摘要:互花米草在红树林湿地中扩散对生境与生态系统造成严重影响，已成为生物入侵问题研究的焦点之一。然而目前关于互花米草扩散动态及其驱动力的研究成果仍为鲜见。论文以广西山口红树林保护区为研究对象，以2009、2013、2019年遥感影像为数据源，采用人机互译、野外勘查结合的方法识别互花米草布局，利用土地类型转移矩阵、质心的变化、景观指数以及灰色关联度等方法分析互花米草扩散特征及其驱动力。结果表明：（1）2009-2019年间，互花米草面积、斑块数量呈现增长趋势，但面积增幅下降，2009-2013年间年均增长率为7.60%，2013-2019年间年均增长率则为1.99%；互花米草面积年均增长率大于红树林，光滩转化为互花米草的面积是其转化为红树林面积的1.507倍；互花米草、红树林均有破碎化趋势；（2）2009-2019年间，互花米草的质心坐标都位于丹兜海潮滩，2009-2013年互花米草斑块质心向西北方向偏移，2013-2019年向东南方向偏移；（3）2009-2019年间，互花米草动态变化受到人为因素与自然因素共同影响。其中，赶海人口比例与最大斑块指数、斑块密度、斑块数相关性最大；年均最高温与互花米草分维数、破碎化指数、面积相关性最大。（4）影响互花米草面积变化的因素依次为：年均最高温、年均最低温、赶海人口比例、地区生产总值；互花米草面积与年均最高、年均低温均呈正相关，与赶海人口比例呈负相关。研究结果将为互花米草监控提供科学借鉴，为红树林保护提供理论依据。



Abstract:Habitats and ecosystems are seriously affected by the spread of Spartina alterniflora in mangrove wetlands. To date, S. alterniflora has been a focus of biological invasion research. However, current research results on the dynamics of landscape patterns and its driving forces remain rare. In this article, remote sensing images in 2009, 2013 and 2019 were taken as data sources and the methods of man-machine translation and field exploration were used to identify the layout of S. alterniflora in the Shankou Mangrove Reserve. At the same time, changes in diffusion characteristics and the driving forces behind them were analysed by means of a land type transfer matrix, centroid variation, landscape index analysis and grey correlation analysis. The results showed that (1) the area and number of patches of S. alterniflora increased from 2009 to 2019. But the growth rate of the area covered by S. alterniflora decreased, the average annual growth rate was 7.60% during 2009-2013, and 1.99% during 2009-2019. The average annual growth rate of the area covered by S. alterniflora was higher than that covered by mangrove. The area of mudflat transformed into S. alterniflora was 1.507 times that of mudflat transformed into mangrove. Both S. alterniflora and mangrove displayed a fragmentation trend. (2)The centroid coordinates of S. alterniflora were located in Dandou tidal flat during 2009-2019.The patch centroid of S. alterniflora shifted to the northwest during 2009-2013 and shifted to the southeast during 2013-2019. (3) The dynamic change of S. alterniflora was affected by both human and natural factors during 2009-2019. The proportion of the sea-going population was the most closely correlated with the maximum patch index, patch density and patch number of S. alterniflora. The annual maximum temperature had the highest correlation with the fractal dimension, fragmentation index and area covered by S. alterniflora. (4) The change in the area covered by S. alterniflora was mainly driven by climate change and human factors. The factors influencing the area covered by S. alterniflora were the lowest annual temperature, the highest annual temperature, the proportion of the sea-going population, and the GDP. The area covered by S. alternifolia was positively correlated with the highest annual average temperature and the lowest annual average low temperature. Also, the area was negatively correlated with the proportion of the sea-going population. It is hoped that this work will provide a valuable reference for the monitoring of S. alterniflora as well as a theoretical basis for mangrove protection.





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