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The distribution of plant communities in the salt marshes of the southwestern coasts of South Korea was studied, along with environmental or plant factors, by canonical correspondence analysis (CCA) and the competitor (C), stress tolerator (S), and ruderal (R) (CSR) ecological strategies. The coastal salt-marsh plants were classified into three plant-factor groups in the CCA biplot diagram. Group 1 was correlated with LS and FP. Group 2 was correlated with CH and SLA, and Group 3 was correlated with LA, LDMC and LDW. The salt-marsh plants were classified into four soil-factor groups in the CCA biplot diagram. First, the group factor was correlated with TN, TOC, and Ca2+. Second, the group factor was distributed according to Mg2+, soil texture as Clay and Silt. Third, the group factor was distributed according to Salinity and Na+ content. Fourth, the group factor was distributed according to Sand content. To clarify the relative significance of competition, stress, and disturbance in the distribution process of plant communities, the CSR distribution model was adopted. The nine species showed CR (competitor-ruderal) strategies: Artemisia fukudo, Artemisia scoparis, Aster tripolium, Atriplex gmelinii, Imperata cylindrica var. koenigii, Salicornia europaea, Suaeda japonica, and Suaeda maritima. The four species with C (competitor) strategies were Artemisia capillaris, Limonium tetragonum, Triglochin maritimum, and Zoysia sinica. Carex scabrifolia and Phragmites communis displayed SC (stress-tolerant-competitor). Both distribution patterns of the CCA diagrams and CSR triangles may provide a useful scientific basis for protecting and restoring salt marshes and their valuable ecosystem services, considering the increasing disturbances.

The query of the K closest object pairs between two object sets frequently occurs at recently retrieval systems. The circular location property of objects should be considered for efficiently process queries finding such a K nearest object pair. In this paper, we propose the optimal algorithm finding the K object pairs which are closest to each other in a search space with a circular domain and show its performance by experiments. The proposed algorithm optimizes the cost of finding the K nearest object pairs by using the circular search distances which is much applied the circular location property.

The number of searched nodes and the computation time in an index should be minimized for optimizing the processing cost of the nearest neighbor query. The Measurement of search distance considered a circular location property of objects is required to accurately select the nodes which will be searched in the nearest neighbor query. In this paper, we propose the processing method of the nearest neighbor query be considered a circular location property of object where the search space consists of a circular domain and show its performance by experiments. The proposed method uses the circular minimum distance and the circular optimal distance which are the search measurements for optimizing the processing cost of the nearest neighbor query.