For a long time, the development of the Lycium barbarum industry has been seriously restricted by root rot disease. In general, the occurrence of plant root rot is considered to be closely related to the composition and diversity of the soil microbial community. It is critical to understand the relationship between the occurrence of root rot in L. barbarum and the soil microbial composition. In this study, samples of the rhizosphere, rhizoplane, and root zone were collected from diseased and healthy plants. The V3–V4 region of bacterial 16S rDNA and the fungal ITS1 fragment of the collected samples were sequenced using Illumina MiSeq high-throughput sequencing technology. The sequencing results were first quality controlled and then aligned with the relevant databases for annotation and analysis. The richness of fungal communities in the rhizoplane and root zone of the healthy plants was significantly higher than that of the diseased plants (p < 0.05), and the community evenness and diversity of all the rhizoplane samples were significantly different from those of the rhizosphere and root zone. The richness of the bacterial communities in the rhizosphere and root zone of healthy plants was significantly greater than those of diseased plants (p < 0.05). The community composition of the rhizoplane was quite different from the other parts. The abundance of Fusarium in the rhizoplane and rhizosphere soil of diseased plants was higher than that in the corresponding parts of healthy plants. The abundances of Mortierella and Ilyonectria in the three parts of the healthy plants were correspondingly higher than those in the three parts of the diseased plants, and Plectosphaerella was the most abundant in the rhizoplane of diseased plants. There was little difference in the composition of the dominant bacteria at the phylum and genus levels between healthy plants and diseased plants, but the abundances of these dominant bacteria were different between healthy and diseased plants. Functional prediction showed that the bacterial community had the largest proportion of functional abundance belonging to metabolism. The functional abundances of the diseased plants, such as metabolism and genetic information processing, were lower than those of the healthy plants. The fungal community function prediction showed that the Animal Pathogen-Endophyte-Lichen Parasite-Plant Pathogen-Soil Saprotroph-Wood Saprotroph group had the largest functional abundance, and the corresponding fungi were Fusarium. In this study, we mainly discussed the differences in the soil microbial communities and their functions between the healthy and diseased L. barbarum cv. Ningqi-5, and predicted the functional composition of the microbial community, which is of great significance to understanding the root rot of L. barbarum.

The genus of Prunus subg. Amygdalus are endangered Tertiary-relict plants that are an essential source of woody plant oil. In order to provide a theoretical basis for better protection and utilization of species in the Prunus subg. Amygdalus. This study collected global distribution information for six species within the Prunus subg. Amygdalus, along with data on 29 environmental and climatic factors. The Maximum Entropy (MaxEnt) model was used to simulate the globally suitable distribution areas for these species within the subgenus. The suitable results showed that the area under the test curve (AUC) values of the simulation results were more than 0.8, indicating that the simulation results have high accuracy. Temperature, precipitation, UV-B, and altitude were critical environmental factors affecting the distribution of each species in Prunus subg. Amygdalus. Currently, the distribution area of six species in this genus, from largest to smallest, is Prunus triloba (Lindl.) Ricker, Prunus tenella Batsch, Prunus amygdalus Batsch, Prunus pedunculata Maxim, Prunus mongolica Maxim and Prunus tangutica (Batal.) Korsh. The simulation results of distribution areas showed that under the ssp2.45 and ssp5.85 scenarios, the potential distribution areas of P. amygdalus, P. tangutica, and P. pedunculata all show a decreasing trend, while the distribution areas of P. mongolica and P. tenella, and P. triloba exhibit an increasing trend. The general distribution of P. amygdalus, P. mongolica, and P. tenella will trend to transfer in a northwest direction. P. tangutica and P. pedunculata were affected by other environmental factors (such as slope, altitude, and soil pH), and the distribution area has a tendency to move northeastward. The P. triloba moved to the southwest. The spatiotemporal distribution patterns of Prunus subg. Amygdalus can be used as a reference for forest management and to formulate species conservation strategies.

Vegetation restoration is critical for ecosystem recovery in abandoned mining areas, yet how restoration age affects soil multifunctionality (SMF) and the underlying microbial regulatory mechanisms remains poorly understood. The space-for-time substitution method was employed in this study. Along a revegetation chronosequence (Restoration 1 year (R1), Restoration 10 year (R10), Restoration 30 year (R30), Restoration 45 year (R45)) in copper mine wasteland in Tongling, China, the dynamics of soil functions, SMF, and microbial communities were quantified, with the key factors influencing soil functions and the most important predictors of SMF subsequently identified. The results showed that the soil moisture regulation function recovered relatively slowly, whereas nutrient cycling functions and SMF were generally enhanced with advancing revegetation. Specifically, these functions all reached their maximum values at R30 (0.39, 0.45, and 0.28, respectively), followed by declines at R45 (−0.74, −0.09, and −0.20, respectively). Furthermore, the soil microbial communities exhibited successional characteristics of increased diversity but reduced dominance. Redundancy analysis indicated that aboveground biomass (AGB), belowground biomass (UGB), and soil total copper were key environmental variables associated with variations in multiple soil functions. Linear regression analysis showed that fungal diversity indices, plant biomass (AGB and UGB), soil total cadmium, and soil total zinc exhibited significant linear relationships with SMF. Random forest analysis further identified UGB, bacterial Simpson index, and fungal Shannon–Wiener index as key predictors of SMF. Importantly, bacterial communities played a more important role in influencing SMF than fungal communities. These results advance the understanding of key drivers of ecosystem functional recovery in mine lands and provide a theoretical basis for optimizing soil function restoration strategies. Ultimately, these findings provide new insights for advancing efforts aimed at halting land degradation and safeguarding biodiversity in degraded mining ecosystems.