Modeling the Invasion of the Large Hive Beetle, Oplostomusfuligineus, into North Africa and South Europe under a Changing Climate

Abou‐Shaara, Hossam F.; Al-Ashaal, Sara A.; Hosni, Eslam M.; Nasser, Mohamed; Ansari, Mohammad Javed; Alharbi, Sulaiman Ali

doi:10.3390/insects12040275

Cited by 20 publications

(17 citation statements)

References 70 publications

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“…BCC-CSM 1.1 is among the most-used models currently available for simulating the global climate response to increasing greenhouse gas concentration. Our four selected future climate data sets, including 2021–2040, 2041–2060, 2061–2080, and 2081–2100, were downloaded from the World Climate Database ( Abou-Shaara et al, 2021 ) with a spatial resolution of 2.5 arc-min. All the environmental variables were in raster format and were prepared in ArcGIS 10.2 to align in the geographic space using a WGS84 datum system with default parameters.…”

Section: Methodsmentioning

confidence: 99%

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Modeling of the Potential Geographical Distribution of Three Fritillaria Species Under Climate Change

et al. 2022

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Fritillaria species, a well-known Chinese traditional medicine for more than 2,000 years, have become rare resources due to excessive harvesting. In order to balance the economical requirement and ecological protection of Fritillaria species, it is necessary to determine (1) the important environmental variables that were responsible for the spatial distribution, (2) distribution change in response to climate change in the future, (3) ecological niche overlap between various Fritillaria species, and (4) the correlation between spatial distribution and phylogenies as well. In this study, the areas with potential ecological suitability for Fritillaria cirrhosa, Fritillaria unibracteata, and Fritillaria przewalskii were predicted using MaxEnt based on the current occurrence records and bioclimatic variables. The result indicated that precipitation and elevation were the most important environmental variables for the three species. Moreover, the current suitable habitats of F. cirrhosa, F. unibracteata, and F. przewalskii encompassed 681,951, 481,607, and 349,199 km2, respectively. Under the scenario of the highest concentration of greenhouse gas emission (SSP585), the whole suitable habitats of F. cirrhosa and F. przewalskii reach the maximum from 2021 to 2100, while those of F. unibracteata reach the maximum from 2021 to 2100 under the scenario of moderate emission (SSP370) from 2021 to 2100. The MaxEnt data were also used to predict the ecological niche overlap, and thus high overlap occurring among three Fritillaria species was observed. The niche overlap of three Fritillaria species was related to the phylogenetic analysis despite the non-significance (P > 0.05), indicating that spatial distribution was one of the factors that contributed to the speciation diversification. Additionally, we predicted species-specific habitats to decrease habitat competition. Overall, the information obtained in this study provided new insight into the potential distribution and ecological niche of three species for the conservation and management in the future.

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Section: Methodsmentioning

confidence: 99%

“… Zhang et al (2018) predicted the potential geographical distribution of two peony species under a change of CO 2 concentration. Abou-Shaara et al (2021) speculated on the possible invasion of Oplostomus fuligineus into North Africa and South Europe from 2050 to 2070.…”

Section: Introductionmentioning

confidence: 99%

Modeling of the Potential Geographical Distribution of Three Fritillaria Species Under Climate Change

et al. 2022

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“…The occurrence data were subjected to three filtration steps to avoid any possible bias. First, duplicated records were removed [ 22 ]; second, records with high spatial uncertainty were eliminated; and third, to prevent redundant records, spatially rarefied occurrence data based on distance in ArcGIS (SDM Toolbox: SDM Tools; Universal Tools—Spatially rarefy occurrence data) were filtered. Finally, the remaining records with 313 points were transformed into comma-delimited (CSV) forms and used to predict the current and future worldwide distribution of the GWM ( Figure 1 ).…”

Section: Methodsmentioning

confidence: 99%

“…The GWM, like other honeybee pests, can thrive under certain bioclimatic conditions. Ecological niche modeling (ENM) tools can establish a statistical correlation between geographical changes in bioclimatic variables and the distribution of a certain species such as honeybee pests [ 22 ]. In the last two decades, a variety of modeling software based on various mathematical techniques has been developed to achieve this goal; however, the Maximum Entropy (Maxent) Model is the most successful and accurate [ 23 , 24 , 25 ].…”

Section: Introductionmentioning

confidence: 99%

Modeling the Potential Global Distribution of Honeybee Pest, Galleria mellonella under Changing Climate

Hosni

Al-Khalaf

Nasser

et al. 2022

Insects

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Beekeeping is essential for the global food supply, yet honeybee health and hive numbers are increasingly threatened by habitat alteration, climate change, agrochemical overuse, pathogens, diseases, and insect pests. However, pests and diseases that have unknown spatial distribution and influences are blamed for diminishing honeybee colonies over the world. The greater wax moth (GWM), Galleria mellonella, is a pervasive pest of the honeybee, Apis mellifera. It has an international distribution that causes severe loss to the beekeeping industry. The GWM larvae burrow into the edge of unsealed cells that have pollen, bee brood, and honey through to the midrib of the wax comb. Burrowing larvae leave behind masses of webs that cause honey to leak out and entangle emerging bees, resulting in death by starvation, a phenomenon called galleriasis. In this study, the maximum entropy algorithm implemented in (Maxent) model was used to predict the global spatial distribution of GWM throughout the world. Two representative concentration pathways (RCPs) 2.6 and 8.5 of three global climate models (GCMs), were used to forecast the global distribution of GWM in 2050 and 2070. The Maxent models for GWM provided a high value of the Area Under Curve equal to 0.8 ± 0.001, which was a satisfactory result. Furthermore, True Skilled Statistics assured the perfection of the resultant models with a value equal to 0.7. These values indicated a significant correlation between the models and the ecology of the pest species. The models also showed a very high habitat suitability for the GWM in hot-spot honey exporting and importing countries. Furthermore, we extrapolated the economic impact of such pests in both feral and wild honeybee populations and consequently the global market of the honeybee industry.

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“…Invertebrates' diversity plays a vital role in all ecosystems, e.g., species, population, and individual ( Cardinale et al, 2006; Bashir, 2019; Shakeel, 2019 ). Members of Phylum Arthropoda play a pivotal role in ecological services ( Rathore and Jasrai, 2013; Abou-Shaara, 2021; Karar, 2020 ). Besides most successful Phyllum, they dominate all types of habitats except for the oceanic benthic zone ( Jamal, 2021; Abrol, 2019 ).…”

Section: Introductionmentioning

confidence: 99%

Moth diversity, species composition, and distributional pattern in Aravalli Hill Range of Rajasthan, India

Dar

Jamal

Alhazmi

et al. 2021

Saudi Journal of Biological Sciences

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Moths are phytophagous, cosmopolitan, agricultural pests, night pollinators, chiefly nocturnal and potential bio-indicators. The current study will be the first report on species diversity, species composition, abundance, and distributional pattern of moth fauna in Aravalli Hill Range Rajasthan. During the survey period of 2018–2019, 758 specimens of moths were collected pertaining to 34 species, 26 genera belonging to 05 families, and 13 subfamilies from three different sites of Aravalli Hill Range. Based on the number of genera, family Sphingidae was most dominant with 9 genera, and family Crambidae was least dominant with 2 genera. Based on the number of species, the family Sphingidae was the most dominant, representing 13 species, followed by Erebidae representing 11 species, Saturniidae and Noctuidae with 4 species each, the least dominant was Crambidae with 2 species. The diversity indices for moths have been calculated for the first time from the Aravalli Range of Rajasthan. Across the survey, Simpson’s Diversity Index (D′), Shannon Diversity Index (H′), Dominance & Evenness was calculated as 0.95, 3.3, 0.04, and 0.8, respectively, which reflects that moth fauna is diverse in the surveyed areas.

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Modeling the Invasion of the Large Hive Beetle, Oplostomusfuligineus, into North Africa and South Europe under a Changing Climate

Cited by 20 publications

References 70 publications

Modeling of the Potential Geographical Distribution of Three Fritillaria Species Under Climate Change

Modeling of the Potential Geographical Distribution of Three Fritillaria Species Under Climate Change

Modeling the Potential Global Distribution of Honeybee Pest, Galleria mellonella under Changing Climate

Moth diversity, species composition, and distributional pattern in Aravalli Hill Range of Rajasthan, India

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