率和产沙量的影响；以及4)景观对外部条件的响应，如气候变化或人为力量。现场数据用于将模型应用于自然系统，而不仅仅是理想化或假想的环境，从而提供了验证或确认模型的可能性。

Landscapes are complex dynamic systems, both geomorphologically and ecologically. Moreover, geomorphological processes are influenced by the landscape's vegetation cover and vice versa. Given these mutual relations it can be expected, and indeed it has been shown, that geomorphological and ecological processes interact and co-determine the evolution of the landscape. However, these interactions are frequently neglected in current landscape simulation studies. Geomorphological landscape evolution models commonly regard vegetation as a secondary factor and either treat it as static or ignore it altogether. Conversely, ecological landscape evolution models usually regard the landscape's morphology as a static stage for vegetation competition and succession.This research aims to improve understanding of interactions and feedbacks between ecological and geomorphological processes in landscape evolution, using an integrated landscape evolution modelling approach. Two new computational models will be developed to systematically investigate: 1) the internal dynamics of geomorphological and ecological process interactions on both reach and catchment scales; 2) the importance of these interactions on landscape evolution; 3) the impact of vegetation dynamics on rates of geomorphological processes and sediment yield; and 4) the landscape's response to external conditions, such as climate change or anthropogenic forcing.Field studies are envisaged to complement the numerical simulations. Field data are used to apply the models in natural systems, rather than idealized or hypothetical environments only, and thereby offer the potential for verification or confirmation of the models.