Background: A method is proposed as follows to establish the ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) fingerprinting and content determination for Fritillaria przewalskii Maxim. (FPM). Materials and Methods: The separation was developed using an Acquity UPLC CSH C18 column (2.1 mm × 100 mm, 1.7 µm). The gradient elution was carried out with acetonitrile solution with 0.1% acetic acid (containing 0.01 mol L−1 ammonium acetate) as the mobile phase, with the flow rate of 0.4 mL min−1, column temperature of 30°C, and injection volume of 2 µL. Fourteen batches of samples were analyzed under the above chromatographic conditions to ascertain the fingerprint of FPM sourced in different areas. A total of 45 common peaks were selected for analysis. Two chromatographic peaks were identified by comparison with the standard compound, and simultaneous content determination of the two compounds was carried out. These two compounds were identified as two alkaloids, peiminine and peimisine. SPSS 25.0 and SIMCA 14.1 were used for cluster analysis (CA), principal component analysis (PCA), and orthogonal partial least squares discriminant analysis (OPLS-DA) on the peak area of the 45 common peaks of FPM. Results: Results from this showed that samples sourced from different regions could be successfully divided into three groups based on their origin. The contents of peiminine and peimisine in different batches of FPM ranged from 57.92 to 76.01 µg/g and 118.12 to 167.39 µg/g. A quick and convenient identification using UPLC fingerprinting combined with PCA was then established to differentiate among FPM samples from different growing regions. Conclusion: This method may prove to be helpful for the quality evaluation and control of FPM and related medicinal plants in the future.

The Qinghai–Tibet Plateau is one of the regions most strongly affected by climate change. The climate feedback of the distribution of plateau pika, a key species, is closely related to the trophic structure of the plateau ecosystem and the development of agriculture and animal husbandry on the plateau. In order to understand the impact of future climate change on the suitable distribution area of plateau pika, potential suitable distribution areas of Plateau pika were predicted using the MaxEnt model under three climate scenarios (SSP 1-2.6, SSP 2-4.5, and SSP 5-8.5) in the near term (2021–2040) and medium term (2041–2060). The predictions were found to be highly accurate with AUC values of 0.997 and 0.996 for the training and test sets. The main results are as follows: (1) The precipitation of the wettest month (BIO 16), mean diurnal range (BIO 2), slope, elevation, temperature seasonality (BIO 4), and annual mean temperature (BIO 1) were the main influencing factors. (2) In the historical period, the total suitable distribution area of Plateau pika in the Qinghai–Tibet Plateau accounted for 29.90% of the total area at approximately 74.74 × 104 km2, concentrated in the eastern and central areas of the Qinghai–Tibet Plateau. (3) The total suitable distribution area of pika exhibited an expansion trend under SSP 1-2.6 and SSP 2-4.5 in the near term (2021–2040), and the expansion area was concentrated in the eastern and central parts of the Qinghai–Tibet Plateau. The expansion area was the largest in Qinghai Province, followed by Sichuan Province and Tibet. In contrast, the suitable distribution area shrank in the Altun Mountains, Xinjiang. Under SSP 5-8.5 in the near term and all scenarios in the medium term (2041–2060), the suitable distribution area of Plateau pika decreased to different degrees. The shrinkage area was concentrated at the margin of the Qaidam Basin, central Tibet, and the Qilian Mountains in the east of Qinghai Province. (4) Plateau pika migrated toward the east or southeast on the Qinghai–Tibet Plateau under the three climate scenarios. Under most of the scenarios, the migration distance was longer in the medium term than in the near term.