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Article

Projection of the Potential Global Geographic Distribution of the Solanum Fruit Fly Bactrocera latifrons (Hendel, 1912) (Diptera: Tephritidae) Based on CLIMEX Models

by
Yajie Wei
1,2,†,
Xiaoqing Xian
3,†,
Haoxiang Zhao
3,
Jianyang Guo
3,
Nianwan Yang
3,4,
Zhi Gong
2,*,
Wanxue Liu
3,* and
Zhengqiang Peng
1,2
1
College of Plant Science & Technology, Huazhong Agricultural University, Wuhan 430070, China
2
Key Laboratory of Integrated Pest Management on Tropical Crops, Ministry of Agriculture and Rural Affairs, China, Environment and Plant Protection Instiute, Chinese Academy of Tropical Agricultural Sciences, Haikou 571101, China
3
State Key Laboratory for Biology of Plant Diseases and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Science, Beijing 100193, China
4
Institute of Western Agriculture, Chinese Academy of Agricultural Sciences, Changji 831100, China
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Horticulturae 2024, 10(9), 977; https://doi.org/10.3390/horticulturae10090977
Submission received: 11 August 2024 / Revised: 10 September 2024 / Accepted: 12 September 2024 / Published: 14 September 2024
(This article belongs to the Special Issue Pest Diagnosis and Control Strategies for Fruit and Vegetable Plants)
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Abstract

:
The solanum fruit fly Bactrocera latifrons (Diptera: Tephritidae) is an invasive alien insect that causes huge economic losses to pepper and other solanaceous plant industries. It is mainly distributed in South and Southeast Asia, SW Europe, Western USA, and in some African countries. However, the potential global geographical distribution of B. latifrons is unknown. Therefore, in this study, based on the current (1981–2010) and future (2040–2059) climatic scenarios determined using the CNRM-CM5, Access1.0, GFDL-ESM-2M, and NorESM1-M models, we used a species distribution model (CLIMEX 4.0) to project the potential global geographic distribution of B. latifrons to prevent further invasion and harm. In the current climate scenario, South America (1286.06 × 104 km2), Africa (1435.47 × 104 km2), and Oceania (410.66 × 104 km2) have the largest proportions of suitable land areas for B. latifrons colonization. Under all four future climate models, the global potential suitable area for Bactrocera latifrons is projected to decrease and shift towards higher latitudes. This study provides an important baseline upon which researchers, quarantine personnel, and governments can develop the appropriate control strategies against B. latifrons.

1. Introduction

Tephritidae are among the most destructive, feared, and well-known fruit and vegetable pests worldwide. Owing to the wide range of host plants affected by these pests and their strong reproductive capacity, they can cause serious crop losses and pose a threat to global fruit and vegetable production and international trade. The solanum fruit fly Bactrocera latifrons—an important pest belonging to Bactrocera (Macquart, 1835)—mainly harms Solanaceae plants with soft fruits [1], especially Capsicum sp. varieties, and occasionally Cucurbitaceae plants [2,3,4]. Economic loss studies have shown that the solanum fruit fly can cause 60–80% loss of red pepper in Malaysia [5] and, under no management, the insects could cause a loss of 7.1–18.7 billion dollars in China [6].
Bactrocera latifrons was first discovered in Taiwan in 1912 and is currently distributed mainly in the South and Southeast Asian countries [7]. In 1983, B. latifrons was discovered on Oahu Island, Hawaii, after which it subsequently invaded the entire island [8]. In Africa, B. latifrons was reported in Tanzania in 2006 [9] and Kenya in 2007 [10], after which it invaded the Congo and Burundi by 2016 [11,12]. Additionally, B. latifrons was detected in the western United States in 2016 [13] and Italy in 2018 [14]. Although B. latifrons is not widely distributed in the world’s main chili pepper production areas, to date, its occurrence has been reported in 21 countries [7]. Between 2007 and 2009, several interceptions of B. latifrons were made at the Charles de Gaulle Airport in France [15]. In 2013, young larvae of B. latifrons were intercepted in Hubei Province, China [16], and two B. latifrons specimens were collected from Campania, Naples Province, Italy, in 2019 [17]. Therefore, it is crucial to determine what other areas are suitable for the proliferation of this pest insect, in addition to the existing distribution areas, in order to curb its spread.
Macro-drivers of biological invasions include commercial activities [18], where continued growth in crop production and frequent international trade create more opportunities for the invasion of exotic pests [19]. Statistical analysis showed that an increase in the rate of first recording of invasive organisms was related to an increase in the value of imports [20]. The deliberate introduction of ornamental plants, fruit, or vegetable trade accelerates the colonization of invasive insects [21,22,23,24]. Global pepper production and harvested areas have continued to grow between 2012 and 2021, peaking in 2021. The global market has recorded the tenth consecutive year of growth in the overseas shipments of chili peppers and green chilli peppers; their global exports peaked in 2021 and, at the same time, global trade is becoming more frequent, thus increasing the risk of B. latifrons spreading [25,26]. Insects spread to new places through trade and transportation; however, climate also has an important effect on insect dispersal, as it affects their survival and colonization [20].
Climate change, particularly shifts in temperature, has a significant impact on the ecology, epidemiology, and distribution of insects [27]. This influence is particularly pronounced for small invertebrates such as insects, which are sensitive to changes in the climate conditions [28].Temperature affects the lifespan of adult B. latifrons, with low temperatures slowing development and high temperatures hastening development [29]. During the warmer years, both the occurrence and area of infestation of B. latifrons increased markedly [26]. According to the Intergovernmental Panel on Climate Change (IPCC) reports, climate problems for the next two decades include global warming of up to 1.5 °C and warming scenarios of more than 1.5 °C for several decades [30]. To prevent the further spread of B. latifrons due to this temperature increase, we should determine its potential future geographic distribution and take precautionary measures as appropriate.
The most commonly used software analysis methods for pest ecological niches include CLIMEX 4.0.0, GARP 1.1.3, DIVA-GIS 7.5.0, and MaxEnt 3.4.4. Since biological data for B. latifrons are already well-established, we chose to use CLIMEX as we did not have a sufficient number of distribution points. CLIMEX is a semi-mechanistic modeling approach for examining the relationships among climate, species distributions, and growth patterns [31], and projecting the fitness zone and relative abundance of a species by analyzing their climatic conditions within a known range. The application of CLIMEX is important for accurate projections of species distribution and has become a common tool for insect risk assessment, especially for Tephritid fruit flies (e.g., Anastrepha obliqua (Macquart, 1835), B. tryoni (Froggatt, 1897), and B. dorsalis (Hendel, 1912)) [32,33,34,35]. Here, we used the CLIMEX model combined with biological characteristics of B. latifrons to project its potential future geographical distribution. This is the first study to project this aspect based on climate change. B. latifrons, with a wide range of dispersal, is likely to increase its colonization potential with the projected increase in trade and elevation of temperature, thereby representing a high economic hazard. Therefore, in this study, we proposed the use of the CLIMEX 4.0 model analysis to achieve the following: (1) project the potential global geographic distribution of B. latifrons in current and future climate scenarios, (2) explore changes in the potential geographical distribution of B. latifrons, and (3) analyze the distribution center shifts between the current climate and future climate changes.

2. Materials and Methods

2.1. Research Model and Software

The CLIMEX model has two basic assumptions as follows: (1) species go through two periods in a year, a period suitable for population growth and a period unfavorable for population growth, and (2) climate is the main factor affecting species distribution. Different responses of species to climate have been described using a series of parameters [31]. CLIMEX describes species responses to these factors by calculating a weekly growth index (GIW) using temperature (TI) and soil moisture (MI) indices. The GIW is integrated into an annual growth index (GIA). Factors that affect a species’ ability to persist in a given site are called stress indices and include heat, cold, moisture, dryness, and their interactions. These individual stress values are combined into an annual stress index (SI). When the SI is combined with the GIA, the program calculates an Ecoclimatic Index (EI), with larger EI values indicating a higher overall suitability of the site for species persistence throughout the year [36].

2.2. Data Collection

2.2.1. Climate Data

The CM30_1995H dataset in CliMond, which includes environmental variables such as the monthly mean rainfall and temperature, daily temperature range, and vapor pressure from 1981 to 2010, was used here. Based on these variables, the average daily maximum and minimum temperature, and average monthly relative humidity from 09:00 to 15:00 from 1981 to 2010 were calculated (https://www.climond.org/, (accessed on 15 March 2024).
Here, four global climate models (GCMs)—ACCESS1-0, CNRM-CM5, GFDL-ESM-2M, and NorESM1-M—and the representative concentration path 8.5 emission scenarios for 2050 were used to characterize the possible future climate [37]. All grid global climate datasets used in the CLIMEX model have a spatial resolution of 30 s (0.5° × 0.5°).

2.2.2. Global Distribution Records of B. latifrons

Bactrocera latifrons occurrence records were collected from the Global Biodiversity Information Facility (GBIF; https://www.gbif.org/, (accessed on 6 February 2024), Barcode of Life Data Systems (BOLD; http://boldsystems.org/, (accessed on 11 September 2024), published literature on the Web of Science (WOS; https://www.webofscience.com/, (accessed 2 February 2024), and China National Knowledge Infrastructure (CNKI; https://www.cnki.net/, (accessed on 8 March 2024). Ultimately, 140 occurrence records of B. latifrons were obtained worldwide. For non-longitude and latitude records, Google Earth was used to obtain precise coordinates. Notably, the eradication of B. latifrons in Italy was as a result of the measures taken by the Italian Government to control the fly. [14]. Figure 1 shows the distribution areas of B. latifrons.

2.3. Research Methods

2.3.1. Fitting CLIMEX Parameters

In this study, we first used the parameters from Ma et al. [38] as the initial values of the iteratively adjusted parameters, and then fitted the CLIMEX parameters based on the biological data and global distribution records of B. latifrons. The adjusted CLIMEX maximized the potential geographic distribution of B. latifrons. Details of the source and process of parameter fitting and the final parameters are listed in Table 1.

2.3.2. Temperature Index

The temperature index consisted of four temperature parameters. For B. latifrons, the starting point temperature, the lowest winter temperature, the highest summer temperature, and the effective accumulated temperature over generations were 15.68, −3.7, 36, and 415.397 °C, respectively [38]. Therefore, we had set the development threshold temperature of DV0 and DV3 to 15.7 and 36 °C, respectively. Since B. latifrons are native to South and Southeast Asia, the lower (DV1) and upper (DV2) limits of the optimal developmental temperature were set at 18 and 33 °C, respectively.

2.3.3. Moisture Index

The moisture index also consisted of four moisture parameters. Because B. latifrons feed on fresh plants, we had set SM0 to 0.1 based on the permanent wilting point of the insect host plant. Moreover, B. latifrons are mainly distributed in South and Southeast Asia, where the climate is humid. As the northern boundary of B. latifrons is in Pakistan [39], the parameters of SM1 and SM2 were too high, and the lower limit of the optimal soil moisture (SM1) was set as 0.5. The upper (SM2) and critical upper (SM3) limits of the optimal soil moisture were set to 1.0 and 1.8, respectively.

2.3.4. Degree-Days per Generation (PDD)

Degree-days per generation (PDD) refers to the degree-days above the DV0. The results show that the PDD of B. latifrons was 415.397DD [38], and the PDD was set as 415.40DD according to the actual geographical distribution of B. latifrons.

2.3.5. Cold Stress

As the northern boundary of the actual geographical distribution of B. latifrons extends to Pakistan [39] and Yulin and Baise of Guangxi [40], the threshold of cold-stress onset accumulation of B. latifrons was set to 2.0.

2.3.6. Heat Stress

According to the actual geographical distribution of B. latifrons in India, the threshold for the onset of heat stress accumulation is set as 36 °C [38], and the accumulation rate of heat stress was set as 0.005, considering the average climate effect.

2.3.7. Dry Stress

The SMDS was set to a permanent wilting point of 0.1—generally representing 10% of soil moisture—to be consistent with SM0. Considering the prevalence of soil moisture in the Congo and Burundi in Africa [11,12], where the distribution of B. latifrons was newly discovered, the accumulation rate of dry stress was adjusted to −0.0025.

2.3.8. Wet Stress

We had set the SMWS to 1.8 based on SM3. To match the actual geographic distribution of Malaysia, Singapore, and Indonesia [7] in Southern Southeast Asia, the rate of wet stress accumulation was adjusted to 0.001.

2.4. Centroid Transfer and Threshold Chosen

The centroid transfer in the geographical distribution from the current climate to future scenarios was calculated using the ArcGIS10.2 software. Here, we focused on the centroid transfer of B. latifrons in the 2050s, considering the climate models Access 1.0, CNRM-CM5, GFDL-ESM-2M, and NorESM1-M. We reclassified the geographical distribution of B. latifrons and transferred it to a ‘.shp’ file from the current climate to future scenarios in the 2050s, which could then be dissolved into a single central point to depict the transfer direction of B. latifrons. Thereafter, we used ArcGIS to track the centroid transfer and transfer distance to analyze the habitat shifts. Here, EI ranged from 0 to 100 and was divided into the following four stages: EI = 0, indicating that environmental conditions are unfavorable for species survival and growth; 0 < EI ≤ 10, marginally favorable; 10 < EI ≤ 20, favorable; 20 < EI, highly favorable. The projected results were obtained through interpolation analysis via ArcGIS. Finally, we derived the potential geographic distribution of B. latifrons from the current climate to future scenarios in the 2050s.

3. Results

3.1. Potential Distribution of B. latifrons under the Current Climate Conditions

Under the current climatic conditions, B. latifrons is projected to be established throughout most of the tropics, subtropics, and some temperate regions (Figure 2). The results indicate high suitability for B. latifrons in Southern North America, Northern and Central South America, Central and Southern Africa, Southern and Southeastern Asia, Northern and Eastern Oceania, and Southern Europe. The global total, highly, moderately, and poorly suitable habitat areas of B. latifrons were measured at 4352.58 × 104, 3136.78 × 104, 390.62 × 104, and 825.18 × 104 km2, respectively (Figure 3). The continent-based largest total, highly, moderately, and poorly suitable habitat areas of 1435.47.20 × 104, 1032.46 × 104, 122.14 × 104, and 280.87 × 104 km2, respectively, were located in Africa and included Angola, Burundi, Benin, Botswana, Central African Republic, Côte d’Ivoire, Cameroon, Democratic Republic of the Congo, Republic of Congo, Ethiopia, Gabon, Ghana, Guinea, Equatorial Guinea, Kenya, Liberia, Madagascar, Mozambique, Namibia, Nigeria, Rwanda, South Sudan, Senegal, Sierra Leone, Somalia, Togo, Tanzania, Uganda, South Africa, Zambia, and Zimbabwe. This was followed by South America with the total, highly, moderately, and poorly suitable habitat areas of 1286.06 × 104, 1215.12 × 104, 29.54 × 104, and 41.40 × 104 km2, respectively, with all but Chile being suitable areas. In Asia, the total, highly, moderately, and poorly suitable habitat areas constituted 846.99 × 104, 575.49 × 104, 98 × 104, and 173.5 × 104 km2, respectively, including Bangladesh, China, Cambodia, Indonesia, Iran, India, Japan, Laos, Lebanon, Myanmar, Malaysia, Pakistan, Philippines, Thailand, Turkey, and Vietnam. In all the Oceanic countries, the total, highly, moderately, and poorly suitable habitat areas constituted 410.66 × 104, 106.56 × 104, 81.66 × 104, and 222.44× 104 km2, respectively. In North America, the total, highly, moderately, and poorly suitable habitat areas constituted 311.8 × 104, 205.56 × 104, 29.33 × 104, and 76.91 × 104 km2, respectively, including Southern America, Costa Rica, Cuba, Dominican Republic, Guatemala, Honduras, Haiti, Jamaica, Mexico, Nicaragua, and El Salvador. In Europe, the total, highly, moderately, and poorly suitable habitat areas constituted 87.4 × 104, 21.94 × 104, 32.2 × 104, and 33.26 × 104 km2, respectively, including Albania, Spain, France, Greece, Italy, and Portugal.

3.2. Changes in Potential Suitable Areas of B. latifrons under Future Climate Scenario Models

The potential geographical distribution patterns of B. latifrons in the 2050s under the four GCMs (ACCESS1-0, CNRM-CM5, GFDL-ESM-2M, and NorESM1-M) are presented in Figure 4. Compared with the current climate scenario, the total suitable habitat area of B. latifrons on each continent expanded, except in Africa and Oceania. Additionally, the area of highly suitable habitats decreased, whereas the areas of moderately and poorly suitable habitats increased (Figure 5). The potential geographical distribution of B. latifrons is primarily concentrated in South America, Africa, Southeast Asia, and Oceania. The total suitable habitat area of B. latifrons decreased in the CNRM-CM5 and NorESM1-M models and conversely increased in the Access 1.0 and GFDL-ESM-2M models. In addition, the moderately and poorly suitable habitat areas increased in all the models, while the highly suitable habitat area decreased. The total, highly, moderately and poorly suitable habitat areas of CNRM-CM5 were 4341.09 × 104, 2818.28 × 104, 622.05 × 104, and 900.76 × 104 km2; NorESM1-M were 4289.74 × 104, 2549.33 × 104, 731.75 × 104, and 1008.66 × 104 km2; Access 1.0 were 3990.2 × 104, 2187.14 × 104, 676.5 × 104, and 1126.56 × 104 km2 and GFDL-ESM-2M were 4182.98 × 104, 2587.99 × 104, 681.5 × 104, and 913.49 × 104 km2, respectively.
Changes in the potential geographical distribution of B. latifrons under the four CMGs in the 2050s are shown in Figure 6. In the four GMEs, the highly suitable habitat area decreased (Figure 7).
In Africa, the total suitable areas as projected by the Access 1.0, CNRM-CM5, GFDL-ESM-2M, and NorESM1-M models were 1164.93 × 104 km2, 1281.1 × 104 km2, 1252.55 × 104 km2, and 1250.73 × 104 km2, respectively. Compared with the current climate conditions, the total habitat area projected by the Access 1.0, CNRM-CM5, GFDL-ESM-2M, and NorESM1-M models decreased by 270.54 × 104 km2, 154.37 × 104 km2, 182.92 × 104 km2, and 184.74 × 104 km2, respectively. The moderately and poorly suitable areas increased, while the highly suitable areas decreased by 296.33 × 104 km2, 158.95 × 104 km2, 211.55 × 104 km2, and 184.02 × 104 km2 as projected by the Access 1.0, CNRM-CM5, GFDL-ESM-2M, and NorESM1-M models, respectively. These areas were concentrated in Angola, Benin, Botswana, Central African Republic, Côte d’Ivoire, Cameroon, Ethiopia, Gabon, Ghana, Guinea, Kenya, Liberia, Mozambique, Namibia, Nigeria, South Sudan, Senegal, Sierra Leone, Somalia, Togo, Republic of South Africa, Zambia, and Zimbabwe.
In South America, the total suitable areas as shown by the Access 1.0 model, CNRM-CM5, GFDL-ESM-2M, and NorESM1-M models were 1145.58 × 104 km2, 1328.95 × 104 km2, 1318.54 × 104 km2, and 1315.97 × 104 km2, respectively. The areas of moderately and poorly suitable areas increased, while the areas of highly suitable areas decreased by 616.34 × 104 km2, 256.8 × 104 km2, 317.1 × 104 km2, and 42.305 × 104 km2 as projected by the Access 1.0, CNRM-CM5, GFDL-ESM-2M, and NorESM1-M models, respectively, and were concentrated in Bolivia, Brazil, Colombia, Ecuador, Guyana, Peru, Paraguay, Suriname, and Venezuela.
In North America, the total suitable areas projected by the Access 1.0 model, CNRM-CM5, GFDL-ESM-2M, and NorESM1-M models were 389.82 × 104 km2, 412.15 × 104 km2, 358.83 × 104 km2, and 388.96 × 104 km2, respectively. Suitable habitats were mainly located in the Southern United States and Mexico. Under the CNRM-CM5 model, the total suitable habitat area of B. latifrons would increase by 100.25 × 104 km2, rising to its maximum, whereas this area would have minimum values under the GFDL-ESM-2M model.
In Asia, the total suitable areas projected by the Access 1.0, CNRM-CM5, GFDL-ESM-2M, and NorESM1-M models were 840.41 × 104 km2, 853.40 × 104 km2, 873.72 × 104 km2, and 856.14 × 104 km2, respectively. The total suitable areas of all future climate conditions increased compared to current climate conditions. The moderately and poorly suitable habitat areas increased, while the highly suitable areas as shown by the Access 1.0, GFDL-ESM-2M, and NorESM1-M models decreased by 68.05 × 104 km2, 15.16 × 104 km2 and 55.01 × 104 km2, respectively, concentrated in Bangladesh, Indonesia, India, Cambodia, Myanmar, Pakistan, Philippines, Thailand, and Vietnam.
In Oceania, the total suitable areas projected by the Access 1.0, CNRM-CM5, GFDL-ESM-2M, and NorESM1-M models were 317.39 × 104 km2, 351.17 × 104 km2, 263.63 × 104 km2, and 363.78 × 104 km2, respectively. Compared with the current climate, the total suitable area of all future climate conditions as shown by the Access 1.0, CNRM-CM5, GFDL-ESM-2M, and NorESM1-M models decreased by 93.27 × 104 km2, 95.49 × 104 km2, 147.03 × 104 km2, and 46.88 × 104 km2, respectively. Except for Central Australia, all other countries were suitable for B. latifrons.
Europe had the smallest suitable area of any continent. The total suitable areas projected by the Access 1.0, CNRM-CM5, GFDL-ESM-2M, and NorESM1-M models were 157.8 × 104 km2,140.17 × 104 km2, 141.55 × 104 km2, and 139.7 × 104 km2, respectively. The highly suitable areas increased by 29.11 × 104 km2, 47.58 × 104 km2, 17.81 × 104 km2, and 36.41 × 104 km2, respectively, as shown by the Access 1.0, CNRM-CM5, GFDL-ESM-2M, and NorESM1-M models, and were concentrated in Albania, Spain, France, Greece, Italy, and Portugal.

3.3. Centroid Shift of Potential Suitable Global Habitats

The potential geographical distribution of the centroid shifts of B. latifrons within the suitable global habitats under the current and future climate scenarios are shown in Figure 8. Under the current climate, the distribution center of B. latifrons is located in Republic of the Congo (14°51′4.789″ E, 0°42′1.034″ S). In the 2050s, under the Access 1.0, CNRM-CM5, GFDL-ESM-2M, and NorESM1-M, the distribution center of B. latifrons would transfer to Gabon (12°21′45″ E, 0°53′26″ N) (10°9′25″ E, 0°25′11″ N), (9°34′15″ E, 0°54′16″ N) and (11°0′55.904″ E, 0°8′53″ N), respectively.
The distribution center of B. latifrons has been transferred 305, 506, 578, and 361 km from the current climate to Access 1.0, CNRM-CM5, GFDL-ESM-2M, and NorESM1-M. In all four future scenarios, the distribution centers are predicted to shift to higher latitudes globally, highlighting a notable northward migration when compared to the current climate distribution.

4. Discussion

Bactridia latifrons is an economically significant pest. For example, B. latifrons, B. correcta (Bezzi, 1916), and B. dorsalis together caused damage to tomatoes, with rates ranging from 3.6% to 28.6% in all the geographical regions of Mizoram, India [41]. To prevent B. latifrons from causing further economic losses to cash crops such as Solanaceae and Cucurbitaceae, the previous studies have explored the biological characteristics and control methods of this pest. Notably, this study is the first to project the potential geographic distribution of B. latifrons based on climate change. The CLIMEX model has proven to be highly accurate, aligning well with the known distribution of B. latifrons. The results of our study, particularly the projected distribution under current and future climatic conditions, provide essential guidance for enhancing quarantine protocols and regulatory measures. By identifying regions most vulnerable to invasion by this pest, the authorities can better target inspections and pest management strategies, reducing the risk of B. latifrons spreading through the international trade of agricultural commodities, particularly Solanaceae and Cucurbitaceae crops such as peppers. According to the model, there will be an expansion in areas suitable for B. latifrons, including a spread to higher latitudes, although some tropical regions may experience a decline in suitability. Incorporating findings from the previous studies [42], we expanded the known distribution points to include Bangladesh, China (Fujian), India (Bihar, Himachal Pradesh, Kerala, Mizoram, and Tripura), Malaysia (Sarawak), Myanmar, and Congo, improving the accuracy of our projections. Therefore, our study offers a more comprehensive forecast of the potential geographic distribution of B. latifrons. Using the CLIMEX4.0 model, we provide the first projection of the future global distribution of B. latifrons. The results indicate that B. latifrons is expected to thrive in tropical and subtropical regions. Cold stress could limit the insect’s geographic distribution in North America, Europe, and Asia. However, as temperatures rise, the adaptive range of the pest is expected to expand. Conversely, in regions such as South America, Africa, and Australia, heat stress may reduce the pest’s adaptive range. Climate change exerts both direct and indirect long-term effects on pests. Additionally, changes in the populations of B. latifrons’ natural enemies, competitors, host plant availability, and physiological and biochemical changes in host plant defense mechanisms may also influence the survival and adaptability of the pest [43]. Furthermore, increased temperatures and water availability are likely to play a critical role in insect survival and growth rates [44], which may alter the geographic distribution of species [45], such as Anastrepha suspensa (Loew, 1862) [46], Rhagoletis pomonella (Walsh, 1867) [47], and Bactrocera zonata (Saunders, 1842) [48]. Thus, with global warming, rising temperatures will shift the unsuitable areas into suitable ranges for B. latifrons growth in the future. Additionally, many currently highly suitable areas may become moderately or poorly suited, while previously unsuitable areas may become favorable. As the northern regions warm, these areas may become more temperate, with little overall change in the total area of suitability.
Climate change is not the only factor influencing the potential distribution of species. Other factors such as global trade, socio-economic development, species dispersal, and interactions—including host plants, competition, and the number of natural enemies—also affect the distribution of pests. Furthermore, the soil type, human activities, and land-use patterns, including oceans and deserts, act as limiting factors for pest distribution [49]. The results of the CLIMEX model have certain limitations, as the model primarily relies on climatic variables. Therefore, additional predictive models should also be considered to provide more detailed risk assessments and scientific projections for invasive pests [32]. Changes in climate, global trade, and land use are likely to alter the potential geographic distribution of pests and, with the acceleration of global warming, pest outbreaks are expected to become more frequent. Climate change significantly affects insect fitness and dispersal [50,51,52]. Our study shows that B. latifrons poses the greatest invasion risk in suitable areas of South America, Africa, and Asia and has the potential to become a serious pest in regions that it has not yet invaded. The projected results provide important insights into the potential geographic distribution of B. latifrons under the current and future climatic conditions, serving as a valuable resource for identifying areas vulnerable to future invasions. Particularly with the globalization of economic trade, quarantine measures should be strengthened to prevent the introduction of B. latifrons, especially through the transport of peppers and other host plants [53]. Furthermore, long-term monitoring should be established in highly suitable habitats to prevent further spread of the pest [54]. Our results provide theoretical insights for developing long-term management strategies aimed at reducing the spread of invasive pests in response to climate change.

5. Conclusions

We used worldwide distribution and meteorological data—temperature, moisture and precipitation—to project the current and future potentially suitable global areas for B. latifrons invasions. The results suggest that the spread of B. latifrons will move to higher latitudes, but there are exceptions; some tropical regions are expected to decline in suitability. Based on the analysis of the driving variables, we showed that cold stress is the main limiting factor under current and future climatic conditions. This study offers a solution for CLIMEX parameter settings when a species undergoes diapause and provides a theoretical basis for preventing the spread of B. latifrons and for early monitoring and warning. In future studies, factors such as soil type, geographical features, natural and geographical obstacles, and human activities need to be taken into account as additional limiting factors affecting the geographical distribution of these pest insects.

Author Contributions

Y.W.: Conceptualization, Methodology, Formal Analysis, Writing—Original Draft, Writing—Review and Editing. X.X.: Conceptualization, Methodology, Formal Analysis, Writing—Original Draft, Writing—Review and Editing. H.Z.: Conceptualization, Methodology, Writing—Review and Editing. J.G.: Conceptualization, Writing—Review and Editing. N.Y.: Conceptualization, Methodology, Writing—Review and Editing. X.X.: Conceptualization, Writing—Review and Editing. Z.G.: Conceptualization, Writing—Review and Editing. W.L.: Conceptualization, Methodology, Writing—Review and Editing. Z.P.: Conceptualization, Writing—Review and Editing. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the National Key R&D Program of China (2023YFC2605200, 2021YFC2600400 and 2021YFD1400100), and Cooperation and high-level talent training projects with Canada, Australia, New Zealand, and Latin America (Liu-Jin-Mei 20221007).

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors on request.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Rattanapun, W.; Tarasin, M.; Thitithanakul, S.; Sontikun, Y. Host Preference of Bactrocera latifrons (Hendel) (Diptera: Tephritidae) Among Fruits of Solanaceous Plants. Insects 2021, 12, 482. [Google Scholar] [CrossRef] [PubMed]
  2. Liquido, N.J.; Harris, E.J.; Dekker, L.A. Ecology of Bactrocera latifrons (Diptera: Tephritidae) populations: Host plants, natural enemies, distribution, and abundance. Ann. Entomol. Soc. Am. 1994, 87, 71–84. [Google Scholar] [CrossRef]
  3. Paulsen, M.J. Nomenclatural changes in the Nearctic Ochodaeinae and description of two new genera (Coleoptera: Scarabaeoidea: Ochodaeidae). Insecta Mundi 2007, 21, 1–13. [Google Scholar]
  4. Mziray, H.A.; Makundi, R.H.; Mwatawala, M.; Maerere, A.; Meyer, M. Host use of Bactrocera latifrons, a new invasive tephritid species in Tanzania. J. Econ. Entomol. 2010, 103, 70–76. [Google Scholar] [CrossRef] [PubMed]
  5. Vijaysegaran, S.; Osman, M.S. Fruit flies in Peninsular Malaysia: Their economic importance and control strategies. In Proceedings of the International Symposium on the Biology and Control of Fruit Flies, Okinawa, Japan, 2–4 September 1991; Kawasaki, K., Iwahashi, O., Kaneshiro, K.Y., Eds.; Okinawa Prefectural Government: Naha, Japan, 1991; pp. 105–115. [Google Scholar]
  6. Kang, D.L.; Sun, H.Y.; Qin, Y.J.; Lu, G.C.; Lan, S.H.; Li, Z.H. The potential economic loss of chili industry in China caused by Bactrocera latifrons (Hendel) based on @RISK. Chin. J. Appl. Entomol. 2019, 56, 500–507. [Google Scholar] [CrossRef]
  7. Available online:. Available online: https://www.cabi.org/isc/datasheet/8719#todistribution (accessed on 8 February 2024).
  8. Steven, L.P.; Grant, T.M. Ecological Aspects of Bactrocera latifrons (Diptera: Tephritidae) on Maui, Hawaii: Movement and Host Preference. Environ. Entomol. 2004, 33, 1722–1731. [Google Scholar]
  9. Mwatawala, M.; Meyer, M.D.; White, I.M.; Maerere, A.; Makundi, R.H. Detection of the solanum fruit fly, Bactrocera latifrons (Hendel) in Tanzania (Dipt., Tephritidae). J. Appl. Entomol. 2007, 131, 501–503. [Google Scholar] [CrossRef]
  10. Available online:. Available online: https://gd.eppo.int/taxon/DACULA/distribution/KE (accessed on 5 February 2024).
  11. Ndayizeye, L.; Balangaliza, C.K. First report of Bactrocera latifrons Hendel in the Democratic Republic of Congo. EPPO Bull. 2021, 51, 311–313. [Google Scholar] [CrossRef]
  12. Ndayizeye, L.; Nzigidahera, B.; Gesmallah, A.E. Current distribution of Bactrocera latifrons Hendel in the different agro-ecological zones of Burundi. Int. J. Trop. Insect Sci. 2019, 39, 125–130. [Google Scholar] [CrossRef]
  13. NAPPO. Phytosanitary Alert System: Bactrocera latifrons (Malaysian Fruit Fly)—Removal of the Quarantine in the Westchester Area of Los Angeles County, California. 2016. Available online: http://www.pestalert.org/oprDetail.cfm?oprID=677 (accessed on 7 February 2024).
  14. Gargiulo, S.; Nugnes, F.; De Benedetta, F.; Bernardo, U. Bactrocera latifrons in Europe: The importance of the right attractant for detection. Bull. Insectology 2021, 74, 311–320. [Google Scholar]
  15. Balmès, V.; Germain, J.F. When fruit flies fly. Data on three years of Tephritidae interception by the French NPPO in Roissy Charles-de-Gaulle airport. In Proceedings of the 8th International Symposium on Fruit Flies of Economic Importance, Valencia, Spain, 26 September–1 October 2010. [Google Scholar]
  16. Sun, T.; Lu, L.H.; Teng, S.N.; Deng, Z.H.; Zhao, Y.; Liu, H.; Kong, D.Y. Identification of Fruit Fly Low Instar Larvae in Imported Red Pepper. Hubei Agric. Sci. 2013, 52, 4385–4387. [Google Scholar] [CrossRef]
  17. Available online:. Available online: https://gd.eppo.int/taxon/DACULA/distribution/IT (accessed on 11 February 2024).
  18. Liu, J.G.; Vanessa, H.; Mateus, B.; Ruth, S.D. Framing Sustainability in a Telecoupled World. Ecol. Soc. 2013, 36, 7870–7885. [Google Scholar] [CrossRef]
  19. Michael, I.W.; Michael, B.; Kathy, M.; Ian, N. The link between international trade and the global distribution of invasive alien species. Biol. Invasions 2008, 10, 391–398. [Google Scholar] [CrossRef]
  20. Seebens, B.; Blackburn, T.M.; Dyer, E.E.; Genovesi, P.; Hulme, P.E.; Jeschke, J.M.; Pagad, S.; Pyšek, P.; van Kleunen, M.; Winter, M.; et al. Global rise in emerging alien species results from increased accessibility of new source pools. Proc. Natl. Acad. Sci. USA 2018, 115, E2264–E2273. [Google Scholar] [CrossRef] [PubMed]
  21. Kenis, M.; Rabitsch, W.; Auger-Rozenberg, M.A.; Roques, A. How can alien species inventories and interception data help us prevent insect invasions? Bull. Entomol. Res. 2007, 97, 489–502. [Google Scholar] [CrossRef]
  22. Roques, A. Taxonomy, time and geographic patterns. Chapter 2. BioRisk 2010, 4, 11–26. [Google Scholar] [CrossRef]
  23. Eschen, R.; Douma, J.C.; Grégoire, J.C.; Mayer, F.; Rigaux, L.; Potting, R.P.J. A risk categorisation and analysis of the geographic and temporal dynamics of the European import of plants for planting. Biol. Invasions 2017, 19, 3243–3257. [Google Scholar] [CrossRef]
  24. Roques, A.; Auger-Rozenberg, M.A.; Blackburn, T.M.; Garnas, J.; Pyšek, P.; Rabitsch, W.; Richardson, D.M.; Wingfield, M.J.; Liebhold, A.M.; Duncan, R.P. Temporal and interspecific variation in rates of spread for insect species invading Europe during the last 200 years. Biol. Invasions 2016, 18, 907–920. [Google Scholar] [CrossRef]
  25. Available online:. Available online: https://www.fao.org/faostat/zh/#data/TCL/visualize (accessed on 25 February 2024).
  26. Kituta, J.A.R.; Berkmans, M.B.J. Current status of the Solanum fruit fly Bactrocera latifrons (Hendel) in the eastern part of Democratic Republic of Congo. Insect Environ. 2021, 24, 370–380. [Google Scholar]
  27. Zhao, C.Y.; Li, J.S.; Xu, J.; Liu, X.Y. Disentangling Environmental and Anthropogenic Impacts on the Distribution of Unintentionally Introduced Invasive Alien Insects in Mainland China. J. Insect Sci. 2017, 17, 77. [Google Scholar] [CrossRef]
  28. Bebber, D.P. Range-Expanding Pests and Pathogens in a Warming World. Annu. Rev. Phytopathol. 2015, 53, 335–356. [Google Scholar] [CrossRef] [PubMed]
  29. Ge, F. Challenges facing entomologists in a changing global climate. Chin. J. Appl. Entomol. 2011, 48, 1117–1122. [Google Scholar]
  30. IPCC. Climate Change 2022: Impacts, Adaptation and Vulnerability; The Intergovernmental Panel on Climate Change: Geneva, Switzerland, 2022. [Google Scholar]
  31. Macfadyen, S.; Kriticos, D.J. Modelling the Geographical Range of a Species with Variable Life-History. PLoS ONE 2012, 7, e40313. [Google Scholar] [CrossRef] [PubMed]
  32. Fu, L.; Li, Z.H.; Huang, G.S.; Wu, X.X.; Ni, W.L.; Qü, W.W. The current and future potential geographic range of West Indian fruit fly, Anastrepha obliqua (Diptera: Tephritidae). Insect Sci. 2014, 21, 234–244. [Google Scholar] [CrossRef]
  33. Sutherst, R.W.; Collyer, B.S.; Yonow, T. The vulnerability of Australian horticulture to the Queensland fruit fly, Bactrocera (Dacus) tryoni, under climate change. Aust. J. Agric. Res. 2000, 51, 467–480. [Google Scholar] [CrossRef]
  34. Stephens, A.E.A.; Kriticos, D.J.; Leriche, A. The current and future potential geographical distribution of the oriental fruit fly, Bactrocera dorsalis (Diptera: Tephritidae). Bull. Entomol. Res. 2007, 97, 369–378. [Google Scholar] [CrossRef]
  35. De Villiers, M.; Hattingh, V.; Kriticos, D.J.; Brunel, S.; Vayssieres, J.F.; Sinzogan, A.; Billah, M.K.; Mohamed, S.A.; Mwatawala, M.; Abdelgader, H.; et al. The potential distribution of Bactrocera dorsalis: Considering phenology and irrigation patterns. Bull. Entomol. Res. 2016, 106, 19–33. [Google Scholar] [CrossRef]
  36. Kriticos, D.J.; Maywald, G.F.; Yonow, T.; Zurcher, E.J.; Herrmann, N.I.; Sutherst, R.W. CLIMEX. Version 4. Exploring the Effects of Climate on Plants, Animals and Diseases; CSIRO: Canberra, Australia, 2015. [Google Scholar]
  37. Darren, J.K.; Bruce, L.W.; Agathe, L.; Noboru, O.; Ian, M.; Janice, B.; John, K.S. CliMond: Global high-resolution historical and future scenario climate surfaces for bioclimatic modelling. Methods Ecol. Evol. 2012, 3, 53–64. [Google Scholar] [CrossRef]
  38. Huang, Z. Morphological Identification, Artificial Diet, Suitability Analysis and Prediction, Qualitative and Quantitative Risk Analysis of Important Bactrocera Species. Master’s Thesis, Hainan University, Haikou, China, 2010. [Google Scholar]
  39. Syed, R.A. Studies on Trypetids and their natural enemies in West Pakistan. Dacus species of lesser importance. Pak. J. Zool. 1970, 2, 17–24. [Google Scholar]
  40. Deng, Y.P.; Qiu, Q. Survey on the occurrence and monitoring of Sitophilus in Guangxi. Guangxi Hortic. 2008, 19, 22–24. [Google Scholar]
  41. Boopathi, T.; Singh, S.B.; Manju, T.; Chowdhury, S.; Singh, A.R.; Duta, S.K.; Dayal, V.; Behere, G.T.; Ngachan, S.V.; Hazarika, S.; et al. First report of economic injury to tomato due to Zeugodacus tau (Diptera Tephritidae): Relative abundance and effects of cultivar and season on injury. Fla. Entomol. 2017, 100, 63–69. [Google Scholar] [CrossRef]
  42. Ma, X.L.; Li, Z.H.; Ni, W.L.; Qu, W.W.; Wu, J.J.; Wan, F.H.; Hu, X.N. The Current and Future Potential Geographical Distribution of the Solanum Fruit Fly, Bactrocera latifrons (Diptera: Tephritidae) in China. In Proceedings of the 5th Computer and Computing Technologies in Agriculture (CCTA), Beijing, China, 29–31 October 2011; pp. 236–246. [Google Scholar]
  43. Ayres, M.P.; Lombardero, M.J. Assessing the consequences of global change for forest disturbance from herbivores and pathogens. Total Env. 2000, 262, 263–286. [Google Scholar] [CrossRef] [PubMed]
  44. Lierop, P.; Lindquist, E.; Sathyapala, S.; Franceschini, G. Global forest area disturbance from fire, insect pests, diseases and severe weather events. For. Ecol. Manag. 2015, 352, 78–88. [Google Scholar] [CrossRef]
  45. Canelles, Q.; Aquilué, N.; James, P.M.A.; Lawler, J.; Brotons, L. Global review on interactions between insect pests and other forest disturbances. Landsc. Ecol. 2021, 36, 945–972. [Google Scholar] [CrossRef]
  46. da Silva Santana, G.; Ronchi-Teles, B.; Dos Santos, C.M.; Soares, M.A.; Souza, P.G.C.; Araújo, F.H.V.; de Aguiar, C.V.S.; da Silva, R.S. Climate suitability modeling for Anastrepha suspensa (Diptera: Tephritidae): Current and future invasion risk analysis. Int. J. Biometeorol. 2023, 67, 1185–1197. [Google Scholar] [CrossRef]
  47. Kumar, S.; Yee, W.L.; Neven, L.G. Mapping Global Potential Risk of Establishment of Rhagoletis pomonella (Diptera: Tephritidae) Using MaxEnt and CLIMEX Niche Models. J. Econ. Entomol. 2016, 109, 2043–2053. [Google Scholar] [CrossRef]
  48. Ni, W.L.; Li, Z.H.; Chen, H.J.; Wan, F.H.; Qu, W.W.; Zhang, Z.; Kriticos, D.J. Including climate change in pest risk assessment: The peach fruit fly, Bactrocera zonata (Diptera: Tephritidae). Bull. Entomol. Res. 2012, 102, 173–183. [Google Scholar] [CrossRef]
  49. Hawkins, E.; Sutton, R. The Potential to Narrow Uncertainty in Regional Climate Predictions. Bull. Am. Meteorol. Soc. 2009, 90, 1095–1107. [Google Scholar] [CrossRef]
  50. Seidl, R.; Thom, D.; Kautz, M.; Martin-Benito, D.; Peltoniemi, M.; Vacchiano, G.; Wild, J.; Ascoli, D.; Petr, M.; Honkaniemi, J.; et al. Forest disturbances under climate change. Nat. Clim. Change 2017, 7, 395–402. [Google Scholar] [CrossRef]
  51. Parmesan, C.; Yohe, G. A globally coherent fingerprint of climate change impacts across natural systems. Nature 2003, 421, 37–42. [Google Scholar] [CrossRef]
  52. IPCC. Climate Change 2021: The Physical Science Basis; Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change; Cambridge University Press: Cambridge, UK, 2021. [Google Scholar] [CrossRef]
  53. Bebber, D.P.; Holmes, T.; Gurr, S.J. The global spread of crop pests and pathogens. Glob. Ecol. Biogeogr. 2014, 23, 1398–1407. [Google Scholar] [CrossRef]
  54. Rao, J.; Zhang, Y.; Zhao, H.; Guo, J.; Wan, F.; Xian, X.; Yang, N.; Liu, W. Projecting the Global Potential Geographical Distribution of Ceratitis capitata (Diptera: Tephritidae) under Current and Future Climates. Biology 2024, 13, 177. [Google Scholar] [CrossRef]
Horticulturae 10 00977 g001
Figure 1. Current global distribution of B. latifrons.
Figure 1. Current global distribution of B. latifrons.
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Figure 2. Potential global suitable areas of Bactrocera latifrons under the current climate scenario (1981–2010).
Figure 2. Potential global suitable areas of Bactrocera latifrons under the current climate scenario (1981–2010).
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Figure 3. Potential suitable areas of Bactrocera latifrons in six continents under the current climate scenario (1981–2010).
Figure 3. Potential suitable areas of Bactrocera latifrons in six continents under the current climate scenario (1981–2010).
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Figure 4. Potential global suitable areas of Bactrocera latifrons under the future climate scenarios (2040–2059).
Figure 4. Potential global suitable areas of Bactrocera latifrons under the future climate scenarios (2040–2059).
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Figure 5. Suitable areas of Bactrocera latifrons in different models under the future climate scenarios (2040–2059).
Figure 5. Suitable areas of Bactrocera latifrons in different models under the future climate scenarios (2040–2059).
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Figure 6. Differences in the ecoclimatic index values for Bactrocera latifrons between current (1981–2010) and future (2040–2059) climate conditions. An EI of 100 represents constant ideal conditions for species survival, and 0 indicates unsuitable conditions. Red denotes EI value increases, and blue denotes EI value decreases, with the intensity proportional to the degree of change.
Figure 6. Differences in the ecoclimatic index values for Bactrocera latifrons between current (1981–2010) and future (2040–2059) climate conditions. An EI of 100 represents constant ideal conditions for species survival, and 0 indicates unsuitable conditions. Red denotes EI value increases, and blue denotes EI value decreases, with the intensity proportional to the degree of change.
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Figure 7. Suitable habitat areas for each continent under different climate conditions.
Figure 7. Suitable habitat areas for each continent under different climate conditions.
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Figure 8. Distribution of the centroid shifts of Bactrocera latifrons under current and future climate scenarios.
Figure 8. Distribution of the centroid shifts of Bactrocera latifrons under current and future climate scenarios.
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Table 1. Parameter values of CLIMEX for B. latifrons.
Table 1. Parameter values of CLIMEX for B. latifrons.
ParameterMa et al. (2012)
[38] Parameter
Values		Current
Parameter
Values
Lower threshold of soil moisture (SM0)0.100.10
Lower limit of optimum soil moisture (SM1)0.500.50
Upper limit of optimum soil moisture (SM2)1.001.00
Upper threshold of soil moisture (SM3)1.801.80
Lower threshold temperature (DV0)15.7 °C15.7 °C
Lower optimum temperature (DV1)18.0 °C18.0 °C
Upper optimum temperature (DV2)33.0 °C33.0 °C
Upper threshold temperature (DV3)36.0 °C36.0 °C
Cold stress temperature threshold (TTCS)2.00 °C2.00 °C
Cold stress accumulation rate (THCS)−0.10/week−0.10/week
Heat stress temperature threshold (TTHS)36.0 °C36.0 °C
Heat stress accumulation rate (THHS)0.005/week0.005/week
Dry stress soil moisture threshold (SMDS)0.100.10
Dry stress accumulation rate (HDS)−0.005/week−0.0025/week
Wet stress soil moisture threshold (SMWS)1.801.80
Wet stress accumulation rate (HWS)0.002/week0.001/week
Degree days taken to complete one generation (PDD)415.40 °C·d415.40 °C·d
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Wei, Y.; Xian, X.; Zhao, H.; Guo, J.; Yang, N.; Gong, Z.; Liu, W.; Peng, Z. Projection of the Potential Global Geographic Distribution of the Solanum Fruit Fly Bactrocera latifrons (Hendel, 1912) (Diptera: Tephritidae) Based on CLIMEX Models. Horticulturae 2024, 10, 977. https://doi.org/10.3390/horticulturae10090977

AMA Style

Wei Y, Xian X, Zhao H, Guo J, Yang N, Gong Z, Liu W, Peng Z. Projection of the Potential Global Geographic Distribution of the Solanum Fruit Fly Bactrocera latifrons (Hendel, 1912) (Diptera: Tephritidae) Based on CLIMEX Models. Horticulturae. 2024; 10(9):977. https://doi.org/10.3390/horticulturae10090977

Chicago/Turabian Style

Wei, Yajie, Xiaoqing Xian, Haoxiang Zhao, Jianyang Guo, Nianwan Yang, Zhi Gong, Wanxue Liu, and Zhengqiang Peng. 2024. "Projection of the Potential Global Geographic Distribution of the Solanum Fruit Fly Bactrocera latifrons (Hendel, 1912) (Diptera: Tephritidae) Based on CLIMEX Models" Horticulturae 10, no. 9: 977. https://doi.org/10.3390/horticulturae10090977

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