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Predicting the Global Distribution of Solenopsis geminata (Hymenoptera: Formicidae) under Climate Change Using the MaxEnt Model.

ABSTRACT: The tropical fire ant Solenopsis geminata (Hymenoptera: Formicidae) is a serious invasive species that causes a decline in agricultural production, damages infrastructure, and harms human health. This study was aimed to develop a model using the maximum entropy (MaxEnt) algorithm to predict the current and future distribution of S. geminata on a global scale for effective monitoring and management. In total, 669 occurrence sites of S. geminata and six bioclimatic variables of current and future climate change scenarios for 2050 and 2100 were used for the modeling. The annual mean temperature, annual precipitation, and precipitation in the driest quarter were the key influential factors for determining the distribution of S. geminata. Although the potential global distribution area of S. geminata is predicted to decrease slightly under global warming, the distribution of favorable habitats is predicted to expand to high latitudes under climate scenarios. In addition, some countries in America and East Asia, such as Brazil, China, South Korea, the USA, and Uruguay, are predicted to be threatened by S. geminata invasion under future climate change. These findings can facilitate the proactive management of S. geminata through monitoring, surveillance, and quarantine measures.

SUBMITTER: Lee CM

PROVIDER: S-EPMC7998871 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:In the context of global warming, the habitats of Ephedra, including Ephedra sinica Stapf, Ephedra intermedia Schrenk ex Mey, and Ephedra equisetina Bunge, have been substantially threatened and deteriorated in recent years. Little is known about the potential geographic dynamics of economically renowned species, including those used in sand fixation and traditional Chinese medicine, under climate change. Therefore, evaluating their potential habitat and determining the crucial environmental variables affecting E. sinica, E. intermedia and E. equisetina under the driving force of global warming are extremely important. In this study, an optimized MaxEnt model in the kuenm package on the basis of occurrence records (a total of 103, 101 and 97 points for E. sinica, E. intermedia and E. equisetina, respectively) and 37 environmental factors were utilized to simulate the distribution of the three species. Two representative concentration pathways (SSP2.6 and SSP8.5) at 2041-2060 and 2061-2080, respectively, were used to establish a future distribution model of the three species. The results indicated that approximately 6.92 × 105 km2, 2.95 × 105 km2, and 11.5 × 105 km2 of suitable regions for E. sinica, E. intermedia and E. equisetina were obtained, which were mostly distributed in central and eastern Inner Mongolia, eastern and southern Gansu, and northern Xinjiang, respectively. Critical environmental variables, such as land cover and annual precipitation, were regarded as critical parameters for the three species. Future assessment revealed that over 60 % of the potential distribution area was affected, and the stability of E. sinica under the SSP8.5 scenario was the greatest. The spatial dynamic changes in suitable areas for E. intermedia were smaller than those for E. equisetina and E. sinica in the future. The comprehensive analysis revealed that the fluctuations in the distributions of the three Ephedra species under climate change are small and provide useful information for future conservation. Therefore, target conservation and management measures should be implemented in combination with the suitability thresholds of different environmental parameters. Our results provide useful recommendations for the current and future protection of Ephedra populations.

Project description:Purpose: We aimed to provide a basis for the adaptive mechanism and a rich resource for the discovery and identification of novel genes involved in the cold stress response in Solenopsis japonica. Retinal transcriptome profiling (RNA-seq) to microarray and quantitative reverse transcription polymerase chain reaction (qRT–PCR) methods and to evaluate protocols for optimal high-throughput data analysis Methods: Solenopsis japonica was reared at lab condition, and incubated at 2 different temperature for 24h (9, and 25℃) under dark conditions. RNA was extracted using Trizol reagent and Illumina sequencing was performed at Macrogen. Illumina short reads were quality-filtered and Illumina-based de novo transcriptome assembly was performed. Differential Gene Expression Analysis was studied for different tempearture conditions. Results: Totally 89,657 unigenes was obtained which overall 43,375 were annotated with gene descriptions, gene ontology terms, and metabolic pathways. 86 GO functional sub-groups and 25 EggNOG terms resulted. DEGs with FC≥2 and FC≤-2, P-value<0.05 were screened and were compared at two different temperatures. We found 138 DEG down regulated and 271 DEG up regulated when the S. japonica incubated at 9 ℃ and compared with 25℃ treated group. Comparing transcriptome profiles for differential gene expression resulted various DE proteins and genes, including cytochrome P450, NADH dehydrogenase subunit 1, cuticle protein and HSP which have previously been reported to be involved in cold and high temperature resistance. GO analysis revealed that antioxidant activity up-regulated under high temperature stress. Conclusions: we compared the transcriptomes of S. japonica under normal room temperature and low-temperature using RNA-Seq technology based on the high-throughput sequencing. Comparative transcriptome analysis identified many genes and a large number of changes were discovered in metabolic pathway through the GO and KEGG enrichment analysis. Our data will facilitate further molecular investigations and genomic research. Many low-temperature significantly up-regulated genes were first identified in this study. These newly found genes may be important and necessary to S. japonica overwintering and its behavior for adaptation in new environment.

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Predicting the Global Distribution of Solenopsis geminata (Hymenoptera: Formicidae) under Climate Change Using the MaxEnt Model.

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