Ulanowicz Robert E
Chesapeake Biological Laboratory, University of Maryland Center for Environmental Science, Solomons, MD 20688-0038, USA.
Comput Biol Chem. 2004 Dec;28(5-6):321-39. doi: 10.1016/j.compbiolchem.2004.09.001.
The analysis of networks of ecological trophic transfers is a useful complement to simulation modeling in the quest for understanding whole-ecosystem dynamics. Trophic networks can be studied in quantitative and systematic fashion at several levels. Indirect relationships between any two individual taxa in an ecosystem, which often differ in either nature or magnitude from their direct influences, can be assayed using techniques from linear algebra. The same mathematics can also be employed to ascertain where along the trophic continuum any individual taxon is operating, or to map the web of connections into a virtual linear chain that summarizes trophodynamic performance by the system. Backtracking algorithms with pruning have been written which identify pathways for the recycle of materials and energy within the system. The pattern of such cycling often reveals modes of control or types of functions exhibited by various groups of taxa. The performance of the system as a whole at processing material and energy can be quantified using information theory. In particular, the complexity of process interactions can be parsed into separate terms that distinguish organized, efficient performance from the capacity for further development and recovery from disturbance. Finally, the sensitivities of the information-theoretic system indices appear to identify the dynamical bottlenecks in ecosystem functioning.
对生态营养转移网络的分析是理解整个生态系统动态的模拟建模的有益补充。营养网络可以在几个层面上以定量和系统的方式进行研究。生态系统中任意两个个体分类群之间的间接关系,其性质或强度往往与其直接影响不同,可以使用线性代数技术进行分析。同样的数学方法也可用于确定任何个体分类群在营养连续体中的运作位置,或将连接网络映射到一个虚拟线性链中,该链总结了系统的营养动力学表现。已经编写了带有剪枝的回溯算法,用于识别系统内物质和能量的循环途径。这种循环模式通常揭示了不同分类群组所表现出的控制模式或功能类型。可以使用信息论对系统在处理物质和能量方面的整体性能进行量化。特别是,过程相互作用的复杂性可以分解为不同的项,以区分有组织、高效的性能与进一步发展和从干扰中恢复的能力。最后,信息论系统指标的敏感性似乎可以识别生态系统功能中的动态瓶颈。