Spacial distribution and suitability for Panonychus ulmi (Tetranychidae) in Brazil

ABSTRACT.

Predictive studies project the geographic distribution of species and can be used to infer climatic niches. However, only a few studies have been conducted on mites. This approach helps map areas with potential for the occurrence of endemic, threatened, or potentially invasive species. Panonychus ulmi (Tetranychidae) is of global economic importance, commonly associated with apple orchards and grapevines. Potential distribution modeling is used to predict areas with environmental suitability for the distribution of a species and/or group. Considering that predictive models on national or regional scales present better data reliability, the present study aimed to analyze the distribution of P. ulmi in Brazil through bioclimatic inferences. The presence of species, bioclimatic variables, and MaxEnt algorithm were used to define a predictive model. The median performance rate of the model was 0.992, indicating its robustness. The variable that made the greatest contribution to the model was the average temperature of the coldest quarter (Bio11). The predictive model of the ecological niche indicated that the southern region of Brazil is environmentally favorable for the adaptation of this mite. The data obtained helped us understand the geographical distribution of P. ulmi in Brazil, and climatically suitable areas for its occurrence were inferred. We believe that this tool can offer indirect assistance to the agricultural sector, especially the producers of apples and grapes in Brazil regarding the presence of P. ulmi.

Keywords:
European red mite; adventive mite species; apple orchard; biogeography; spatial distribution

Introduction

Globally, Brazil is among the ten largest apple producers, and its southern region stands out for the cultivation and production of this fruit. It is an important source of income for local producers and the regional economy, particularly in the states of Santa Catarina and Rio Grande do Sul (Kist, 2015; Kist et al., 2019). In addition to apple production, the region stands out in viticulture, with the production of grapes, wine, and its derivatives (Mattuela & Mello, 1999). Viticulture is an essential source of income for wine producers and cooperatives in several states of Brazil (Mello, 2008; Instituto Brasileiro do Vinho [IBRAVIN], 2019; Mello, 2019).

Among tetranychids, Panonychus ulmi (Koch), known as the European red mite, is economically important in apple orchards and wineyards in Asia, America, Europe, and Oceania (Migeon & Dorkeld, 2020). The first record of P. ulmi in Brazil was on apple trees of Argentinian origin (Flechtmann, 1967). In 1972, Bleicher (1974) reported an infestation of this species in an apple orchard in Fraiburgo (state of Santa Catarina, Brazil). However, the first record of grapevine infestation in Brazil was in the 2005-2006 growing season, causing damage to the Vitis vinifera L. [Vitaceae] cultivar Merlot in Bento Gonçalves (state of Rio Grande do Sul, Brazil) (Ferla & Botton, 2008), and the second record was in 2006 in Pirapora (state of Minas Gerais, Brazil) by Mendonça (2009). The late occurrence in grapevines may have occurred due to the geographical proximity of apple and grapevine-growing areas in Rio Grande do Sul State, where apple trees present better reproductive performance. According to Flechtmann (1967), this may have occurred because of the transit of contaminated plant material.

In Brazil, abamectin is often used to control spider mites (Andrei, 2005). Biological control can also be applied using predatory mites (Phytoseiidae) (Lindquist, 1996; McMurtry, Moraes, & Sourassou, 2013), especially Neoseiulus californicus (McGregor) (Phytoseiidae), a species present on the vines in Rio Grande do Sul that is mainly associated with populations of P. ulmi (eg., Johann & Ferla, 2012). With favorable environmental conditions and the absence of natural enemies, P. ulmi can cause significant damage to crops (Monteiro, 2002). This phytophagous mite causes damage by feeding on the cytoplasmic content of plant cells, leading to the loss of chlorophyll in the affected areas, tanning, and reddish spots on the adaxial surface of the leaves. Severe attacks can result in defoliation, and in extreme cases, a reduction in fruit size and even death (Kovaleski & Vendramin, 1993; Ferla & Botton, 2008; Moraes & Flechtmann, 2008).

Studies predicting the potential geographic distribution of environmental niches of mites are scarce. This methodology could be used to map environmentally suitable areas for the occurrence of these species. Direct or indirect climatic factors can contribute to the distribution patterns of economically important species, thereby generating information for control decisions (Lu, Ma, Chen, Lu, & Xu, 2012; Amaro & Moraes, 2013; Meynard, Migeon, & Navajas, 2013; Parsa et al., 2015; Navia, Hamada, Gondim, & Benito, 2016; Litskas, Migeon, Navajas, Tixier, & Stavrinides, 2019; Corrêa, Silva, Nascimento, Oliveira, & Ferla, 2021). Considering that the distribution of most organisms is associated with environmental conditions at a given location or region (Soberón, 2010; Townsend, Begon, & Harper, 2010), this approach can be used to assess the potential distribution of species at the pest level (Parsa et al., 2015; Corrêa et al., 2021).

Considering that predictive models at national or regional scales present better data reliability, the present study aimed to analyze the potential distribution of P. ulmi in Brazil through bioclimatic inferences, aiming at delimiting areas with viable environmental suitability for the establishment of this species.

Material and methods

Occurrence data

Data on the occurrence of P. ulmi in Brazil was obtained from previous studies by Monteiro, Souza, and Pastori (2006), Ferla and Botton (2008), Mendonça (2009), Ferla, Johann, Klock, Majolo, and Botton (2011), Johann & Ferla (2012), and Johann, Horn, Carvalho, and Ferla (2014); the online database SpeciesLink (http://www.splink.org.br/); the online database Spider Mites Web (https://www1.montpellier.inra.fr/CBGP/spmweb/) (Migeon & Dorkeld, 2020), and information available from the Laboratory of Acarology, University of Vale do Taquari (Univates), Brazil. The data from the Laboratory of Acarology were obtained from research conducted over more than 15 years in southern Brazil. Only one record of P. ulmi per city was considered to eliminate data overlap bias. The records were georeferenced in geographic coordinates according to the collection location and/or center of the municipality in a satellite image of high spatial resolution in Google Earth in the format of decimal degrees, Datum WGS-84, for further analysis.

Data analysis

We obtained the bioclimatic variables (from Bio1 to Bio19) from the WorldClim database (https://www.worldclim.org/), which includes bioclimatic information from 1960 to 2018. The variables available were the average minimum temperature (°C), average maximum temperature (°C), and total precipitation (mm) (Fick & Hijmans, 2017). The layers were cut according to the geographic space of Brazil using a conversion tool in Quantum GIS for subsequent analysis. Although the potential for the translocation of invasive species is known, distinctions can be made regarding the inferences of geographical barriers with the risk of colonization of new environments. In a more restricted analysis, the risks of errors and misinterpretation of the results are lower in the elaboration of models of geographic distribution (Barve et al., 2011).

To perform environmental suitability analysis for P. ulmi, we used the MaxEnt algorithm (maximum entropy). To perform this analysis, we selected all the bioclimatic variables (Bio1-Bio19) (Phillips, Anderson, & Schapire, 2006; Phillips & Dudik, 2008). We used 80% of the points as training data and 20% as test data (Anderson, Lew, & Peterson, 2003). They were selected from ten replicates using a bootstrapping method with standard software functions (Phillips et al., 2006; Phillips & Dudik, 2008). In this study, the variables that contributed to the development of the predictive model for P. ulmi in the Brazilian territory were Annual Mean Temperature (Bio1), isothermality (Bio3), Temperature Seasonality (Bio4), minimum temperature of the coldest month (Bio6), Mean Temperature of Driest Quarter (Bio9), Mean Temperature of Coldest Quarter (Bio11), Precipitation of Driest Month (Bio14), and Precipitation Seasonality (Bio15). Using these bioclimatic variables, we performed a new round of analysis following the same procedure mentioned above.

Through a model executed using the MaxEnt algorithm (using points of presence and bioclimatic variables), a file (asc) was made available and converted into a predictive map. Final editing was performed using Quantum GIS. The model presents the average rating of the area under the curve (AUC), which provides the performance, where values close to one indicate high performance (Elith et al., 2006; Soberón, 2007). The geographical distribution of P. ulmi in Brazilian states involved in the cultivation and production of apples and grapes is shown in Figure 1 (Mattuela & Mello, 1999; Mello, 2008; Kist, 2015; IBRAVIN, 2019; Kist et al., 2019; Mello, 2019).

Figure 1
Map indicating the Brazilian regions and states that present commercial cultivation of apples and grapevines.

Results and discussion

According to the data obtained, P. ulmi occurs in 29 municipalities in Brazil and is distributed among the states of Minas Gerais, Paraná, Rio Grande do Sul, Santa Catarina, and São Paulo. The use of the predictive modeling tool through bioclimatic inferences indicated a potential scenario in which the southern region of the Brazilian territory presents greater environmental suitability for this species. However, the model also indicated that the southeastern and central-western regions had potential environmental characteristics suitable for the presence of P. ulmi (Figure 2). Of the bioclimatic variables evaluated, the mean temperature of the coldest quarter (Bio11) was the bioclimatic variable with the highest percentage contribution, indicating greater suitability for its distribution (Table 1). The average predictive performance rate was 0.992. As shown in Figure 1, the southern, southeastern, and northeastern regions present high concentrations of areas under cultures of apples and grapevines in Brazil.

The analysis of bioclimatic inferences indicated climatically suitable areas for the distribution of P. ulmi in the Brazilian territory, where the southern region showed high environmental suitability. Regions with the occurrence of P. ulmi in Brazil are within a temperate to subtropical climate, where annual mean temperatures can vary between 12 and 24°C and annual mean precipitation between 1000 and 2500 mm (Alvares, Stape, Sentelhas, Gonçalves, & Sparovek, 2013). However, in these regions of Brazil, succinct variations in temperature and precipitation between the four seasons can occur during some periods due to climate change (Mota & Agendes, 1986; Nery, 2005; Conti, 2011; Alvares et al., 2013). In the southern region for example, between the states of Paraná, Santa Catarina and Rio Grande do Sul (Mota & Agendes, 1986; Nery, 2005), where of P. ulmi occurrence is mostly reported (Ferla & Botton, 2008; Ferla et al., 2011; Johann & Ferla, 2012; Johann et al., 2014). Winter is the coldest season, and the most representative month is July when the mean daily minimum varied between 6 and 12°C (Nery, 2005).

Figure 2
Distribution of environmental suitability for Panonychus ulmi in Brazil indicating points of presence of the species at the borders or in adjacent areas. Warm colors indicate a high probability of environmental suitability for P. ulmi.

Table 1
Predictive variables used in the environmental suitability model for Panonychus ulmi in Brazilian territory and their contributions (%).

Data	Type	%
Bio11_br	Mean Temperature of Coldest Quarter	62,5
Bio9_br	Mean Temperature of Driest Quarter	13,7
Bio14_br	Precipitation of Driest Month	8,1
Bio15_br	Precipitation Seasonality	7,1
Bio6_br	Min Temperature of Coldest Month	3,1
Bio4_br	Temperature Seasonality	2,6
Bio1_br	Annual Mean Temperature	2,5
Bio3_br	Isothermality	0,5

This region may reach temperatures close to 0°C during this period, and negative temperature records may occur, which differs from other regions of the Brazilian territory (Mota & Agendes, 1986; Conti, 2011; Alvares et al., 2013). This temperature pattern corroborated the bioclimatic variable (mean temperature of the coldest quarter), which had the greatest contribution in this study to the model of environmental adequacy for P. ulmi. Therefore, we can consider this region favorable for the species, even as a producer of perennial fruits such as apples and grapes. P. ulmi can survive in these places because of its diapause (winter eggs deposited on the branches of the plant and summer eggs on the leaves without interruption) (Cuthbertson & Murchie, 2010).

Geographic distribution models have been used to determine patterns of areas with aptitude for the occurrence of several species (Anderson et al., 2003; Soberón & Peterson, 2005; Soberón, 2007; Migeon et al., 2009; Soberón, 2010; Meynard et al., 2013, Parsa et al., 2015; Litskas et al., 2019), and to determine whether a location or region is satisfactory for the species under different environmental conditions. Such models do not necessarily state whether a region is currently occupied by the species but are more appropriate for determining the bioclimatic conditions suitable for its occupation (Phillips et al., 2006; Phillips, 2008; Phillips & Dudik, 2008; Soberón, 2010).

However, for mites of economic importance, climatically suitable areas may promote infestation (Lu et al., 2012; Amaro & Moraes, 2013; Parsa et al., 2015; Navia et al., 2016; Corrêa et al., 2021). Considering that the distribution of these organisms is associated with abiotic factors (Rabbinge, 1976), climate change may interfere with their distribution patterns, which may be beneficial or limited (Migeon et al., 2009; Meynard et al., 2013; Navia et al., 2016; Litskas et al., 2019; Corrêa et al., 2021). However, even with these environmental factors, climatic limitations on distribution may coincide with host plant occurrence (Ragusa & Tsolakis 2000). The presence of mites and their patterns of occurrence are correlated with environmental factors (Rabbinge, 1976; Johann & Ferla, 2012; Amaro & Moraes, 2013; Corrêa et al., 2021), indicating that P. ulmi is established in the southern region of Brazil (Ferla & Moraes, 2002; Ferla & Botton, 2008). However, we cannot ignore other conditions that may be associated with this adaptation, such as the constant use of phytosanitary products which might eliminate natural control agents and, consequently, allow a population increase in phytophagous mites (Ferla & Moraes, 2002; Duso, Pozzebon, Kreiter, Tixier, & Candolfi, 2012; Gräff, Johann, Souza, & Ferla, 2017).

Some Brazilian states, such as Mato Grosso do Sul, Sergipe, and Paraíba, which also have areas of apple production (Kist, 2015; Kist et al., 2019), and the states of Ceará, Goiás, Piauí, Rondônia, and Mato Grosso do Sul (Mattuela & Mello, 1999; Mello, 2008; IBRAVIN, 2019; Mello, 2019), which presently have grapevine production, do not present reports in the literature indicating the presence of P. ulmi. The geographic model built in this study indicated a low or nonexistent probability of this phytophagous mite in these regions. Considering that the distribution of some mite species may be associated with the host plant (Ragusa & Tsolakis, 2000), P. ulmi may have reached these regions through vegetative material transit. However, even in the presence of an appropriate host plant (apple tree or grapevine), it cannot be established because of unfavorable environmental conditions. Considering that these regions have distinctions in minimum temperatures when compared to the states of Santa Catarina, Paraná, and Rio Grande do Sul (Nery, 2005; Conti, 2011; Alvarez et al., 2013), this could be a viable explanation for the absence of P. ulmi in other regions of Brazil. However, we cannot ignore an additional factor: the presence of predatory mites that might act as biological controls that prevent P. ulmi from achieving pest status.

Considering the scarcity of studies that mention patterns in the potential distribution of phytophagous mites at the regional level, geographic modeling is an essential tool that can contribute to such studies. In this study, we identified areas with environmental suitability for P. ulmi in Brazil, delimiting some factors that would assist in understanding areas that are suitable for accommodating the species. Based on this information, apple and grapevine producers would remain alert in these regions and plan preventive actions by implementing management and control measures to minimize possible damage to production. For example, several biological control measures can be applied in such areas. However, this information is of great importance for future academic studies on this species, particularly in the southern region of Brazil.

Conclusion

The median performance rate of the model was 0.992, indicating its robustness. The variable that made the greatest contribution to the model was the average temperature of the coldest quarter (Bio11). The predictive model of the ecological niche indicated that the southern region of Brazil is environmentally favorable for the adaptation of this mite. The data obtained helped us understand the geographical distribution of P. ulmi in Brazil, and climatically suitable areas for its occurrence were inferred. We believe that this tool can offer indirect assistance to the agricultural sector, especially the producers of apples and grapes in Brazil regarding the presence of P. ulmi.

Acknowledgements

Luiz L. C. Corrêa thanks the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) for offering a post-doctorate scholarship. Noeli Juarez Ferla was supported by the CNPq Productivity Research Scholarship (313658/2020-0).

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Publication Dates

• Publication in this collection
  23 Aug 2024
• Date of issue
  2024

History

• Received
  04 Feb 2023
• Accepted
  16 May 2023