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BACKGROUND: Strawberry (Fragaria×ananassa Duch.) is a species of great economic and nutritional importance. It is widely cultivated in different regions of the world. However, climatic factors have a significant influence on its production. OBJECTIVE: To evaluate the ecoclimatic suitability and growth index of F.×ananassa in the face of the impacts of climate change in Brazil and the world. METHODS: The potential global distribution of F.×ananassa it was based on predicted global climate changes using CLIMEX and the A1B and A2 emissions scenario for the years 2050 and 2100. CLIMEX weekly growth index (GIw) was applied, and productivity data in commercial strawberry cultivation in Brazilian areas were collected. RESULTS: The results indicate a progressive reduction in areas suitable for strawberry cultivation globally, mainly on the African continent, Australia, China, and the Americas for the years 2050 and 2100. In Brazil, only the South region and part of the Southeast will continue to be suitable for strawberry production. CONCLUSIONS: The CLIMEX model predicts a reduction in the suitable area for cultivating Fragaria×ananassa Duch between 2050 and 2100 due to climate change. The generated maps can help identify new cultivation areas and support genetic improvement programmes to develop cultivars more tolerant to heat. [ABSTRACT FROM AUTHOR]

Brassica napus, a versatile crop with significant socioeconomic importance, serves as a valuable source of nutrition for humans and animals while also being utilized in biodiesel production. The expansion potential of B. napus is profoundly influenced by climatic variations, yet there remains a scarcity of studies investigating the correlation between climatic factors and its distribution. This research employs CLIMEX to identify the current and future ecological niches of B. napus under the RCP 8.5 emission scenario, utilizing the Access 1.0 and CNRM-CM5 models for the time frame of 2040–2059. Additionally, a sensitivity analysis of parameters was conducted to determine the primary climatic factors affecting B. napus distribution and model responsiveness. The simulated outcomes demonstrate a satisfactory alignment with the known current distribution of B. napus, with 98% of occurrence records classified as having medium to high climatic suitability. However, the species displays high sensitivity to thermal parameters, thereby suggesting that temperature increases could trigger shifts in suitable and unsuitable areas for B. napus, impacting regions such as Canada, China, Brazil, and the United States. [ABSTRACT FROM AUTHOR]

The red palm mite, Raoiella indica Hirst, is the most invasive pest, having spread quickly to several countries. In Brazil it is already present in several regions and has a high potential for dispersion to other regions, which could severely affect the cultivation of coconuts, bananas, native and exotic palm trees, and tropical flowers, such as those of the Heliconiaceae family. Thus, we aimed to determine the regions of Brazil most prone to the occurrence of R. indica using Maxent with updated data on its occurrence and a selection of bioclimatic variables that may influence its establishment. The occurrence data used were obtained through a literature search, online databases, and surveys carried out in the field. The model indicated a high potential for the establishment of R. indica in the following locations: a large part of the State of Roraima, the eastern part of the State of Amazonas, the northern and central-western parts of the State of Pará, and parts of the states of Acre and Amapá (North Region); the coast of Brazil from Rio Grande do Norte to the states of Paraíba, Pernanbuco, Alagoas, Sergipe and Bahia (Northeast Region); the states of Rio de Janeiro and Espírito Santo, the far east of Minas Gerais, and almost the entire state of São Paulo, except the northern part (Southeast Region); most of the State of Mato Grosso do Sul and the most southern portion of the State of Mato Grosso (Midwest Region); and the northern part of the State of Paraná and small parts of the states of Santa Catarina and Rio Grande do Sul (South Region). The bioclimatic variables that most influenced the potential geographical distribution of R. indica were precipitation of driest month (Bio14), precipitation of wettest month (Bio13), mean diurnal range (Bio2), and isothermality (Bio3). The parameterization for the Maxent model provides an updated model to prevention invasion of R. indica due updated data on its occurrence used. Thus, potential geographic distribution of R. indica in Brazil should be consider from this study. [ABSTRACT FROM AUTHOR]

• Oral transmission of Chagas disease is frequently overlooked and increasing. • Rhodnius kissing bugs and palm trees play key role in this transmission. • Distribution of vectors and palm trees drive oral Chagas disease spread. • Niche modeling indicates broader potential habitats than current records indicate. • Projections suggest increased suitability by 2040, reducing by 2080. Chagas disease, a neglected global health concern primarily transmitted through the bite and feces of kissing bugs, has garnered increasing attention due to recent outbreaks in northern Brazil, highlighting the role of oral transmission facilitated by the kissing bugs species Rhodnius robustus and Rhodnius pictipes. These vectors are associated with palm trees with large crowns, such as the maripa palm (Attalea maripa) and moriche palm (Mauritia flexuosa). In this study, we employ maximum entropy (MaxEnt) ecological niche models to analyze the spatial distribution of these vectors and palm species, predicting current and future climate suitability. Our models indicate broader potential habitats than documented occurrences, with high suitability in northern South America, southern Central America, central Africa, and southeast Asia. Projections suggest increased climate suitability by 2040, followed by a reduction by 2080. This study identifies present and future areas suitable for kissing bugs and palm tree species due to climate change, aiding in the design of prevention and management strategies. [ABSTRACT FROM AUTHOR]

• We assessed how the size of the study area impacts the distribution of Raoiella indica. • The size of the area used during model training significantly influences the model outcomes. • Models developed using smaller study areas exhibited a higher number of false-negative predictions. • The extent of the study area is crucial when developing models for invasive species. Ecological niche models are used to quantify the relationships between known occurrence records of a given species and environmental variables at these locations. Maxent is among the most widely used algorithms for modeling species distribution and has demonstrated better performance compared to other methods. However, the extent of the study area is a critical issue in the development of presence-only species distribution models because it encompasses the region used to extract the background points employed to characterize the environments accessible to the species. Thus, this study evaluated the effect of the extension of the study area on the species distribution modeling with the Maxent algorithm and occurrence data from the invasive species Raoiella indica Hirst (Acari: Tenuipalpidae). The increase in the study area extent inflated most of the threshold-dependent and -independent metrics used to assess model performance. The selection of the study area also affected the predicted suitable areas for the species (its potential distribution). The analysis shows that models developed with smaller study areas resulted in model overfitting and an increase in false-negative predictions. The extent of the area used during model training has a strong influence on the model outputs, with significant consequences for predicting the potential distribution of invasive species and thus for the areas under risk of invasion. [ABSTRACT FROM AUTHOR]