Foundational ecological models characterize dispersal with two behavioral traits, speed and directional bias. We hypothesized that these two traits can predict the order of colonization by fishes in a heterogenous landscape. Colonization patterns following hydrological disturbance were documented from a 20-year multi-site time series of marsh fish, and we evaluated the ability of a two-parameter model to predict these patterns. The maximum aerobic swimming speed (U_CRIT) for six coexisting fish species were estimated using endurance tests; field estimates of directedness and swimming speed were previously documented using encounter samplers. We incorporated interspecific variation in speed, direction, and density into several Agent Based Models to simulate dispersal following disturbance. Six virtual “species” with varying levels of directedness, “swam” in an artificial environment to reach a refuge habitat. The time of first arrival for each species was saved at the end of each run and used to calculate the probability of arrival order. Our simulated results generated predictions on order of arrival consistent with observed colonization patterns in our long-term dataset. Swim tunnel results revealed that fast (high U_CRIT) estimates were characteristic of early colonizing species; whereas, slow (low U_CRIT) estimates were characteristic of late colonizing species. Directional bias better predicted order of arrival than speed and was robust to inter-specific variation in density. This study demonstrated that two parameters were adequate to predict the order of species colonization in a complex landscape. These results support the use of relatively simple trait-based models to generate realistic community assembly dynamics.

基础生态模型具有两个行为特征，即速度和方向偏差，来表征分散。我们假设这两个特征可以预测异质景观中鱼类定殖的顺序。在20年的多地点沼泽鱼类时间序列中，记录了水文扰动后的定居模式，我们评估了两参数模型预测这些模式的能力。最大有氧游泳速度（U _CRIT）使用耐力测试估算了6种共存的鱼类; 以前使用encounter碰采样器记录了定向​​性和游泳速度的现场估计值。我们将种间在速度，方向和密度上的变化纳入了几个基于Agent的模型中，以模拟扰动后的扩散。六个虚拟的“物种”，具有不同的定向度，在人工环境中“游动”以到达避难所栖息地。每个物种的首次到达时间在每次运行结束时保存，并用于计算到达顺序的概率。我们的模拟结果对到达顺序的预测与长期数据集中观察到的定殖模式一致。游泳隧道结果表明，快（高û _CRIT）估计是早期殖民物种的特征；而缓慢的（较低的U _CRIT）估计是晚期定居物种的特征。方向偏差比速度更好地预测了到达的顺序，并且对种间密度变化具有鲁棒性。这项研究表明，两个参数足以预测复杂景观中物种定殖的顺序。这些结果支持使用相对简单的基于特征的模型来生成现实的社区装配动态。