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The Zagros forests in western Iran are a crucial source of environmental services, but are severely threatened by climatic and anthropological constraints. One crucial forest parameter is the amount of canopy coverage which enables an indirect assessment of aboveground biomass and, in turn, the carbon emission and sequestration. The aim of this study is estimation of forest crown density using Pleiades satellite data and three non-parametric classification include random forest (RF), boosted regression tree (BRT) and classification and regression tree (CART) in Kaka Reza of Lorestan province, western Iran. For this purpose, we then ensured the accuracy of geometric images, creating the necessary processing such as vegetation indices, principal component analysis and texture analysis was performed on the original bands using a random—systematic sampling design, 96 sample plots were taken. Results showed that RF compared to the two other algorithms with overall accuracy of 75% and kappa coefficient of 0.73 could better classify the forest crown density, while the CART method had the lowest accuracy with overall accuracy of 71% and kappa coefficient of 0.68. Also results showed BRT had overall accuracy of 71% and kappa coefficient of 0.68. Overall results showed Pleiades satellite data and non-parametric classification method had high capability for separation crown density in Zagros region.

Topography is the most factor that has the greatest impact of all factor that affect the distribution. To study the diversity of trees and shrub species in the Perc forest situated in Khorramabad, Lorestan, 140 circular plots of 1200 m2 in a grid of 300 m × 250 m were surveyed, using a systematic random sampling method. In each plot, the Margalef richness index, Shannon–Wiener diversity index, Hill’s N 1 and Simpson indices and the evenness index of Simpson and Smith-Wilson were calculated and ordered on the basis of different classes of elevation, exposition and slope. The results indicated that slope did not have any significant effect on the indices. Exposition and elevation classes significant impacted the richness and diversity indices, but did not influence evenness. In general, the highest plant diversity was observed for slopes less than 15 %, northern aspects, without geographical direction, and elevations of 2100–2200 m. This information can be very useful in achieving the goals for sustainable management of forests. In addition to greater protection for regions with high diversity and reforestation (compatible species) in degraded area, we can help increase diversity in forests.

Managers in conservation biology are continually faced with the dilemma of needing to demonstrate which areas should receive conservation priority based on the diversity of species contained. Darenasab (Hashtadpahloo) forest catchment with domi- nated oak species in Mediterranean forests of Zagross in Iran was chosen as a case study. In order to estimate plant species richness in different vegetation types at landscape level, field method that sample both trees and herbs strata simultaneously (modified multi-scale Whittaker plots) was used to make species-area curves. Twenty-one modified multi-scale Whittaker plots (250 m 2 area) were located randomly in four vegetation types. Three species-area, species-log (area) and log (species)-log (area) curves models were con- structed. The log (species)-log (area) model had the highest adjusted r 2 among others. Based on Jaccard's coefficient, the pure oak vegetation type was the most heterogeneous (22% overlap), and the cushion plants vegetation type is the most homogeneous (29% overlap). The slope of species-area curves had the least range (0.05) and the slope of species-log (area) curves had the largest range (4.38). When the slopes of species-log (area) curves divided by mean Jaccard's coefficient, the species-log (area) curves esti- mated values closest to those observed. The index of vegetation types contribution to regional diversity for determining conservation priority in off-reserve area, based on ranking of the observed mean species per plots, slopes of the species-log (area) curves, mean of Jaccard's coefficient, mean unique species per plot, and the number of threatened species in each vegetation types were calculated. This composite index may provide a scientific method to rank vegetation types with high conservation value.