## 3 Results
### Relationship Between Ecological Factors and Biomass of Halophytes Under Salt Stress Conditions
#### 3.4.3 Structural Equation Modeling of Different Ecological Factors and Halophytes Biomass  
Structural equation modeling allows the visualization of the relationships between different indicators, calculation of path coefficients between indicators, and comparison of the magnitude of impact. However, since the measures vary from indicator to indicator, the same type of indicator needs to be downscaled to extract the new variables and then analyzed using structural equation modeling. Redundancy analysis revealed that salt concentration, plant height, malondialdehydedehyde, chlorophyll a, intercellular carbon dioxide concentration, stem diameter, chlorophyll b, atmospheric temperature, net photosynthesis rate, stomatal conductance, and relative humidity had longer line segments, which were more correlated with the biomass of the halophytes, so the above metrics were selected for the downscaling process. According to relevant professional knowledge, the variables of the \"meteorological factor\" are extracted from the atmospheric temperature and relative humidity. The \"growth morphological factors\" variable was extracted from plant height and stem diameter. Regarding the extraction of \"physiological factors\" variables from chlorophyll a, chlorophyll b, and malondialdehydedehyde, the \"photosynthetic factors\" variable was extracted from the net photosynthetic rate, stomatal conductance, and intercellular carbon dioxide concentration. Salt concentration was then used as a separate variable. From Figure 12a-c, it can be seen that the results of structural equation modeling analysis of different ecological factors with a halophyte biomass of \(\chi^{2}/\mathrm{df}\) were all in the range of 1 to 3, with a \(p\) value greater than 0.05, CFI and GFI greater than 0.9, RMSE below 0.08, and good overall model fit. Figure 11: Relationship between different ecological factors and biomass of halophytes. (**a**) RDA ordination plot of ecological factors versus halophytes biomass; (**b**) degree of explanation of halophyte biomass by each ecological factor; \"ACO2\" is atmospheric carbon dioxide concentration. “Tr” is transpiration rate. “Tchl” is total chlorophyll. “Wue” is water use efficiency. “Rh” is relative humidity. “Gs” is stomatal conductance. “Pn” is net photosynthetic rate. “Ta” is atmospheric temperature. “Ch” is chlorophyll b. “D” is stem diameter. “Ci” is intercellular carbon dioxide concentration. “Ca” is chlorophyll a. “MDA” is malondialdehydedehyde. “H” is plant height. “Sc” is salt concentration. “TB” is total biomass. * represents \(p<0.05\). A comprehensive analysis of the structural equation model results of three different types of halophytes shows that different ecological factors play different roles in different haplotypes. In the structural equation model of Ha, salt concentration and growth morphological factors play a core driving role in biomass, among which salt concentration has a highly significant negative impact, and the path coefficient is \(-0.86\) (\(p<0.001\)). Although the growth morphological factors were influenced by salt concentration, meteorological factors, photosynthetic factors, and physiological factors, the growth morphological factors still showed a highly significant positive impact on Ha biomass, with a path coefficient of 0.72 (\(p<0.001\)). The influence of meteorological factors on Ha biomass was not significant (\(p>0.05\)). Under the influence of salt concentration and meteorological factors, photosynthetic factors and physiological factors have positive effects on biomass, but photosynthetic factors have more obvious effects on Ha biomass, and the path coefficient is 0.50 (\(p<0.05\)). In the structural equation model of Tc, salt concentration, growth morphological factors, and meteorological factors all have effects on biomass, among which salt concentration has a very significant negative effect, and the path coefficient is \(-0.67\) (\(p<0.01\)). Meteorological factors showed a significant negative impact, and the path coefficient was \(-0.55\) (\(p<0.05\)).