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Article

Assessing Habitat Suitability for Hippophae rhamnoides subsp. turkestanica Amid Climate Change Using the MaxEnt Model

by
Fanyan Ma
1,†,
Mengyao He
1,†,
Mei Wang
2,*,
Guangming Chu
1,
Zhen’an Yang
1,
Cunkai Luo
1,
Mingwang Zhou
1,
Ying Hui
1 and
Junjie Ding
3,*
1
College of Agriculture, Shihezi University, Shihezi 832003, China
2
College of Science, Shihezi University, Shihezi 832003, China
3
Xinjiang Academy of Agricultural and Reclamation Science, Shihezi 832003, China
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Forests 2025, 16(3), 468; https://doi.org/10.3390/f16030468
Submission received: 22 January 2025 / Revised: 26 February 2025 / Accepted: 4 March 2025 / Published: 6 March 2025
(This article belongs to the Section Forest Ecology and Management)
Browse Figures
Versions Notes

Abstract

:
Hippophae rhamnoides subsp. turkestanica is mainly distributed in the mountains, valleys, and desert edges of Central Asia. It plays a vital role in maintaining ecological stability in arid and semiarid areas. In this study, the MaxEnt model was used to simulate the habitat suitability of H. rhamnoides subsp. turkestanica, and the key environmental factors affecting its distribution were identified. Additionally, we explored habitat sensitivity to climate change, and provided essential information for the conservation and management of this important subspecies in arid and semiarid regions. Under four different climate scenarios (SSP126, SSP245, SSP370, and SSP585) in 2040, 2060, 2080, and 2100, the prediction of habitat suitability and changes in species distribution centroids in the future were simulated. The results revealed that suitable habitats for H. rhamnoides subsp. turkestanica are primarily located in Tajikistan, Kyrgyzstan, China, Pakistan, and Afghanistan. Altitude (Alt), isothermality (bio3), and slope (Slo) emerged as the main environmental factors. Projections suggest a significant expansion in the total area of suitable habitat under future climate scenarios. By 2100, the suitable habitat areas under the SSP126, SSP245, SSP370, and SSP585 scenarios will reach 10,526,800 km2, 12,930,200 km2, 15,449,900 km2 and 14,504,800 km2, respectively. In addition, a slight northwestward shift was observed in the distribution centroid. These findings provide important insights for conservation efforts aimed at protecting H. rhamnoides subsp. turkestanica and supporting its biodiversity. By understanding the factors affecting habitat suitability and predicting changes in climate scenarios, this study provides valuable guidance for developing long-term conservation strategies.

1. Introduction

The Intergovernmental Panel on Climate Change (IPCC) reports that the global mean temperature has risen by approximately 1.1 °C since the pre-industrial era. Even under lower-emission scenarios, the 1.5 °C threshold is likely to be exceeded by the mid-21st century [1]. Temperature serves as a pivotal factor regulating photosynthesis and other biological processes in plants, and climate change will profoundly alter plant development and reproduction [2]. Continued warming at the current trajectory risks breaching ecological tipping points, triggering irreversible and cascading impacts on global ecosystems [3]. Notably, anthropogenic warming has intensified the frequency of extreme weather events, exacerbating the vulnerability of arid ecosystems. Enhancing the mechanistic understanding of climate–biosphere interactions is imperative for designing restoration strategies for fragile ecosystems. In-depth investigations into climate-driven shifts in vegetation survival and geographical distribution are critical to advancing predictive frameworks and informing evidence-based adaptive measures.
Hippophae rhamnoides L. (Elaeagnaceae), a deciduous shrub or small shrub, is widely distributed across temperate Eurasia [4]. China hosts the most extensive resource of this species, accounting for approximately 90% of the global total [5]. Renowned as a “pioneer species in soil conservation”, H. rhamnoides integrates ecological [6], economic [7,8,9], and socioeconomic value [10], driving multidisciplinary research interest [11]. The subspecies Hippophae rhamnoides subsp. turkestanica (Rousi) Y.S. Lian) occupies ecologically fragile regions, including Xinjiang, Tibet, and Gansu in China, as well as western India, Uzbekistan, and Pakistan. Adapted to hyperarid conditions, this subspecies thrives through deep-rooted systems, salt-alkali tolerance, and exceptional sand stabilization capacity, serving as a keystone species in desert–steppe ecotones. However, emerging evidence indicates that rising temperatures and altered precipitation regimes reduce its water-use efficiency, potentially compromising its ecological functions [12]. Thus, elucidating the adaptive mechanisms of H. rhamnoides is imperative to sustaining its multifunctional benefits—spanning ecological stabilization, economic productivity, and social welfare—under escalating climatic and anthropogenic pressures.
To quantify the potential impacts of climate change on species distributions and formulate adaptive strategies, species distribution models (SDMs) have emerged as critical tools. Species distribution models (SDMs) employ statistical and mathematical approaches to reveal relationships between species and their environments [13,14]. These models are widely used for the conservation of endangered species [15], evaluation of climate change impacts on species distributions [16], management and protection of ecosystems [17], and ecological restoration efforts [18]. Prominent SDMs include MaxEnt [19], boosted regression trees [20], generalized linear models [21], and Biomod [22]. Among the various models, MaxEnt is widely recognized for its application in species distribution analysis [23]. Its key advantages include its ability to utilize presence-only data, tolerate moderate spatial inaccuracies, and generate robust models, even with limited location records [24]. Additionally, MaxEnt’s ability to integrate multiple environmental variables enhances its ability to assess different climate scenarios [25,26]. The model has been extensively used to predict species distribution. For example, the potential distribution of the desert locust (Schistocerca gregaria (Forskål, 1775)) under current and future climate change scenarios was simulated using the MaxEnt model, revealing the impact of climate change on its geographical distribution range and its possible ecological risks [27]; the model has also assessed the impacts of global climate change on the growth and distribution of high-latitude medicinal plants such as Panax ginseng C.A. Mey. [28]. Moreover, MaxEnt has been instrumental in assessing the distribution and invasion potential of snapping turtles (Chelydra serpentina (Linnaeus, 1758)) both globally and in China [29]. Furthermore, MaxEnt has been applied to study the climate-change-related shifts in the spatial distribution of three Ephedra L. species [30].
Current research on the distribution of H. rhamnoides has predominantly focused on Hippophae rhamnoides subsp. sinensi Rousi [31,32] and Hippophae rhamnoides subsp. yunnanensis Rousi [33], primarily relying on contemporary climate data and single-model approaches for distribution predictions. In contrast, limited attention has been paid to the factors influencing the distribution of H. rhamnoides subsp. turkestanica, and there is a notable absence of predictions regarding its distribution under future climate change scenarios. Therefore, this study aimed to address the following critical questions: (1) What environmental variables govern the distribution of H. rhamnoides subsp. turkestanica? (2) How will the distribution of H. rhamnoides subsp. turkestanica be affected under the projected climate change scenarios? (3) What are the expected migration patterns of H. rhamnoides subsp. turkestanica in response to climate changes?

2. Materials and Methods

2.1. Species Distribution Data

In this study, 152 distribution records of H. rhamnoides subsp. turkestanica were obtained from multiple sources, including the Global Biodiversity Information Facility (GBIF, https://www.gbif.org) (accessed on 5 July 2024), National Plant Specimen Resource Center of China (http://www.cvh.org) (accessed on 10 July 2024), Chinese Plant Image Database (http://ppbc.iplant.cn) (accessed on 12 July 2024), and the relevant literature. For records lacking latitude and longitude but containing specific geographic details (e.g., town names), coordinates were derived using Google Maps (24.47.01.697822364). To minimize sampling bias and mitigate the risk of overfitting caused by closely clustered distribution points, the data were refined using ENMTools.pl software (v3.1.2), ensuring that only one point was retained per 2.5 km grid (5 km × 5 km). Following this refinement, 154 unique distribution records remained, and a distribution map was subsequently generated using ArcGIS 10.4 (ESRI, Redlands, CA, USA) (Figure 1).

2.2. Environmental Variables

This study examined three environmental factors: climate, topography, and soil type. Nineteen climate variables (bio1–bio19) and three topographic variables (altitude, slope, and slope position) were sourced from the WorldClim 2.1 database (https://www.worldclim.org) (accessed on 20 July 2024), while thirty-two soil variables were obtained from the World Soil Information Service v1.2 (https://www.fao.org) (accessed on 3 August 2024). To ensure compatibility with the MaxEnt 3.4.1 model, environmental data were resampled to a resolution of 2.5′ (5 km × 5 km) using ArcGIS 10.4. Given that multicollinearity among environmental variables can compromise SDMs [24] and reduce the predictive accuracy of the MaxEnt model [34], the ENMTools.pl tool was employed to assess correlations among the variables, excluding those with high correlation coefficients (|r| ≥ 0.8). Ultimately, nine variables were retained for the analysis: annual mean temperature (bio1), isothermality (bio3), temperature seasonality (bio4), maximum temperature of the warmest month (bio5), annual temperature range (bio7), mean temperature of the warmest quarter (bio10), altitude (Alt), slope (Slo), and soil base saturation (s_bs).
Future bioclimatic variables were derived from the shared socioeconomic pathway (SSP) scenario described by CMIP6, with particular attention paid to specific combinations of representative concentration pathways (RCPs) [35]. These variables were generated using the Beijing Climate Center Climate System Model 2 (BCC-CSM2-MR) [36]. This study aimed to identify potential habitats for H. rhamnoides subsp. turkestanica under future environmental conditions, using SSP126, SSP245, SSP370, and SSP585 to represent the low, medium, high, and very high emission scenarios, respectively [37]. Four distinct time intervals were selected for the future predictions: 2021–2040, 2041–2060, 2061–2080, and 2081–2100. A methodological framework aligning with the objectives and core principles of the MaxEnt model was developed to simulate both the current and projected future distributions of H. rhamnoides subsp. turkestanica (Figure 2).

3. Results

3.1. Model Accuracy Assessment and the Importance of Environmental Variables

This study utilized 152 distribution data points and nine environmental variables to model the global potential distribution of H. rhamnoides subsp. turkestanica. The AUC for the training and testing datasets were 0.986 and 0.985, respectively (Figure 3a). Predictions for future periods consistently yielded AUC values exceeding 0.9 (Table 1).
The analysis of the percentage contributions and the jackknife method revealed that slope, altitude, and isothermality were the primary determinants of suitable habitats for H. rhamnoides subsp. turkestanica. Specifically, Slo and Alt contributed 35.2% and 20.6% of the total contribution, respectively (Table 2). Figure 3 highlights the significance of the environmental variables in the MaxEnt model, including the results of the regularized training gain, which is a technique used to assess the relative contribution of each variable. This method accounts for the variable interrelationships and standardizes their effects to improve comparability. The results demonstrated that the model’s performance was superior when all variables were included, as indicated by the “With all variables” scenario outperforming both the “Without variable” and “With only variable” models. Notably, when specific variables were isolated, slope, altitude, and isothermality showed higher normalized gain values, underscoring their critical roles in model accuracy (Figure 3b–d).

3.2. Potential Distribution of Hippophae rhamnoides in Central Asia Under Current Climate Conditions

According to the distribution of potential suitable habitats (Figure 4) and the area statistics of these habitats (Table 3) under the current climate scenario for H. rhamnoides subsp. turkestanica, it is evident that the high-suitability habitat covers approximately 665,500 km2. It is primarily distributed along the southern edge of Kyrgyzstan, throughout Tajikistan, central and northeastern Afghanistan, northeastern Pakistan, northern India, and western China, with a smaller distribution observed along the northern edge of Iran. The medium-suitability habitat spans approximately 2,936,000 km2, with a primary distribution in most parts of Kyrgyzstan, western Tajikistan, central Afghanistan, western China, northwestern Iran, and eastern Turkey. The low-suitability habitat covers approximately 55,788,700 km2, primarily distributed across much of China, southern Mongolia, northwestern Iran, western Turkey, the southern and northern borders of Georgia, the southwestern region of Russia, and the northern and western borders of Azerbaijan. In total, the suitable habitat area encompasses approximately 9,380,300 km2, excluding the regions mentioned above.

3.3. Global Distribution of Hippophae rhamnoides Under Future Climate Change

H. rhamnoides subsp. turkestanica primarily inhabits arid and semiarid regions, where temperature fluctuations and precipitation patterns significantly influence its growth, making climate change a critical concern for the species. Using the MaxEnt model, we predicted the potentially suitable habitats for H. rhamnoides subsp. turkestanica under the SSP126, SSP245, SSP370, and SSP585 scenarios for the 2040s, 2060s, 2080s, and 2100s. The predicted future habitat suitability for H. rhamnoides subsp. turkestanica was categorized into high-, medium-, and low-suitability zones (Figure 5), and the habitat area changes were classified as stable, shrinking, expanding, or unchanged (Figure 6). Over the long term, suitable habitat areas for H. rhamnoides subsp. turkestanica in Central Asia are expected to grow under different social development and emission scenarios. All scenarios predicted an increase in suitable habitats by 2100. In the SSP126 scenario, the habitat area was projected to increase initially, followed by a slight decline with only minor fluctuations. A slight reduction in habitat area is expected between 2080 and 2100, with the total suitable habitat area projected to be 10,568,000 km2 by 2100 (Table 4). This suggests that under a moderate climate scenario, the decline in suitable habitats for H. rhamnoides subsp. turkestanica may occur gradually. Under the SSP245 and SSP370 scenarios, significant increases in habitat area are expected, with total suitable habitats projected to reach 12,930,200 km2 and 15,449,900 km2 by 2100 (Table 4). These scenarios indicate that greater social development and emission pathways may substantially benefit the habitats of H. rhamnoides subsp. turkestanica. Under the SSP585 scenario, the habitat area is anticipated to show a marked upward trend, particularly between 2040 and 2060, with minimal fluctuations, and a slight increase thereafter. Between 2060 and 2080, an increase of 144,790 km2 is expected. However, from 2080 to 2100, the habitat area is predicted to rise gradually, reaching 14,504,800 km2 by 2100 (Table 4). This highlights the challenges faced by H. rhamnoides subsp. turkestanica under high social development and emission scenarios, underscoring the considerable effects of climate warming on this species.
The geographical distribution of H. rhamnoides subsp. turkestanica (Figure 5 and Figure 6) indicates that highly suitable habitats are expected to expand under various climate scenarios. Specifically, the projected increases in highly suitable habitat areas under the SSP126, SSP245, SSP370, and SSP585 scenarios are 130,800 km2, 464,300 km2, 1,694,4 00 km2, and 2,135,700 km2, respectively. Under the SSP126 scenario, low-suitability habitats are projected to decrease by 2,167,000 km2, primarily affecting regions in Kyrgyzstan, Pakistan, India, Afghanistan, and Iran. Conversely, under the SSP245, SSP370, and SSP585 scenarios, the expected increases in suitable habitats transitioning from low suitability are 878,300 km2, 1,594,800 km2, and 1,310,900 km2, respectively. Overall, the suitable habitat area for H. rhamnoides subsp. turkestanica, encompassing high-, medium-, and low-suitability habitats, is expected to increase significantly, primarily in China, Tajikistan, Kyrgyzstan, Afghanistan, Turkey, Azerbaijan, Iran, and the surrounding regions.
In summary, climate warming is expected to positively impact the habitats of H. rhamnoides subsp. turkestanica. However, under SSP126, the anticipated expansion of suitable habitats remains relatively limited. Over time, the area of suitable habitat is expected to increase, suggesting that H. rhamnoides subsp. turkestanica demonstrates considerable adaptability under moderate climate scenarios.

3.4. Centroid Shift of Hippophae rhamnoides Under Future Climate Scenarios

The movement of the optimal habitat center for H. rhamnoides subsp. turkestanica in Central Asia is anticipated to gradually shift under various climate scenarios as time progresses. According to our findings (Figure 7), the habitat center is generally trending northwest from the present to future projections. Currently, the habitat center is located in Afghanistan, with coordinates of 70.31° E and 37.53° N. Under the SSP126 scenario, the center is projected to shift northwest between 2040 and 2060 before transitioning southeast by 2100. This movement is expected to pass through Turkmenistan and culminate in Uzbekistan, with projected coordinates of 67.62° E and 38.00° N. Under the SSP245 and SSP370 scenarios, the center’s northwestward trajectory continues, reaching Turkey by 2100 at coordinates of 41.64° E and 40.51° N. Under the SSP585 scenario, the habitat center is anticipated to move northwestward between 2020 and 2080, reaching Azerbaijan at 46.17° E and 40.29° N. From 2080 to 2100, it is projected to shift southwest and ultimately settle in Armenia by 2100 at 44.98° E and 40.09° N.

4. Discussion

4.1. Impact of Environmental Variables on the Distribution of H. rhamnoides subsp. turkestanica

Plant distribution is heavily influenced by climate, with species responding differently to changes in climate and other environmental conditions. For instance, global climate change is anticipated to expand the suitable habitat for Ziziphus jujuba Mill. [38] and Ephedra equisetina Bunge [39]. Conversely, warming trends are projected to negatively impact Gymnadenia conopsea (L.) R. Br., resulting in decreased habitat suitability [40]. In this study, under various climate change scenarios, suitable habitats for H. rhamnoides subsp. turkestanica showed an overall westward expansion (Figure 5). This trend is attributed to the gradual increase in temperature and precipitation in the western region of Central Asia due to global warming. The primary climatic factors influencing the distribution of H. rhamnoides is water–heat conditions [41]. Although H. rhamnoides possesses unique morphological and physiological adaptations that confer a high water-retention capacity and strong resilience to arid, cold, and barren environments [42,43,44], numerous studies have highlighted that this species requires specific water–heat conditions for its growth and development. Water stress can significantly impair photosynthesis and negatively affect plant growth and development, as well as fruit yield [10,12,44]. In regions where H. rhamnoides is distributed, high growing-season temperatures and active transpiration make precipitation and temperature critical factors [10,44]. Model analysis in this study further confirmed that isothermality and related climatic variables are the main factors shaping the distribution of H. rhamnoides subsp. turkestanica (Figure 3b–d).
In addition to climatic factors, other environmental variables significantly influence the geographical distribution of plant species, with key factors including vegetation cover [43], topography [22,43], and soil conditions [45]. Consequently, this study incorporated both topographic and edaphic factors, along with climatic variables, to enhance the accuracy of predictions regarding the potential distribution of H. rhamnoides subsp. turkestanica over time. Preliminary results indicated that soil saturation content had the highest contribution among soil factors, while slope aspect contributed most significantly among topographic variables (Figure 3b–d). Therefore, one soil factor and one topographic factor were selected to predict the distribution of sea buckthorn in Central Asia. Previous studies have highlighted the critical roles of soil base saturation and sand content as limiting factors in the distribution of H. rhamnoides subsp. turkestanica [22,46]. Additionally, variations in the slope gradient and aspect may indirectly influence species distribution by modulating soil moisture, light availability, and other associated environmental factors [47]. Therefore, to accurately model the geographical distribution of H. rhamnoides subsp. turkestanica, it is essential to consider a comprehensive range of relevant environmental variables.

4.2. Changes in Suitable Habitats for H. rhamnoides subsp. turkestanica Under Current and Future Climate Change Scenarios

H. rhamnoides subsp. turkestanica is found in Central Asia. This study also explored future distribution predictions based on current models (Figure 5). Increased greenhouse gas emissions from human activities are expected to drive global warming, leading to more frequent extreme-weather events and natural disasters [48]. This will affect the habitat changes of some wild plants [49]. Therefore, it is crucial to assess the effect of these changes on the potential distribution of H. rhamnoides subsp. turkestanica. Simulations of its distribution under four future time periods and climate scenarios revealed shifts in its potentially suitable habitat area. Under the SSP126, SSP245, and SSP370 scenarios, the overall suitable habitat for H. rhamnoides subsp. turkestanica is projected to increase steadily (Table 4). In contrast, the SSP585 scenario suggested a slight decrease in the suitable habitat area. Between 2021 and 2100, SSP370 was predicted to be the most favorable for the growth of H. rhamnoides subsp. turkestanica (Table 4). This trend likely reflects the adaptive limits of the species being exceeded under higher-emission scenarios that increase atmospheric CO2 levels and radiative forcing, potentially stressing species survival. In this context, pursuing a sustainable development pathway that minimizes mitigation pressures and reduces radiative forcing is optimal for the long-term viability of the species. Despite climate-driven changes that may lower the density of its distribution, H. rhamnoides subsp. turkestanica demonstrates resilience, with its total suitable habitat expected to expand over the next 60 years. Moreover, this species is expected to expand into high-latitude and high-altitude regions in the northwest.
This study has some limitations. Firstly, while the BCC-CSM2-MR model has proven effective in simulating the spatial distribution and changes in terrestrial surface variables [50], it may exhibit biases in intensity simulations, which could influence predictions of H. rhamnoides subsp. turkestanica’s distribution. In the future forecast results, some suitable habitats appear in North America, which may be a true reflection of the similarity in climate.
Secondly, while the effects of climate, soil, and topographic factors on species distribution were considered, the effects of interspecies interactions and human activities were not. Incorporating these additional factors into the model and optimizing model simulations to improve accuracy are essential directions for future research on SDMs.

5. Conclusions

In this study, the MaxEnt model was used to predict the potential distribution of H. rhamnoides subsp. turkestanica under future climate scenarios. Species distribution was expected to be affected by factors such as altitude, slope, and temperature fluctuations. Currently, H. rhamnoides subsp. turkestanica is mainly distributed throughout in Central Asia, particularly in Tajikistan, Kyrgyzstan, China, Pakistan, and Afghanistan. Under future climate scenarios, the region suitable for this subspecies is predicted to expand, with its core distribution likely shifting to the northwest within Central Asia. These findings offer critical insights for the conservation and management of H. rhamnoides subsp. turkestanica, particularly regarding the identification and protection of its optimal habitats.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/f16030468/s1, Table S1: Occurrence records; Table S2: Environmental variables used in this study.

Author Contributions

F.M. and M.H.: Conceptualization, writing—original draft, and methodology. M.W.: Conceptualization, investigation, formal analysis, and funding acquisition. G.C.: Conceptualization and formal analysis. J.D.: Formal analysis and funding acquisition. C.L.: Formal analysis. Z.Y.: Validation and writing—review and editing. Y.H.: Formal analysis. M.Z.: Validation and visualization. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Science and Technology Plan Project of Xinjiang Production and Construction Corps (2024DA024), the Science and Technology Innovation Project of Xinjiang Academy of Agricultural Reclamation Sciences (NCG2023010).

Data Availability Statement

The original contributions presented in the study are included in the article and Supplementary Materials, further inquiries can be directed to the corresponding authors.

Acknowledgments

We wish to express our gratitude to all the authors of this study, and all provided useful feedback on our manuscript.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Occurrence records of Hippophae rhamnoides subsp. turkestanica in the study area.
Figure 1. Occurrence records of Hippophae rhamnoides subsp. turkestanica in the study area.
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Figure 2. The framework of this study’s contribution.
Figure 2. The framework of this study’s contribution.
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Figure 3. Reliability test of distribution model created for H. rhamnoides subsp. turkestanica (a) and jackknife tests for evaluating the influence of environmental variables on H. rhamnoides subsp. turkestanica distribution prediction using training gain (b), test gain (c), and AUC (d).
Figure 3. Reliability test of distribution model created for H. rhamnoides subsp. turkestanica (a) and jackknife tests for evaluating the influence of environmental variables on H. rhamnoides subsp. turkestanica distribution prediction using training gain (b), test gain (c), and AUC (d).
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Figure 4. Distribution of suitable areas for H. rhamnoides subsp. turkestanica under the current climate scenario.
Figure 4. Distribution of suitable areas for H. rhamnoides subsp. turkestanica under the current climate scenario.
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Figure 5. Spatial distribution map of predicted suitable habitats for H. rhamnoides subsp. turkestanica under future scenarios.
Figure 5. Spatial distribution map of predicted suitable habitats for H. rhamnoides subsp. turkestanica under future scenarios.
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Figure 6. Dynamic changes in the habitat area of H. rhamnoides subsp. turkestanica.
Figure 6. Dynamic changes in the habitat area of H. rhamnoides subsp. turkestanica.
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Figure 7. Migration of the geographical centroid of suitable habitats for H. rhamnoides subsp. turkestanica.
Figure 7. Migration of the geographical centroid of suitable habitats for H. rhamnoides subsp. turkestanica.
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Table 1. AUC values for different periods.
Table 1. AUC values for different periods.
PeriodSSP126
(Training Data)		SSP245
(Training Data)		SSP370
(Training Data)		SSP585
(Training Data)
2021–20400.9860.9860.9850.983
2041–20600.9810.9840.9820.984
2061–20800.9820.9790.9830.979
2081–21000.9830.9810.9820.981
Table 2. The contribution of each environmental variable to modelling the distribution of H. rhamnoides subsp. turkestanica with MaxEnt.
Table 2. The contribution of each environmental variable to modelling the distribution of H. rhamnoides subsp. turkestanica with MaxEnt.
VariablePercent Contribution (%)Permutation Importance
Slo35.20.8
Alt20.621.6
bio0410.714.5
bio0510.31.3
bio0310.28.1
s_bs6.57.4
bio102.40.3
bio072.42.5
bio011.643.6
Table 3. Statistical area of potentially suitable distribution zones under the current climate scenario.
Table 3. Statistical area of potentially suitable distribution zones under the current climate scenario.
Suitability ClassPredicted ValueDistribution Area/104 km2
High-suitability area0.6~165.55
Moderate-suitability area0.3~0.6293.60
Low-suitability area0.1~0.3578.87
Table 4. The area of each habitat of Hippophae rhamnoides subsp. turkestanica in different climates and periods (×104 km2).
Table 4. The area of each habitat of Hippophae rhamnoides subsp. turkestanica in different climates and periods (×104 km2).
Scenario Period Low-SuitabilityModerate-SuitabilityHigh-SuitabilityTotal Suitable
SSP1262021–2040578.18374.5096.101048.78
2041–2060599.00375.94112.641087.58
2061–2080577.03411.29121.301109.61
2081–2100556.51386.98109.181052.68
SSP2452021–2040598.37370.46106.591075.42
2041–2060628.07390.00126.681144.75
2061–2080631.13423.74128.701183.57
2081–2100686.20453.80153.021293.02
SSP3702021–2040582.96398.57109.261090.79
2041–2060637.59375.89151.731165.21
2061–2080684.66479.26206.931370.85
2081–2100742.44523.84278.701544.99
SSP5852021–2040556.38392.0090.991039.38
2041–2060605.13413.56165.481184.17
2061–2080702.70490.60235.031428.34
2081–2100687.47458.45304.561450.48
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Ma, F.; He, M.; Wang, M.; Chu, G.; Yang, Z.; Luo, C.; Zhou, M.; Hui, Y.; Ding, J. Assessing Habitat Suitability for Hippophae rhamnoides subsp. turkestanica Amid Climate Change Using the MaxEnt Model. Forests 2025, 16, 468. https://doi.org/10.3390/f16030468

AMA Style

Ma F, He M, Wang M, Chu G, Yang Z, Luo C, Zhou M, Hui Y, Ding J. Assessing Habitat Suitability for Hippophae rhamnoides subsp. turkestanica Amid Climate Change Using the MaxEnt Model. Forests. 2025; 16(3):468. https://doi.org/10.3390/f16030468

Chicago/Turabian Style

Ma, Fanyan, Mengyao He, Mei Wang, Guangming Chu, Zhen’an Yang, Cunkai Luo, Mingwang Zhou, Ying Hui, and Junjie Ding. 2025. "Assessing Habitat Suitability for Hippophae rhamnoides subsp. turkestanica Amid Climate Change Using the MaxEnt Model" Forests 16, no. 3: 468. https://doi.org/10.3390/f16030468

APA Style

Ma, F., He, M., Wang, M., Chu, G., Yang, Z., Luo, C., Zhou, M., Hui, Y., & Ding, J. (2025). Assessing Habitat Suitability for Hippophae rhamnoides subsp. turkestanica Amid Climate Change Using the MaxEnt Model. Forests, 16(3), 468. https://doi.org/10.3390/f16030468

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