Three distinct types of dynamic behaviour shown by a single planktonic system
Three distinct types of dynamic behaviour shown by a single planktonic system
复制标题
单个浮游系统表现出三种不同类型的动态行为
作者：
W. Murdoch;E. Mccauley
通过研究不同的捕食者-被捕食者系统1，发现了广泛的动态行为，包括种群稳定性、周期和非周期波动。然而，我们还没有发现过这样的例子，即在不同的时间，在同一个自然的捕食者-被捕食者种群中，或者在不同但相似的群落中发现的一个给定的捕食者-被捕食者系统中，发现了性质上不同的动态。相比之下，捕食者-被捕食者系统的数学模型预测，任何特定的系统都可能仅仅由于速率参数的变化而表现出整个动态范围，例如在不同温度下可能发生的变化。事实上，May提出了一种可能性，即实验室中不同的Daphnia藻类动力学是由不同温度下时间滞后和增长率的相对值差异引起的。因此，为了产生不同的动力学，模型不需要经历任何结构上的变化，例如可能发生在不同系统或生物群体中的变化。在这里，我们表明，现场人口的捕食者，zooepartonic草食动物Daphnia，和它的藻类猎物表现出三种不同类型的动态行为。这一发现支持了一个基本前提，即不同的动态可以产生于一个恒定的结构框架内的数量差异，因此假设系统之间的动态变化可以用同一方式解释为一个单一的系统内的差异。
A wide range of dynamic behaviour has been uncovered by studying disparate predator–prey systems1, ranging over population stability, cycles and non-cyclic fluctuations. We know of no instance, however, in which qualitatively different dynamics have been found in the same natural predator–prey populations at different times, or in a given predator–prey system found in different but similar communities. Mathematical models of predator–prey systems, by contrast, predict that any particular system may exhibit the whole range of dynamics simply as a result of changes in rate parameters, such as those that might occur at different temperatures. Indeed, May raises the possibility that differentDaphnia–algal dynamics in the laboratory are caused by differences in the relative values of time lags and rates of increase at different temperatures2. Therefore, to produce the different dynamics, the models need not undergo any change in structure, such as might occur in different systems or groups of organisms. Here we show that field populations of a predator, the zooplanktonic herbivoreDaphnia, and its algal prey exhibit three qualitatively different types of dynamic behaviour. This finding supports the basic premise that different dynamics can result from quantitative differences within a constant structural framework, and hence the hypothesis that variations in dynamics between systems can be explained in the same way as differences within a single system.