A Spatially-explicit, Hierarchical Model of Pattern-process Dynamics of Grassland Landscape (Jianguo Wu)

本研究的目的是：（1）开发一个 系统的，计算机化的程序来检测结构 在加州的碧玉岭的草原景观中， 主要基于二维网函数插值 理论;（2）构建和验证一个层次 结构化的，空间上明确的，随机模拟模型， 模式过程动力学，主要基于来自碧玉的数据 山脊草原生态系统。 该模型将考虑到 涉及小规模/高频率的审议过程， 中尺度/低频和大尺度/甚低频 现象。 每个过程中的随机性必须是 incorporated. 大规模的现象可能包括天气 波动（例如，降水、温度）、风/水 侵蚀、长期干旱和不定期的火灾。 小- 另一方面，规模现象可能涉及物理 环境斑块与筑丘动物活动 比如地鼠和蚂蚁。 总的来说，该模型将 草原小规模干扰的人口统计学，监测 斑块的时间变化，以及痕迹老化和灭绝 不同尺度的斑块。 空间明确， 多尺度模式归纳模型采用自底向上的 方法，从以下方面得出草地的草地水平动态： 即可分层分解的较低层次。 的 时空统计分析的计算需求 模式，灵敏度分析和蒙特卡罗 模型的模拟，将使可取的和必要的， 利用超级计算机设施的并行能力。 拟议研究的完成将大大增加 理解自然发生的干扰在 在创建模式-过程动态中的各种尺度， 一个模型框架，用于进一步比较研究 不同类型的草地生态系统， 比较草原和森林， 超级电脑设施对改善生态环境的重要性 认识

The objectives of the proposed research are (1) to develop a systematic, computerized procedure to detect the structural patterns in the grassland landscape of Jasper Ridge, California, based primarily on the 2-Dimensional Net Function Interpolation Theory; (2) to construct and validate a hierarchically structured, spatially explicit, stochastic simulation model of pattern-process dynamics, based mainly on data from the Jasper Ridge grassland ecosystem. The model will take into consideration processes involving small-scale/high frequency, middle-scale/low frequency, and large-scale/very low frequency phenomena. Stochasticity in each process will have to be incorporated. Large-scale phenomena may include weather fluctuations (e.g., precipitation, temperature), wind/water erosion, prolonged drought, and irregularly timed, fires. Small- scale phenomena, on the other hand, may involve physical environmental patchiness and activities of mound-building animals such as gophers and ants. Overall, the model will incorporate demographics of small-scaled disturbances in grasslands, monitor the temporal changes of patches, and trace aging and extinction of the patches at various scales. The spatially explicit, multiple-scale pattern induction model takes a bottom-up approach, deriving landscape-level dynamics of the grassland from that of hierarchically decomposable lower levels. The computational demand in spatial and temporal statistical analyses of patterns, and the sensitivity anaLysis and Monte Carlo simulation of the model, will make desirable and imperative the use of the parallel capabilities of the supercomputer facilities. The completion of the proposed study will add substantially to understanding of the role of naturally occurring disturbances at various scales in creating the pattern-process dynamics, provide a modeling framework for further comparative investigation on different types o grassland ecosystems, serve as a strong basis for comparing grasslands with forests, and exemplify the significance of supercomputer facilities in enhancing ecological understanding.