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Litsea cubeba (Lour.) Pers. is an important woody spice tree in southern China, and its fruit is a rich source of valuable essential oil. We surveyed and sampled L. cubeba germplasm resources from 36 provenances in nine Chinese provinces, and detected rich phenotypic diversity. The survey results showed that plants of SC-KJ, SC-HJ, and SC-LS provenance presented higher leaf area (LA); YN-SM and YN-XC plants had larger thousand-grain fresh weight (TFW); and HN-DX plants had the highest essential oil content (EOC). To explain the large differences in the phenotypes of L. cubeba among different habitats, we used Pearson’s correlation analysis, multiple stepwise regression path analysis, and redundancy analysis to evaluate the phenotypic diversity of L. cubeba. It was found that compared to other traits, leaf and fruit traits had more significant geographical distributions, and that leaf phenotypes were correlated to fruit phenotypes. The results showed that elevation, latitude, longitude, total soil porosity (SP), soil bulk density (SBD), and average annual rainfall (AAR, mm) contributed significantly to the phenotypic diversity of L. cubeba. Geographical factors explained a higher percentage of variation in phenotypic diversity than did soil factors and climate factors. Plants of SC-KJ and HN-DX provenances could be important resources for domestication and breeding to develop new high-yielding varieties of this woody aromatic plant. This study describes significant phenotypic differences in L. cubeba related to adaptation to different environments, and provides a theoretical basis for the development of a breeding strategy and for optimizing L. cubeba cultivation.

Litsea cubeba (Lour.) Pers. is an important economic tree. We aimed to explore the phenotypic diversity of wild L. cubeba provenances from Jiangxi province and identify the germplasms with desirable characteristics. Nest variance analysis, multiple comparisons, correlation analysis, path analysis, redundancy analysis, and cluster analysis were conducted to compare the phenotypes of 526 wild L. cubeba trees from 27 provenances. We detected significant differences in the growth traits, fruit traits, and essential oil (EO) content of L. cubeba provenances, as well as significant differences in tree height, thousand seed dry weight, and the proportion of five essential oil components (citral, neral, geranial, D-limonene, and citronellal) within the provenances. The fresh fruit yield (FFY) was mainly determined by the ground diameter and the annual average minimum temperature. The EO content was mainly affected by the water content, annual average temperature, longitude, and latitude. The proportion of citral (CitrP) was negatively affected by extreme low temperatures. Four individual L. cubeba trees had a high FFY of over 10.00 kg·tree−1. Two trees had a high EO content exceeding 5%, with their CitrP over 80%. The provenances with high FFY were Guixi and Yushan (2.65 kg·tree−1; 2.89 kg·tree−1). The provenances with a high EO content of about 4.00% were Dayu, Yudu, Ji’an, Xinfeng, and Yushan. The provenance with the highest CitrP level (80.61%) was Ningdu.

Litsea cubeba is an important woody oil plant. The essential oils (EOs) can be extracted from its flowers, leaves and peels and, by volume, it is the most exported natural EOs from China. Thus, L. cubeba has important economic and medicinal value. Although there is demand for the rapid expansion of L. cubeba production, there has been a sharp reduction in natural resources. Therefore, determining the potentially suitable area for L. cubeba and expanding its cultivation will help meet the growing demand for volatile oil. Based on 453 distribution records of L. cubeba in China and 16 major environmental factors, we simulated the distribution pattern of the potentially suitable area of L. cubeba under three different climate change scenarios (SSP126, SSP370 and SSP585) in three time periods: the current period, 2050 s, and 2070 s. The analysis was implemented using the MaxEnt model, optimized using the ENMeval package. The jackknife test, percent contribution and response curve were used to determine the most important environmental factors and response intervals affecting the distribution of L. cubeba. We found that the parameter settings of the optimal model were RM = 2.5 and FC = LQH. The results of the MaxEnt model exhibited a high prediction accuracy and a low degree of overfitting. Precipitation of the driest quarter, annual precipitation, temperature annual range and minimum temperature of the coldest month were the dominant factors affecting the distribution of L. cubeba, and their thresholds were ≥ 36.21 mm, ≥905.95 mm, ≤32.44 °C and ≥ -3.73 °C, respectively. The results showed that the total potentially suitable area of L. cubeba in China was 208.19 × 104 km2 under current climate conditions. The predicted potentially suitable area was mainly concentrated in the 19 provinces and cities in the Yangtze River Basin and its southern area. Under future climate change conditions, the predicted potentially suitable area of L. cubeba increased with time, and the centroid of the predicted potentially suitable area of each grade moved northward. The results of this study can be used to guide the selection of future introductions, as well as the development, artificial cultivation and resource conservation of L. cubeba.