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Effects of Climatic Change on Potential Distribution of Spogostylum ocyale (Diptera: Bombyliidae) in the Middle East Using Maxent Modelling.

Mustafa M SolimanAreej A Al-KhalafMagdi S A El-Hawagry
Published in: Insects (2023)
Spogostylum ocyale (Wiedemann 1828) is a large robust species of bee fly (family Bombyliidae), known to be a larval ectoparasitoid as well as an important flower pollinator as an adult. This species has become extremely rare or has disappeared from many of its historic habitats due to substantial changes in floral and faunal compositions in recent years. Climate change and urbanisation, together with other anthropogenic activities, may be to blame for these changes. Distribution modelling based on environmental variables together with known occurrences is a powerful tool in analytical biology, with applications in ecology, evolution, conservation management, epidemiology and other fields. Based on climatological and topographic data, the current and future distributions of the parasitoid in the Middle East region was predicted using the maximum entropy model (Maxent). The model performance was satisfactory (AUC mean = 0.834; TSS mean = 0.606) and revealed a good potential distribution for S. ocyale featured by the selected factors. A set of seven predictors was chosen from 19 bioclimatic variables and one topographic variable. The results show that the distribution of S. ocyale is mainly affected by the maximum temperature of the warmest period (Bio5) and temperature annual range (Bio7). According to the habitat suitability map, coastal regions with warm summers and cold winters had high to medium suitability. However, future scenarios predict a progressive decline in the extent of suitable habitats with global climate warming. These findings lead to robust conservation management measures in current or future conservation planning.
Keyphrases
  • climate change
  • human health
  • current status
  • multiple sclerosis
  • electronic health record
  • mass spectrometry
  • heavy metals
  • genetic diversity
  • data analysis
  • water quality