The effects of environmental factors on plant diversity of Darab natural ecosystems in Fars province, Iran.

This research quantitatively evaluated the diversity of plants to protect vulnerable species. To measure vegetation information, the appropriate sampling plot size was determined based on the canopy cover of the dominant species of the study area (1 m2). Then, in each unit, sampling was done along 3 transects of 100 m. Along each transect, 10 plots with dimensions of one square meter were placed at a distance of 10 m from each other. In each plot, the type, life forms, frequency of plant species, and species density were recorded. Species diversity indices were calculated using Ecological Methodology software. The values obtained from these indicators were analyzed in SPSS 24 statistical software and using the F test. The results of the Analysis of variance (ANOVA) showed that the highest values of the species diversity indices are in the middle altitudes (ecotone) class. ANOVA of the richness, evenness, and heterogeneity indices in different altitude classes showed that the values of the richness indices were not significant, but among the indices related to the heterogeneity, the Hill index and all the evenness indices were significant. Comparing the numerical indices of our communities enables us to determine the impact of environmental stress in a single community to choose the best habitat among a similar group for conservation. A community that has high diversity and richness is important for conservation. Therefore, the authorities must prevent the destruction of the vegetation of the study area in connection with the implementation of principled and correct management by the potential of the region, but also to reduce the pressure of livestock grazing and carry out corrective and restoration operations, to turn these rangelands towards rich diversity.

Forthcoming risk of Prosopis juliflora global invasion triggered by climate change: implications for environmental monitoring and risk assessment.

Climate is a determinant factor in species distribution and climate change will affect the species abilities to occupy geographic regions. Prosopis juliflora is one of the most problematic invasive species and its biological invasion causes various negative effects in tropical, arid, and semi-arid regions of the world. As eradication efforts subsequent to the establishment of an alien invasive species are costly and time-consuming, assessing patterns of the introduction of an invasive species to new regions is among the most cost-effective means of monitoring and management of natural ecosystems. In this study by using the concept of species distribution modeling (SDM) and maximum entropy (MaxEnt) method, the effect of climate change on the current and future distribution of P. juliflora has been assessed at a global scale. Bioclimatic variables in current condition and 2050 regarding two global circulation models (GCM) and two climate change scenarios were considered as explanatory variables. Our results showed that annual mean temperature (BIO1), annual precipitation (BIO12), and temperature mean diurnal range (BIO2) represented more than 87% of the variations in the model, and with an AUC of 0.854 and TSS of 0.51, the model showed a good predictive performance. Our results indicate that on a global scale, suitable ranges for P. juliflora increase across all the GCM and RCP scenarios. In a global scale, Mediterranean Basin, Middle East, and North America are regions with the highest risk of range expansion in the future. Regarding the negative impacts of P. juliflora on structure and function of natural habitats in the invaded areas, findings of this study could be considered as a warning appliance for the environmental monitoring of the regions highly sensitive to the global invasion of the species. We suggest that assessing impacts of climate change on the global distribution of the invasive species could be used as an efficient tool to implement broad-scale and priority-setting monitoring programs in natural ecosystems.