| The dynamic variation of aquatic plant communities in wetlands may reflect the health degree of wetland ecosystems and ecological services. The establishment of Spatio-TemPora distribution model of emergent plants communities, the quantitative analysis of response relationship between wetland environmental change and the distribution of emergent plant communities,the exploration of complex non-linear law of wetlands evolution and the analysis of evolutionary mechanism may provide the sustainable development of wetlands with a scientific basis and decision support.With the support of remote sensing and geographic information system, the pattern and the dynamic variation characteristics of all kinds of wetland landscape in Wuliangsuhai wetland from 1986 to 2008 were studied quantitatively by landscape index. Furthermore, the location of center of gravity of the emergent plant communities and their moving tracks were calculated, and impact factors of the spread of emergent plants were analyzed. Taking cellular automata as a model framework, the Spatio-TemPora distribution dynamic model of emergent plants was established and the diffusion process of wetland emergent plant communities was simulated in Wuliangsuhai wetland on the basis of spatial statistics and the method of artificial intelligence respectively. The main research results are as follows:(1)Based on multi-source remote sensing data, the information of the type of Wuliangsuhai wetlands was extracted, and the index variation of wetlands landscape was analyzed quantitatively. The results showed that from the year 1986 to 2008, the area of emergent plants in the wetland grew from 120.89km2 to 167.43 km2; the number of patches declined from 1138 to 690; patches density decreased from 1.2335/km2 down to 0.7479个/km2; the ratio of the gest patches area increased from 6.7002% to 17.3879% ; the shape index fell from 36.2997 to 33.8494. Emergent plants swallowed clear water areas and shallow marshes areas, which became a dominant type of wetland landscape. The degree of fragmentation of patches was decreased and the edge structure became simple. Wetland emergent plant communities developed with imbalance, in 22 years, the barycenter of emergent plant communities has shifted through three basic stages. From 1986 to1997, the location of barycenter moved from the (E108°50'55 .35 ", N40°58'53 .78") to (E 108°50'25 .26 ", N 40°58'37 .57"), shifting 863.03m toward southwest; From 1997 to 2000, the location of barycenter moved from the (E 108°50′25.26″,N 40°58′37.57″) to (E 108°50′35.33″,N 40°58′28.32″), shifting 369.76m toward southeast; From2000 to 2008, the location of barycenter moved from the (E 108°50′50.12″,N 40°58′39.11″)to (E 108°50′35.33″,N 40°58′28.32″), shifting 487.73m toward northeast.(2)Correlation analysis of impact factors of emergent plant communities diffusion were carried out on the basis of the measured data. By stepwise regression analysis, the water depth and TN were further identified to be the main impact factors of diffusion of emergent plants in Wuliangsuhai, and their regression coefficients were -0.46 and 0.17 respectively. Where the water depth was more than 1.5m, diffusion of emergent plants stopped and N/P was not more than 14 in emergent plants. TN still promoted the diffusion of emergent plants in Wuliangsuhai. Temporal and spatial distribution of the water depth and TN at different stages were simulated with the method of geostatistical interpolation .(3)Spatial Statistics theory was used to calculate the dynamic degree of emergent plants diffusion(LC)in Wuliangsuhai at different times, so that the turning point of diffusion speed of emergent plants can be obtained . And then the diffusion process of emergent plants communities in Wuliangsuhai was divided into the diffusion period (1986-2002) and the stagnant period (2002-2008), in which the dynamic degrees of emergent plants diffusion were 2.1% and 0.61% respectively. Logistic-CA model of sub-optimal dynamic degree was established to simulate the process of spatio-tempora distribution of emergent plants. The results showed that the overall accuracies of simulation were 74.01%, 72.29% and 74.36%, Kappa coefficients were 0.6222, 0.6103 and 0.6370, and actual Moran I coefficient were 0.641, 0.712 and 0.720 in 1997,2002 and 2008 respectively. Accuracy and quantitative test on consistency of spatial form and control of the decline of the simulation accuracy of Logistic regression CA model whose dynamic degree was proofread were all better than those of conventional one.(4)That case-based reasoning (CBR) was led in Geo-CA model of wetland emergent plants diffusion solved many problems, including that simulation area of wetland emergent plants diffusion is large, simulation time is long, impact factors are complex, non-linear transformation rules are difficult to obtain and so on. Cellular automaton model (CBR-CA) of large emergent plants diffusion in Wuliangsuhai was constructed on the basis of case-based reasoning. According to the similarity of geographical features and spatial features, k nearest neighbors were searched in dynamic historical case library, conversion rules of Geo-CA were obtained implicitly, and the diffusion process of emergent plants communities was simulated. The results suggested that the overall accuracies of simulation were 76.41%, 73.05% and 75.91%, Kappa coefficients were 0.6402, 0.6382 and 0.6393, actual Moran I coefficients were 0.628, 0.686 and 0.709, and Moran I coefficients that simulated the results were 0.640, 0.710and 0.718 in 1997,2002 and 2008 respectively. CBR-CA model can adapt to rapid changes of wetland environments and reflect the Self-adaptability of complex systems.(5)Based on LC -Logistic-CA model and CBR-CA model respectively, the diffusion condition of the emergent plants in Wuliangsuhai wetlands in 2015 was predicted and the results showed that the area of the emergent plants were 174.34km2 and 172.92 km2, the number of patches were 634 and 646, patches density were 0. 7287/km2 and 0.7311/km2, the ratio of the gest patches area were 18.0019% and 17.9558%, the shape index were 32.8392 and 33.1556 and the degree of fragmentation of patches decreased, moreover, the edge structure became simple.
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