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Article

Prediction of Suitable Habitats for Tibetan Medicinal Gentiana Plants of Jieji- and Bangjian-Type Gentianas Based on the MaxEnt Model

by
Hao Su
1,
Ba Qiang
2,
Shengnan Zhang
1,
Sujuan Wang
1,
Shiyan Wang
1,
Ke Zhang
1 and
Ji De
1,3,*
1
Key Laboratory of Biodiversity and Environment on the Qinghai-Tibetan Plateau, Ministry of Education, School of Ecology and Environment, Xizang University, Lhasa 850000, China
2
Xizang Cheezheng Xizang Medicine Co., Ltd., Lhasa 850000, China
3
State Key Laboratory for Quality Ensurance and Sustainable Use of Dao-di Herbs, Beijing 100700, China
*
Author to whom correspondence should be addressed.
Diversity 2025, 17(12), 857; https://doi.org/10.3390/d17120857
Submission received: 5 November 2025 / Revised: 10 December 2025 / Accepted: 11 December 2025 / Published: 15 December 2025
(This article belongs to the Section Plant Diversity)
Browse Figures
Versions Notes

Abstract

The Gentianaceae family, particularly the genus Gentiana, is predominantly distributed across the Qinghai–Tibet Plateau and its adjacent regions. As a widely used traditional medicinal resource in Tibetan medicine, these plants possess diverse pharmacological activities, including heat-clearing, detoxification, antibacterial, antitumor, and immunomodulatory effects. Based on their medicinal properties and traditional use, Gentiana plants in Tibetan medicine are classified into two major groups: Bangjian-type and Jieji-type plants. In the context of intensifying climate change, understanding the responses of these two Tibetan medicinal plant groups to future climate scenarios is of great significance for the effective conservation and sustainable utilization of Gentiana resources. In this study, distribution data from 355 Bangjian-type Gentiana and 417 Jieji-type Gentiana medicinal plants, along with 12 selected key environmental variables, were used to predict their potential suitable habitats under three climate scenarios—SSP126 (low-carbon), SSP245 (medium-carbon), and SSP585 (high-carbon)—across the present and four future time periods, using the Maximum Entropy (MaxEnt) model. The average AUC values of the Bangjian-type and Jieji-type Gentiana models were 0.925 and 0.924, respectively, indicating high predictive reliability. Under current climatic conditions, the estimated suitable habitat areas for Bangjian-type and Jieji-type Gentiana plants are 208.86 × 104 km2 and 211.70 × 104 km2, respectively. The most suitable regions are primarily located in the Southeastern Qinghai–Tibet Plateau, with distribution centroids in Jiangda County, Chamdo, Xizang, China. Altitude was the most influential environmental factor shaping their distribution, followed by precipitation and temperature. In the future, climate change is expected to reduce the overall habitat of Jieji-type Gentiana, with only moderate expansion projected in Central China under the SSP126 scenario. In contrast, Bangjian-type Gentiana is projected to experience habitat expansion in most climate scenarios, with only minor contractions under SSP585. These findings highlight the potential shifts in the distribution of Gentiana resources under various climate scenarios and provide a scientific basis for developing conservation strategies for Tibetan medicinal plants in the face of climate change.

1. Introduction

China’s exceptional biodiversity, surpassing that of comparable latitudes, underscores its critical role in the global ecological landscape [1,2]. However, this richness is imperiled by global climate change, a process that disrupts plant ranges and undermines ecological stability through unpredictable species movements [3,4]. The predicament of the Qinghai–Tibet Plateau highlights this susceptibility. This region, which is home to great plant diversity and precious Tibetan medicinal resources, is witnessing a rapid loss of unique species due to climate change, as demonstrated by altered phenology and diminishing habitats [5,6]. Therefore, systematically assessing future shifts in suitable habitats for medicinal plants is crucial, forming the basis for effective conservation, sustainable resource management, and the preservation of ecosystem services.
The Gentianaceae are widely distributed worldwide. In China, the family comprises 15 genera and approximately 410 species, of which 251 are endemic. The genus Gentiana is the largest, containing about 230 species. The Qinghai–Tibet Plateau and its neighboring regions represent the center of Gentiana diversity. Gentiana species have been used in Tibetan medicine for centuries [7,8,9]. The medicinal use of their dried flowers or whole flowering plants—for clearing heat, detoxification, and anti-inflammatory purposes—is documented in foundational Classical Tibetan medical texts such as The Four Medical Tantras, Materia Medica of Tibetan Medicine, Crystal Pearl Materia Medica, and Crystal Mirror Materia Medica.
In Tibetan medicine, medicinal Gentiana species are historically categorized into two primary groups—“Jieji” and “Bangjian”—based on their therapeutic effects and physical qualities. The Jieji group primarily corresponds to the Gentiana sect. Cruciata, while the Bangjian group mainly includes species of sect. Monopodiae and sect. Frigida [10,11,12]. This traditional classification system is based on differences in medicinal efficacy (e.g., heat-clearing, detoxifying, or anti-inflammatory functions) and morphological traits (such as flower color and root morphology). It forms the basis of Tibetan medical usage and is closely linked to the ecological niches and distribution patterns of these species.
Representative species of the Jieji group are perennial herbs with slightly fleshy, fibrous, conical, or cylindrical taproots. The plant base is surrounded by persistent leaf sheaths and has a well-developed rosette of basal leaves, with flowers appearing large to medium-sized (Figure 1). According to flower color, the Jieji group is divided into white-flowered (Jieji Gabo, mainly G. straminea Maxim) and black-flowered (Jieji Nabo, mainly G. crassicaulis Duthie ex Burkill) types. White-flowered species are traditionally used to treat heat-related syndromes, while black-flowered species are used for “yellow water” disease. Ecologically, Jieji species are typically found in riverbanks, shrublands, and forest understories [8,10,13].
Bangjian-type plants, including sect. Monopodiae and sect. Frigida. Sect. Monopodiae species are perennial herbs with residual stems or membranous leaf sheaths at the base, shallowly lobed corollas with prominent plicae, and generally large flowers. Sect. Frigida species are characterized by short rhizomes and fibrous roots, a well-developed basal leaf rosette, and monocarpic flowering branches that wither after blooming; these flowers are medium to large. Bangjian species can be classified by flower color into white (Bangjian Gabo, e.g., G. purdomii C. Marquand, G. szechenyii Kanitz), blue (Bangjian Wenbo, e.g., G. veitchiorum Hemsl, G. lawrencei var. farreri (Balf. f.) T. N. Ho), and variegated (Bangjian Nabo, e.g., G. nubigena Edgew, G. futtereri Diels & Gilg). Pharmacologically, they are used for detoxification, various heat-related syndromes, and throat inflammation, and ecologically, they inhabit alpine meadows, marshes, gravel slopes, and upland grasslands [8,14,15].
The classification of Jieji and Bangjian, based on morphology, flower color, and pharmacological use, is closely linked to ecology and environmental distribution. Species of different categories occupy distinct altitudes and habitat types. These ecological features provide a rationale for modeling their potentially suitable habitats. By analyzing the potential distribution of Jieji and Bangjian species, this study aims to reveal ecological preferences and inform the conservation and sustainable use of Tibetan medicinal plant resources.
Despite their high medicinal value, two major challenges exist to the long-term use of Gentiana: first, the primary medicinal part—the flowers—is primarily harvested from wild populations, resulting in a limited supply; second, the botanical origins of commercial Gentiana are frequently misidentified. While Tibetan medicine theoretically distinguishes between “Jieji” and “Bangjian” types, the indiscriminate substitution of species in practice compromises product quality. Therefore, systematic studies on taxonomy, resource distribution, and habitat prediction are crucial for identifying dominant medicinal species and conserving biodiversity. Nevertheless, studies on habitat suitability prediction for these two Tibetan medicinal categories remain scarce.
Species Distribution Models (SDMs) are essential instruments in ecology and conservation, forecasting optimal habitats for species by evaluating the correlation between species occurrence and environmental variables. They offer a comprehensive framework for forecasting habitat suitability in the context of climate change and are extensively utilized in biodiversity evaluation and the conservation of medicinal plants [16,17]. The Maximum Entropy (MaxEnt) model is a prominent and widely used species distribution modeling technique. This ecological niche modeling method conceptualizes a species and its environment as an integrated system. Based on the maximum entropy principle, it determines the most probable species distribution that maximizes entropy given environmental restrictions, thereby inferring the species–environment link and accurately forecasting prospective geographic ranges [18,19]. Due to its computational speed and dependable performance with small sample numbers, MaxEnt is highly successful for simulating dynamic shifts in suitable habitats, making it particularly applicable to endangered species and widely utilized in studies on Tibetan medicinal plants [20,21].
This study employs the Maximum Entropy (MaxEnt) model to predict the suitable habitats of fourteen medicinal Gentiana species, comprising eight “Bangjian” types (G. veitchiorum Hemsl, G. lawrencei var. farreri (Balf. f.) T. N. Ho, G. purdomii C. Marquand, G. obconica T. N. Ho, G. erectosepala T. N. Ho, G. stipitata Edgew, G. szechenyii Kanitz, and G. sino-ornata Balf. f.) and six “Jieji” types (G. lhassica Burkill, G. waltonii Burkill, G. tibetica King ex Hook. f., G. crassicaulis Duthie ex Burkill, G. straminea Maxim, and G. robusta King ex Hook. f.). Among the Bangjian species, G. obconica T. N. Ho and G. erectosepala T. N. Ho are endemic to Xizang and are typical alpine plants restricted to high-elevation habitats. Their narrow spread makes them highly sensitive to environmental changes. In the Jieji group, G. lhassica Burkill is listed as Near Threatened, and G. waltonii Burkill is classed as Critically Endangered, and both taxa have very limited and fragmented populations. Understanding how their suitable habitats may move under climate change is therefore important for their long-term conservation. Specifically, the study intends to (1) evaluate the links and variances between the current regional distributions of these Gentiana species and major environmental parameters and (2) predict probable range changes for distinct Gentiana taxa under future climatic conditions. The findings are likely to provide scientific support for the sustainable use and protection of Gentiana-derived Tibetan medicinal resources.

2. Materials and Methods

2.1. Biological Characteristics of the Main Source Species of “Jieji” and “Bangjian” Types

Representative herbarium specimens and field photos of the studied species are shown in Figure 1 and were used to verify the classification of species into the Jieji or Bangjian groups. Species classification was based on morphological characteristics, flower color, and literature references [10,11,12], as detailed in the Introduction.

2.2. Distribution Data Acquisition and Filtering

We obtained distribution records of Tibetan medicinal Gentiana species from the Chinese Virtual Herbarium (CVH, http://www.cvh.org.cn (accessed on 16 September 2025)), the National Specimen Information Infrastructure (NSII, http://www.nsii.org.cn (accessed on 16 September 2025)), the Global Biodiversity Information Facility (GBIF, https://www.gbif.org/zh/ (accessed on 29 May 2025)), and published literature [22,23,24,25]. We additionally conducted field investigations in Xizang from August to October 2024, resulting in a total of 693 Bangjian-type and 623 Jieji-type populations being recorded. (Figure 2). To prevent model overfitting, we spatially filtered the records in R, merging those within each 5 × 5 km grid. This process yielded a final set of 355 Bangjian and 417 Jieji populations for model construction.
Several species, such as G. erectosepala T. N. Ho, G. lhassica Burkill, and G. waltonii Burkill, had fewer than 30 raw records, and even fewer after spatial filtering, approaching the minimum threshold for reliable MaxEnt modeling (10–20 records) [26]. To maintain model robustness, we therefore conducted grouped modeling based on the traditional Tibetan medicinal classification (Bangjian vs. Jieji) [27], which allows assessment of climate-driven habitat shifts at the level relevant to medicinal use.

2.3. Acquisition and Selection of Environmental Variables

We obtained 19 bioclimatic variables and elevation from the WorldClim database (https://www.worldclim.org/ (accessed on 29 May 2025)) and 18 soil variables from the FAO World Soil Database’s China soil dataset (https://www.fao.org/ (accessed on 29 May 2025)). Future climate data were derived from the BCC-CSM2-MR model under three emission scenarios (SSP126, SSP245, SSP585) [28]. All layers were resampled to 2.5 arc-minutes. To avoid overfitting, we refined the variable set as follows: First, we ran MaxEnt 10 times with all 38 variables and removed those with consistently low contributions (<0.1). Subsequently, we performed Spearman correlation analysis on the remaining variables and retained only the variable with higher ecological relevance from any correlated pair (|r| > 0.8). The resulting dominant variables and their contributions are presented in Table 1.

2.4. Model Parameter Optimization

We used the ENMeval package (version 2.0.5) in R [29] to optimize key MaxEnt parameters, such as the feature classes (FC) and the regularization multiplier (RM), to reduce overfitting and make the model more reliable. We tried six different types of FC (L, H, LQ, LQH, LQHP, and LQHPT) and RM values from 0 to 4, with 0.5 increments. Cross-validation was used to test each model configuration, and the parameter set with a delta AICc value of zero was chosen as the best one for building the final model. MaxEnt also had a 75% occurrence point rate for training, a 25% occurrence point rate for validation, a maximum of 10 iterations, 10,000 background points, and a logistic output format. The area under the receiver operating characteristic curve (AUC) was used to measure how well the model worked. AUC values were interpreted as follows: 0.7–0.8 for moderate, 0.8–0.9 for adequate performance, and 0.9–1.0 for excellent predictive performance [30].

2.5. Data Processing

All data processing, habitat suitability classification, and visualization were conducted in R. The raw habitat suitability indices generated by MaxEnt were imported and reclassified into four levels—unsuitability, low, medium, and high suitability area—using the Natural Breaks (Jenks) method (Table 2).
Using the “raster” package (version 3.6.32) in R, the current habitat suitability distribution of Gentiana species was analyzed, and the dynamic changes in suitable areas were projected under 12 future climate scenarios [31]. The “geosphere” package (version 1.5.20) was employed to calculate the centroid shift distances of Tibetan medicinal Gentiana species under different climate scenarios, thereby identifying the current and projected suitable areas of Bangjian and Jieji groups [32].

3. Results

3.1. Model Optimization and Evaluation Results

The Maximum Entropy (MaxEnt) model displayed good accuracy in finding ideal habitats for the medicinal Gentiana species, with mean test AUC values of 0.925 for the Bangjian group and 0.924 for Jieji. These habitat predictions, based on species occurrence records and screened environmental variables, utilized group-specific parameter values modified for each group (Bangjian: FC = LQH, RM = 0.5; Jieji: FC = LQHPT, RM = 1.5).

3.2. Environmental Variables and Response Curves

The Jackknife test identified the dominant environmental controls on the distribution of the Tibetan medicinal Gentiana species (Figure 3 and Figure 4). Elevation was the most influential variable for both groups. Regarding climate, isothermality (bio3) was a key temperature variable for both, while precipitation of the warmest quarter (bio18) and annual precipitation (bio12) were primary for Bangjian and Jieji, respectively. For soil properties, cation exchange capacity (T_CEC_CLAY) and carbonate content (T_CACO3) were associated with Bangjian and Jieji, respectively.
Suitable habitats (occurrence probability > 0.5) were characterized by distinct environmental ranges. The Bangjian group primarily occurred at an altitude of 3003.6–4640.5 m, with optimal isothermality of 38.7–47.8, warmest-quarter precipitation of 274.5–396.7 mm, and cation exchange capacity of 66.3–87.2. In contrast, the Jieji group occupied elevations of 2835.7–4523.2 m, with optimal isothermality of 38.5–47.3, annual precipitation of 311.9–825.9 mm, and carbonate content of 0.2–3.8. Overall, while altitude was the foremost factor, Bangjian distribution was more strongly governed by precipitation, whereas Jieji was more sensitive to temperature variation (Table 1, Figure 3).

3.3. Suitable Habitat Area

Under current climatic conditions, the potentially suitable area was similar for both groups, with Bangjian-type Gentiana covering 204.86 × 104 km2 and Jieji-type covering 211.70 × 104 km2. Both were predominantly concentrated on the Qinghai–Tibet Plateau and its periphery. The high-suitability zone for Bangjian (55.91 × 104 km2, 27.3%) was primarily located in Western Sichuan and Southeastern Xizang, whereas for Jieji (53.90 × 104 km2, 25.5%), it was found in Western Sichuan, Southern Xizang, and Eastern Qinghai. The medium-suitability area was more extensive for Jieji (63.61 × 104 km2, 30.0%) than for Bangjian (51.92 × 104 km2, 25.3%), with core distributions across Xizang, Qinghai, and Sichuan for both. Conversely, Bangjian had a larger proportion of low-suitability area (97.03 × 104 km2, 47.4%) compared to Jieji (94.19 × 104 km2, 44.5%), with both extending into Gansu and Yunnan provinces (Figure 5).

3.4. Dynamic Changes in Suitable Areas Under Different Climate Scenarios

The dynamics of appropriate habitats under future warming scenarios indicated distinct trends for each category (Figure 6, Table 3). Under SSP126, Bangjian-type Gentiana demonstrated an initial shrinkage followed by growth, characterized by a net increase of 6.6 × 104 km2 during 2041–2060. In a contrary pattern, Jieji-type Gentiana increased consistently until 2060, peaking at an expansion of 5.44 × 104 km2 in 2041–2060, before shrinking in the final period (2081–2100).
Under SSP245, Bangjian’s pattern followed that under SSP126 but resulted in a more considerable net increase of 11.68 × 104 km2 during 2081–2100. Jieji, however, experienced a “contraction–expansion” transition, with a net loss of 6.1 × 104 km2 over 2021–2080 before a late-period increase.
The high-emission SSP585 scenario offered the most severe issues. Bangjian showed a changing “contraction–expansion–contraction” pattern, with a brief expansion phase (1.52 × 104 km2) in 2061–2080 amidst general contraction. Jieji fared poorly, increasing only in 2021–2040 (+2.53 × 104 km2) and then enduring chronic contraction, which was most severe in 2081–2100 with a loss of 5.75 × 104 km2.

3.5. Center of Mass Migration

The distribution centroids for both Bangjian and Jieji groups were consistently located in Jiangda County, Changdu City, Xizang, across all assessed climate scenarios and time periods (Figure 7). The current centroids were identified near Boluo Village (98.36893° E, 31.43862° N) for Bangjian and Dedeng Village (97.95395° E, 31.82757° N) for Jieji. Under future climate scenarios, the distribution centroids of both Bangjian and Jieji groups are projected to shift predominantly eastward to southeastward from their current positions (Table 4). Despite this stability, the models indicate a consistent directional trend in centroid migration towards the east-southeast under future climate conditions.

4. Discussion

4.1. Model Performance and Factor Analysis

The Maximum Entropy (MaxEnt) model, first established by Jaynes in 1957 [33], uses occurrence records and environmental variables to forecast species’ ecological niches. It is still one of the most extensively used species distribution models (SDMs) [34]. In this work, environmental predictors were submitted to a two-stage filtering process: an initial screening using MaxEnt to identify low-contribution variables, followed by Pearson correlation analysis to remove significantly intercorrelated predictors (|r| > 0.8). This strategy was implemented to mitigate overfitting and multicollinearity, thus improving model accuracy [35,36]. The ENMeval package in R was used to fine-tune the regularization multiplier (RM) and feature classes (FC) after that. We used Akaike’s Information Criterion corrected for small sample sizes (AICc) to determine how well the model fits, and we chose the optimal parameter configuration (lowest AICc) for the final forecast. The area under the receiver operating characteristic curve (AUC) was utilized to further test the model’s performance. This is a standard method for assessing model accuracy and preventing overfitting [37,38]. Following optimization, the models for the Bangjian and Jieji groups achieved high AUC values of 0.925 and 0.924, respectively, confirming their strong predictive reliability in identifying suitable habitats for these Tibetan medicinal plants across China.

4.2. Dominant Environmental Drivers

Elevation was the primary factor affecting the distribution of both medicinal Gentiana types. It contributed 44.5% and 34% to the models for Bangjian and Jieji, respectively. Prediction results showed that highly suitable areas were mainly in high-altitude regions like Qinghai, Southeastern Xizang, and Western Sichuan. This distribution is comparable with data in the Flora of China [8], with an average altitude exceeding 4000 m [39], which likely explains why elevation emerged as a dominant driver in our models. Studies by Li Haiming, Li Xiaoli, Sun Chenglin et al. on alpine medicinal plants, including Stellera chamaejasme L., Rhododendron anthopogonoides Maxim., and Saussurea medusa Maxim., likewise revealed elevation as the key factor impacting distribution [40,41,42], corroborating our findings.
Temperature and moisture were also important factors, besides elevation. Due to China’s complex topography, rainfall and temperature vary greatly across different regions [43]. Interestingly, precipitation added more to Bangjian’s distribution than temperature, while the opposite was true for Jieji. This may relate to their different habitats: our field surveys found that Bangjian often grows in moist environments like slopes and marshlands, while Jieji usually occurs in forest understory and slopes. Isothermality (bio3) was the most influential temperature variable for both types, providing 12.1% for Bangjian and 30.9% for Jieji. For precipitation, the key factors differed: precipitation of the warmest quarter (bio18) was most important for Bangjian (29.1%), while annual precipitation (bio12) was dominant for Jieji (20.6%). These patterns match the genus’s known preference for cool, moist habitats such as meadows, proving its ecological adaptation to “cool-moist” conditions and sensitivity to dry-warm environments [44,45]. Studies of G. veitchiorum Hemsl [46] also stressed warm-season precipitation as a key factor, aligning with our results.
Soil factors had the least influence on distribution. Both Gentiana types are mainly found on the Qinghai–Tibet Plateau and surrounding areas, where diverse landforms create varied soil types. Our field surveys confirmed that Bangjian and Jieji grow in different soil types, which may explain why soil is not a limiting factor. Similarly, studies on Ophiocordyceps sinensis and Przewalskia tangutica also reported minimal soil influence on distribution in this region [47,48].

4.3. Climate Change Impacts and Habitat Dynamics

Climate serves as a key driver of species distribution, and its ongoing changes greatly reshape suitable habitat ranges [49,50]. Studies suggest that climate warming may elevate temperatures by over 1.5 °C and increase annual precipitation by more than 10% across much of China [51]. Our findings show that under SSP126 and SSP245 scenarios, Bangjian-type Gentiana exhibits long-term expansion of suitable habitats, despite short-term declines. In contrast, Jieji-type Gentiana stays most stable under SSP126, showing expansion in three of the four studied periods, except during 2081–2100. Under SSP245 and SSP585 scenarios, however, its habitats usually contract. Under the high-emission SSP585 scenario, both medicinal types experience major habitat loss, shifting from low-elevation areas–such as Shaanxi, Shanxi, and Southeastern Yunnan–toward the Tibetan Plateau. This upward shift is also found in predictions for other alpine plants [52]. Bangjian’s expansion under moderate climate situations (SSP126 and SSP245) may stem from its lower sensitivity to temperature compared to Jieji. Field surveys show that Bangjian flowers 1–2 months later and usually grows at higher elevations. Warmer conditions may advance its flowering time, potentially facilitating habitat expansion [53,54]. Under the extreme SSP585 situation, however, both species retreat to higher altitudes. Intensive warming raises temperatures, increases glacial meltwater, and improves precipitation in high-elevation zones, creating more favorable conditions for alpine plants. In contrast, warming and humidity changes in low-elevation areas likely exceed the ecological limits of these two Gentiana species [2,55,56]. These projected shifts stress the urgency of building region-specific conservation strategies to safeguard these Tibetan medicinal plants and their habitats under ongoing climate change.

4.4. Limitations and Future Research

This study provides projections of potentially suitable habitats for two major types of Tibetan medicinal Gentiana using 12 environmental variables, yet several limitations should be recognized. (1) Exclusion of manmade factors: Human impact was not incorporated into the model. Specific data on herb-gathering by local communities were lacking, preventing its inclusion in the projections. While human activities such as tourism, grazing, and industrialization greatly impact alpine plants through soil alteration and local climate disruption [57], available human footprint data are limited to 2000–2020. Moreover, human activity indices often aggregate diverse pressures into a single metric, which may mask sector-specific effects [58]. Future studies should integrate more thorough and prospective human activity data. (2) Model constraints: The MaxEnt model simplifies species–environment links by evaluating variables individually, thus failing to fully capture complex interactions among environmental factors [59]. Furthermore, as model performance is highly dependent on data quality, this study primarily utilized readily available and reliable datasets for analysis. (3) Taxonomic and genetic resolution: Although this study classified species according to traditional Tibetan medicinal categories–which suitably reflects local resource use patterns–the analysis was hampered by limited genetic diversity studies and small sample sizes for some species. This stopped species-level modeling aligned with modern taxonomy. Future work should combine more comprehensive genetic and occurrence data to assess distribution patterns at finer taxonomic resolutions.

4.5. Conservation Implications

Conservation strategies for Bangjian-type and Jieji-type Gentiana should account for their specific ecological traits and adaptive capacities. For the more ecologically tolerant Bangjian group, focus should be given to protecting habitat integrity and sustaining ecosystem stability. For the more vulnerable Jieji group—particularly endangered species such as G. lhassica Burkill (CR) and G. waltonii Burkill (VU), which show significant habitat contraction and low reproductive capacity—enhanced artificial propagation, germplasm conservation, and ex situ protection are recommended to strengthen population resilience. Areas anticipated to remain constant or expand under future climatic scenarios should be identified as priority conservation zones, functioning as possible climate refugia. Additionally, building a climate-informed dynamic habitat monitoring and early-warning system, linked into regional biodiversity management plans, would enable prompt strategy revisions and improve adaptive management. The complementary application of in situ preservation and assisted propagation measures will ensure the long-term conservation and sustainable exploitation of these unique Tibetan medicinal plant resources.

5. Conclusions

(1)
Utilizing the Maximum Entropy (MaxEnt) model with twelve selected environmental factors, this study found that altitude, temperature, and precipitation are the primary dominant factors determining the distribution of the Tibetan medicinal herbs Bangjian and Jieji.
(2)
Under current climatic conditions, the total suitable habitat for Bangjian and Jieji was estimated to be 208.86 × 104 km2 and 211.70 × 104 km2, respectively. The highly suitable areas for both are primarily concentrated in the southeastern part of the Qinghai–Tibet Plateau.
(3)
Under future climate scenarios, the suitable habitat for Jieji is projected to contract, showing a moderate expansion trend towards Central China only under the SSP126 scenario. In contrast, the suitable habitat for Bangjian is generally expected to expand, except under the SSP585 scenario. The centroid of suitable habitats for both types is projected to shift eastward.
(4)
Based on future climate projections, JieJi-class Tibetan medicines exhibit higher climate sensitivity compared to BangJian-class varieties, warranting prioritized conservation measures such as the establishment of seed banks and nature reserves.
(5)
These findings establish a scientific basis for understanding the potential impacts of climate change on the distribution of Gentiana-based Tibetan medicinal resources and offer critical insights to inform ecological conservation strategies and future research.
(6)
Future research should aim to integrate anthropogenic factors and develop species-specific distribution models for individual medicinal plants.

Author Contributions

Conceptualization, H.S.; methodology, H.S.; software, B.Q.; validation, B.Q., S.Z. and S.W. (Shiyan Wang); formal analysis, H.S.; investigation, B.Q. and K.Z.; resources, J.D.; data curation, H.S.; writing—original draft preparation, H.S.; writing—review and editing, S.Z.; visualization, S.W. (Sujuan Wang); supervision, S.W. (Sujuan Wang); project administration, J.D.; funding acquisition, J.D. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Central Government Support for Local Everest Scholars Talent Development Support Program (zdbs202210) to Ji De, Key project at central government level: The ability establishment of sustainable use for valuable Chinese medicine resources (2060302) to Ji De; Tibet Autonomous Region Science and Technology Program Projects (XZ202501ZY0101) to Ji De.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.

Conflicts of Interest

Author Ba Qiang is employed by the company Xizang Cheezheng Xibetan Medicine Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Figure 1. Representative plants of Bangjian-type and Jieji-type Gentiana, illustrating the typical morphology of each group. (a) and (b) show Bangjian-type species G. purdomii C. Marquand and G. veitchiorum Hemsl, respectively; (c) and (d) show Jieji-type species G. straminea Maxim and G. crassicaulis Duthie ex Burkill, respectively. Photos were taken by SU Hao. Voucher specimens are deposited in the Herbarium of College of Ecology and Environment, Xizang University, with voucher numbers: (a) MX5401022024072; (b) LYZ404212024006; (c) MH5403232024022; (d) CJ5404252024013. The original specimen label in Chinese is visible in the image as an integral part of the historical record.
Figure 1. Representative plants of Bangjian-type and Jieji-type Gentiana, illustrating the typical morphology of each group. (a) and (b) show Bangjian-type species G. purdomii C. Marquand and G. veitchiorum Hemsl, respectively; (c) and (d) show Jieji-type species G. straminea Maxim and G. crassicaulis Duthie ex Burkill, respectively. Photos were taken by SU Hao. Voucher specimens are deposited in the Herbarium of College of Ecology and Environment, Xizang University, with voucher numbers: (a) MX5401022024072; (b) LYZ404212024006; (c) MH5403232024022; (d) CJ5404252024013. The original specimen label in Chinese is visible in the image as an integral part of the historical record.
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Figure 2. Distribution Point of Bangjian-type and Jieji-type plants in China.
Figure 2. Distribution Point of Bangjian-type and Jieji-type plants in China.
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Figure 3. Regularized Training Gain Curves: Bangjian (A); Jieji (B).
Figure 3. Regularized Training Gain Curves: Bangjian (A); Jieji (B).
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Figure 4. Response curves of the environmental variables used in the MaxEnt models. Panel (A) shows the response curves for the Bangjian population, and Panel (B) shows the response curves for the Jieji population. Subplots (a–d) represent the four variables for Bangjian: (a) bio3 (isothermality); (b) elevation; (c) bio18 (precipitation of the warmest quarter); and (d) T_CEC_CLAY (cation exchange capacity). Subplots (e–h) represent the four variables for Jieji: (e) bio3 (isothermality); (f) elevation; (g) bio12 (annual precipitation); and (h) T_CACO3 (carbonate content).
Figure 4. Response curves of the environmental variables used in the MaxEnt models. Panel (A) shows the response curves for the Bangjian population, and Panel (B) shows the response curves for the Jieji population. Subplots (a–d) represent the four variables for Bangjian: (a) bio3 (isothermality); (b) elevation; (c) bio18 (precipitation of the warmest quarter); and (d) T_CEC_CLAY (cation exchange capacity). Subplots (e–h) represent the four variables for Jieji: (e) bio3 (isothermality); (f) elevation; (g) bio12 (annual precipitation); and (h) T_CACO3 (carbonate content).
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Figure 5. Potential current suitable habitat distribution of Tibetan medicinal Gentiana: (A) Bangjian-type Gentiana species; (B) Jieji-type Gentiana species.
Figure 5. Potential current suitable habitat distribution of Tibetan medicinal Gentiana: (A) Bangjian-type Gentiana species; (B) Jieji-type Gentiana species.
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Figure 6. Spatiotemporal dynamics of suitable habitats for Bangjian (A) and Jieji (B) Tibetan medicines across future periods. Subplots (a–c) show Bangjian under SSP126, SSP245, and SSP585 scenarios, respectively; subplots (d–f) show Jieji under SSP126, SSP245, and SSP585 scenarios, respectively. For each subplot, the four time periods correspond to 2021–2040, 2041–2060, 2061–2080, and 2081–2100.
Figure 6. Spatiotemporal dynamics of suitable habitats for Bangjian (A) and Jieji (B) Tibetan medicines across future periods. Subplots (a–c) show Bangjian under SSP126, SSP245, and SSP585 scenarios, respectively; subplots (d–f) show Jieji under SSP126, SSP245, and SSP585 scenarios, respectively. For each subplot, the four time periods correspond to 2021–2040, 2041–2060, 2061–2080, and 2081–2100.
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Figure 7. Centroid shifts in suitable habitats across time periods: (a) Bangjian-type species; (b) Jieji-type species.
Figure 7. Centroid shifts in suitable habitats across time periods: (a) Bangjian-type species; (b) Jieji-type species.
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Table 1. Contribution of Dominant Environmental Variables to the Habitat Suitability of Tibetan Medicinal Gentiana Based on the MaxEnt Model.
Table 1. Contribution of Dominant Environmental Variables to the Habitat Suitability of Tibetan Medicinal Gentiana Based on the MaxEnt Model.
AbbreviationBio-Climatic VariablesBangjianJieji
Percent ContributionPermutation ImportancePercent ContributionPermutation Importance
ElevationElevation44.55.9345.7
bio3Isothermality12.122.130.950.9
bio12Annual PrecipitationNANA20.628.6
bio11Mean Temperature of Coldest Quarter77.65.25
bio4Temperature Seasonality3.316.94.38.5
bio18Precipitation of Warmest Quarter29.143.9NANA
T_CACO3Carbonate or lime contentNANA3.20.8
T_BSBasic SaturationNANA1.80.5
T_ESPExchangeable sodium saltNANA0.10.1
T_CEC_CLAYCation Exchange Capacity of Clayey Soils2.93NANA
T_SILTSilt content0.80.3NANA
T_PH_H2OpH level0.30.2NANA
Table 2. Suitability Index Grading Based on the Natural Breaks Method.
Table 2. Suitability Index Grading Based on the Natural Breaks Method.
CategoryUnsuitability AreaLow Suitability AreaMedium Suitability AreaHigh Suitability Area
BangJian0–0.0680.068–0.25010.2501–0.48810.4881–0.8424
JieJi0–0.07070.0707–0.24230.2423–0.48280.4828–0.8280
Table 3. Spatiotemporal Changes in Suitable Habitats for Tibetan Medicinal Species of Gentiana Across Periods.
Table 3. Spatiotemporal Changes in Suitable Habitats for Tibetan Medicinal Species of Gentiana Across Periods.
CategoryScenariosPeriodStable Area (×104 km2)Expansion Area (×104 km2)Contraction Area (×104 km2)Expansion/Contraction (×104 km2)
BangJianSSP1262021–2040195.778.73−1.73
2041–2060197.3813.657.05+6.60
2061–2080197.69.276.84+2.43
2081–2100198.9911.345.45+5.89
SSP2452021–2040196.098.178.34−0.17
2041–2060199.0512.85.39+7.41
2061–2080196.6614.327.78+6.54
2081–2100198.4617.665.98+11.68
SSP5852021–2040196.476.727.97−1.25
2041–2060194.007.410.44−3.04
2061–2080195.3210.639.11+1.52
2081–2100189.9513.114.49−1.39
JieJiSSP1262021–2040202.99.058.79+0.26
2041–2060202.1514.979.53+5.44
2061–2080203.6512.828.04+4.78
2081–2100200.0211.1111.66−0.55
SSP2452021–2040197.538.0614.16−6.10
2041–2060200.2311.1611.45−0.29
2061–2080197.6210.8114.06−3.25
2081–2100199.719.7411.98+7.76
SSP5852021–2040202.0312.199.66+2.53
2041–2060198.719.2812.97−3.69
2061–2080195.413.0616.29−3.23
2081–2100191.1714.7620.51−5.75
Table 4. Migration of the Plant Center of Gentiana Species in Tibetan Medicine Across Different Periods.
Table 4. Migration of the Plant Center of Gentiana Species in Tibetan Medicine Across Different Periods.
CategoryScenariosPeriodxyDistance Traveled (km)Movement Direction
BangJianCurrentCurrent98.3689331.43862NANA
SSP1262021–204098.5296931.4395715.28Southeast
2041–206098.6025131.416967.36Southeast
2061–208098.6169731.401962.16Southeast
2081–210098.5597931.419605.78Northwest
SSP2452021–204098.3050631.3660310.08Southwest
2041–206098.6523631.5024336.32Northeast
2061–208098.4866031.3684921.65Southwest
2081–210098.7073031.3849821.07Northeast
SSP5852021–204098.4788031.3835412.10Southeast
2041–206098.5678631.5165817.01Northeast
2061–208098.5087431.3111923.46Southwest
2081–210098.3613831.2292616.72Southwest
JieJiCurrentCurrent97.9539531.82757NANA
SSP1262021–204098.1066931.7048919.86Southeast
2041–206098.1916631.9294126.16Northeast
2061–208098.1482931.7373421.69Southwest
2081–210098.0372831.8095713.22Northwest
SSP2452021–204097.8280031.7456614.99Southwest
2041–206098.0420831.8361122.62Northeast
2061–208098.1327331.822528.71Southeast
2081–210098.2241831.9109713.08Northeast
SSP5852021–204098.3097131.7733834.22Southeast
2041–206098.0105331.7720628.34West
2061–208098.2320931.7115922.04Southeast
2081–210097.9732131.6462625.59Southwest
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Su, H.; Qiang, B.; Zhang, S.; Wang, S.; Wang, S.; Zhang, K.; De, J. Prediction of Suitable Habitats for Tibetan Medicinal Gentiana Plants of Jieji- and Bangjian-Type Gentianas Based on the MaxEnt Model. Diversity 2025, 17, 857. https://doi.org/10.3390/d17120857

AMA Style

Su H, Qiang B, Zhang S, Wang S, Wang S, Zhang K, De J. Prediction of Suitable Habitats for Tibetan Medicinal Gentiana Plants of Jieji- and Bangjian-Type Gentianas Based on the MaxEnt Model. Diversity. 2025; 17(12):857. https://doi.org/10.3390/d17120857

Chicago/Turabian Style

Su, Hao, Ba Qiang, Shengnan Zhang, Sujuan Wang, Shiyan Wang, Ke Zhang, and Ji De. 2025. "Prediction of Suitable Habitats for Tibetan Medicinal Gentiana Plants of Jieji- and Bangjian-Type Gentianas Based on the MaxEnt Model" Diversity 17, no. 12: 857. https://doi.org/10.3390/d17120857

APA Style

Su, H., Qiang, B., Zhang, S., Wang, S., Wang, S., Zhang, K., & De, J. (2025). Prediction of Suitable Habitats for Tibetan Medicinal Gentiana Plants of Jieji- and Bangjian-Type Gentianas Based on the MaxEnt Model. Diversity, 17(12), 857. https://doi.org/10.3390/d17120857

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