Spatial analysis and sequential equation modeling (SEM) of genetic diversity in date palm (Phoenix dactylifera L.)

Date palms are considered an important source of food with a high economic value in many countries including Iran. Though more than 400 date palm cultivars are cultivated in Iran no report is present on the landscape genetics of these trees in the country. The present study was performed to study the genetic diversity by SSR markers and structure of 22 date palm cultivars in Iran and provide data on their landscape genetics. The species distribution modeling (SDM) was used to identify the potential adaptive geographical regions that are suitable for date palms of Iran cultivation in response to future climate change. Similarly, sequential equation modeling (SEM) was performed to illustrate the interaction among environmental, bioclimate, and genetic factors affecting date palm structuring. Discriminant analysis of principal components (DAPC) scattered date palm trees in three genetic groups. The Manhattan plot showed that some of the SSR (simple sequence repeat) loci contribute the most to the differentiation of date palm cultivars and are potentially adaptive to the local conditions. The sPCA (Spatial principal components analysis) showed significant positive (global structuring), and negative (local structuring) eigenvalues. Therefore, date palm trees' genetic differences and variability are affected by both global and local spatial features of their cultivation areas in Iran. Species distribution modeling (SDM) identified the bioclimate variables affecting the geographical distribution of date palm trees and the sequential equation (SEM) showed a strong negative association between resistance distance and the genetic distance, but showed a strong positive relationship with the environmental variables.