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Article

Evaluating the Impact of Climate Change on the Asia Habitat Suitability of Troides helena Using the MaxEnt Model

by
Fengrong Yang
1,†,
Quanwei Liu
1,†,
Junyi Yang
1,
Biyu Liu
1,
Xinqi Deng
1,
Tingjiang Gan
2,
Xue Liao
1,
Xiushan Li
1,
Danping Xu
1 and
Zhihang Zhuo
1,*
1
College of Life Science, China West Normal University, Nanchong 637002, China
2
Engineering Research Centre of Chuanxibei Rural Human Settlement (RHS) Construction, Mianyang Teachers’ College, Mianyang 621016, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Insects 2025, 16(1), 79; https://doi.org/10.3390/insects16010079
Submission received: 20 November 2024 / Revised: 10 January 2025 / Accepted: 13 January 2025 / Published: 14 January 2025
(This article belongs to the Section Insect Ecology, Diversity and Conservation)
Browse Figures
Figure 1
<p>Evaluation of the modeling results for <span class="html-italic">T. helena</span> using the ROC curve and AUC.</p> "> Figure 2
<p>Variable importance, as determined via the folding jackknife test, for <span class="html-italic">T. helena</span>.</p> "> Figure 3
<p>Potential distribution and occurrence records of <span class="html-italic">T. helena</span> under current climate conditions. The red triangles represent the occurrence records of <span class="html-italic">T. helena</span>.</p> "> Figure 4
<p>Potential distribution of <span class="html-italic">T. helena</span> in future periods (2050s, 2090s) under the SSP1-2.6, SSP2-4.5, and SSP5-8.5 climate change scenarios. (<b>A</b>) represents the potential suitable habitat under the SSP1-2.6 scenario in the 2050s, (<b>B</b>) represents the potential suitable habitat under the SSP2-4.5 scenario in the 2050s, (<b>C</b>) represents the potential suitable habitat under the SSP5-8.5 scenario in the 2050s, (<b>D</b>) represents the potential suitable habitat under the SSP1-2.6 scenario in the 2090s, (<b>E</b>) represents the potential suitable habitat under the SSP2-4.5 scenario in the 2090s, and (<b>F</b>) represents the potential suitable habitat under the SSP5-8.5 scenario in the 2090s.</p> "> Figure 5
<p>Changes in the High Suitability Habitat of <span class="html-italic">T. helena</span> from the Present to the Future; “Gain” indicates areas where high suitability habitats have increased, “Lost” indicates areas where high suitability habitats have decreased, “Abs” indicates the area where non-high suitability habitats (unsuitable, low, and medium suitability) remain unchanged, and “Pres” indicates the area where high suitability habitats remain unchanged. (<b>A</b>) represents the changes in potential suitable habitat from the current scenario to the SSP1-2.6 scenario in the 2050s, (<b>B</b>) represents the changes in potential suitable habitat from the current scenario to the SSP2-4.5 scenario in the 2050s, (<b>C</b>) represents the changes in potential suitable habitat from the current scenario to the SSP5-8.5 scenario in the 2050s, (<b>D</b>) represents the changes in potential suitable habitat from the current scenario to the SSP1-2.6 scenario in the 2090s, (<b>E</b>) represents the changes in potential suitable habitat from the current scenario to the SSP2-4.5 scenario in the 2090s, and (<b>F</b>) represents the changes in potential suitable habitat from the current scenario to the SSP5-8.5 scenario in the 2090s.</p> "> Figure 6
<p>Response curves of <span class="html-italic">T. helena</span> to the five dominant environmental variables. The blue area represents the range of occurrence probability, while the red curve represents the average occurrence probability.</p> ">
Versions Notes

Simple Summary
Troides helena, a species within the Papilionidae family and Troides genus, was an endangered tropical butterfly in urgent need of conservation. The MaxEnt model was used to predict its global distribution, aiming to assess suitable future conservation measures. The results indicated that T. helena was primarily distributed in tropical regions, and its distribution range was projected to expand in the future. This study evaluated the distribution of T. helena, provided conservation recommendations, and offered guidance for future conservation efforts.
Abstract
Butterflies are highly sensitive to climate change, and Troides helena, as an endangered butterfly species, is also affected by these changes. To enhance the conservation of T. helena and effectively plan its protected areas, it is crucial to understand the potential impacts of climate change on its distribution. This study utilized a MaxEnt model in combination with ArcGIS technology to predict the global potential suitable habitats of T. helena under current and future climate conditions, using the species’ distribution data and relevant environmental variables. The results indicated that the MaxEnt model provided a good prediction accuracy for the distribution of T. helena. Under the current climate scenario, the species is primarily distributed in tropical regions, with high suitability areas concentrated in tropical rainforest climates. In future climate scenarios, the suitable habitat areas for T. helena in medium and high suitability categories generally show an expansion trend, which increases over time. Especially under the SSP5-8.5 scenario, by the 2090s, the area of high suitability for T. helena is projected to increase by 42.85%. The analysis of key environmental factors revealed that precipitation of the wettest quarter (Bio16) was the most significant environmental factor affecting the distribution of T. helena. The species has high demands for precipitation and temperature and can adapt to future climate warming. This study is valuable for identifying the optimal conservation areas for T. helena and provides a reference for future conservation efforts.

1. Introduction

Global climate warming has become a proven fact, which has had a significant impact on the survival of biological communities [1,2] and has also altered the distribution range of species [3]. These impacts are generally negative, leading to a sharp decline in species distribution [4]. Studies have shown that the impact of climate change on the distribution of insects is significantly higher than that on other species [5,6]. Insects account for 76% to 98% of the global animal biomass [7], making them one of the most diverse and widely distributed animals in the biosphere, and they play an important role in ecosystem functions and services [8]. Like most species, insect biodiversity has decreased under climate influence [9], and their distribution range has been compressed. However, in certain regions, insect biomass has increased with the accumulation of heat [10]. As a type of insect, butterflies, due to their high sensitivity to environmental changes, are considered ecological indicator species [11], often used to monitor ecosystem health. The biodiversity of butterflies is also influenced by various environmental factors, and it has been confirmed that climate factors, particularly temperature and precipitation, are the main influences [12,13]. Although climate change has some harmful effects on tropical butterflies, they can adapt to temperature changes by regulating themselves [14]; therefore, tropical butterflies may exhibit different responses to environmental changes. Troides helena, belonging to the genus Troides in the family Papilionidae, is primarily distributed in tropical regions, with its larvae feeding on plants in the Aristolochiaceae family [15]. The adult butterfly plays a role in pollination, contributing to the genetic diversity of plants [16]. T. helena has strict habitat requirements, particularly being sensitive to microclimatic conditions and vegetation cover. Its population and distribution changes often reflect fluctuations in environmental quality [17,18]. It is listed as a nationally protected species of Level II in the “National List of Key Protected Wild Animals”. In the face of the threats posed by climate change, the conservation of endangered butterfly species, such as T. helena, is essential. Studying the impact of climate change on the distribution range of T. helena contributes to its conservation efforts, which not only helps maintain species diversity but also benefits the health of habitat ecosystems.
In the conservation of species’ habitats, evaluating the suitable habitat areas based on environmental variables is of great significance [19]. Currently, species distribution models (SDMs) are widely used in ecology and conservation biology to study species distribution [20]. These models predict potential distribution areas by analyzing the relationship between species’ geographic distribution data and environmental variables [21]. SDMs include various methods, with the MaxEnt model being the most widely used [22]. It can be applied in fields such as biodiversity, invasive species management, species conservation, and protected area planning and management [23]. The MaxEnt model was first proposed in 2004 [24], and it is based on the maximum entropy principle. It estimates the ecological requirements of a species and simulates its potential distribution using species presence data and environmental variables [25]. Due to its advantages, such as low data requirements, high prediction accuracy, and ease of use, it has stood out among many species distribution models and has been widely applied [26,27]. Previously, the MaxEnt model has been extensively used in the conservation of Lepidoptera species. For example, Hernández-Baz et al. used the model to predict the potential geographic distribution of the Mexican endemic moth Coreura albicosta [28]. Pilar Fernández et al. utilized the MaxEnt model to predict that the overwintering habitats of the monarch butterfly in coastal California might shift to higher altitudes due to climate change [29]. Such studies not only provide scientific evidence for species conservation but also demonstrate the advantages of the MaxEnt model in addressing complex environmental changes. Today, the MaxEnt model has become an indispensable tool in the fields of ecology and conservation biology. Using the MaxEnt model to study species distributions helps understand and protect biodiversity, holding significant scientific and practical value.
Current research on T. helena mainly focuses on material characteristics [30,31], with limited studies on its distribution [15]. Furthermore, there is a need for further research on the adaptability of T. helena’s habitat, which has restricted the conservation efforts for this species to some extent. This study employed the MaxEnt model and ArcGIS v 10.8 software to predict the potential geographical distribution of T. helena globally, assess the impact of various environmental parameters on its distribution, explore the suitability of current and future habitats, and analyze the relationship between environmental variables and the species, in order to identify key conservation areas for T. helena. The aim was to provide a scientific theoretical foundation for future conservation efforts for T. helena.

2. Materials and Methods

2.1. Species Distribution Data

The establishment of the MaxEnt model requires that accurate and sufficiently abundant distribution point data be available. The distribution point data used in this study were obtained from the following three sources: (1) the Global Biodiversity Information Facility (GBIF Occurrence Download https://doi.org/10.15468/dl.xw4wnb, accessed on 8 August 2024); (2) the National Animal Specimen Resource Center (http://museum.ioz.ac.cn/, accessed on 8 August 2024); and (3) by searching relevant literature using “Troides helena” as a search term in CNKI (https://www.cnki.net/, 8 August 2024) and Web of Science (https://www.webofscience.com/wos/, accessed on 8 August 2024), from which distribution records of T. helena were obtained. The coordinates were then obtained through Google Maps (https://maps.google.com/, accessed on 8 August 2024). After obtaining the coordinates, to reduce the impact of data redundancy between the coordinate points, spatial filtering was applied to the coordinates using ENMTools v 1.4. Only one data point was retained in each minimum grid (4.5 × 4.5 km) [32]. A total of 514 distribution point data for the species were obtained.

2.2. Selection of Environmental Variables

A total of 22 environmental variables were selected in this study (Table S1). Among them, 19 bioclimatic variables were obtained from the WorldClim 2.1 dataset (http://www.worldclim.org/, accessed on 8 August 2024), which was constructed based on the Coupled Model Intercomparison Project 6 (CMIP6) of the IPCC’s Sixth Assessment Report, and 3 topographic variables were obtained from the National Centers for Environmental Information (NCEI, https://www.ngdc.noaa.gov/, accessed on 8 August 2024). All variables were selected based on the version released in 2023. This study selected three scenarios for modeling: the sustainable development scenario (SSP1-2.6), the moderate scenario that maintains development with no changes (SSP2-4.5), and the high greenhouse gas emission scenario with no control measures (SSP5-8.5) [33]. Not all environmental variables were used in the model construction, as an excessive number of variables could lead to issues such as multicollinearity, overfitting, and reduced interpretability. A Pearson correlation analysis was performed on the 22 selected environmental variables (Table S2), and variables with correlation coefficients (r) < |0.7| were selected [34]. Ultimately, 7 environmental variables were retained (Table 1).

2.3. Model Optimization

To improve the accuracy of model predictions, we adjusted two parameters: the regularization multiplier (RM) and feature combination (FC) [35,36]. First, the distribution point data and related environmental variables for T. helena were selected. Then, 25% of the data were randomly assigned as a test set, with the remaining 75% used as the training set. The RM and FC parameters were adjusted using the R package kuenm. Five feature combinations (FC) and corresponding regularization multipliers (RM) were set, generating five candidate models. These models were tested using the kuenm package, and the best model was selected based on the following two criteria: omission rate (OR) < 5% and Delta AICc (Akaike Information Criterion) < 2. Finally, the model with the smallest Delta AICc value was selected as the optimized model, which corresponds to the best parameter settings for the regularization multiplier and feature combination.

2.4. Model Evaluation and Habitat Suitability Classification

In the study, the accuracy of the MaxEnt model simulation results was typically evaluated using AUC (Area Under the ROC Curve). The AUC value ranges from 0.5 to 1, with larger values indicating better model performance [37]. The modeling results were visualized using ArcGIS v10.8 software, simulating the geographical distribution map of T. helena’s suitable habitat under current and future climate conditions. The suitable habitat was classified into four categories: unsuitable areas (0–0.173), low suitability areas (0.173–0.347), moderate suitability areas (0.347–0.521), and high suitability areas (0.521–1), based on the maximum training sensitivity threshold [38,39]. Subsequently, ArcGIS tools were used to analyze the changes in the high-suitability areas and centroids of T. helena under current and future conditions.

3. Results

3.1. Modeling Results and Key Environmental Factors Affecting T. helena

After 10 repeated runs, the final model used to predict T. helena had an AUC of 0.971 for both AUCtraining and AUCtest (Figure 1, Table S3) and the model omission rate was 0.021, indicating that the MaxEnt model has high predictive performance for the distribution of T. helena and can be used to construct a suitability distribution model for the species on a global scale. Based on the analysis of the importance and contribution rate of each environmental variable, the five most significant factors affecting the distribution of T. helena, ranked by contribution rate, are as follows (Table S4): Precipitation of Wettest Quarter (Bio16, 55.1%), Annual Precipitation (Bio12, 25.4%), Min Temperature of Coldest Month (Bio6, 4.7%), and the average diurnal temperature range (Bio2, 4.5%), which together account for 89.7% of the total contribution. Based on the score from the jackknife method (Figure 2, Table S4), the top four most important environmental factors are Min Temperature of Coldest Month (Bio6, 52.5%), Precipitation of Wettest Quarter (Bio16, 19.6%), average diurnal temperature range (Bio2, 14.8%), and Precipitation of Driest Quarter (Bio17, 6.5%). Finally, we chose to discuss Precipitation of Wettest Quarter, Annual Precipitation, Min Temperature of Coldest Month, and the average diurnal temperature range.

3.2. Analysis of the Potential Suitable Habitat of T. helena Under Current Climate Conditions

According to Figure 3, the modeling results show a range slightly larger than the actual range of T. helena occurrence. The high-suitability habitat areas for T. helena are primarily located in the tropics, with a wide distribution across East Asia, Southeast Asia, and South Asia (Figure 3), covering a total area of 1514.13 × 103 km2 (Table 2). The potential suitable habitat (Figure 3) closely matches the current distribution records of the species (Figure 3), mainly occurring in China, Myanmar, Cambodia, Thailand, Vietnam, the Philippines, Malaysia, Indonesia, as well as in Eastern India and Bangladesh in South Asia. The medium-suitability areas are predominantly found in the tropical and subtropical regions, covering an area of 1851.44 × 103 km2 (Table 2), with a broad distribution in China within Asia. The low-suitability areas, which are similar to the medium-suitability areas but are located further from the tropics, are mainly found in subtropical regions, covering a total area of 2102.08 × 103 km2 (Table 2). Overall, T. helena has a wide distribution in tropical regions and is suited to environments with high temperatures and abundant precipitation.

3.3. Prediction of Suitable Habitats for T. helena Under Future Climate Conditions

As shown in Figure 4, the potential distribution of T. helena under different future climate scenarios was simulated. The analysis revealed that the suitable habitat of T. helena varied under different scenarios. In the 2050s, the area of high suitability habitat changed between 4.01% and 38.28% (Table 2), with larger variations observed in southern China and Southeast Asia (Figure 4A–C). The area of moderate suitability habitat decreased, with the reduction ranging from 3.66% to 7.57% (Table 2). Additionally, the area of low suitability habitat increased, with the increase ranging from 0.09% to 26.94% (Table 2). Notably, under the SSP5-8.5 scenario in the 2050s (Table 2), the area of moderate suitability habitat increased the most, while the reduction in high suitability habitat was the greatest. By the 2090s, the area of high suitability habitat decreased under the SSP1-2.6 and SSP2-4.5 scenarios compared to the 2050s, but under the SSP5-8.5 scenario, the area increased the most compared to the present, reaching 42.85% (Table 2). The area of moderate suitability habitat also increased, with the largest increase observed under the SSP5-8.5 scenario, reaching 23.28% (Table 2). Overall, the suitable habitat of T. helena is expected to expand in the future, with high suitability habitats remaining primarily in tropical regions, while some suitable habitats may expand towards higher latitudes.

3.4. Changes in the High Suitable Habitats of T. helena from Present to Future

The contraction and expansion of the high suitability habitat for T. helena in the future is shown in Figure 5. In the 2050s, the changes in high suitability habitat for T. helena were mainly observed in Southeast Asia, particularly in Indonesia and Malaysia, with some expansion in India (Figure 5A–C). The area of expansion reached its maximum under the SSP2-4.5 scenario, with an increase of 670.56 × 103 km2 (Table 3). Additionally, the area of contraction was smallest under the SSP2-4.5 scenario, with an increase of only 90.97 × 103 km2 (Table 3). In the 2090s, the high suitability habitat for T. helena showed signs of migrating to higher altitudes, with a notable expansion within China. The expansion reached its maximum under the SSP5-8.5 scenario, with an increase of 840.02 × 103 km2 (Table 3). Furthermore, significant contraction was observed in Indonesia and Malaysia (Figure 5D–F), with the smallest contraction area under the SSP1-2.6 scenario, with an increase of only 647.73 × 103 km2 (Table 3).

3.5. Response Analysis of Dominant Environmental Variables

Based on the response curves of environmental variables to the distribution probability of T. helena in the MaxEnt model (Figure 6 and Figure S1), the suitable environmental variable ranges for the potential distribution of T. helena were determined (Table 4 and Table S5). The suitable ranges and optimal values for the environmental variables for T. helena are as follows: mean diurnal range was −0.84 to 6.17 °C (Bio2, optimal value: 1.02 °C), minimum temperature of the coldest month was 22.25 to 23.29 °C (Bio6, optimal value: 22.88 °C), annual precipitation was 2156.04 to 7355.73 mm (Bio12, optimal value: 6690.76 mm), and precipitation of the wettest quarter was 636.18 to 2965.72 mm (Bio16, optimal value: 758.00 mm). The distribution probability of T. helena increased with the increasing values of environmental variables but began to decrease once the optimal value was reached. Notably, except for the mean diurnal range, T. helena maintained a high distribution probability regardless of how the other three environmental variables changed.

4. Discussion

4.1. Evaluation and Prediction Results of the MaxEnt Model

In this study, the MaxEnt model was used to predict the potential suitable habitat areas for T. helena worldwide, based on its distribution data and 10 environmental variables, for both current and future periods. The accuracy of the model was evaluated using the AUC, and the average AUC value of the MaxEnt model was 0.971, indicating that the model provided good predictions of the distribution area of T. helena, with high reliability [25]. The model predictions show that the current potential suitable habitat for T. helena is located in the tropical rainforests and coastal areas of East Asia, where high temperatures and abundant precipitation provide a favorable environment. The total area of the high-suitability habitat is 1514.13 × 103 km2. Under different future scenarios, the high-suitability habitat for T. helena is projected to increase over time, consistent with findings from studies on other tropical insects [40,41]. The analysis of current and future changes suggests a trend of northward migration of the species’ suitable habitat, a pattern that has been confirmed by several previous studies [42,43].

4.2. Key Environmental Variables and Ecological Characteristics

The study, by analyzing the key environmental factors affecting the occurrence probability of T. helena, derived the species’ response curves to these environmental variables. The results indicate that precipitation is a key factor influencing the distribution of T. helena, including precipitation of wettest quarter (Bio16, 55.1%) and annual precipitation (Bio12, 25.4%), which together contribute a total of 80.5% to the species’ distribution. Additionally, the min temperature of coldest month (Bio6, 4.7%) and mean diurnal temperature range (Bio2, 4.5%) also play significant roles in shaping the distribution of T. helena.
Some studies have shown that in areas with latitudes lower than 40°, precipitation is more likely to become the dominant factor limiting butterfly survival [44], a result consistent with our study. Precipitation contributes more to the distribution than temperature and is the primary environmental factor influencing its distribution. A reduction in precipitation may lead to decreased larval hatching rates and habitat degradation [45,46]. This study indicates that T. helena requires higher levels of precipitation, as even with precipitation levels above its suitable range, the occurrence probability remains relatively high, suggesting a significant demand for precipitation. Research has shown that insect abundance is positively correlated with precipitation [47]. Therefore, drought, as an important factor limiting insect diversity [48], may also be a crucial condition limiting the distribution of T. helena. Temperature is also an important environmental variable affecting the distribution of T. helena. The min temperature of coldest (Bio6) and the mean diurnal range (Bio2) were found to have a significant impact on the distribution of T. helena. Body temperature was a key factor influencing butterfly survival, and butterflies needed to maintain their body temperature within a suitable range [49]. As small ectothermic animals, butterflies were highly dependent on the environment for thermoregulation and were, therefore, vulnerable to temperature fluctuations [50]. In the tropics, where temperatures were consistently high, the suitable temperature range for T. helena was also relatively high, with the min temperature of coldest ranging from 8.29 to 18.52 and 22.19 to 23.29 °C, which was much higher than the suitable range for non-tropical species like the monarch butterfly [51], explaining why T. helena was primarily distributed in tropical regions. Research has shown that butterflies in warmer regions adapted to higher temperatures, which could lead to population increases in the future under climate warming [52], consistent with the results of this study showing an expansion of high suitability areas for T. helena in tropical regions.
Under the current scenario, the distribution area of T. helena was concentrated in the tropics. In the future, the suitable areas for T. helena would expand, especially in tropical rainforest climates and coastal areas, further validating that precipitation and temperature were the major factors affecting butterflies, with environments of high temperature and high precipitation being suitable for their survival. This study contributed to understanding the relationship between environmental factors and T. helena populations, determining its distribution range, and promoting the conservation of butterfly species diversity.

4.3. Limitations of the Model and Species Conservation

The MaxEnt model is a species distribution prediction tool based on the maximum entropy principle, widely applied in ecological research and species conservation planning [53]. Studies have shown that T. helena is widely distributed in tropical rainforest climates and may experience range expansion in the future, which is beneficial for its conservation. However, MaxEnt modeling cannot account for all factors [54]. For instance, it does not consider the distribution of host plant species, and changes in climate, such as warming and variations in precipitation, can affect plant–herbivore interactions, thereby influencing the distribution of animals [55]. Like other species in the butterfly family, T. helena is oligophagous, primarily feeding on Aristolochiaceae plants [15], and its distribution range is largely constrained by the availability of host plants [56]. Therefore, even if the climate is suitable, T. helena may not be able to thrive in certain areas if sufficient food sources are lacking. The inability to account for such factors limits the model’s accuracy, often leading to predicted suitable habitats that exceed the actual distribution range [57]. Thus, when applying modeling results, it is essential to consider both species characteristics and local environmental conditions comprehensively. The projected increase in the suitable habitat for T. helena does not imply that its population will be free from risk; conservation efforts are still needed, and people must join forces to contribute to its protection. The predicted increase in suitable habitats for T. helena in the future does not imply that the species will be free from danger. Conservation efforts still require significant contributions from people to protect the species. The high-suitability habitat of T. helena is relatively stable in tropical regions, while the success rate of ex situ conservation measures is lower [58]. Therefore, in situ conservation should be the primary focus for protecting T. helena. Establishing nature reserves is the optimal in situ conservation method. The selection of nature reserves should consider areas with stable future suitability, such as countries in China, Vietnam, eastern India, and Indonesia. Additionally, on-site investigations are necessary to ensure the presence of suitable host plant distributions in these areas [59]. This is because the plants consumed by the larvae are crucial for the distribution of T. helena [15]. Future conservation efforts should include the cultivation of Aristolochiaceae plants, increasing the availability of food sources for larvae and, thereby, improving the survival chances of T. helena in these areas [55,60]. Ongoing monitoring of the population distribution dynamics, in combination with key environmental factors, is essential for developing effective conservation strategies for T. helena.

5. Conclusions

This study successfully predicted the current and future potential suitable habitats of Troides helena using the MaxEnt model. The results indicate that future climate change could have a positive impact on the distribution of T. helena. Precipitation variables (Bio12 and Bio16) and temperature variables (Bio6 and Bio2) all influence the species’ distribution, with Bio16 contributing 55.1%, making it the most significant environmental factor. Under current conditions, the high-suitability habitat of T. helena is primarily distributed across China and Southeast Asia. In the future, the potential suitable habitat is expected to increase, especially under the SSP5-8.5 scenario, where the area of high-suitability habitat in the 2090s is predicted to increase by 42.85%. A comparison of current and future distribution changes reveals that the increase in high-suitability habitat is most pronounced in China, while significant contractions occur in Indonesia and Malaysia. Based on the current distribution of T. helena, in situ conservation efforts should focus on countries such as China, Vietnam, eastern India, and Indonesia. This study evaluates the distribution patterns of T. helena and its future changes, providing valuable support for future conservation efforts.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/insects16010079/s1, Figure S1: Response curves of T. helena to the five dominant environmental variables. Table S1. Lists the 19 bioclimatic variables used in the modeling process. Table S2. The Pearson correlation coefficient between environmental factors and T. helena. Table S3. AUCtraining and AUCtest in modeling process. Table S4. Percentage contribution and ranking of environment variables in Maxent model. Table S5: Suitable environmental variable ranges for the potential distribution of T. helena.

Author Contributions

Conceptualization, Z.Z.; data curation, Q.L., D.X. and Z.Z.; formal analysis, T.G. and X.L. (Xiushan Li); financing acquisition, D.X., X.L. (Xiushan Li) and Z.Z.; investigation, F.Y., J.Y., X.L. (Xue Liao) and X.D.; methodology: Q.L., B.L. and T.G.; resources, D.X. and X.L. (Xiushan Li); software, B.L., X.L. (Xue Liao) and X.D.; visualization, F.Y., X.L. (Xue Liao), J.Y. and X.D.; writing—original manuscript, F.Y. and Q.L.; article review editor D.X. and Z.Z.; producer, D.X. and Z.Z. All authors have read and agreed to the published version of the manuscript.

Funding

This work was funded by the National Key R&D Program of China (2022YFE0115200), and Fundamental Research Funds of China West Normal University (20A007, 20E051, 21E040, and 22kA011).

Data Availability Statement

The data supporting the results are available in a public repository at: https://figshare.com/s/974ad58c1e2b5a6d2ab6, 20 November 2024; GBIF.org (8 August 2024) GBIF Occurrence Download https://doi.org/10.15468/dl.xw4wnb, accessed on 8 August 2024.

Conflicts of Interest

The authors declare no conflicts of interest.

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Insects 16 00079 g001
Figure 1. Evaluation of the modeling results for T. helena using the ROC curve and AUC.
Figure 1. Evaluation of the modeling results for T. helena using the ROC curve and AUC.
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Insects 16 00079 g002
Figure 2. Variable importance, as determined via the folding jackknife test, for T. helena.
Figure 2. Variable importance, as determined via the folding jackknife test, for T. helena.
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Insects 16 00079 g003
Figure 3. Potential distribution and occurrence records of T. helena under current climate conditions. The red triangles represent the occurrence records of T. helena.
Figure 3. Potential distribution and occurrence records of T. helena under current climate conditions. The red triangles represent the occurrence records of T. helena.
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Figure 4. Potential distribution of T. helena in future periods (2050s, 2090s) under the SSP1-2.6, SSP2-4.5, and SSP5-8.5 climate change scenarios. (A) represents the potential suitable habitat under the SSP1-2.6 scenario in the 2050s, (B) represents the potential suitable habitat under the SSP2-4.5 scenario in the 2050s, (C) represents the potential suitable habitat under the SSP5-8.5 scenario in the 2050s, (D) represents the potential suitable habitat under the SSP1-2.6 scenario in the 2090s, (E) represents the potential suitable habitat under the SSP2-4.5 scenario in the 2090s, and (F) represents the potential suitable habitat under the SSP5-8.5 scenario in the 2090s.
Figure 4. Potential distribution of T. helena in future periods (2050s, 2090s) under the SSP1-2.6, SSP2-4.5, and SSP5-8.5 climate change scenarios. (A) represents the potential suitable habitat under the SSP1-2.6 scenario in the 2050s, (B) represents the potential suitable habitat under the SSP2-4.5 scenario in the 2050s, (C) represents the potential suitable habitat under the SSP5-8.5 scenario in the 2050s, (D) represents the potential suitable habitat under the SSP1-2.6 scenario in the 2090s, (E) represents the potential suitable habitat under the SSP2-4.5 scenario in the 2090s, and (F) represents the potential suitable habitat under the SSP5-8.5 scenario in the 2090s.
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Figure 5. Changes in the High Suitability Habitat of T. helena from the Present to the Future; “Gain” indicates areas where high suitability habitats have increased, “Lost” indicates areas where high suitability habitats have decreased, “Abs” indicates the area where non-high suitability habitats (unsuitable, low, and medium suitability) remain unchanged, and “Pres” indicates the area where high suitability habitats remain unchanged. (A) represents the changes in potential suitable habitat from the current scenario to the SSP1-2.6 scenario in the 2050s, (B) represents the changes in potential suitable habitat from the current scenario to the SSP2-4.5 scenario in the 2050s, (C) represents the changes in potential suitable habitat from the current scenario to the SSP5-8.5 scenario in the 2050s, (D) represents the changes in potential suitable habitat from the current scenario to the SSP1-2.6 scenario in the 2090s, (E) represents the changes in potential suitable habitat from the current scenario to the SSP2-4.5 scenario in the 2090s, and (F) represents the changes in potential suitable habitat from the current scenario to the SSP5-8.5 scenario in the 2090s.
Figure 5. Changes in the High Suitability Habitat of T. helena from the Present to the Future; “Gain” indicates areas where high suitability habitats have increased, “Lost” indicates areas where high suitability habitats have decreased, “Abs” indicates the area where non-high suitability habitats (unsuitable, low, and medium suitability) remain unchanged, and “Pres” indicates the area where high suitability habitats remain unchanged. (A) represents the changes in potential suitable habitat from the current scenario to the SSP1-2.6 scenario in the 2050s, (B) represents the changes in potential suitable habitat from the current scenario to the SSP2-4.5 scenario in the 2050s, (C) represents the changes in potential suitable habitat from the current scenario to the SSP5-8.5 scenario in the 2050s, (D) represents the changes in potential suitable habitat from the current scenario to the SSP1-2.6 scenario in the 2090s, (E) represents the changes in potential suitable habitat from the current scenario to the SSP2-4.5 scenario in the 2090s, and (F) represents the changes in potential suitable habitat from the current scenario to the SSP5-8.5 scenario in the 2090s.
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Figure 6. Response curves of T. helena to the five dominant environmental variables. The blue area represents the range of occurrence probability, while the red curve represents the average occurrence probability.
Figure 6. Response curves of T. helena to the five dominant environmental variables. The blue area represents the range of occurrence probability, while the red curve represents the average occurrence probability.
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Table 1. Environmental variables affecting T. helena and host plants distribution.
Table 1. Environmental variables affecting T. helena and host plants distribution.
CodeVariableUnit
Bio2Mean Diurnal Range°C
Bio6Min Temperature of Coldest Month°C
Bio12Annual Precipitationmm
Bio16Precipitation of Wettest Quartermm
Bio17Precipitation of Driest Quartermm
elevelevm
Slopeslope°
Table 2. Area of suitable habitats for T. helena under current and future climate conditions.
Table 2. Area of suitable habitats for T. helena under current and future climate conditions.
Predicted Area (×103 km2)Comparison with Current Distribution (%)
Low Habitat SuitabilityMedium Habitat SuitabilityHighly Habitat SuitabilityMedium Habitat SuitabilityLow Habitat SuitabilityHighly Habitat Suitability
Current2102.081851.441514.13\\\
2050sSSP1-2.62103.911783.631938.350.09%−3.66%28.02%
SSP2-4.52223.871711.352093.725.79%−7.57%38.28%
SSP5-8.52668.351760.831574.8126.94%−4.89%4.01%
2090sSSP1-2.62269.251989.531769.247.95%7.46%16.85%
SSP2-4.52604.642035.381655.5923.91%9.94%9.34%
SSP5-8.52111.652282.432162.880.46%23.28%42.85%
Table 3. Area of Changes in T. helena from Present to Future.
Table 3. Area of Changes in T. helena from Present to Future.
Gain (×103 km2)Abs (×103 km2)Pres (×103 km2)Lost (×103 km2)
2050sSSP1-2.6567.9757,825.731370.38143.75
SSP2-4.5670.5657,723.141423.1690.97
SSP5-8.5445.3157,948.391129.50384.64
2090sSSP1-2.6598.1357,795.571171.11343.02
SSP2-4.5532.9957,860.711122.60391.53
SSP5-8.5840.0257,553.681322.86191.27
Table 4. Suitable environmental variable ranges for the potential distribution of T. helena.
Table 4. Suitable environmental variable ranges for the potential distribution of T. helena.
Environmental VariablesSuitable RangeSuitable Range
Bio2−0.84–8.83 °C1.02 °C
Bio68.29–18.52; 22.19–23.29 °C22.88 °C
Bio122156.04–7355.73 mm6690.76 mm
Bio16636.18–2965.72 mm758.00 mm
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Yang, F.; Liu, Q.; Yang, J.; Liu, B.; Deng, X.; Gan, T.; Liao, X.; Li, X.; Xu, D.; Zhuo, Z. Evaluating the Impact of Climate Change on the Asia Habitat Suitability of Troides helena Using the MaxEnt Model. Insects 2025, 16, 79. https://doi.org/10.3390/insects16010079

AMA Style

Yang F, Liu Q, Yang J, Liu B, Deng X, Gan T, Liao X, Li X, Xu D, Zhuo Z. Evaluating the Impact of Climate Change on the Asia Habitat Suitability of Troides helena Using the MaxEnt Model. Insects. 2025; 16(1):79. https://doi.org/10.3390/insects16010079

Chicago/Turabian Style

Yang, Fengrong, Quanwei Liu, Junyi Yang, Biyu Liu, Xinqi Deng, Tingjiang Gan, Xue Liao, Xiushan Li, Danping Xu, and Zhihang Zhuo. 2025. "Evaluating the Impact of Climate Change on the Asia Habitat Suitability of Troides helena Using the MaxEnt Model" Insects 16, no. 1: 79. https://doi.org/10.3390/insects16010079

APA Style

Yang, F., Liu, Q., Yang, J., Liu, B., Deng, X., Gan, T., Liao, X., Li, X., Xu, D., & Zhuo, Z. (2025). Evaluating the Impact of Climate Change on the Asia Habitat Suitability of Troides helena Using the MaxEnt Model. Insects, 16(1), 79. https://doi.org/10.3390/insects16010079

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