Spatial pattern and spatial association analysis are important in the study of population characteristics and interspecies relationships. To investigate the spatial distribution pattern and association in different developmental stages in a Quercus acutissima population, the natural secondary Q. acutissima forest of the Qiaoshan Mountains in the southern area of the Loess Plateau was used as our study area. One forest plot (50 m×50 m) was established in each Q. acutissima natural secondary pure forest (plot A) and Q. acutissima-Pinus tabuliformis natural secondary mixed forest (plot B). The coordinate of each Q. acutissima was mapped, the diameter at breast height and height of each individual were measured by plot to investigate means. We divided the individuals into four growth stages using the method of diameter class. The spatial distribution pattern and associations were analyzed using Ripley's L(r) Function. The results showed the followings: (1)The quantity structure of each developmental stage of the Q. acutissima population in the Qiaoshan Mountains exhibited an irregular inverted "J" type, indicating a stable population structure with persistent regeneration capability. (2) The spatial distribution of the two populations was greatly influenced by habitat heterogeneity. Spatial distribution exhibited high aggregation at the scale of 0-10 m in plot A, whereas it showed low aggregation at the scale of 5-35 m. In plot B, the degree of aggregation changed quickly in response to habitat heterogeneity. It exhibited high aggregation at the 0-5 m scale and low aggregation at the 5-35 m scale. (3) With the development of populations and increase in scale, the spatial aggregation of the Q. acutissima population was reduced. In plot A, the seedling stage showed an aggregated distribution at the small scale of 0-6 m and a random distribution at the larger scale of 6-12 m. The sapling stage showed an aggregated distribution at all scales. The mid-mature stage and mature stage showed a random distribution at all scales. In plot B, all stages showed a random distribution at all the scales, except for the aggregated distribution of the seedling stage at the small scale of 0-6 m. (4) The spatial correlation between different growth stages and scales was discriminating in the two plots. In plot A, we found a negative correlation between the seedling and sapling stage at the 1-2 m scale. Positive correlation was found between the sapling and mid-mature stage at the 8 m scale. However, the relationship among other stages was not significant at any scale. In plot B, there was a significant positive correlation between the sapling and mid-mature stage at the 2-12 m scale. There was almost no correlation among other stages at any scales. Population distribution patterns were influenced by developmental stages, biological characteristics, and ecological factors. In future forest management, different managerial measures need to be taken to promote the regeneration of the population according to the different developmental stages and different habitats of the population.