
==== Front
Ecol Evol
Ecol Evol
10.1002/(ISSN)2045-7758
ECE3
Ecology and Evolution
2045-7758
John Wiley and Sons Inc. Hoboken

10.1002/ece3.70314
ECE370314
ECE-2024-04-00788.R2
Biodiversity Ecology
Conservation Ecology
Global Change Ecology
Research Article
Research Article
Potential adaptive habitats for the narrowly distributed and rare bamboo species Chimonobambusa tumidissinoda J. R. Xue & T. P. Yi ex Ohrnb. under future climate change in China
Wang et al.
Wang Wei‐Hua 1
Peng Shu‐Lei 1 2
Shu Hua 1
Fu Xi 1
Ye Xia‐Ying https://orcid.org/0000-0003-2066-945X
1 34007@ztu.edu.cn
yexiaying199056@163.com

1 Agronomy and Life Science Department Zhaotong University Zhaotong Yunnan China
2 College of Agronomy and Biotechnology Yunnan Agricultural University Kunming China
* Correspondence
Xia‐Ying Ye, Agronomy and Life Science Department, Zhaotong University, Zhaotong, Yunnan 657000, China.
Email: 34007@ztu.edu.cn and yexiaying199056@163.com

15 9 2024
9 2024
14 9 10.1002/ece3.v14.9 e7031427 8 2024
21 4 2024
03 9 2024
© 2024 The Author(s). Ecology and Evolution published by John Wiley & Sons Ltd.
https://creativecommons.org/licenses/by/4.0/ This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Abstract

The global climate change has resulted in substantial modifications to the distribution patterns of narrowly distributed species across different time periods, leading to an imminent threat to the survival of some vulnerable species. Chimonobambusa tumidissinoda J. R. Xue & T. P. Yi ex Ohrnb., a bamboo species endemic to the transition zone from the Yunnan‐Guizhou Plateau to the Sichuan Basin with high economic and ecological value, exhibits a limited range and rarity. Utilizing eight environmental variables and 56 occurrence records, we employed the MaxEnt model to predict the potential distribution range of C. tumidissinoda under current and future climate scenarios. The findings revealed that precipitation of the driest month (Bio14), elevation and isothermality (Bio3) were the crucial factors determining the species' distribution, accounting for 31.24%, 28.27% and 17.24% of data variability, respectively. The distribution centroid of C. tumidissinoda is anticipated to shift towards higher latitudes in response to future climate change, and the projected habitat suitability is expected to expand under ssp245 and ssp585 scenarios while remaining unchanged or contracting under the ssp126 scenario. Despite these expansions, the suitable habitats remain limited, with the largest being approximately 2.08 × 104 km2, indicating a significant threat to its survival. Our study provides insights into the adaptive responses of C. tumidissinoda to climate change, enriching scientific knowledge for developing effective conservation measurements as well as sustainable utilization.

Chimonobambusa tumidissinoda is a rare and narrowly distributed bamboo species, we utilized MaxEnt model to predict its potential distribution range and evaluate its vulnerability under future climate scenarios. Simulation results revealed that although the suitable area for C. tumidissinoda is projected to expand under two climate scenarios, the habitat range of this bamboo remains limited across various scenarios with precipitation and elevation being the primary influencing factors. Therefore, more emphasis should be placed on its conservation efforts.

bamboo
Chimonobambusa tumidissinoda
climate change
environmental variables
MaxEnt model
suitable habitats
Applied Basic Research Foundation of Yunnan Province 10.13039/100007471 202301AT070348 Cultivating Plan Program for the Leader in Science and Technology of Yunnan Province 10.13039/501100013047 202305AC160056 Zhaotong City Fenghuang PlanNational Natural Science Foundation of China 10.13039/501100001809 3220307 source-schema-version-number2.0
cover-dateSeptember 2024
details-of-publishers-convertorConverter:WILEY_ML3GV2_TO_JATSPMC version:6.4.8 mode:remove_FC converted:15.09.2024
Wang, W.‐H. , Peng, S.‐L. , Shu, H. , Fu, X. , & Ye, X.‐Y. (2024). Potential adaptive habitats for the narrowly distributed and rare bamboo species Chimonobambusa tumidissinoda J. R. Xue & T. P. Yi ex Ohrnb. under future climate change in China. Ecology and Evolution, 14 , e70314. 10.1002/ece3.70314
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pmc1 INTRODUCTION

The sixth assessment report of the Intergovernmental Panel on Climate Change (IPCC) highlights that the global temperature of 2011–2020 was approximately 1.1°C warmer than that of 1850–1900. And this warming trend is continuing, with projections indicating a temperature rise exceeding 1.5°C by 2100 in spite of the implementation of low‐emission technologies (IPCC, 2023). The dramatic climate change plays a crucial effect on shaping the distribution of plants and acts as one of the main drivers for habitat fragmentation and species extinction (Qiu, Fu, et al., 2023; Rong et al., 2023; Wang et al., 2024), especially for narrowly distributed and/or endangered species (Ohlemuller et al., 2008; Tang et al., 2022; Zhang et al., 2024). These impacts are becoming increasingly significant on a global scale, resulting in the loss of biodiversity and degradation of ecosystems. Therefore, it is essential to understand how these species will respond to future climate change and the probability of extinction for developing effective conservation measurements and maintaining biodiversity.

Chimonobambusa tumidissinoda J. R. Xue & T. P. Yi ex Ohrnb., commonly known as Qiongzhu or Luohanzhu, belongs to the genus Chimonobambusa of the tribe Arundinarieae (Poaceae, Bambusoideae) (Li et al., 2006). This bamboo species is a perennial herbaceous plant primarily propagated clonally through rhizomes and exhibits an extended sexual reproductive cycle (approximately 40 years, Ye et al., 2024), which may render it more susceptible to the impacts of climate change. The distribution range of C. tumidissinoda is limited, confined solely to the transition zone from the Yunnan‐Guizhou Plateau to the Sichuan Basin. As a result of this restricted distribution, it has been classified as a rare and endangered species since 1991 (Fu, 1991). This species possesses significant ecological and economic value. It is characterized by its occurrence in cloud‐shrouded hilltops at elevations ranging from 1300 to 2200 m. Moreover, it acts as an essential component of wet evergreen broadleaved forest in China (Keng & Wang, 1996). This plant is commonly utilized for handicraft production and cultivated as an ornamental plant due to its distinctive disk‐shaped nodes and elegant morphology. Since the Han Dynasty, the culms of this graceful species have been utilized as walking sticks and presented to foreign guests as prestigious gifts. However, previous study has indicated that C. tumidissinoda has undergone severe population degradation due to excessive human interference (Dong, 2006), and the plant growth could be affected by different environmental conditions, such as temperature, soil water and nutrition (Dong et al., 2002; Wu et al., 2019; Wu et al., 2020). Moreover, population genomics has revealed that this bamboo species exhibits a limited level of genetic diversity, indicating its vulnerability to future climate change (Ye et al., 2024). The findings of these aforementioned studies suggest that climate change has the potential to exacerbate its endangerment status, necessitating efforts to elucidate its future distribution trend. Currently, research on C. tumidissinoda mostly focus on its bamboo shoots (Wang et al., 2023; Yang et al., 2015; Yuan et al., 2008), genetic structure and diversity (Dong et al., 2016; Qiu et al., 2017; Ru et al., 2010; Ye et al., 2024), gene cloning and expression (Dai et al., 2023; Gao et al., 2021; Li et al., 2021), and physiological and community characteristics (Jia & Wang, 2021; Wang et al., 2012; Zhang et al., 2020; Zheng et al., 2021; Zhong et al., 2023). The research on the geographic distribution of this species under future environmental conditions remains insufficient.

With the rapid development of spatial distribution technology, species distribution models (SDM) are widely used to predict potential geographic ranges of species under current or future environmental scenarios based on their geographic distribution information (Guisan & Zimmermann, 2000; Vasconcelos et al., 2011). The prediction can provide valuable insights for assessing the ecological crisis and serve as a fundamental basis for biodiversity conservation. Among various SDM methods, the maximum entropy (MaxEnt) modeling stands out due to its exceptional performance and widespread utilization (Elith et al., 2006; Phillips et al., 2006). It employs a machine‐learning approach with presence‐only records to evaluate the potential distribution range of species. Furthermore, it exhibits superior accuracy compared to other SDM tools and have a better performance even when confronted with limited geographic distribution information (Elith et al., 2006; Phillips et al., 2006; Shi et al., 2023). In recent decades, the MaxEnt model has been extensively applied in the prevention of the invasion of alien species (Blackburn et al., 2020; McCulloch‐Jones et al., 2023; Tu et al., 2021), the protection of rare and endangered species (Gao et al., 2022; Tang et al., 2022; Zhang et al., 2023), the management of diseases and pests (Rawien & Jairam‐Doerga, 2022; Zhou et al., 2021), the evaluation of protected areas (Li et al., 2023; Thapa et al., 2018), etc.

In this study, we employed the MaxEnt model to evaluate the potential suitable areas for C. tumidissinoda in China under current and six future climate scenarios, based on its geographic distribution records along with bioclimate, topography and soil factors. Our objectives encompass: (1) identifying the predominant environmental factors influencing the distribution of C. tumidissinoda in China; (2) predicting the suitable distribution range of C. tumidissinoda in China across different time periods and climate scenarios; (3) elucidating the temporal dynamics of the potential suitable areas for C. tumidissinoda from present to future. This research provides invaluable insights for scientific exploration and conservation efforts for this narrowly distributed and rare bamboo species, C. tumidissinoda.

2 MATERIALS AND METHODS

2.1 Species distribution data and processing

The geographic distribution records of C. tumidissinoda were mainly obtained from two sources: (1) our field survey between 2020 and 2023 covering its distribution range and (2) specimen records from the Chinese Virtual Herbarium database (CVH: https://www.cvh.ac.cn/), the Global Biodiversity Information Facility (GBIF; https://www.gbif.org), the National Specimen Information Infrastructure (NSII: https://www.nsii.org.cn/), and published literature (Dong et al., 2016). The records were filtered to exclude those with duplicate coordinates, obvious identification errors, and unreliable distribution beyond its designated range. For records lacking geo‐coordinates but having specific locations, Baidu map was utilized to estimate approximate coordinates based on the geographic information provided in the specimen.

To reduce the impact of spatial autocorrelation, we employed SDM Toolbox v2.5 (Brown, 2014) in ArcGIS 10.7 to establish a buffer zone with a grid size 1 × 1 km (30 s), which is consistent with the resolution of bioclimatic variables utilized in this study. Subsequently, only one occurrence point was retained within each grid cell. Following filtering procedures, we obtained a final dataset consisting of 56 distribution records (Figure 1; Table S1). To meet the requirements of MaxEnt software, we stored the occurrence records in Excel and converted them into “.csv” format for future modeling.

FIGURE 1 The study area and sampling records of Chimonobambusa tumidissinoda.

2.2 Environmental variables and processing

We selected bioclimate, topography and soil factors to simulate the distribution pattern of C. tumidissinoda under current and future climate scenarios. We downloaded 19 bioclimate variables of near‐current (1970–2000) and two future periods (2041–2060/2050s and 2080–2100/2090s) from the WorldClim v2.1 (https://worldclim.org/) at a 30 arc‐second resolution (approximately 1 km2) (Fick & Hijmans, 2017). The future climate data were generated based on the BCC‐CSM2‐MR (Beijing Climate Center Climate System Model) climate system derived from the Coupled Model Intercomparison Project 6 (CMIP6). To provide a comprehensive comparison, three Shared Socioeconomic Pathways (SSPs) were selected for the future time periods: ssp126 (low forcing scenario with radiative forcing reaches 2.6 W/m2 in 2100), ssp245 (medium forcing scenario with 4.5 W/m2) and ssp585 (high forcing scenario with 8.5 W/m2). Subsequently, we acquired the elevation data from the Geospatial Information Authority of Japan (https://globalmaps.github.io/el.html). Slope and aspect were extracted from the elevation data in ArcGIS 10.7. Soil factors were obtained from the Harmonized World Soil Database v2.0 (https://www.fao.org/soils‐portal/). It assumed that both topographic and soil factors remained constant throughout the future period. All environmental variables layers were resampled uniformly at a resolution of 30 arc‐second and rasterized to match the same boundaries, cell size and coordinate systems as the occurrence data layer.

In order to address the issue of multicollinearity among variables and reduce model overfitting, we conducted a correlation analysis using Pearson's method on the 56 environmental factors. Firstly, bioclimatic factors with a contribution percentage greater than 1.0% (Qiu, Jacquemyn, et al., 2023) were identified through the pre‐simulation of all environmental factors in MaxEnt v3.4.4. Secondly, if the pairs of selected environmental variables exhibited an absolute Pearson's r value exceeding 0.8, the factor with a higher percent contribution was chosen. Finally, eight environmental factors were included in the further ecological niche modeling (Table 1).

TABLE 1 Environmental variables ultimately involved in MaxEnt modeling.

Category	Variable	Description	Unit	
Climate	Bio3	Isothermality (BIO2/BIO7) (×100)	%	
Bio7	Temperature Annual Range (BIO5‐BIO6)	°C	
Bio14	Precipitation of Driest Month	mm	
Bio18	Precipitation of Warmest Quarter	mm	
Topography	Elevation	Elevation	m	
Slope	Slope	°	
Soil	Alum_sat	Aluminum saturation	%	
Gypsum	Gypsum content	%	

2.3 MaxEnt modeling and evaluating

The potential spatial distributions of C. tumidissinoda were simulated using MaxEnt v3.4.4 based on 56 effective occurrence records and selected environmental variables. In this study, a random test percentage of 25% was used to verify the model's performance, while the remaining served as the training data. The regularization multiplier was set to 1, and the feature combination was automatically determined. We conducted 10 replicates of training to minimize the impact of random aberrations. Additionally, we utilized the jackknife method with options for “create response curves” and “Do jackknife” to assess the relative significance of each environmental factor. The final results were calculated from the average of 10 replicates and exported in ASCII format.

The accuracy of the simulated distribution models was evaluated based on the Area Under Receiver‐Operating Characteristic Curve (AUC) (Radosavljevic & Anderson, 2013). AUC values ranged from 0 to 1, with higher values indicating greater confidence in the prediction results. The category of AUC values are usually as follows: failed (AUC ≤0.6), poor (0.6 < AUC ≤ 0.7), fair (0.7 < AUC ≤ 0.8), good (0.8 < AUC ≤ 0.9), and excellent (0.9 < AUC ≤1) (Swets, 1988).

2.4 Classification of suitable areas

To determine the suitable and unsuitable regions of C. tumidissinoda, the resulting file was imported into ArcGIS 10.7 software and reclassified based on the 10‐percentile training presence logistic threshold value (TH) output by MaxEnt (Hughes, 2017; Radosavljevic & Anderson, 2013). According to the average TH value and the classification criteria outlined by IPCC (Mastrandrea et al., 2010), we categorized the potential distribution areas into three distinct groups based on their suitability levels (the Habitat Suitability Index, HSI): unsuitable area (HIS < TH), moderately suitable area (TH < HSI < 0.66), and highly suitable area (HIS ≥0.66), as previously employed in relevant studies (Qiu, Jacquemyn, et al., 2023; Shi et al., 2021; Yan, Gu, et al., 2021).

2.5 Species potential distribution change and centroid shifts

We utilized ArcGIS 10.7 to calculate the area of suitable habitat for C. tumidissinoda across different climate periods. Furthermore, the trend of changes in suitable habitat under various emission scenarios was assessed in comparison to the current condition. The contraction, expansion, and unchanged areas were determined using the “distribution changes between binary SDMs” tool from the SDM Toolbox v2.5 (Brown, 2014). Subsequently, we predicted the centroid location of the distribution area and identified the direction of shift between the current period and future climate scenarios (ssp126, ssp245 and ssp585 of 2050s and 2090s, respectively) using the “centroid changes clines” tool.

3 RESULTS

3.1 Model accuracy and potential current habitat distribution

The average AUC values for all models of C. tumidissinoda ranged from 0.991 to 0.995 (Table 2), indicating exceptional model performance. The projected suitable area for C. tumidissinoda under the current climate scenario closely aligns with its existing physical distribution, with only 3.57% of occurrence records found in unsuitable area (Figure 2). The predominant concentration of these suitable habitats is primarily located in Zhaotong, Yunnan province and its adjacent area in Sichuan and Guizhou province, encompassing a relatively small range of 1.13 × 104 km2 (Table 3). Within the suitable area, the proportion of highly suitable area only accounts for 18.58%, indicating a scarcity of areas that provide optimal conditions for C. tumidissinoda.

TABLE 2 AUC mean value of the simulated model of Chimonobambusa tumidissinoda under current and six future climate scenarios.

	Current	2050s	2090s	
ssp126	ssp245	ssp585	ssp126	ssp245	ssp585	
AUC	0.995	0.994	0.991	0.994	0.995	0.993	0.994	

FIGURE 2 Potential distribution habitats for Chimonobambusa tumidissinoda under current climate scenario.

TABLE 3 Area (×104 km2) and proportion (%) of suitable habitats for Chimonobambusa tumidissima under current and future climate scenarios.

Period	Moderately suitable are (%)	Highly suitable area (%)	Total suitable area (%)	Unsuitable area (%)	
Current (1970–2000)	0.92 (0.49)	0.21 (0.11)	1.13 (0.60)	187.80 (99.40)	
ssp126_2050s	0.98 (0.52)	0.16 (0.08)	1.14 (0.60)	187.79 (99.40)	
ssp245_2050s	1.82 (0.96)	0.26 (0.14)	2.08 (1.10)	186.86 (98.90)	
ssp585_2050s	1.03 (0.55)	0.26 (0.14)	1.29 (0.68)	187.65 (99.32)	
ssp126_2090s	0.82 (0.43)	0.22 (0.12)	1.04 (0.55)	187.90 (99.45)	
ssp245_2090s	1.10 (0.58)	0.21 (0.11)	1.31 (0.69)	187.62 (99.30)	
ssp585_2090s	1.08 (0.57)	0.26 (0.14)	1.34 (0.71)	187.59 (99.30)	

3.2 Key environmental factors affecting the distribution of C. Tumidissinoda

Based on the percentage contribution of environmental variables generated by the MaxEnt model (Figure 3), the geographic distribution of C. tumidissinoda is primarily determined by precipitation of driest month (Bio14, averaging 31.24%) and elevation (averaging 28.27%), followed by isothermality (Bio3, averaging 17.24%), which collectively account for approximately 77% of the predictive power of the model. The distribution of this bamboo species is also influenced by two other bioclimate factors (Bio7 and Bio18), which contribute approximately 20% in total. However, the proportion of these factors varies across different scenarios (Figure 3).

FIGURE 3 Contribution percentage of selected environmental variables on the distribution of Chimonobambusa tumidissima.

The response curves of key environmental factors can provide valuable insights into the relationship between the predicted occurrence probability and environmental variables, thereby elucidating the influence of each variable on the distribution pattern of C. tumidissinoda. The environmental factors are typically deemed conducive to plant growth when their probability of existence exceeds 0.5 (Fang et al., 2024; Yan, Wang, et al., 2021). The red lines depicted in Figure 4 illustrate the isolated impact of specific environmental factors on the projected probability of occurrence. Specifically, precise thresholds are necessary for the suitable distribution of C. tumidissinoda, including an elevation range of 1343−1907 m, an isothermality range of 27.69%–32.35%, and a precipitation range of 11.80–15.23 mm during the driest month (Figure 4).

FIGURE 4 Response curves of key environmental variables based on individual variables. The red line represents the mean value, and the gray area indicates the range between the minimum and maximum values.

3.3 Potential adaptive habitats of C. Tumidissinoda under future climate scenarios

The potential adaptive range of C. tumidissinoda under future climate scenarios (ssp126, ssp245 and ssp585) for the 2050s (2041–2060) and 2090s (2080–2100) was predicted in this study. The suitable habitat for C. tumidissinoda continues to primarily concentrate in Zhaotong, Yunnan province, and its adjacent regions with some variations compared to the current scenario (Figure 5).

FIGURE 5 Potential suitable areas for Chimonobambusa tumidissima under future climate scenarios. The 2050s represents 2040–2060s period and the 2090s represents 2080–2100 s period.

Under the scenario of ssp126, the total suitable areas for C. tumidissinoda show limited changes, with only a 100 km2 expansion projected in the 2050s (Table 3). However, there is an observed degradation of highly suitable areas into moderately suitable ones at a rate of 23.81%, indicating a loss of preferred habitat of this bamboo species within this timeframe. In the 2090s, both the moderately suitable and total suitable areas experience reductions, with a slight decrease of 1.6 × 103 km2 (16.33%) and 1.0 × 103 km2 (8.77%), respectively, compared to the period in the 2050s.

Under the scenario of ssp245, there is a substantial growth of 9.5 × 103 km2 (84.07%) in the total extent of suitable areas by 2050s compared to the current size, with nearly a doubling rise (197.83%) of moderately suitable areas and an expansion of highly suitable areas to 2.6 × 103 km2 (123.81%) (Table 3). In contrast, during the 2090s, the total suitable area contracts to only 62.98% of its previous region in the 2050s, with both highly suitable areas and moderately suitable areas experiencing notable contractions. When compared to its current size, there is an expansion of approximately 19.57% in the overall extent of suitable areas.

Under the scenario of ssp585, the total habitat suitable for C. tumidissinoda shows a gradual expansion over time, reaching 114.16% of its current size by the 2050s and further increasing to 118.58% by the 2090s (Table 3). In terms of the highly suitable areas, they expand to cover an area of 2.6 × 103 km2 (123.81%) in the 2050s and maintain stability thereafter. The moderately suitable areas exhibit a gradual increase over time as the total suitable areas, with their size reaching 111.96% by the 2050s and expanding further to 117.39% by the 2090s compared to their current size.

3.4 Range changes between current and future climate scenarios

The potential distribution shifts of C. tumidissinoda are illustrated in Figure 6. The most significant contraction of suitable areas mainly occurs in Guizhou province under the ssp126 scenario of the 2090s (3686 km2, Figure 7). The stable area, predominantly encompassing Zhaotong in Yunnan province, continues to present the largest proportion of distribution areas and exhibits a significant stability under the ssp245 scenario in the 2050s (11,573 km2). The expansion of distribution mainly occurs in the northwestern region of Guizhou, the central part of Sichuan and the junction zone of Sichuan, Shaanxi and Chongqing. The most significant expansion is observed during the ssp245 scenario in the 2050s period (Figure 6).

FIGURE 6 Potential habitat changes of Chimonobambusa tumidissima from current to future climate scenarios.

FIGURE 7 Changes of suitable habitat areas of Chimonobambusa tumidissima from current to future climate scenarios. Red represents potential range expansion, blue represents potential range contraction, and green represents the overlap of current and future projected ranges.

The current distribution center is situated at the border of Weixin in Yunnan province and Xuyong in Sichuan province (104°55′03.88″ E, 28°9′39.88″ N). With the progression of time and the intensification of climate conditions (from ssp126 to ssp585), the centroid of the suitable area is observed to be shifting towards the northeast compared to its current location (Figure 8). According to projections based on the ssp126 scenario, it is anticipated that the distribution center will migrate approximately 54.98 and 85.48 km by the 2050s and 2090s, respectively. A more substantial displacement is observed under the ssp245 scenario, with an estimated shift of around 123.94 km and 121.26 km compared to its current position. Under the ssp585 scenario, it is expected that there will be a northward migration of about 98.48 km by the 2050s and a shift of approximately 44.28 km towards northeast by the 2090s.

FIGURE 8 Shift of distribution centroid of Chimonobambusa tumidissima from current to future climate scenarios.

4 DISCUSSION

4.1 Environmental variables determining the distribution of C. Tumidissinoda

C. tumidissinoda, a dominant species found in the subalpine zone transitioning from Yunnan‐Guizhou Plateau to Sichuan Basin, typically exhibits a preference for mild and humid environmental conditions. The jackknife method elucidates that the distribution of C. tumidissinoda is minimally influenced by soil and slope, but predominantly affected by Bio14 (31.24%), elevation (28.27%), and Bio3 (17.24%), which are concordant with its specific habitat requirements. Li et al. (2019) reported that precipitation plays a pivotal role in determining the distribution of bamboo forests, followed closely by temperature. Additionally, Zhao et al. (2023) revealed that precipitation and temperature are crucial factors in the germination and development of bamboo shoots of Bashania fargesii, which serves as a primary food source for giant panda. It is worth noting that when the precipitation of the driest month (Bio14) falls below 7 mm, C. tumidissinoda is unable to survive. We have observed that both the germination process and rapid growth of C. tumidissinoda bamboo shoots coincide with the onset of the rainy season, indicating a highly sensitivity to precipitation conditions in its growth processes, similar to other bamboo species (Hu & He, 2020; Li et al., 2019; Zhao et al., 2023). Simultaneously, the growth of C. tumidissinoda is also susceptible to temperature and requires a narrow range for optimal development, characterized by an isothermality (Bio3) ranging from 27.69% to 32.35%. This indicates that significant fluctuations in temperature could have detrimental effects on its growth, consistent with the findings from study on tropical bamboo Dendrocalamus sinicus (Dou et al., 2022). Dong et al. (2002) have observed that the daily increase of C. tumidissinoda bamboo height is positively correlated with the daily mean temperature, further verifying that temperature is also a main factor affecting the rapid growth of this bamboo species.

Previous researches have demonstrated that elevation plays a crucial role in shaping the distribution patterns of montane plants (Du et al., 2024; Hu & He, 2020; Huan et al., 2023; Qiu, Fu, et al., 2023). Our simulation results further validate this relationship by confirming that elevation (28.27%) is one of the critical factors determining the distribution pattern of this particular bamboo species, similar to the bamboo species found in the Hengduan mountains (Hu & He, 2020). And the optimal altitude range for plant growth of C. tumidissinoda is observed between 1341 and 1905 m, which corresponds with its subalpine adaptive habitat.

4.2 Distribution range shift for C. Tumidissinoda

By employing the MaxEnt model, we successfully delineated the suitable habitat for C. tumidissinoda in Zhaotong, Yunnan province and its surrounding areas under prevailing climatic conditions. Previous studies have documented a tendency of montane plants to migrate towards higher latitudes in response to climate change (He, Burgess, Gao, & Li, 2019; Liang et al., 2018). The findings of this investigation revealed a similar phenomenon. The results indicate that within our research zone, the current distribution range of C. tumidissinoda spans from 27° N to 29° N, with its centroid located at latitude 28°9′39.88″ N. Under future climate scenarios, it is projected that there will be a shift towards northeast in the range of C. tumidissinoda. The estimated migration distance ranges from 44.28 to 123.94 km, with latitudes spanning from 28°26′50.44″ N to 29°4′6.06″ N. Historical demographical analyses have suggested that a cold and arid climate may contribute to the population decline of C. tumidissinoda (Ye et al., 2024). Regions with higher latitudes can potentially drive the geographical shift of this bamboo species by providing more humid and warmer climate conditions (Chen et al., 2011). Similarly, projections for alpine bamboo Bashania fargesii (Zhao et al., 2023) in the Qinling Mountains and African bamboo Oxytenanthera abyssinica (Gebrewahid et al., 2020) in Ethiopia also presented a shift towards higher latitudes. And this tendency has also been observed in other plant species such as Dactylorhiza hatagirea (Singh et al., 2022), Meconopsis (He, Burgess, Yang, et al., 2019), Habenaria (Qiu, Jacquemyn, et al., 2023) and Senegalia senegal (Fang et al., 2024).

Moreover, the adaptability of this bamboo species to future environments is expected to be higher under both moderate and pessimistic climate scenarios, with a significant potential for expansion ranging from 14.16% to 84.07%. Specifically, C. tumidissinoda is projected to colonize new habitats in the central region of Sichuan province and at the junction of Sichuan, Shaanxi and Chongqing under future climate scenarios, particularly during the ssp245 period of the 2050s (Figure 6). The increase in global temperature of this scenario may lead to a more humid climate, which could account for the expansion of C. tumidissinoda into these new habitats. Furthermore, bamboo species typically propagate through rhizomes and exhibit a robust capacity for asexual reproduction. Once established in a particular area, it possesses the potential to become a dominant species. This phenomenon could be attributed as an important factor contributing to its future expansion under changing climatic conditions. However, the suitable area of this bamboo will decrease by 7.96% under an optimistic climate change scenario of the 2090s, contrasting with its current size. This implies that extreme climate change does not necessarily lead to a reduction in the range of suitable areas and different species have varying ability to adapt to climate change. For example, Fang et al. (2024) reported that the suitable zone of Senegalia senegal will increase significantly under the pessimistic climate scenario when compared to other more optimistic scenarios. Wang et al. (2024) found that the potential suitable area of relict plant Davidia involucrate decreased under the ssp126 and ssp585 scenarios but increased under the ssp370 climate scenario (2070s). Therefore, the resilience to extreme climate change for different species needs to be analyzed case‐by‐case.

4.3 Suggestions for conservation and introduction strategies

Although there is an expansion of suitable area for C. tumidissinoda under future moderate and pessimistic climate scenarios, the total suitable habitats remain limited (ranging from 1.29 to 2.08 × 104 km2), and are primarily concentrated in Zhaotong and adjacent areas. Population genomics analysis revealed that C. tumidissinoda exhibits a low level of genetic diversity (H O  = 0.085, H E  = 0.115, π = 0.116) and may have limited adaptability to future climate change (Ye et al., 2024). Furthermore, apart from the environmental factors considered in this study such as bioclimate, topography and soil properties, numerous interactive factors including human activities and physiological properties could potentially influence the growth of C. tumidissinoda as well. Given the increasing attention towards healthy eating habits and the growing popularity of green foods like bamboo shoots among people today, it is important to consider how human activities might impact the distribution of C. tumidissinoda. Additionally, the blooming of C. tumidissinoda can lead to plant mortality (Janzen, 1976), posing a further threat to its survival. Therefore, it is imperative to develop conservation strategies, and the regions currently exhibiting suitability for C. tumidissinoda and overlapping with the existing area can serve as in situ conservation sites. In these future scenarios, the central region of Sichuan province and the junction area of Sichuan, Shaanxi and Chongqing have emerged as newly identified highly suitable areas. However, due to limited dispersal capacity and fragmentation of these regions, natural colonization by C. tumidissinoda is unlikely and transplantation of individuals into these areas would be optimal. Based on the MaxEnt results, the southeast of Sichuan and northwest of Guizhou are predicted to be at high risk of disappearing in the future. Therefore, it is crucial to pay more attention to these areas and germplasm resources should be collected to avoid the loss of rare genes in these populations.

In addition, C. tumidissinoda has a high economic value for its elegant form and can be cultivated as ornamental plants. But unregulated introduction may lead to unsuccessful cultivation attempts. The distribution map presented in this study, which illustrates the suitable areas and crucial environmental factors for both current and future scenarios of C. tumidissinoda, can facilitate its controlled introduction and assist in urban cultivation planning. Specifically, the newly identified suitable habitats of C. tumidissinoda can be prioritized for introduction and cultivation.

5 CONCLUSION

In this study, we employed the MaxEnt model to predict the suitable areas of C. tumidissinoda under current and varying future climate scenarios. The precipitation of the driest month (Bio14), elevation and isothermality (Bio3) were identified as crucial environmental factors influencing the species' distribution. Under current conditions, only 0.6% of the research area exhibited suitability for its occurrence. Furthermore, significant disparities were observed in the species' responses to different climate changes. The projected habitat suitability for C. tumidissinoda is anticipated to contract or remain unchanged in the optimistic climate change scenario but expand in moderate and pessimistic climate scenarios. In response to future climate change, the potential range of C. tumidissinoda is projected to shift towards higher latitude and fragmented regions, such as central Sichuan and the junction region of Sichuan, Shaanxi and Chongqing. Furthermore, there will be a northeastward shift in the distribution centroid. Based on these distribution dynamics, regions that maintain their suitability from current to future climate scenarios may be serve as valuable climate refugia for C. tumidissinoda and should be prioritized for in situ conservation efforts. Meanwhile, the newly identified habitats can be utilized as ex situ conservation sites for introduction and cultivation. In conclusion, our findings establish a foundation for evaluating the adaptability of C. tumidissinoda to climate change, as well as for formulating effective strategies for conservation and sustainable utilization.

AUTHOR CONTRIBUTIONS

Wei‐Hua Wang: Formal analysis (lead); methodology (equal); writing – original draft (lead). Shu‐Lei Peng: Methodology (equal); software (equal). Hua Shu: Investigation (lead); software (equal). Xi Fu: Data curation (lead). Xia‐Ying Ye: Funding acquisition (lead); supervision (lead); writing – original draft (supporting); writing – review and editing (lead).

CONFLICT OF INTEREST STATEMENT

The authors declare no conflicts of interest.

Supporting information

Table S1: Occurrence records of Chimonobambusa tumidissinoda utilized in this study.

ACKNOWLEDGMENTS

We are grateful to Li Qiu from Nanchang University for her invaluable technical supports. This research was funded by Cultivating Plan Program for the Leader in Science and Technology of Yunnan Province, grant number 202305 AC160056, the National Natural Science Foundation of China, grant number 3220307, the Applied Basic Research Foundation of Yunnan Province, grant number 202301AT070348 and Zhaotong City Fenghuang Plan.

DATA AVAILABILITY STATEMENT

All necessary data have already been provided in the main text and supporting information.
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