Characterization of chaotic dynamics in stem water content of plants

Plant water systems can typically exhibit complex spatiotemporal patterns, due to the nonlinear interactions with the surrounding environment. This study aims to investigate the chaotic properties in the plant water content system. The chaotic behaviors were determined in the water content time series of plant stem using phase space reconstruction, correlation dimension (CD), and largest Lyapunov exponent (LLE). The image data was collected from the broadleaf species in Inner Mongolia Autonomous Region and Beijing, China. The period of data collection was set as 4-10 months. Among them, Malus spectabilis, Sorbus pohuashanensis, Syringa pekinensis, and Sabina virginiana were located in the nursery of the Hesheng Institute of Ecological Science and Technology, Hulinger County, Hohhot City District, Inner Mongolia Autonomous Region (111°50 '28''E, 40°32'33''N) in a mid-temperate continental monsoon climate, with the test dates from September to December 2018; Populus and another part of Malus spectabilis were located in Sanqingyuan Nursery, Haidian District, Beijing (116°21'14''E, 40°0'54''N) in a warm-temperate semi-humid semi-arid monsoon climate, with the test dates from May to February 2022. The tree samples were selected as approximately 5 cm in diameter at breast height. At the same time, the eco-climatic parameters were measured with intervals of 10 min for the data collection. Firstly, the data was collected from the Malus spectabilis, Sorbus pohuashanensis, Syringa pekinensis, and Sabina virginiana at the same location in the same time period. Different plant samples were then used to test for the presence of chaos in the stem water content system. A comparison was also made to clarify the differences between the phase space reconstruction, CD, and LLE among different plants. Finally, a series of experiments were implemented on the plant samples from different test sites, including Malus spectabilis in Inner Mongolia and Malus spectabilis in Beijing. The results show that there were chaotic properties in the plant stem moisture system. The plant moisture dynamics were determined by a deterministic system with a limited number of control variables. There were also general differences in the stem moisture chaotic parameters of different plant species. Usually, the complexity of climate led to the chaotic characteristics of environmental factors, such as temperature, humidity, precipitation, and solar radiation in the plant growth environment. The chaotic behavior of the stem water content system depended mainly on the environmental factors and the plant's own regulation. Next, the chaotic influencing parameters were explored on the complexity of the stem water system using Populus data from the same period, location, and species under different stress treatments. The intrinsic links were then analyzed among the chaotic characteristic parameters, stem water content, and plant growth status. There were similar chaos parameters of stem dry moisture when the growth states of the same plant were similar. The chaos parameters were changed significantly when the growth states were different. For example, the LLE values of Populus were below 0.006 and 0.007 under drought and xylem destruction stress, respectively, where the average values were 0.010 and 0.019 in the control group, respectively. The values derived from the weighted analysis of CD and LLE can effectively characterize the occurrence of stress. Therefore, the chaotic characteristic parameter was closely related to the severity of the stress suffered by the plant. As such, the qualitative prediction can be realized for the retrospection of the plant's life state. In addition, the phase space reconstruction proved the data filling, prediction, and backtracking from a quantitative point of view using the local features of phase space trajectories. This finding is the first attempt to analyze the complexity of the plant water system from the perspective of chaos theory, providing a new way to understand the chaotic behavior of plant water dynamics.