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Updated: May 10, 2025

Using Generative Art to Convey Past and Future Climate Transitions
Published on: March 31, 2023
Current and Projected Future Spatial Distribution Patterns of Prunus microcarpa in the Kurdistan Region of Iraq
Renas Y Qadir1, Nabaz R Khwarahm2
1Department of Natural Resources, College of Agricultural Engineering Sciences, University of Sulaimani, Sulaimani 334, Kurdistan Region, Iraq.
Abstract:
Prunus microcarpa is an endemic species prevalent throughout the highlands of the Kurdistan Region of Iraq. Conservation, introduction, and restoration efforts require an in-depth understanding of the species' current and future habitat distributions under different climate change scenarios. This study utilized field observations, species distribution modeling, geospatial techniques, and environmental predictors to analyze the distribution and forecast potential habitats for P. microcarpa in the highlands of Iraq. Findings indicate that, according to the global climate models (i.e., BCC-CSM2-MR and MRI-ESM2.0), the reduction in habitat for the species is projected to be more than the potential expansion. Specifically, the area of habitat is expected to reduce by 2351.908 km2 (4.6%) and 2216.957 km2 (4.3%), while it could increase by 1306.384 km2 (2.5%) and 1015.612 km2 (2.0%) for the respective climate models. Topographic features such as elevation and slope, climatic conditions, precipitation seasonality, and annual mean temperature relatively shape the distribution of P. microcarpa. The modeling demonstrated good predictive capability (area under the curve (AUC) score = 0.933). The total study area is approximately 51,558.327 km2, with around 20.5% (10,602 km2) identified as suitable habitat for P. microcarpa. These findings offer essential baseline information for conservation strategies and provide new insights into where the species currently resides and where it could be found in the future. This underscores how combining distribution modeling with geospatial techniques can be effective, particularly in data-deficient regions like Iraq.
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