在地理空间尺度上，气候因素（如热量、降水量等）一直被认为是物种多样性的主要驱动因素。然而，气候因素能否解释湿地植物多样性格局仍不清楚。研究探讨了环境因素尤其水分和热量条件对湿地物种分布的影响，具体包括经度、纬度、海拔、年平均降水量、年平均气温、年平均蒸发量和年平均日照时数总计7个指标，研究对象涉及新疆3个二级流域的26处湿地公园，应用结构方程模型分析了各指标对湿地植物丰富度影响的相对大小及其相互作用关系。另外，还利用莫兰指数（Moran’s I）对各变量残差进行了空间相关性分析，以评估空间相关性的影响。结果表明：（1） 结构方程模型总计解释了41.8%的物种丰富度变异，以年平均降水量对物种丰富度总效应最高，为0.47，其次是年平均日照时数，为-0.42，其中年平均降水量为正效应，年平均日照时数为负效应。其他各指标对物种丰富度的效应均不显著。（2） 年平均降水量对植物丰富度的影响主要表现为直接效应，占总效应的92.86%，年平均日照时数对植物丰富度的影响主要是间接效应，占总效应的54.76%。（3） 空间相关性分析表明年平均降水量和年平均日照时数的残差均不存在空间相关性，莫兰指数在-0.15~0.10范围内波动，可以认为是可靠的预测指标。综上，新疆湿地植物丰富度主要受水热条件的共同驱动，且热量的作用依赖于水分条件，在未来湿地植物多样性保护工作中，应加强气候变化对植物多样性影响的评估和应对措施。

On the geographic spatial scale, climate factors (such as environmental energy and precipitation) are the main driving factors of plant species diversity. However, it remains unclear whether climatic factors can explain the plant diversity in wetlands. This study discusses the influence of environmental factors, especially the effect of water and heat conditions on the distribution of wetland species. Specifically, it includes four categories and seven indicators, including spatial factors (longitude and latitude), terrain factors (altitude), water factors (annual average precipitation and evaporation), and heat factors (annual average air temperature and sunshine hours). The research objects involve 26 wetland parks in three secondary river basins in Xinjiang, China. The structural equation model is used to explore the relative importance of each indicator on wetland plant richness and their interaction. In addition, Moran’s I index is used to analyze the spatial correlation of the residuals of each variable to evaluate the impact of spatial correlation. The results show that (1) the structural equation model explains 41.8% of the variation in plant species richness. The total effect of annual average precipitation on species richness is the highest, which is 0.47, followed by the annual average sunshine hours, which is -0.42. Among them, the annual average precipitation has a positive effect, whereas the annual average sunshine hours have a negative effect. The effects of other indices on species richness are insignificant. (2) The influence of annual average precipitation on plant richness is primarily a direct effect, which is 0.39, accounting for 92.86% of the total effect. The influence of annual average sunshine hours on plant richness is primarily an indirect effect, which is -0.23, accounting for 54.76% of the total effect. (3) Spatial correlation analysis shows that there is no spatial correlation between the residuals of annual average precipitation and sunshine hours on different spatial scales, and the Moran’s I index fluctuates within the range of -0.15 to 0.10, which could be considered reliable prediction indices. (4) The direct effects of spatial factors such as longitude and latitude on plant richness are insignificant, whereas the indirect effects are significant. Longitude significantly affects the annual average precipitation, and latitude significantly affects the annual average sunshine hours and temperature, indicating that spatial factors indirectly affect the species richness by affecting the annual average precipitation and sunshine hours. In conclusion, the plant richness of the wetlands in Xinjiang is primarily driven by water and heat conditions. The role of heat depends on the water conditions. In future wetland plant diversity protection studies, the assessment and response measures of the impact of climate change on plant diversity should be strengthened.